├── .gitignore ├── .gitmodules ├── ACKNOWLEDGMENTS ├── AUTHORS ├── CONTRIBUTING.md ├── ISSUE_TEMPLATE.md ├── LICENSE ├── README.md ├── RELEASE.md ├── WORKSPACE ├── avro.BUILD ├── boost.BUILD ├── boringssl.BUILD ├── bower.BUILD ├── build_pip_package.sh ├── build_user_op.sh ├── bzip2.BUILD ├── configure ├── eigen.BUILD ├── farmhash.BUILD ├── gmock.BUILD ├── jpeg.BUILD ├── jsoncpp.BUILD ├── navbar.md ├── png.BUILD ├── six.BUILD ├── tensorflow ├── BUILD ├── __init__.py ├── cc │ ├── BUILD │ ├── ops │ │ ├── cc_op_gen.cc │ │ ├── cc_op_gen.h │ │ ├── cc_op_gen_main.cc │ │ ├── const_op.cc │ │ ├── const_op.h │ │ └── standard_ops.h │ └── tutorials │ │ └── example_trainer.cc ├── contrib │ ├── BUILD │ ├── README.md │ ├── __init__.py │ ├── avro │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ └── example.json │ ├── bayesflow │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ └── __init__.py │ ├── cmake │ │ ├── CMakeLists.txt │ │ ├── README.md │ │ ├── external │ │ │ ├── eigen.cmake │ │ │ ├── jpeg.cmake │ │ │ ├── png.cmake │ │ │ └── re2.cmake │ │ ├── install.cmake │ │ ├── patches │ │ │ └── jpeg │ │ │ │ └── CMakeLists.txt │ │ ├── tests.cmake │ │ ├── tf_cc_ops.cmake │ │ ├── tf_core_cpu.cmake │ │ ├── tf_core_direct_session.cmake │ │ ├── tf_core_framework.cmake │ │ ├── tf_core_kernels.cmake │ │ ├── tf_core_ops.cmake │ │ ├── tf_models.cmake │ │ ├── tf_stream_executor.cmake │ │ └── tf_tutorials.cmake │ ├── copy_graph │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ ├── __init__.py │ │ │ └── util │ │ │ ├── __init__.py │ │ │ ├── copy_elements.py │ │ │ └── copy_test.py │ ├── ctc │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── ctc_decoder_ops_test.py │ │ ├── ctc_loss_op_test.py │ │ └── ctc_ops.py │ ├── distributions │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ ├── __init__.py │ │ │ ├── kernel_tests │ │ │ ├── chi2_test.py │ │ │ ├── dirichlet_multinomial_test.py │ │ │ ├── exponential_test.py │ │ │ ├── gamma_test.py │ │ │ ├── mvn_test.py │ │ │ ├── normal_conjugate_posteriors_test.py │ │ │ ├── normal_test.py │ │ │ ├── student_t_test.py │ │ │ └── uniform_test.py │ │ │ └── ops │ │ │ ├── chi2.py │ │ │ ├── dirichlet_multinomial.py │ │ │ ├── distribution.py │ │ │ ├── exponential.py │ │ │ ├── gamma.py │ │ │ ├── mvn.py │ │ │ ├── normal.py │ │ │ ├── normal_conjugate_posteriors.py │ │ │ ├── student_t.py │ │ │ └── uniform.py │ ├── ffmpeg │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── decode_audio_op.cc │ │ ├── decode_audio_op_test.py │ │ ├── default │ │ │ ├── BUILD │ │ │ ├── ffmpeg_lib.cc │ │ │ └── ffmpeg_lib_test.cc │ │ ├── encode_audio_op.cc │ │ ├── encode_audio_op_test.py │ │ ├── ffmpeg_lib.h │ │ ├── ffmpeg_ops.py │ │ └── testdata │ │ │ ├── mono_10khz.ogg │ │ │ ├── mono_10khz.wav │ │ │ ├── mono_16khz.mp3 │ │ │ ├── stereo_48khz.mp3 │ │ │ └── test_sound1.mp3 │ ├── framework │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ └── python │ │ │ ├── framework │ │ │ ├── __init__.py │ │ │ ├── tensor_util.py │ │ │ └── tensor_util_test.py │ │ │ └── ops │ │ │ ├── __init__.py │ │ │ ├── arg_scope.py │ │ │ ├── arg_scope_test.py │ │ │ ├── embedding_ops.py │ │ │ ├── embedding_ops_test.py │ │ │ ├── ops.py │ │ │ ├── ops_test.py │ │ │ ├── variables.py │ │ │ └── variables_test.py │ ├── grid_rnn │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ ├── __init__.py │ │ │ ├── kernel_tests │ │ │ └── grid_rnn_test.py │ │ │ └── ops │ │ │ ├── __init__.py │ │ │ └── grid_rnn_cell.py │ ├── ios_example │ │ ├── AppDelegate.h │ │ ├── AppDelegate.mm │ │ ├── RunModel-Info.plist │ │ ├── RunModelViewController.h │ │ ├── RunModelViewController.mm │ │ ├── RunModelViewController.xib │ │ ├── data │ │ │ └── grace_hopper.jpg │ │ ├── ios_image_load.h │ │ ├── ios_image_load.mm │ │ ├── main.mm │ │ └── tf_ios_makefile_example.xcodeproj │ │ │ └── project.pbxproj │ ├── layers │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── kernels │ │ │ ├── BUILD │ │ │ ├── bucketization_kernel.cc │ │ │ └── sparse_feature_cross_kernel.cc │ │ ├── ops │ │ │ ├── bucketization_op.cc │ │ │ └── sparse_feature_cross_op.cc │ │ └── python │ │ │ ├── kernel_tests │ │ │ ├── bucketization_op_test.py │ │ │ └── sparse_feature_cross_op_test.py │ │ │ ├── layers │ │ │ ├── __init__.py │ │ │ ├── feature_column.py │ │ │ ├── feature_column_ops.py │ │ │ ├── feature_column_ops_test.py │ │ │ ├── feature_column_test.py │ │ │ ├── initializers.py │ │ │ ├── initializers_test.py │ │ │ ├── layers.py │ │ │ ├── layers_test.py │ │ │ ├── optimizers.py │ │ │ ├── optimizers_test.py │ │ │ ├── regularizers.py │ │ │ ├── regularizers_test.py │ │ │ ├── summaries.py │ │ │ ├── summaries_test.py │ │ │ └── utils.py │ │ │ └── ops │ │ │ ├── bucketization_op.py │ │ │ └── sparse_feature_cross_op.py │ ├── learn │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ ├── __init__.py │ │ │ └── learn │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── dataframe │ │ │ ├── __init__.py │ │ │ ├── column.py │ │ │ ├── dataframe.py │ │ │ ├── queues │ │ │ │ ├── feeding_functions.py │ │ │ │ └── feeding_queue_runner.py │ │ │ ├── transform.py │ │ │ └── transforms │ │ │ │ ├── csv_parser.py │ │ │ │ ├── example_parser.py │ │ │ │ ├── in_memory_source.py │ │ │ │ └── reader_source.py │ │ │ ├── datasets │ │ │ ├── __init__.py │ │ │ ├── base.py │ │ │ ├── data │ │ │ │ ├── boston_house_prices.csv │ │ │ │ └── iris.csv │ │ │ ├── mnist.py │ │ │ └── text_datasets.py │ │ │ ├── estimators │ │ │ ├── __init__.py │ │ │ ├── _sklearn.py │ │ │ ├── autoencoder.py │ │ │ ├── base.py │ │ │ ├── dnn.py │ │ │ ├── dnn_linear_combined.py │ │ │ ├── dnn_linear_combined_test.py │ │ │ ├── dnn_test.py │ │ │ ├── estimator.py │ │ │ ├── estimator_test.py │ │ │ ├── linear.py │ │ │ ├── linear_test.py │ │ │ ├── rnn.py │ │ │ ├── run_config.py │ │ │ ├── tensor_signature.py │ │ │ └── tensor_signature_test.py │ │ │ ├── graph_actions.py │ │ │ ├── io │ │ │ ├── __init__.py │ │ │ ├── dask_io.py │ │ │ ├── data_feeder.py │ │ │ ├── graph_io.py │ │ │ ├── graph_io_test.py │ │ │ └── pandas_io.py │ │ │ ├── models.py │ │ │ ├── monitors.py │ │ │ ├── ops │ │ │ ├── __init__.py │ │ │ ├── array_ops.py │ │ │ ├── autoencoder_ops.py │ │ │ ├── batch_norm_ops.py │ │ │ ├── conv_ops.py │ │ │ ├── dnn_ops.py │ │ │ ├── dropout_ops.py │ │ │ ├── embeddings_ops.py │ │ │ ├── losses_ops.py │ │ │ ├── seq2seq_ops.py │ │ │ └── tests │ │ │ │ ├── __init__.py │ │ │ │ ├── test_dropout_ops.py │ │ │ │ ├── test_ops.py │ │ │ │ └── test_seq2seq_ops.py │ │ │ ├── preprocessing │ │ │ ├── __init__.py │ │ │ ├── categorical.py │ │ │ ├── categorical_vocabulary.py │ │ │ ├── tests │ │ │ │ ├── __init__.py │ │ │ │ ├── test_categorical.py │ │ │ │ ├── test_categorical_vocabulary.py │ │ │ │ └── test_text.py │ │ │ └── text.py │ │ │ ├── tests │ │ │ ├── __init__.py │ │ │ ├── dataframe │ │ │ │ ├── __init__.py │ │ │ │ ├── mocks.py │ │ │ │ ├── test_column.py │ │ │ │ ├── test_csv_parser.py │ │ │ │ ├── test_dataframe.py │ │ │ │ ├── test_example_parser.py │ │ │ │ ├── test_feeding_queue_runner.py │ │ │ │ ├── test_in_memory_source.py │ │ │ │ ├── test_reader_source.py │ │ │ │ └── test_transform.py │ │ │ ├── test_base.py │ │ │ ├── test_custom_decay.py │ │ │ ├── test_data_feeder.py │ │ │ ├── test_early_stopping.py │ │ │ ├── test_estimators.py │ │ │ ├── test_grid_search.py │ │ │ ├── test_io.py │ │ │ ├── test_multioutput.py │ │ │ ├── test_nonlinear.py │ │ │ ├── test_regression.py │ │ │ └── test_saver.py │ │ │ └── utils │ │ │ ├── __init__.py │ │ │ ├── checkpoints.py │ │ │ ├── checkpoints_test.py │ │ │ └── inspect_checkpoint.py │ ├── linear_optimizer │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── kernels │ │ │ ├── BUILD │ │ │ ├── hinge-loss.h │ │ │ ├── logistic-loss.h │ │ │ ├── loss.h │ │ │ ├── loss_test.cc │ │ │ ├── resources.cc │ │ │ ├── resources.h │ │ │ ├── resources_test.cc │ │ │ ├── sdca_ops.cc │ │ │ ├── sdca_ops_test.cc │ │ │ └── squared-loss.h │ │ ├── ops │ │ │ └── sdca_ops.cc │ │ └── python │ │ │ ├── kernel_tests │ │ │ └── sdca_ops_test.py │ │ │ └── ops │ │ │ └── sdca_ops.py │ ├── lookup │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── lookup_ops.py │ │ └── lookup_ops_test.py │ ├── losses │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ └── python │ │ │ └── losses │ │ │ ├── __init__.py │ │ │ ├── loss_ops.py │ │ │ └── loss_ops_test.py │ ├── makefile │ │ ├── Makefile │ │ ├── README.md │ │ ├── compile_android_protobuf.sh │ │ ├── compile_ios_protobuf.sh │ │ ├── compile_ios_tensorflow.sh │ │ ├── download_dependencies.sh │ │ ├── gen_file_lists.sh │ │ ├── proto_text_cc_files.txt │ │ ├── proto_text_pb_cc_files.txt │ │ ├── proto_text_pb_h_files.txt │ │ ├── tf_cc_files.txt │ │ ├── tf_pb_text_files.txt │ │ └── tf_proto_files.txt │ ├── metrics │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── kernels │ │ │ ├── BUILD │ │ │ └── set_kernels.cc │ │ ├── ops │ │ │ └── set_ops.cc │ │ └── python │ │ │ ├── kernel_tests │ │ │ ├── confusion_matrix_ops_test.py │ │ │ ├── histogram_ops_test.py │ │ │ └── set_ops_test.py │ │ │ ├── metrics │ │ │ ├── __init__.py │ │ │ ├── classification.py │ │ │ └── classification_test.py │ │ │ └── ops │ │ │ ├── confusion_matrix_ops.py │ │ │ ├── histogram_ops.py │ │ │ ├── metric_ops.py │ │ │ ├── metric_ops_test.py │ │ │ └── set_ops.py │ ├── opt │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ └── python │ │ │ └── training │ │ │ ├── external_optimizer.py │ │ │ └── external_optimizer_test.py │ ├── quantization │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── kernels │ │ │ ├── BUILD │ │ │ ├── dequantize_op.cc │ │ │ ├── load_quantized_kernels_so.py │ │ │ ├── quantization_utils.h │ │ │ ├── quantization_utils_test.cc │ │ │ ├── quantize_and_dequantize_op.cc │ │ │ ├── quantize_and_dequantize_op.h │ │ │ ├── quantize_and_dequantize_op_gpu.cu.cc │ │ │ ├── quantize_and_dequantize_op_test.cc │ │ │ ├── quantize_down_and_shrink_range.cc │ │ │ ├── quantize_down_and_shrink_range_op_test.cc │ │ │ ├── quantize_op.cc │ │ │ ├── quantize_op_test.cc │ │ │ ├── quantized_activation_ops.cc │ │ │ ├── quantized_activation_ops_test.cc │ │ │ ├── quantized_batch_norm_op.cc │ │ │ ├── quantized_batch_norm_op_test.cc │ │ │ ├── quantized_bias_add_op.cc │ │ │ ├── quantized_bias_add_op_test.cc │ │ │ ├── quantized_concat_op.cc │ │ │ ├── quantized_concat_op_test.cc │ │ │ ├── quantized_conv_ops.cc │ │ │ ├── quantized_conv_ops_test.cc │ │ │ ├── quantized_matmul_op.cc │ │ │ ├── quantized_matmul_op_test.cc │ │ │ ├── quantized_pooling_ops.cc │ │ │ ├── quantized_pooling_ops_test.cc │ │ │ └── reference_gemm.h │ │ ├── load_quantized_ops_so.py │ │ ├── ops │ │ │ ├── array_ops.cc │ │ │ ├── math_ops.cc │ │ │ └── nn_ops.cc │ │ ├── python │ │ │ ├── __init__.py │ │ │ ├── array_ops.py │ │ │ ├── dequantize_op_test.py │ │ │ ├── math_ops.py │ │ │ ├── nn_ops.py │ │ │ └── quantized_conv_ops_test.py │ │ └── tools │ │ │ ├── BUILD │ │ │ ├── graph_to_dot.py │ │ │ ├── quantize_graph.py │ │ │ └── quantize_graph_test.py │ ├── rnn │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ ├── __init__.py │ │ │ ├── kernel_tests │ │ │ └── rnn_cell_test.py │ │ │ └── ops │ │ │ └── rnn_cell.py │ ├── skflow │ │ ├── BUILD │ │ └── __init__.py │ ├── tensor_forest │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── core │ │ │ └── ops │ │ │ │ ├── best_splits_op.cc │ │ │ │ ├── count_extremely_random_stats_op.cc │ │ │ │ ├── finished_nodes_op.cc │ │ │ │ ├── grow_tree_op.cc │ │ │ │ ├── sample_inputs_op.cc │ │ │ │ ├── scatter_add_ndim_op.cc │ │ │ │ ├── tree_predictions_op.cc │ │ │ │ ├── tree_utils.cc │ │ │ │ ├── tree_utils.h │ │ │ │ ├── tree_utils_test.cc │ │ │ │ └── update_fertile_slots_op.cc │ │ └── python │ │ │ ├── __init__.py │ │ │ ├── kernel_tests │ │ │ ├── best_splits_op_test.py │ │ │ ├── count_extremely_random_stats_op_test.py │ │ │ ├── finished_nodes_op_test.py │ │ │ ├── grow_tree_op_test.py │ │ │ ├── sample_inputs_op_test.py │ │ │ ├── scatter_add_ndim_op_test.py │ │ │ ├── tree_predictions_op_test.py │ │ │ └── update_fertile_slots_op_test.py │ │ │ ├── ops │ │ │ ├── inference_ops.py │ │ │ └── training_ops.py │ │ │ ├── tensor_forest.py │ │ │ └── tensor_forest_test.py │ ├── testing │ │ ├── BUILD │ │ ├── __init__.py │ │ └── python │ │ │ └── framework │ │ │ └── test_util.py │ └── util │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── convert_graphdef_memmapped_format.cc │ │ ├── convert_graphdef_memmapped_format_lib.cc │ │ ├── convert_graphdef_memmapped_format_lib.h │ │ ├── convert_graphdef_memmapped_format_test.cc │ │ └── inspect_checkpoint.cc ├── core │ ├── BUILD │ ├── client │ │ ├── tensor_c_api.cc │ │ └── tensor_c_api_test.cc │ ├── common_runtime │ │ ├── allocator_retry.cc │ │ ├── allocator_retry.h │ │ ├── bfc_allocator.cc │ │ ├── bfc_allocator.h │ │ ├── build_graph_options.cc │ │ ├── build_graph_options.h │ │ ├── constant_folding.cc │ │ ├── constant_folding.h │ │ ├── constant_folding_test.cc │ │ ├── copy_tensor.cc │ │ ├── copy_tensor.h │ │ ├── costmodel_manager.cc │ │ ├── costmodel_manager.h │ │ ├── device.cc │ │ ├── device.h │ │ ├── device_factory.cc │ │ ├── device_factory.h │ │ ├── device_mgr.cc │ │ ├── device_mgr.h │ │ ├── device_set.cc │ │ ├── device_set.h │ │ ├── device_set_test.cc │ │ ├── direct_session.cc │ │ ├── direct_session.h │ │ ├── direct_session_test.cc │ │ ├── direct_session_with_tracking_alloc_test.cc │ │ ├── dma_helper.h │ │ ├── eigen_thread_pool.h │ │ ├── executor.cc │ │ ├── executor.h │ │ ├── function.cc │ │ ├── function.h │ │ ├── function_test.cc │ │ ├── gpu │ │ │ ├── cupti_wrapper.cc │ │ │ ├── cupti_wrapper.h │ │ │ ├── gpu_allocator_retry_test.cc │ │ │ ├── gpu_bfc_allocator.cc │ │ │ ├── gpu_bfc_allocator.h │ │ │ ├── gpu_bfc_allocator_test.cc │ │ │ ├── gpu_debug_allocator.cc │ │ │ ├── gpu_debug_allocator.h │ │ │ ├── gpu_debug_allocator_test.cc │ │ │ ├── gpu_device.cc │ │ │ ├── gpu_device.h │ │ │ ├── gpu_device_factory.cc │ │ │ ├── gpu_event_mgr.cc │ │ │ ├── gpu_event_mgr.h │ │ │ ├── gpu_event_mgr_test.cc │ │ │ ├── gpu_init.cc │ │ │ ├── gpu_init.h │ │ │ ├── gpu_stream_util.cc │ │ │ ├── gpu_stream_util.h │ │ │ ├── gpu_stream_util_test.cc │ │ │ ├── gpu_tracer.cc │ │ │ ├── gpu_tracer.h │ │ │ ├── gpu_tracer_test.cc │ │ │ ├── gpu_util.cc │ │ │ ├── gpu_util.h │ │ │ ├── gpu_util_platform_specific.cc │ │ │ ├── pool_allocator.cc │ │ │ ├── pool_allocator.h │ │ │ ├── pool_allocator_test.cc │ │ │ ├── process_state.cc │ │ │ └── process_state.h │ │ ├── gpu_device_context.h │ │ ├── graph_optimizer.cc │ │ ├── graph_optimizer.h │ │ ├── kernel_benchmark_testlib.cc │ │ ├── kernel_benchmark_testlib.h │ │ ├── local_device.cc │ │ ├── local_device.h │ │ ├── memory_types.cc │ │ ├── memory_types.h │ │ ├── memory_types_test.cc │ │ ├── pending_counts.h │ │ ├── pending_counts_test.cc │ │ ├── process_util.cc │ │ ├── process_util.h │ │ ├── rendezvous_mgr.cc │ │ ├── rendezvous_mgr.h │ │ ├── session.cc │ │ ├── session_factory.cc │ │ ├── session_factory.h │ │ ├── session_options.cc │ │ ├── session_state.cc │ │ ├── session_test.cc │ │ ├── simple_graph_execution_state.cc │ │ ├── simple_graph_execution_state.h │ │ ├── simple_placer.cc │ │ ├── simple_placer.h │ │ ├── simple_placer_test.cc │ │ ├── step_stats_collector.cc │ │ ├── step_stats_collector.h │ │ ├── threadpool_device.cc │ │ ├── threadpool_device.h │ │ ├── threadpool_device_factory.cc │ │ └── visitable_allocator.h │ ├── distributed_runtime │ │ ├── BUILD │ │ ├── README.md │ │ ├── base_rendezvous_mgr.cc │ │ ├── base_rendezvous_mgr.h │ │ ├── call_options.cc │ │ ├── call_options.h │ │ ├── call_options_test.cc │ │ ├── executor_test.cc │ │ ├── graph_mgr.cc │ │ ├── graph_mgr.h │ │ ├── master.cc │ │ ├── master.h │ │ ├── master_env.h │ │ ├── master_interface.h │ │ ├── master_session.cc │ │ ├── master_session.h │ │ ├── master_session_interface.h │ │ ├── master_test.cc │ │ ├── remote_device.cc │ │ ├── remote_device.h │ │ ├── remote_device_test.cc │ │ ├── rendezvous_mgr_interface.h │ │ ├── rpc │ │ │ ├── BUILD │ │ │ ├── async_service_interface.h │ │ │ ├── grpc_call.h │ │ │ ├── grpc_channel.cc │ │ │ ├── grpc_channel.h │ │ │ ├── grpc_channel_test.cc │ │ │ ├── grpc_client_cq_tag.h │ │ │ ├── grpc_master_service.cc │ │ │ ├── grpc_master_service.h │ │ │ ├── grpc_remote_master.cc │ │ │ ├── grpc_remote_master.h │ │ │ ├── grpc_remote_worker.cc │ │ │ ├── grpc_remote_worker.h │ │ │ ├── grpc_server_lib.cc │ │ │ ├── grpc_server_lib.h │ │ │ ├── grpc_session.cc │ │ │ ├── grpc_session.h │ │ │ ├── grpc_session_test.cc │ │ │ ├── grpc_tensorflow_server.cc │ │ │ ├── grpc_testlib.cc │ │ │ ├── grpc_testlib.h │ │ │ ├── grpc_testlib_ops.cc │ │ │ ├── grpc_testlib_server.cc │ │ │ ├── grpc_util.h │ │ │ ├── grpc_worker_cache.cc │ │ │ ├── grpc_worker_cache.h │ │ │ ├── grpc_worker_service.cc │ │ │ ├── grpc_worker_service.h │ │ │ ├── rpc_rendezvous_mgr.cc │ │ │ ├── rpc_rendezvous_mgr.h │ │ │ └── rpc_rendezvous_mgr_test.cc │ │ ├── server_lib.cc │ │ ├── server_lib.h │ │ ├── worker_cache.h │ │ ├── worker_cache_logger.cc │ │ ├── worker_cache_logger.h │ │ ├── worker_cache_partial.cc │ │ ├── worker_cache_partial.h │ │ ├── worker_env.h │ │ └── worker_interface.h │ ├── example │ │ ├── example.proto │ │ ├── example_parser_configuration.cc │ │ ├── example_parser_configuration.h │ │ ├── example_parser_configuration_test.cc │ │ ├── feature.proto │ │ ├── feature_util.cc │ │ ├── feature_util.h │ │ ├── feature_util_test.cc │ │ └── testdata │ │ │ └── parse_example_graph_def.pbtxt │ ├── framework │ │ ├── allocation_description.proto │ │ ├── allocator.cc │ │ ├── allocator.h │ │ ├── allocator_test.cc │ │ ├── attr_value.proto │ │ ├── attr_value_util.cc │ │ ├── attr_value_util.h │ │ ├── attr_value_util_test.cc │ │ ├── bfloat16.cc │ │ ├── bfloat16.h │ │ ├── bfloat16_test.cc │ │ ├── cancellation.cc │ │ ├── cancellation.h │ │ ├── cancellation_test.cc │ │ ├── control_flow.h │ │ ├── cost_graph.proto │ │ ├── device_attributes.proto │ │ ├── device_base.cc │ │ ├── device_base.h │ │ ├── fake_input.cc │ │ ├── fake_input.h │ │ ├── function.cc │ │ ├── function.h │ │ ├── function.proto │ │ ├── function_test.cc │ │ ├── function_testlib.cc │ │ ├── function_testlib.h │ │ ├── graph.proto │ │ ├── graph_def_util.cc │ │ ├── graph_def_util.h │ │ ├── graph_def_util_test.cc │ │ ├── kernel_def.proto │ │ ├── kernel_def_builder.cc │ │ ├── kernel_def_builder.h │ │ ├── kernel_def_builder_test.cc │ │ ├── load_library.cc │ │ ├── log_memory.cc │ │ ├── log_memory.h │ │ ├── log_memory.proto │ │ ├── lookup_interface.cc │ │ ├── lookup_interface.h │ │ ├── memory_types.cc │ │ ├── memory_types.h │ │ ├── memory_types_test.cc │ │ ├── node_def_builder.cc │ │ ├── node_def_builder.h │ │ ├── node_def_builder_test.cc │ │ ├── node_def_util.cc │ │ ├── node_def_util.h │ │ ├── node_def_util_test.cc │ │ ├── numeric_op.h │ │ ├── numeric_types.h │ │ ├── op.cc │ │ ├── op.h │ │ ├── op_compatibility_test.cc │ │ ├── op_def.proto │ │ ├── op_def_builder.cc │ │ ├── op_def_builder.h │ │ ├── op_def_builder_test.cc │ │ ├── op_def_util.cc │ │ ├── op_def_util.h │ │ ├── op_def_util_test.cc │ │ ├── op_gen_lib.cc │ │ ├── op_gen_lib.h │ │ ├── op_kernel.cc │ │ ├── op_kernel.h │ │ ├── op_kernel_test.cc │ │ ├── op_segment.cc │ │ ├── op_segment.h │ │ ├── op_segment_test.cc │ │ ├── partial_tensor_shape.cc │ │ ├── partial_tensor_shape.h │ │ ├── partial_tensor_shape_test.cc │ │ ├── queue_interface.h │ │ ├── reader_interface.h │ │ ├── reader_op_kernel.cc │ │ ├── reader_op_kernel.h │ │ ├── register_types.h │ │ ├── rendezvous.cc │ │ ├── rendezvous.h │ │ ├── rendezvous_test.cc │ │ ├── resource_mgr.cc │ │ ├── resource_mgr.h │ │ ├── resource_mgr_test.cc │ │ ├── selective_registration.h │ │ ├── session_state.h │ │ ├── step_stats.proto │ │ ├── summary.proto │ │ ├── tensor.cc │ │ ├── tensor.h │ │ ├── tensor.proto │ │ ├── tensor_description.proto │ │ ├── tensor_reference.cc │ │ ├── tensor_reference.h │ │ ├── tensor_shape.cc │ │ ├── tensor_shape.h │ │ ├── tensor_shape.proto │ │ ├── tensor_shape_test.cc │ │ ├── tensor_slice.cc │ │ ├── tensor_slice.h │ │ ├── tensor_slice.proto │ │ ├── tensor_slice_test.cc │ │ ├── tensor_test.cc │ │ ├── tensor_testutil.cc │ │ ├── tensor_testutil.h │ │ ├── tensor_types.h │ │ ├── tensor_util.cc │ │ ├── tensor_util.h │ │ ├── tensor_util_test.cc │ │ ├── tracking_allocator.cc │ │ ├── tracking_allocator.h │ │ ├── tracking_allocator_test.cc │ │ ├── type_index.h │ │ ├── type_traits.h │ │ ├── types.cc │ │ ├── types.h │ │ ├── types.proto │ │ ├── types_test.cc │ │ ├── unique_tensor_references.cc │ │ ├── unique_tensor_references.h │ │ ├── unique_tensor_references_test.cc │ │ ├── variable.proto │ │ ├── versions.cc │ │ ├── versions.h │ │ └── versions.proto │ ├── graph │ │ ├── algorithm.cc │ │ ├── algorithm.h │ │ ├── algorithm_test.cc │ │ ├── colors.cc │ │ ├── colors.h │ │ ├── costmodel.cc │ │ ├── costmodel.h │ │ ├── default_device.h │ │ ├── dot.cc │ │ ├── dot.h │ │ ├── edgeset.cc │ │ ├── edgeset.h │ │ ├── edgeset_test.cc │ │ ├── equal_graph_def.cc │ │ ├── equal_graph_def.h │ │ ├── equal_graph_def_test.cc │ │ ├── gradients.cc │ │ ├── gradients.h │ │ ├── graph.cc │ │ ├── graph.h │ │ ├── graph_constructor.cc │ │ ├── graph_constructor.h │ │ ├── graph_constructor_test.cc │ │ ├── graph_def_builder.cc │ │ ├── graph_def_builder.h │ │ ├── graph_def_builder_test.cc │ │ ├── graph_partition.cc │ │ ├── graph_partition.h │ │ ├── graph_partition_test.cc │ │ ├── graph_test.cc │ │ ├── node_builder.cc │ │ ├── node_builder.h │ │ ├── node_builder_test.cc │ │ ├── optimizer_cse.cc │ │ ├── optimizer_cse.h │ │ ├── optimizer_cse_test.cc │ │ ├── subgraph.cc │ │ ├── subgraph.h │ │ ├── subgraph_test.cc │ │ ├── tensor_id.cc │ │ ├── tensor_id.h │ │ ├── tensor_id_test.cc │ │ ├── testlib.cc │ │ ├── testlib.h │ │ ├── types.h │ │ ├── validate.cc │ │ ├── validate.h │ │ └── validate_test.cc │ ├── kernels │ │ ├── BUILD │ │ ├── adjust_contrast_op.cc │ │ ├── adjust_contrast_op.h │ │ ├── adjust_contrast_op_benchmark_test.cc │ │ ├── adjust_contrast_op_gpu.cu.cc │ │ ├── adjust_contrast_op_test.cc │ │ ├── aggregate_ops.cc │ │ ├── aggregate_ops.h │ │ ├── aggregate_ops_cpu.h │ │ ├── aggregate_ops_gpu.cu.cc │ │ ├── argmax_op.cc │ │ ├── argmax_op.h │ │ ├── argmax_op_gpu.cu.cc │ │ ├── assign_op.h │ │ ├── attention_ops.cc │ │ ├── avgpooling_op.cc │ │ ├── avgpooling_op.h │ │ ├── avgpooling_op_gpu.cu.cc │ │ ├── basic_ops_benchmark_test.cc │ │ ├── batch_matmul_op.cc │ │ ├── batch_matrix_band_part_op.cc │ │ ├── batch_matrix_band_part_op.h │ │ ├── batch_matrix_band_part_op_gpu.cu.cc │ │ ├── batch_matrix_diag_op.cc │ │ ├── batch_matrix_diag_op.h │ │ ├── batch_matrix_diag_op_gpu.cu.cc │ │ ├── batch_norm_op.cc │ │ ├── batch_norm_op.h │ │ ├── batch_norm_op_gpu.cu.cc │ │ ├── batch_norm_op_test.cc │ │ ├── batchtospace_op.cc │ │ ├── batchtospace_op.h │ │ ├── batchtospace_op_gpu.cu.cc │ │ ├── bcast_ops.cc │ │ ├── bias_op.cc │ │ ├── bias_op.h │ │ ├── bias_op_gpu.cu.cc │ │ ├── bias_op_gpu.h │ │ ├── binary_linalg_ops_common.cc │ │ ├── binary_linalg_ops_common.h │ │ ├── bitcast_op.cc │ │ ├── bitcast_op.h │ │ ├── bounds_check.h │ │ ├── candidate_sampler_ops.cc │ │ ├── cast_op.cc │ │ ├── cast_op.h │ │ ├── cast_op_gpu.cu.cc │ │ ├── cast_op_test.cc │ │ ├── check_numerics_op.cc │ │ ├── check_numerics_op_gpu.cu.cc │ │ ├── cholesky_grad.cc │ │ ├── cholesky_op.cc │ │ ├── colorspace_op.cc │ │ ├── colorspace_op.h │ │ ├── colorspace_op_gpu.cu.cc │ │ ├── colorspace_op_test.cc │ │ ├── concat_lib.h │ │ ├── concat_lib_cpu.cc │ │ ├── concat_lib_gpu.cu.cc │ │ ├── concat_op.cc │ │ ├── concat_op_test.cc │ │ ├── constant_op.cc │ │ ├── constant_op.h │ │ ├── constant_op_gpu.cu.cc │ │ ├── constant_op_test.cc │ │ ├── control_flow_ops.cc │ │ ├── control_flow_ops.h │ │ ├── control_flow_ops_test.cc │ │ ├── conv_2d.h │ │ ├── conv_3d.h │ │ ├── conv_grad_ops.cc │ │ ├── conv_grad_ops_3d.cc │ │ ├── conv_ops.cc │ │ ├── conv_ops_3d.cc │ │ ├── conv_ops_gpu.h │ │ ├── conv_ops_gpu_2.cu.cc │ │ ├── conv_ops_gpu_3.cu.cc │ │ ├── count_up_to_op.cc │ │ ├── cross_op.cc │ │ ├── cross_op.h │ │ ├── cross_op_gpu.cu.cc │ │ ├── cross_op_test.cc │ │ ├── ctc_decoder_ops.cc │ │ ├── ctc_loss_op.cc │ │ ├── cuda_device_array.h │ │ ├── cuda_device_array_gpu.h │ │ ├── cudnn_pooling_gpu.cc │ │ ├── cudnn_pooling_gpu.h │ │ ├── cwise_op_abs.cc │ │ ├── cwise_op_acos.cc │ │ ├── cwise_op_add.cc │ │ ├── cwise_op_asin.cc │ │ ├── cwise_op_atan.cc │ │ ├── cwise_op_ceil.cc │ │ ├── cwise_op_complex.cc │ │ ├── cwise_op_conj.cc │ │ ├── cwise_op_cos.cc │ │ ├── cwise_op_digamma.cc │ │ ├── cwise_op_div.cc │ │ ├── cwise_op_equal_to.cc │ │ ├── cwise_op_erf.cc │ │ ├── cwise_op_erfc.cc │ │ ├── cwise_op_exp.cc │ │ ├── cwise_op_floor.cc │ │ ├── cwise_op_gpu_abs.cu.cc │ │ ├── cwise_op_gpu_acos.cu.cc │ │ ├── cwise_op_gpu_add.cu.cc │ │ ├── cwise_op_gpu_asin.cu.cc │ │ ├── cwise_op_gpu_atan.cu.cc │ │ ├── cwise_op_gpu_ceil.cu.cc │ │ ├── cwise_op_gpu_complex.cu.cc │ │ ├── cwise_op_gpu_conj.cu.cc │ │ ├── cwise_op_gpu_cos.cu.cc │ │ ├── cwise_op_gpu_digamma.cu.cc │ │ ├── cwise_op_gpu_div.cu.cc │ │ ├── cwise_op_gpu_equal_to.cu.cc │ │ ├── cwise_op_gpu_erf.cu.cc │ │ ├── cwise_op_gpu_erfc.cu.cc │ │ ├── cwise_op_gpu_exp.cu.cc │ │ ├── cwise_op_gpu_floor.cu.cc │ │ ├── cwise_op_gpu_greater.cu.cc │ │ ├── cwise_op_gpu_greater_equal.cu.cc │ │ ├── cwise_op_gpu_igammas.cu.cc │ │ ├── cwise_op_gpu_imag.cu.cc │ │ ├── cwise_op_gpu_inverse.cu.cc │ │ ├── cwise_op_gpu_isfinite.cu.cc │ │ ├── cwise_op_gpu_isinf.cu.cc │ │ ├── cwise_op_gpu_isnan.cu.cc │ │ ├── cwise_op_gpu_less.cu.cc │ │ ├── cwise_op_gpu_less_equal.cu.cc │ │ ├── cwise_op_gpu_lgamma.cu.cc │ │ ├── cwise_op_gpu_log.cu.cc │ │ ├── cwise_op_gpu_logical_and.cu.cc │ │ ├── cwise_op_gpu_logical_not.cu.cc │ │ ├── cwise_op_gpu_logical_or.cu.cc │ │ ├── cwise_op_gpu_maximum.cu.cc │ │ ├── cwise_op_gpu_minimum.cu.cc │ │ ├── cwise_op_gpu_mod.cu.cc │ │ ├── cwise_op_gpu_mul.cu.cc │ │ ├── cwise_op_gpu_neg.cu.cc │ │ ├── cwise_op_gpu_not_equal_to.cu.cc │ │ ├── cwise_op_gpu_pow.cu.cc │ │ ├── cwise_op_gpu_real.cu.cc │ │ ├── cwise_op_gpu_rsqrt.cu.cc │ │ ├── cwise_op_gpu_select.cu.cc │ │ ├── cwise_op_gpu_sigmoid.cu.cc │ │ ├── cwise_op_gpu_sign.cu.cc │ │ ├── cwise_op_gpu_sin.cu.cc │ │ ├── cwise_op_gpu_sqrt.cu.cc │ │ ├── cwise_op_gpu_square.cu.cc │ │ ├── cwise_op_gpu_squared_difference.cu.cc │ │ ├── cwise_op_gpu_sub.cu.cc │ │ ├── cwise_op_gpu_tan.cu.cc │ │ ├── cwise_op_gpu_tanh.cu.cc │ │ ├── cwise_op_gpu_zeta.cu.cc │ │ ├── cwise_op_greater.cc │ │ ├── cwise_op_greater_equal.cc │ │ ├── cwise_op_igammas.cc │ │ ├── cwise_op_imag.cc │ │ ├── cwise_op_inverse.cc │ │ ├── cwise_op_isfinite.cc │ │ ├── cwise_op_isinf.cc │ │ ├── cwise_op_isnan.cc │ │ ├── cwise_op_less.cc │ │ ├── cwise_op_less_equal.cc │ │ ├── cwise_op_lgamma.cc │ │ ├── cwise_op_log.cc │ │ ├── cwise_op_logical_and.cc │ │ ├── cwise_op_logical_not.cc │ │ ├── cwise_op_logical_or.cc │ │ ├── cwise_op_maximum.cc │ │ ├── cwise_op_minimum.cc │ │ ├── cwise_op_mod.cc │ │ ├── cwise_op_mul.cc │ │ ├── cwise_op_neg.cc │ │ ├── cwise_op_not_equal_to.cc │ │ ├── cwise_op_pow.cc │ │ ├── cwise_op_real.cc │ │ ├── cwise_op_rsqrt.cc │ │ ├── cwise_op_select.cc │ │ ├── cwise_op_sigmoid.cc │ │ ├── cwise_op_sign.cc │ │ ├── cwise_op_sin.cc │ │ ├── cwise_op_sqrt.cc │ │ ├── cwise_op_square.cc │ │ ├── cwise_op_squared_difference.cc │ │ ├── cwise_op_sub.cc │ │ ├── cwise_op_tan.cc │ │ ├── cwise_op_tanh.cc │ │ ├── cwise_op_zeta.cc │ │ ├── cwise_ops.h │ │ ├── cwise_ops_common.cc │ │ ├── cwise_ops_common.h │ │ ├── cwise_ops_gpu_common.cu.h │ │ ├── cwise_ops_test.cc │ │ ├── decode_csv_op.cc │ │ ├── decode_jpeg_op.cc │ │ ├── decode_png_op.cc │ │ ├── decode_raw_op.cc │ │ ├── dense_update_ops.cc │ │ ├── dense_update_ops.h │ │ ├── dense_update_ops_gpu.cu.cc │ │ ├── depthtospace_op.cc │ │ ├── depthtospace_op.h │ │ ├── depthtospace_op_gpu.cu.cc │ │ ├── depthwise_conv_grad_op.cc │ │ ├── depthwise_conv_op.cc │ │ ├── depthwise_conv_op.h │ │ ├── depthwise_conv_op_gpu.cu.cc │ │ ├── determinant_op.cc │ │ ├── diag_op.cc │ │ ├── draw_bounding_box_op.cc │ │ ├── dynamic_partition_op.cc │ │ ├── dynamic_partition_op_test.cc │ │ ├── dynamic_stitch_op.cc │ │ ├── dynamic_stitch_op_test.cc │ │ ├── edit_distance_op.cc │ │ ├── eigen_activations.h │ │ ├── eigen_activations_test.cc │ │ ├── eigen_attention.h │ │ ├── eigen_attention_test.cc │ │ ├── eigen_backward_cuboid_convolutions.h │ │ ├── eigen_backward_spatial_convolutions.h │ │ ├── eigen_backward_spatial_convolutions_test.cc │ │ ├── eigen_cuboid_convolution.h │ │ ├── eigen_patch_3d.h │ │ ├── eigen_pooling.h │ │ ├── eigen_pooling_test.cc │ │ ├── eigen_softmax.h │ │ ├── eigen_softmax_test.cc │ │ ├── eigen_spatial_convolutions.h │ │ ├── eigen_spatial_convolutions_test.cc │ │ ├── encode_jpeg_op.cc │ │ ├── encode_png_op.cc │ │ ├── example_parsing_ops.cc │ │ ├── example_parsing_ops_test.cc │ │ ├── fact_op.cc │ │ ├── fft_ops.cc │ │ ├── fifo_queue.cc │ │ ├── fifo_queue.h │ │ ├── fifo_queue_op.cc │ │ ├── fill_functor.h │ │ ├── fixed_length_record_reader_op.cc │ │ ├── gather_nd_op.cc │ │ ├── gather_nd_op.h │ │ ├── gather_nd_op_gpu.cu.cc │ │ ├── gather_nd_op_test.cc │ │ ├── gather_op.cc │ │ ├── gather_op.h │ │ ├── gather_op_gpu.cu.cc │ │ ├── gather_op_test.cc │ │ ├── identity_op.cc │ │ ├── identity_op.h │ │ ├── identity_op_test.cc │ │ ├── identity_reader_op.cc │ │ ├── image_resizer_state.h │ │ ├── immutable_constant_op.cc │ │ ├── immutable_constant_op.h │ │ ├── immutable_constant_op_test.cc │ │ ├── in_topk_op.cc │ │ ├── initializable_lookup_table.cc │ │ ├── initializable_lookup_table.h │ │ ├── l2loss_op.cc │ │ ├── l2loss_op.h │ │ ├── l2loss_op_gpu.cu.cc │ │ ├── linalg_ops_common.cc │ │ ├── linalg_ops_common.h │ │ ├── listdiff_op.cc │ │ ├── logging_ops.cc │ │ ├── logging_ops_test.cc │ │ ├── lookup_table_init_op.cc │ │ ├── lookup_table_op.cc │ │ ├── lookup_table_op.h │ │ ├── lookup_util.cc │ │ ├── lookup_util.h │ │ ├── lrn_op.cc │ │ ├── lrn_op_test.cc │ │ ├── matching_files_op.cc │ │ ├── matmul_op.cc │ │ ├── matmul_op.h │ │ ├── matmul_op_test.cc │ │ ├── matrix_inverse_op.cc │ │ ├── matrix_solve_ls_op.cc │ │ ├── matrix_solve_op.cc │ │ ├── matrix_triangular_solve_op.cc │ │ ├── maxpooling_op.cc │ │ ├── maxpooling_op.h │ │ ├── maxpooling_op_gpu.cu.cc │ │ ├── maxpooling_op_gpu.h │ │ ├── mirror_pad_op.cc │ │ ├── mirror_pad_op.h │ │ ├── mirror_pad_op_gpu.cu.cc │ │ ├── multinomial_op_test.cc │ │ ├── nn_ops_test.cc │ │ ├── no_op.cc │ │ ├── no_op.h │ │ ├── one_hot_op.cc │ │ ├── one_hot_op.h │ │ ├── one_hot_op_gpu.cu.cc │ │ ├── ops_testutil.h │ │ ├── ops_util.cc │ │ ├── ops_util.h │ │ ├── ops_util_test.cc │ │ ├── pack_op.cc │ │ ├── pad_op.cc │ │ ├── pad_op.h │ │ ├── pad_op_gpu.cu.cc │ │ ├── padding_fifo_queue.cc │ │ ├── padding_fifo_queue.h │ │ ├── padding_fifo_queue_op.cc │ │ ├── pooling_ops_3d.cc │ │ ├── pooling_ops_common.cc │ │ ├── pooling_ops_common.h │ │ ├── pooling_ops_common_gpu.h │ │ ├── queue_base.cc │ │ ├── queue_base.h │ │ ├── queue_op.h │ │ ├── queue_ops.cc │ │ ├── random_crop_op.cc │ │ ├── random_op.cc │ │ ├── random_op.h │ │ ├── random_op_gpu.cu.cc │ │ ├── random_op_test.cc │ │ ├── random_shuffle_op.cc │ │ ├── random_shuffle_queue_op.cc │ │ ├── range_sampler.cc │ │ ├── range_sampler.h │ │ ├── range_sampler_test.cc │ │ ├── reader_base.cc │ │ ├── reader_base.h │ │ ├── reader_base.proto │ │ ├── reader_ops.cc │ │ ├── reduce_join_op.cc │ │ ├── reduction_ops.h │ │ ├── reduction_ops_all.cc │ │ ├── reduction_ops_any.cc │ │ ├── reduction_ops_common.cc │ │ ├── reduction_ops_common.h │ │ ├── reduction_ops_gpu.cu.cc │ │ ├── reduction_ops_max.cc │ │ ├── reduction_ops_mean.cc │ │ ├── reduction_ops_min.cc │ │ ├── reduction_ops_prod.cc │ │ ├── reduction_ops_sum.cc │ │ ├── reduction_ops_test.cc │ │ ├── relu_op.cc │ │ ├── relu_op.h │ │ ├── relu_op_functor.h │ │ ├── relu_op_gpu.cu.cc │ │ ├── reshape_op.cc │ │ ├── reshape_op.h │ │ ├── resize_area_op.cc │ │ ├── resize_bicubic_op.cc │ │ ├── resize_bicubic_op_test.cc │ │ ├── resize_bilinear_op.cc │ │ ├── resize_bilinear_op_test.cc │ │ ├── resize_nearest_neighbor_op.cc │ │ ├── resize_nearest_neighbor_op_benchmark_test.cc │ │ ├── resize_nearest_neighbor_op_gpu.cu.cc │ │ ├── resize_nearest_neighbor_op_gpu.h │ │ ├── resize_nearest_neighbor_op_test.cc │ │ ├── restore_op.cc │ │ ├── restore_op_test.cc │ │ ├── reverse_op.cc │ │ ├── reverse_op.h │ │ ├── reverse_op_gpu.cu.cc │ │ ├── reverse_op_test.cc │ │ ├── reverse_sequence_op.cc │ │ ├── reverse_sequence_op.h │ │ ├── reverse_sequence_op_gpu.cu.cc │ │ ├── sample_distorted_bounding_box_op.cc │ │ ├── save_op.cc │ │ ├── save_op_test.cc │ │ ├── save_restore_tensor.cc │ │ ├── save_restore_tensor.h │ │ ├── scatter_op.cc │ │ ├── scatter_op.h │ │ ├── scatter_op_gpu.cu.cc │ │ ├── scatter_op_test.cc │ │ ├── segment_reduction_ops.cc │ │ ├── segment_reduction_ops_test.cc │ │ ├── self_adjoint_eig_op.cc │ │ ├── sendrecv_ops.cc │ │ ├── sendrecv_ops.h │ │ ├── sequence_ops.cc │ │ ├── serialize_sparse_op.cc │ │ ├── session_ops.cc │ │ ├── shape_ops.cc │ │ ├── slice_op.cc │ │ ├── slice_op.h │ │ ├── slice_op_gpu.cu.cc │ │ ├── slice_op_test.cc │ │ ├── softmax_op.cc │ │ ├── softmax_op.h │ │ ├── softmax_op_functor.h │ │ ├── softmax_op_gpu.cu.cc │ │ ├── softplus_op.cc │ │ ├── softplus_op.h │ │ ├── softplus_op_gpu.cu.cc │ │ ├── softsign_op.cc │ │ ├── softsign_op.h │ │ ├── softsign_op_gpu.cu.cc │ │ ├── spacetobatch_op.cc │ │ ├── spacetobatch_op.h │ │ ├── spacetobatch_op_gpu.cu.cc │ │ ├── spacetodepth_op.cc │ │ ├── spacetodepth_op.h │ │ ├── spacetodepth_op_gpu.cu.cc │ │ ├── sparse_add_grad_op.cc │ │ ├── sparse_add_op.cc │ │ ├── sparse_add_op_test.cc │ │ ├── sparse_concat_op.cc │ │ ├── sparse_dense_binary_op_shared.cc │ │ ├── sparse_dense_binary_op_shared_test.cc │ │ ├── sparse_matmul_op.cc │ │ ├── sparse_matmul_op.h │ │ ├── sparse_matmul_op_test.cc │ │ ├── sparse_reduce_sum_op.cc │ │ ├── sparse_reduce_sum_op_test.cc │ │ ├── sparse_reorder_op.cc │ │ ├── sparse_softmax_op.cc │ │ ├── sparse_split_op.cc │ │ ├── sparse_tensor_dense_add_op.cc │ │ ├── sparse_tensor_dense_add_op.h │ │ ├── sparse_tensor_dense_matmul_op.cc │ │ ├── sparse_tensor_dense_matmul_op.h │ │ ├── sparse_tensor_dense_matmul_op_gpu.cu.cc │ │ ├── sparse_tensor_dense_matmul_op_test.cc │ │ ├── sparse_to_dense_op.cc │ │ ├── sparse_to_dense_op_test.cc │ │ ├── sparse_xent_op.cc │ │ ├── sparse_xent_op.h │ │ ├── sparse_xent_op_gpu.cu.cc │ │ ├── sparse_xent_op_test.cc │ │ ├── split_lib.h │ │ ├── split_lib_cpu.cc │ │ ├── split_lib_gpu.cu.cc │ │ ├── split_op.cc │ │ ├── stack_ops.cc │ │ ├── string_to_hash_bucket_op.cc │ │ ├── string_to_hash_bucket_op.h │ │ ├── string_to_number_op.cc │ │ ├── summary_audio_op.cc │ │ ├── summary_audio_op_test.cc │ │ ├── summary_image_op.cc │ │ ├── summary_image_op_test.cc │ │ ├── summary_op.cc │ │ ├── summary_op_test.cc │ │ ├── tensor_array.cc │ │ ├── tensor_array.h │ │ ├── tensor_array_ops.cc │ │ ├── text_line_reader_op.cc │ │ ├── tf_record_reader_op.cc │ │ ├── tile_ops.cc │ │ ├── tile_ops.h │ │ ├── tile_ops_gpu.cu.cc │ │ ├── topk_op.cc │ │ ├── training_ops.cc │ │ ├── training_ops.h │ │ ├── training_ops_gpu.cu.cc │ │ ├── training_ops_test.cc │ │ ├── transpose_functor.h │ │ ├── transpose_functor_cpu.cc │ │ ├── transpose_functor_gpu.cu.cc │ │ ├── transpose_op.cc │ │ ├── transpose_op.h │ │ ├── typed_queue.h │ │ ├── unique_op.cc │ │ ├── unique_op_test.cc │ │ ├── unpack_op.cc │ │ ├── variable_ops.cc │ │ ├── variable_ops.h │ │ ├── where_op.cc │ │ ├── where_op.h │ │ ├── whole_file_read_ops.cc │ │ ├── xent_op.cc │ │ ├── xent_op.h │ │ ├── xent_op_gpu.cu.cc │ │ └── xent_op_test.cc │ ├── lib │ │ ├── core │ │ │ ├── arena.cc │ │ │ ├── arena.h │ │ │ ├── arena_test.cc │ │ │ ├── bit_cast_test.cc │ │ │ ├── bits.h │ │ │ ├── blocking_counter.h │ │ │ ├── blocking_counter_test.cc │ │ │ ├── casts.h │ │ │ ├── coding.cc │ │ │ ├── coding.h │ │ │ ├── coding_test.cc │ │ │ ├── error_codes.proto │ │ │ ├── errors.h │ │ │ ├── notification.h │ │ │ ├── notification_test.cc │ │ │ ├── raw_coding.h │ │ │ ├── refcount.h │ │ │ ├── refcount_test.cc │ │ │ ├── status.cc │ │ │ ├── status.h │ │ │ ├── status_test.cc │ │ │ ├── status_test_util.h │ │ │ ├── stringpiece.cc │ │ │ ├── stringpiece.h │ │ │ ├── stringpiece_test.cc │ │ │ ├── threadpool.cc │ │ │ ├── threadpool.h │ │ │ └── threadpool_test.cc │ │ ├── gtl │ │ │ ├── array_slice.h │ │ │ ├── array_slice_internal.h │ │ │ ├── array_slice_test.cc │ │ │ ├── edit_distance.h │ │ │ ├── edit_distance_test.cc │ │ │ ├── inlined_vector.h │ │ │ ├── inlined_vector_test.cc │ │ │ ├── int_type.h │ │ │ ├── int_type_test.cc │ │ │ ├── iterator_range.h │ │ │ ├── iterator_range_test.cc │ │ │ ├── manual_constructor.h │ │ │ ├── manual_constructor_test.cc │ │ │ ├── map_util.h │ │ │ ├── map_util_test.cc │ │ │ ├── stl_util.h │ │ │ ├── top_n.h │ │ │ └── top_n_test.cc │ │ ├── hash │ │ │ ├── crc32c.cc │ │ │ ├── crc32c.h │ │ │ ├── crc32c_test.cc │ │ │ ├── hash.cc │ │ │ ├── hash.h │ │ │ └── hash_test.cc │ │ ├── histogram │ │ │ ├── histogram.cc │ │ │ ├── histogram.h │ │ │ └── histogram_test.cc │ │ ├── io │ │ │ ├── block.cc │ │ │ ├── block.h │ │ │ ├── block_builder.cc │ │ │ ├── block_builder.h │ │ │ ├── format.cc │ │ │ ├── format.h │ │ │ ├── inputbuffer.cc │ │ │ ├── inputbuffer.h │ │ │ ├── inputbuffer_test.cc │ │ │ ├── iterator.cc │ │ │ ├── iterator.h │ │ │ ├── match.cc │ │ │ ├── match.h │ │ │ ├── match_test.cc │ │ │ ├── path.cc │ │ │ ├── path.h │ │ │ ├── path_test.cc │ │ │ ├── record_reader.cc │ │ │ ├── record_reader.h │ │ │ ├── record_writer.cc │ │ │ ├── record_writer.h │ │ │ ├── recordio_test.cc │ │ │ ├── table.cc │ │ │ ├── table.h │ │ │ ├── table_builder.cc │ │ │ ├── table_builder.h │ │ │ ├── table_format.txt │ │ │ ├── table_options.h │ │ │ ├── table_test.cc │ │ │ ├── two_level_iterator.cc │ │ │ └── two_level_iterator.h │ │ ├── jpeg │ │ │ ├── jpeg_handle.cc │ │ │ ├── jpeg_handle.h │ │ │ ├── jpeg_mem.cc │ │ │ ├── jpeg_mem.h │ │ │ ├── jpeg_mem_unittest.cc │ │ │ └── testdata │ │ │ │ ├── bad_huffman.jpg │ │ │ │ ├── corrupt.jpg │ │ │ │ ├── corrupt34_2.jpg │ │ │ │ ├── corrupt34_3.jpg │ │ │ │ ├── corrupt34_4.jpg │ │ │ │ ├── jpeg_merge_test1.jpg │ │ │ │ └── jpeg_merge_test1_cmyk.jpg │ │ ├── png │ │ │ ├── png_io.cc │ │ │ ├── png_io.h │ │ │ └── testdata │ │ │ │ ├── lena_gray.png │ │ │ │ └── lena_rgba.png │ │ ├── random │ │ │ ├── distribution_sampler.cc │ │ │ ├── distribution_sampler.h │ │ │ ├── distribution_sampler_test.cc │ │ │ ├── exact_uniform_int.h │ │ │ ├── philox_random.h │ │ │ ├── philox_random_test.cc │ │ │ ├── philox_random_test_utils.h │ │ │ ├── random.cc │ │ │ ├── random.h │ │ │ ├── random_distributions.h │ │ │ ├── random_distributions_test.cc │ │ │ ├── random_test.cc │ │ │ ├── simple_philox.cc │ │ │ ├── simple_philox.h │ │ │ ├── simple_philox_test.cc │ │ │ ├── weighted_picker.cc │ │ │ ├── weighted_picker.h │ │ │ └── weighted_picker_test.cc │ │ ├── strings │ │ │ ├── numbers.cc │ │ │ ├── numbers.h │ │ │ ├── numbers_test.cc │ │ │ ├── ordered_code.cc │ │ │ ├── ordered_code.h │ │ │ ├── ordered_code_test.cc │ │ │ ├── proto_text_util.cc │ │ │ ├── proto_text_util.h │ │ │ ├── regexp.h │ │ │ ├── scanner.cc │ │ │ ├── scanner.h │ │ │ ├── scanner_test.cc │ │ │ ├── str_util.cc │ │ │ ├── str_util.h │ │ │ ├── str_util_test.cc │ │ │ ├── strcat.cc │ │ │ ├── strcat.h │ │ │ ├── strcat_test.cc │ │ │ ├── stringprintf.cc │ │ │ ├── stringprintf.h │ │ │ └── stringprintf_test.cc │ │ └── wav │ │ │ ├── wav_io.cc │ │ │ ├── wav_io.h │ │ │ └── wav_io_test.cc │ ├── ops │ │ ├── array_grad.cc │ │ ├── array_grad_test.cc │ │ ├── array_ops.cc │ │ ├── candidate_sampling_ops.cc │ │ ├── compat │ │ │ ├── BUILD │ │ │ ├── backwards_compatibility_test.cc │ │ │ ├── op_compatibility_lib.cc │ │ │ ├── op_compatibility_lib.h │ │ │ ├── ops_history.v0.pbtxt │ │ │ └── update_ops_main.cc │ │ ├── control_flow_ops.cc │ │ ├── ctc_ops.cc │ │ ├── data_flow_ops.cc │ │ ├── function_ops.cc │ │ ├── functional_grad.cc │ │ ├── functional_ops.cc │ │ ├── image_ops.cc │ │ ├── io_ops.cc │ │ ├── linalg_ops.cc │ │ ├── logging_ops.cc │ │ ├── math_grad.cc │ │ ├── math_grad_test.cc │ │ ├── math_ops.cc │ │ ├── nn_grad.cc │ │ ├── nn_ops.cc │ │ ├── no_op.cc │ │ ├── ops.pbtxt │ │ ├── parsing_ops.cc │ │ ├── random_grad.cc │ │ ├── random_ops.cc │ │ ├── script_ops.cc │ │ ├── sendrecv_ops.cc │ │ ├── sparse_ops.cc │ │ ├── state_ops.cc │ │ ├── string_ops.cc │ │ └── training_ops.cc │ ├── platform │ │ ├── cloud │ │ │ ├── BUILD │ │ │ ├── auth_provider.h │ │ │ ├── base64.cc │ │ │ ├── base64.h │ │ │ ├── base64_test.cc │ │ │ ├── gcs_file_system.cc │ │ │ ├── gcs_file_system.h │ │ │ ├── gcs_file_system_test.cc │ │ │ ├── google_auth_provider.cc │ │ │ ├── google_auth_provider.h │ │ │ ├── google_auth_provider_test.cc │ │ │ ├── http_request.cc │ │ │ ├── http_request.h │ │ │ ├── http_request_fake.h │ │ │ ├── http_request_test.cc │ │ │ ├── oauth_client.cc │ │ │ ├── oauth_client.h │ │ │ ├── oauth_client_test.cc │ │ │ └── testdata │ │ │ │ ├── application_default_credentials.json │ │ │ │ ├── service_account_credentials.json │ │ │ │ └── service_account_public_key.txt │ │ ├── cuda.h │ │ ├── default │ │ │ ├── build_config.bzl │ │ │ ├── build_config │ │ │ │ └── BUILD │ │ │ ├── build_config_root.bzl │ │ │ ├── dynamic_annotations.h │ │ │ ├── fingerprint.h │ │ │ ├── integral_types.h │ │ │ ├── logging.cc │ │ │ ├── logging.h │ │ │ ├── mutex.h │ │ │ ├── platform.bzl │ │ │ ├── protobuf.h │ │ │ ├── stream_executor.h │ │ │ ├── strong_hash.h │ │ │ ├── test_benchmark.cc │ │ │ ├── thread_annotations.h │ │ │ ├── tracing.cc │ │ │ └── tracing_impl.h │ │ ├── demangle.h │ │ ├── denormal.cc │ │ ├── denormal.h │ │ ├── env.cc │ │ ├── env.h │ │ ├── env_test.cc │ │ ├── file_system.cc │ │ ├── file_system.h │ │ ├── fingerprint.h │ │ ├── host_info.h │ │ ├── init_main.h │ │ ├── integral_types_test.cc │ │ ├── jpeg.h │ │ ├── load_library.cc │ │ ├── load_library.h │ │ ├── logging.h │ │ ├── logging_test.cc │ │ ├── macros.h │ │ ├── mem.h │ │ ├── mutex.h │ │ ├── platform.h │ │ ├── png.h │ │ ├── port_test.cc │ │ ├── posix │ │ │ ├── env.cc │ │ │ ├── port.cc │ │ │ ├── posix_file_system.cc │ │ │ ├── posix_file_system.h │ │ │ └── test.cc │ │ ├── protobuf.h │ │ ├── protobuf_util.cc │ │ ├── regexp.h │ │ ├── snappy.h │ │ ├── stream_executor.h │ │ ├── strong_hash.h │ │ ├── tensor_coding.cc │ │ ├── tensor_coding.h │ │ ├── test.cc │ │ ├── test.h │ │ ├── test_benchmark.h │ │ ├── test_main.cc │ │ ├── thread_annotations.h │ │ ├── tracing.cc │ │ ├── tracing.h │ │ └── types.h │ ├── protobuf │ │ ├── config.proto │ │ ├── master.proto │ │ ├── master_service.proto │ │ ├── meta_graph.proto │ │ ├── named_tensor.proto │ │ ├── queue_runner.proto │ │ ├── saver.proto │ │ ├── tensorflow_server.proto │ │ ├── worker.proto │ │ └── worker_service.proto │ ├── public │ │ ├── README.md │ │ ├── session.h │ │ ├── session_options.h │ │ ├── tensor_c_api.h │ │ └── version.h │ ├── user_ops │ │ ├── BUILD │ │ ├── build.sh │ │ ├── fact.cc │ │ ├── roi_pooling_op.cc │ │ ├── roi_pooling_op.cu.cc │ │ ├── roi_pooling_op.cu.o │ │ ├── roi_pooling_op.so │ │ ├── roi_pooling_op_grad.cc │ │ └── roi_pooling_op_grad.so │ └── util │ │ ├── bcast.cc │ │ ├── bcast.h │ │ ├── bcast_test.cc │ │ ├── checkpoint_reader.cc │ │ ├── checkpoint_reader.h │ │ ├── command_line_flags.cc │ │ ├── command_line_flags.h │ │ ├── command_line_flags_test.cc │ │ ├── ctc │ │ ├── BUILD │ │ ├── ctc_beam_entry.h │ │ ├── ctc_beam_scorer.h │ │ ├── ctc_beam_search.h │ │ ├── ctc_beam_search_test.cc │ │ ├── ctc_decoder.h │ │ ├── ctc_loss_calculator.cc │ │ ├── ctc_loss_calculator.h │ │ └── ctc_loss_util.h │ │ ├── cuda_kernel_helper.h │ │ ├── device_name_utils.cc │ │ ├── device_name_utils.h │ │ ├── device_name_utils_test.cc │ │ ├── event.proto │ │ ├── events_writer.cc │ │ ├── events_writer.h │ │ ├── events_writer_test.cc │ │ ├── example_proto_helper.cc │ │ ├── example_proto_helper.h │ │ ├── example_proto_helper_test.cc │ │ ├── guarded_philox_random.cc │ │ ├── guarded_philox_random.h │ │ ├── memmapped_file_system.cc │ │ ├── memmapped_file_system.h │ │ ├── memmapped_file_system.proto │ │ ├── memmapped_file_system_test.cc │ │ ├── memmapped_file_system_writer.cc │ │ ├── memmapped_file_system_writer.h │ │ ├── mirror_pad_mode.cc │ │ ├── mirror_pad_mode.h │ │ ├── padding.cc │ │ ├── padding.h │ │ ├── port.cc │ │ ├── port.h │ │ ├── reporter.cc │ │ ├── reporter.h │ │ ├── reporter_test.cc │ │ ├── saved_tensor_slice.proto │ │ ├── saved_tensor_slice_util.cc │ │ ├── saved_tensor_slice_util.h │ │ ├── saved_tensor_slice_util_test.cc │ │ ├── sparse │ │ ├── README.md │ │ ├── dim_comparator.h │ │ ├── group_iterator.cc │ │ ├── group_iterator.h │ │ ├── sparse_tensor.h │ │ └── sparse_tensor_test.cc │ │ ├── stat_summarizer.cc │ │ ├── stat_summarizer.h │ │ ├── tensor_format.cc │ │ ├── tensor_format.h │ │ ├── tensor_slice_reader.cc │ │ ├── tensor_slice_reader.h │ │ ├── tensor_slice_reader_cache.cc │ │ ├── tensor_slice_reader_cache.h │ │ ├── tensor_slice_reader_test.cc │ │ ├── tensor_slice_set.cc │ │ ├── tensor_slice_set.h │ │ ├── tensor_slice_set_test.cc │ │ ├── tensor_slice_util.h │ │ ├── tensor_slice_util_test.cc │ │ ├── tensor_slice_writer.cc │ │ ├── tensor_slice_writer.h │ │ ├── tensor_slice_writer_test.cc │ │ ├── test_log.proto │ │ ├── tf_status_helper.cc │ │ ├── tf_status_helper.h │ │ ├── use_cudnn.cc │ │ ├── use_cudnn.h │ │ ├── util.cc │ │ ├── util.h │ │ ├── work_sharder.cc │ │ ├── work_sharder.h │ │ └── work_sharder_test.cc ├── examples │ ├── __init__.py │ ├── android │ │ ├── AndroidManifest.xml │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── jni │ │ │ ├── __init__.py │ │ │ ├── imageutils_jni.cc │ │ │ ├── jni_utils.cc │ │ │ ├── jni_utils.h │ │ │ ├── limiting_file_input_stream.h │ │ │ ├── rgb2yuv.cc │ │ │ ├── rgb2yuv.h │ │ │ ├── tensorflow_jni.cc │ │ │ ├── tensorflow_jni.h │ │ │ ├── yuv2rgb.cc │ │ │ └── yuv2rgb.h │ │ ├── res │ │ │ ├── drawable-hdpi │ │ │ │ ├── ic_action_info.png │ │ │ │ ├── ic_launcher.png │ │ │ │ └── tile.9.png │ │ │ ├── drawable-mdpi │ │ │ │ ├── ic_action_info.png │ │ │ │ └── ic_launcher.png │ │ │ ├── drawable-xhdpi │ │ │ │ ├── ic_action_info.png │ │ │ │ └── ic_launcher.png │ │ │ ├── drawable-xxhdpi │ │ │ │ ├── ic_action_info.png │ │ │ │ └── ic_launcher.png │ │ │ ├── layout-land │ │ │ │ └── camera_connection_fragment.xml │ │ │ ├── layout │ │ │ │ ├── activity_camera.xml │ │ │ │ └── camera_connection_fragment.xml │ │ │ ├── values-sw600dp │ │ │ │ ├── template-dimens.xml │ │ │ │ └── template-styles.xml │ │ │ ├── values-v11 │ │ │ │ ├── styles.xml │ │ │ │ └── template-styles.xml │ │ │ ├── values-v14 │ │ │ │ └── styles.xml │ │ │ ├── values-v21 │ │ │ │ ├── base-colors.xml │ │ │ │ └── base-template-styles.xml │ │ │ └── values │ │ │ │ ├── attrs.xml │ │ │ │ ├── base-strings.xml │ │ │ │ ├── colors.xml │ │ │ │ ├── strings.xml │ │ │ │ ├── styles.xml │ │ │ │ ├── template-dimens.xml │ │ │ │ └── template-styles.xml │ │ └── src │ │ │ └── org │ │ │ └── tensorflow │ │ │ └── demo │ │ │ ├── AutoFitTextureView.java │ │ │ ├── CameraActivity.java │ │ │ ├── CameraConnectionFragment.java │ │ │ ├── Classifier.java │ │ │ ├── RecognitionScoreView.java │ │ │ ├── TensorflowClassifier.java │ │ │ ├── TensorflowImageListener.java │ │ │ └── env │ │ │ ├── ImageUtils.java │ │ │ └── Logger.java │ ├── how_tos │ │ └── reading_data │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ ├── convert_to_records.py │ │ │ ├── fully_connected_preloaded.py │ │ │ ├── fully_connected_preloaded_var.py │ │ │ └── fully_connected_reader.py │ ├── image_retraining │ │ ├── BUILD │ │ ├── retrain.py │ │ └── retrain_test.py │ ├── label_image │ │ ├── BUILD │ │ ├── README.md │ │ ├── data │ │ │ └── grace_hopper.jpg │ │ └── main.cc │ ├── roi_pooling │ │ ├── cat.png │ │ ├── demo.ipynb │ │ ├── gradient_test.ipynb │ │ ├── performance_test.ipynb │ │ └── roi_pooling_test.ipynb │ ├── skflow │ │ ├── BUILD │ │ ├── README.md │ │ ├── boston.py │ │ ├── digits.py │ │ ├── dnn_autoencoder_iris.py │ │ ├── hdf5_classification.py │ │ ├── iris.py │ │ ├── iris_custom_decay_dnn.py │ │ ├── iris_custom_model.py │ │ ├── iris_run_config.py │ │ ├── iris_save_restore.py │ │ ├── iris_val_based_early_stopping.py │ │ ├── iris_with_pipeline.py │ │ ├── language_model.py │ │ ├── mnist.py │ │ ├── mnist_weights.py │ │ ├── multioutput_regression.py │ │ ├── multiple_gpu.py │ │ ├── neural_translation.py │ │ ├── neural_translation_word.py │ │ ├── out_of_core_data_classification.py │ │ ├── resnet.py │ │ ├── text_classification.py │ │ ├── text_classification_builtin_rnn_model.py │ │ ├── text_classification_character_cnn.py │ │ ├── text_classification_character_rnn.py │ │ ├── text_classification_cnn.py │ │ └── text_classification_save_restore.py │ ├── tutorials │ │ ├── __init__.py │ │ ├── deepdream │ │ │ ├── README.md │ │ │ ├── deepdream.ipynb │ │ │ └── pilatus800.jpg │ │ ├── mnist │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ ├── fully_connected_feed.py │ │ │ ├── input_data.py │ │ │ ├── mnist.py │ │ │ ├── mnist_softmax.py │ │ │ └── mnist_with_summaries.py │ │ └── word2vec │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ └── word2vec_basic.py │ └── udacity │ │ ├── .gitignore │ │ ├── 1_notmnist.ipynb │ │ ├── 2_fullyconnected.ipynb │ │ ├── 3_regularization.ipynb │ │ ├── 4_convolutions.ipynb │ │ ├── 5_word2vec.ipynb │ │ ├── 6_lstm.ipynb │ │ ├── Dockerfile │ │ └── README.md ├── g3doc │ ├── __init__.py │ ├── api_docs │ │ ├── cc │ │ │ ├── ClassEnv.md │ │ │ ├── ClassEnvWrapper.md │ │ │ ├── ClassPartialTensorShape.md │ │ │ ├── ClassPartialTensorShapeUtils.md │ │ │ ├── ClassRandomAccessFile.md │ │ │ ├── ClassSession.md │ │ │ ├── ClassStatus.md │ │ │ ├── ClassTensor.md │ │ │ ├── ClassTensorShape.md │ │ │ ├── ClassTensorShapeUtils.md │ │ │ ├── ClassThread.md │ │ │ ├── ClassWritableFile.md │ │ │ ├── StructSessionOptions.md │ │ │ ├── StructState.md │ │ │ ├── StructTF_Buffer.md │ │ │ ├── StructTensorShapeDim.md │ │ │ ├── StructThreadOptions.md │ │ │ └── index.md │ │ ├── index.md │ │ ├── leftnav_files │ │ └── python │ │ │ ├── array_ops.md │ │ │ ├── check_ops.md │ │ │ ├── client.md │ │ │ ├── constant_op.md │ │ │ ├── contrib.copy_graph.md │ │ │ ├── contrib.distributions.md │ │ │ ├── contrib.ffmpeg.md │ │ │ ├── contrib.layers.md │ │ │ ├── contrib.learn.md │ │ │ ├── contrib.metrics.md │ │ │ ├── contrib.util.md │ │ │ ├── control_flow_ops.md │ │ │ ├── framework.md │ │ │ ├── functional_ops.md │ │ │ ├── functions_and_classes │ │ │ ├── shard0 │ │ │ │ ├── tf.ReaderBase.md │ │ │ │ ├── tf.SparseTensorValue.md │ │ │ │ ├── tf.TensorShape.md │ │ │ │ ├── tf.VariableScope.md │ │ │ │ ├── tf.add_check_numerics_ops.md │ │ │ │ ├── tf.add_n.md │ │ │ │ ├── tf.add_to_collection.md │ │ │ │ ├── tf.assert_non_positive.md │ │ │ │ ├── tf.batch_matrix_triangular_solve.md │ │ │ │ ├── tf.case.md │ │ │ │ ├── tf.cholesky.md │ │ │ │ ├── tf.cond.md │ │ │ │ ├── tf.contrib.distributions.MultivariateNormal.md │ │ │ │ ├── tf.contrib.layers.l2_regularizer.md │ │ │ │ ├── tf.contrib.learn.extract_pandas_matrix.md │ │ │ │ ├── tf.contrib.learn.read_batch_record_features.md │ │ │ │ ├── tf.contrib.metrics.set_size.md │ │ │ │ ├── tf.contrib.util.ops_used_by_graph_def.md │ │ │ │ ├── tf.delete_session_tensor.md │ │ │ │ ├── tf.depth_to_space.md │ │ │ │ ├── tf.device.md │ │ │ │ ├── tf.errors.CancelledError.md │ │ │ │ ├── tf.errors.DataLossError.md │ │ │ │ ├── tf.errors.DeadlineExceededError.md │ │ │ │ ├── tf.fft.md │ │ │ │ ├── tf.fft2d.md │ │ │ │ ├── tf.get_seed.md │ │ │ │ ├── tf.get_session_handle.md │ │ │ │ ├── tf.global_norm.md │ │ │ │ ├── tf.ifft3d.md │ │ │ │ ├── tf.image.adjust_brightness.md │ │ │ │ ├── tf.image.decode_jpeg.md │ │ │ │ ├── tf.image.grayscale_to_rgb.md │ │ │ │ ├── tf.image.random_brightness.md │ │ │ │ ├── tf.image.rgb_to_grayscale.md │ │ │ │ ├── tf.is_finite.md │ │ │ │ ├── tf.is_nan.md │ │ │ │ ├── tf.is_non_decreasing.md │ │ │ │ ├── tf.is_numeric_tensor.md │ │ │ │ ├── tf.mod.md │ │ │ │ ├── tf.mul.md │ │ │ │ ├── tf.name_scope.md │ │ │ │ ├── tf.nn.avg_pool3d.md │ │ │ │ ├── tf.nn.l2_normalize.md │ │ │ │ ├── tf.not_equal.md │ │ │ │ ├── tf.py_func.md │ │ │ │ ├── tf.reduce_sum.md │ │ │ │ ├── tf.reshape.md │ │ │ │ ├── tf.reverse_sequence.md │ │ │ │ ├── tf.segment_min.md │ │ │ │ ├── tf.sparse_tensor_to_dense.md │ │ │ │ ├── tf.sqrt.md │ │ │ │ ├── tf.train.ExponentialMovingAverage.md │ │ │ │ ├── tf.train.add_queue_runner.md │ │ │ │ ├── tf.train.limit_epochs.md │ │ │ │ ├── tf.tuple.md │ │ │ │ └── tf.zeros_initializer.md │ │ │ ├── shard1 │ │ │ │ ├── tf.AggregationMethod.md │ │ │ │ ├── tf.FIFOQueue.md │ │ │ │ ├── tf.IdentityReader.md │ │ │ │ ├── tf.NoGradient.md │ │ │ │ ├── tf.Print.md │ │ │ │ ├── tf.Tensor.md │ │ │ │ ├── tf.Variable.from_proto.md │ │ │ │ ├── tf.accumulate_n.md │ │ │ │ ├── tf.all_variables.md │ │ │ │ ├── tf.assert_less_equal.md │ │ │ │ ├── tf.assert_rank_at_least.md │ │ │ │ ├── tf.batch_fft.md │ │ │ │ ├── tf.batch_matrix_inverse.md │ │ │ │ ├── tf.batch_to_space.md │ │ │ │ ├── tf.constant_initializer.md │ │ │ │ ├── tf.contrib.distributions.StudentT.md │ │ │ │ ├── tf.contrib.layers.summarize_tensors.md │ │ │ │ ├── tf.contrib.learn.extract_pandas_data.md │ │ │ │ ├── tf.contrib.learn.train.md │ │ │ │ ├── tf.contrib.metrics.streaming_mean_squared_error.md │ │ │ │ ├── tf.contrib.metrics.streaming_sparse_recall_at_k.md │ │ │ │ ├── tf.contrib.util.constant_value.md │ │ │ │ ├── tf.convert_to_tensor.md │ │ │ │ ├── tf.diag.md │ │ │ │ ├── tf.erf.md │ │ │ │ ├── tf.errors.AlreadyExistsError.md │ │ │ │ ├── tf.get_default_session.md │ │ │ │ ├── tf.gradients.md │ │ │ │ ├── tf.greater_equal.md │ │ │ │ ├── tf.igammac.md │ │ │ │ ├── tf.image.adjust_hue.md │ │ │ │ ├── tf.image.central_crop.md │ │ │ │ ├── tf.image.random_hue.md │ │ │ │ ├── tf.image.resize_bicubic.md │ │ │ │ ├── tf.invert_permutation.md │ │ │ │ ├── tf.is_strictly_increasing.md │ │ │ │ ├── tf.linspace.md │ │ │ │ ├── tf.map_fn.md │ │ │ │ ├── tf.matching_files.md │ │ │ │ ├── tf.merge_all_summaries.md │ │ │ │ ├── tf.nn.compute_accidental_hits.md │ │ │ │ ├── tf.nn.embedding_lookup_sparse.md │ │ │ │ ├── tf.nn.moments.md │ │ │ │ ├── tf.nn.normalize_moments.md │ │ │ │ ├── tf.nn.sampled_softmax_loss.md │ │ │ │ ├── tf.parse_single_example.md │ │ │ │ ├── tf.random_uniform_initializer.md │ │ │ │ ├── tf.read_file.md │ │ │ │ ├── tf.reduce_any.md │ │ │ │ ├── tf.reduce_join.md │ │ │ │ ├── tf.string_to_hash_bucket_strong.md │ │ │ │ ├── tf.test.get_temp_dir.md │ │ │ │ ├── tf.train.AdadeltaOptimizer.md │ │ │ │ ├── tf.train.ClusterSpec.md │ │ │ │ ├── tf.train.GradientDescentOptimizer.md │ │ │ │ ├── tf.train.LooperThread.md │ │ │ │ ├── tf.train.Server.create_local_server.md │ │ │ │ ├── tf.train.generate_checkpoint_state_proto.md │ │ │ │ ├── tf.train.shuffle_batch_join.md │ │ │ │ ├── tf.zeros.md │ │ │ │ └── tf.zeros_like.md │ │ │ ├── shard2 │ │ │ │ ├── tf.DType.md │ │ │ │ ├── tf.Graph.md │ │ │ │ ├── tf.InteractiveSession.md │ │ │ │ ├── tf.TFRecordReader.md │ │ │ │ ├── tf.TextLineReader.md │ │ │ │ ├── tf.WholeFileReader.md │ │ │ │ ├── tf.assert_non_negative.md │ │ │ │ ├── tf.batch_matrix_determinant.md │ │ │ │ ├── tf.cholesky_solve.md │ │ │ │ ├── tf.constant.md │ │ │ │ ├── tf.contrib.copy_graph.get_copied_op.md │ │ │ │ ├── tf.contrib.distributions.Chi2.md │ │ │ │ ├── tf.contrib.distributions.Uniform.md │ │ │ │ ├── tf.contrib.layers.optimize_loss.md │ │ │ │ ├── tf.contrib.learn.BaseEstimator.md │ │ │ │ ├── tf.contrib.learn.ModeKeys.md │ │ │ │ ├── tf.contrib.learn.TensorFlowDNNRegressor.md │ │ │ │ ├── tf.contrib.metrics.set_difference.md │ │ │ │ ├── tf.contrib.metrics.streaming_auc.md │ │ │ │ ├── tf.contrib.metrics.streaming_mean.md │ │ │ │ ├── tf.contrib.metrics.streaming_mean_relative_error.md │ │ │ │ ├── tf.contrib.metrics.streaming_sparse_precision_at_k.md │ │ │ │ ├── tf.digamma.md │ │ │ │ ├── tf.edit_distance.md │ │ │ │ ├── tf.errors.ResourceExhaustedError.md │ │ │ │ ├── tf.expand_dims.md │ │ │ │ ├── tf.gather_nd.md │ │ │ │ ├── tf.get_variable_scope.md │ │ │ │ ├── tf.identity.md │ │ │ │ ├── tf.imag.md │ │ │ │ ├── tf.image.encode_jpeg.md │ │ │ │ ├── tf.image.per_image_whitening.md │ │ │ │ ├── tf.image_summary.md │ │ │ │ ├── tf.initialize_all_variables.md │ │ │ │ ├── tf.initialize_local_variables.md │ │ │ │ ├── tf.is_variable_initialized.md │ │ │ │ ├── tf.matmul.md │ │ │ │ ├── tf.minimum.md │ │ │ │ ├── tf.neg.md │ │ │ │ ├── tf.nn.embedding_lookup.md │ │ │ │ ├── tf.nn.log_uniform_candidate_sampler.md │ │ │ │ ├── tf.nn.relu.md │ │ │ │ ├── tf.random_uniform.md │ │ │ │ ├── tf.real.md │ │ │ │ ├── tf.report_uninitialized_variables.md │ │ │ │ ├── tf.scatter_update.md │ │ │ │ ├── tf.shape_n.md │ │ │ │ ├── tf.sin.md │ │ │ │ ├── tf.sparse_placeholder.md │ │ │ │ ├── tf.split.md │ │ │ │ ├── tf.squeeze.md │ │ │ │ ├── tf.test.assert_equal_graph_def.md │ │ │ │ ├── tf.test.compute_gradient.md │ │ │ │ ├── tf.test.is_built_with_cuda.md │ │ │ │ ├── tf.to_int32.md │ │ │ │ ├── tf.train.Saver.from_proto.md │ │ │ │ ├── tf.train.global_step.md │ │ │ │ ├── tf.train.latest_checkpoint.md │ │ │ │ ├── tf.train.shuffle_batch.md │ │ │ │ ├── tf.train.start_queue_runners.md │ │ │ │ └── tf.uniform_unit_scaling_initializer.md │ │ │ ├── shard3 │ │ │ │ ├── tf.RegisterGradient.md │ │ │ │ ├── tf.SparseTensor.md │ │ │ │ ├── tf.assert_rank.md │ │ │ │ ├── tf.assert_type.md │ │ │ │ ├── tf.batch_ifft3d.md │ │ │ │ ├── tf.batch_self_adjoint_eig.md │ │ │ │ ├── tf.ceil.md │ │ │ │ ├── tf.check_numerics.md │ │ │ │ ├── tf.complex_abs.md │ │ │ │ ├── tf.contrib.copy_graph.copy_op_to_graph.md │ │ │ │ ├── tf.contrib.distributions.ContinuousDistribution.md │ │ │ │ ├── tf.contrib.distributions.DirichletMultinomial.md │ │ │ │ ├── tf.contrib.distributions.Exponential.md │ │ │ │ ├── tf.contrib.distributions.Gamma.md │ │ │ │ ├── tf.contrib.distributions.normal_conjugates_known_sigma_posterior.md │ │ │ │ ├── tf.contrib.ffmpeg.encode_audio.md │ │ │ │ ├── tf.contrib.layers.summarize_activation.md │ │ │ │ ├── tf.contrib.layers.variance_scaling_initializer.md │ │ │ │ ├── tf.contrib.learn.Estimator.md │ │ │ │ ├── tf.contrib.learn.extract_dask_data.md │ │ │ │ ├── tf.contrib.metrics.auc_using_histogram.md │ │ │ │ ├── tf.control_dependencies.md │ │ │ │ ├── tf.convert_to_tensor_or_indexed_slices.md │ │ │ │ ├── tf.decode_csv.md │ │ │ │ ├── tf.decode_raw.md │ │ │ │ ├── tf.errors.OutOfRangeError.md │ │ │ │ ├── tf.errors.UnauthenticatedError.md │ │ │ │ ├── tf.exp.md │ │ │ │ ├── tf.foldl.md │ │ │ │ ├── tf.group.md │ │ │ │ ├── tf.ifft2d.md │ │ │ │ ├── tf.image.adjust_contrast.md │ │ │ │ ├── tf.image.adjust_saturation.md │ │ │ │ ├── tf.image.convert_image_dtype.md │ │ │ │ ├── tf.image.decode_png.md │ │ │ │ ├── tf.image.random_contrast.md │ │ │ │ ├── tf.image.random_saturation.md │ │ │ │ ├── tf.local_variables.md │ │ │ │ ├── tf.logical_xor.md │ │ │ │ ├── tf.multinomial.md │ │ │ │ ├── tf.nn.dropout.md │ │ │ │ ├── tf.nn.log_softmax.md │ │ │ │ ├── tf.nn.max_pool.md │ │ │ │ ├── tf.nn.softsign.md │ │ │ │ ├── tf.pack.md │ │ │ │ ├── tf.placeholder.md │ │ │ │ ├── tf.random_shuffle.md │ │ │ │ ├── tf.reduce_min.md │ │ │ │ ├── tf.register_tensor_conversion_function.md │ │ │ │ ├── tf.scalar_summary.md │ │ │ │ ├── tf.segment_mean.md │ │ │ │ ├── tf.shape.md │ │ │ │ ├── tf.sparse_concat.md │ │ │ │ ├── tf.sparse_softmax.md │ │ │ │ ├── tf.sparse_split.md │ │ │ │ ├── tf.stop_gradient.md │ │ │ │ ├── tf.test.compute_gradient_error.md │ │ │ │ ├── tf.to_double.md │ │ │ │ ├── tf.trace.md │ │ │ │ ├── tf.train.AdagradOptimizer.md │ │ │ │ ├── tf.train.QueueRunner.md │ │ │ │ ├── tf.train.Server.md │ │ │ │ ├── tf.train.batch_join.md │ │ │ │ ├── tf.train.range_input_producer.md │ │ │ │ └── tf.unique_with_counts.md │ │ │ ├── shard4 │ │ │ │ ├── tf.Assert.md │ │ │ │ ├── tf.FixedLengthRecordReader.md │ │ │ │ ├── tf.argmin.md │ │ │ │ ├── tf.assert_less.md │ │ │ │ ├── tf.batch_ifft.md │ │ │ │ ├── tf.batch_matrix_band_part.md │ │ │ │ ├── tf.batch_matrix_diag_part.md │ │ │ │ ├── tf.batch_matrix_solve.md │ │ │ │ ├── tf.clip_by_value.md │ │ │ │ ├── tf.complex.md │ │ │ │ ├── tf.contrib.learn.RunConfig.md │ │ │ │ ├── tf.contrib.learn.TensorFlowEstimator.md │ │ │ │ ├── tf.contrib.learn.TensorFlowLinearClassifier.md │ │ │ │ ├── tf.contrib.learn.TensorFlowRNNRegressor.md │ │ │ │ ├── tf.contrib.learn.evaluate.md │ │ │ │ ├── tf.contrib.learn.read_batch_features.md │ │ │ │ ├── tf.contrib.learn.run_feeds.md │ │ │ │ ├── tf.contrib.metrics.set_union.md │ │ │ │ ├── tf.contrib.metrics.streaming_recall_at_k.md │ │ │ │ ├── tf.contrib.util.stripped_op_list_for_graph.md │ │ │ │ ├── tf.errors.FailedPreconditionError.md │ │ │ │ ├── tf.floor.md │ │ │ │ ├── tf.greater.md │ │ │ │ ├── tf.histogram_fixed_width.md │ │ │ │ ├── tf.image.hsv_to_rgb.md │ │ │ │ ├── tf.initialize_variables.md │ │ │ │ ├── tf.log.md │ │ │ │ ├── tf.nn.conv2d_transpose.md │ │ │ │ ├── tf.nn.depthwise_conv2d.md │ │ │ │ ├── tf.nn.depthwise_conv2d_native.md │ │ │ │ ├── tf.nn.l2_loss.md │ │ │ │ ├── tf.nn.max_pool3d.md │ │ │ │ ├── tf.nn.nce_loss.md │ │ │ │ ├── tf.nn.softplus.md │ │ │ │ ├── tf.nn.sparse_softmax_cross_entropy_with_logits.md │ │ │ │ ├── tf.placeholder_with_default.md │ │ │ │ ├── tf.reduce_all.md │ │ │ │ ├── tf.reduce_mean.md │ │ │ │ ├── tf.segment_max.md │ │ │ │ ├── tf.select.md │ │ │ │ ├── tf.sparse_add.md │ │ │ │ ├── tf.sparse_to_indicator.md │ │ │ │ ├── tf.string_to_hash_bucket_fast.md │ │ │ │ ├── tf.sub.md │ │ │ │ ├── tf.tile.md │ │ │ │ ├── tf.train.match_filenames_once.md │ │ │ │ ├── tf.train.update_checkpoint_state.md │ │ │ │ ├── tf.train.write_graph.md │ │ │ │ ├── tf.unpack.md │ │ │ │ ├── tf.unsorted_segment_sum.md │ │ │ │ └── tf.while_loop.md │ │ │ ├── shard5 │ │ │ │ ├── tf.OpError.md │ │ │ │ ├── tf.RandomShuffleQueue.md │ │ │ │ ├── tf.add.md │ │ │ │ ├── tf.assert_integer.md │ │ │ │ ├── tf.batch_cholesky_solve.md │ │ │ │ ├── tf.batch_matmul.md │ │ │ │ ├── tf.boolean_mask.md │ │ │ │ ├── tf.bytes.md │ │ │ │ ├── tf.cast.md │ │ │ │ ├── tf.clip_by_global_norm.md │ │ │ │ ├── tf.clip_by_norm.md │ │ │ │ ├── tf.contrib.layers.convolution2d.md │ │ │ │ ├── tf.contrib.layers.fully_connected.md │ │ │ │ ├── tf.contrib.layers.sum_regularizer.md │ │ │ │ ├── tf.contrib.layers.summarize_collection.md │ │ │ │ ├── tf.contrib.learn.TensorFlowDNNClassifier.md │ │ │ │ ├── tf.contrib.learn.run_n.md │ │ │ │ ├── tf.contrib.metrics.accuracy.md │ │ │ │ ├── tf.contrib.metrics.streaming_percentage_less.md │ │ │ │ ├── tf.cos.md │ │ │ │ ├── tf.diag_part.md │ │ │ │ ├── tf.div.md │ │ │ │ ├── tf.errors.PermissionDeniedError.md │ │ │ │ ├── tf.errors.UnavailableError.md │ │ │ │ ├── tf.floordiv.md │ │ │ │ ├── tf.histogram_summary.md │ │ │ │ ├── tf.image.flip_left_right.md │ │ │ │ ├── tf.image.flip_up_down.md │ │ │ │ ├── tf.image.pad_to_bounding_box.md │ │ │ │ ├── tf.image.resize_image_with_crop_or_pad.md │ │ │ │ ├── tf.image.resize_nearest_neighbor.md │ │ │ │ ├── tf.image.sample_distorted_bounding_box.md │ │ │ │ ├── tf.inv.md │ │ │ │ ├── tf.listdiff.md │ │ │ │ ├── tf.load_file_system_library.md │ │ │ │ ├── tf.logical_and.md │ │ │ │ ├── tf.logical_not.md │ │ │ │ ├── tf.make_template.md │ │ │ │ ├── tf.merge_summary.md │ │ │ │ ├── tf.nn.conv3d.md │ │ │ │ ├── tf.nn.sigmoid_cross_entropy_with_logits.md │ │ │ │ ├── tf.nn.top_k.md │ │ │ │ ├── tf.no_op.md │ │ │ │ ├── tf.range.md │ │ │ │ ├── tf.sign.md │ │ │ │ ├── tf.sparse_segment_sqrt_n_grad.md │ │ │ │ ├── tf.test.main.md │ │ │ │ ├── tf.to_int64.md │ │ │ │ ├── tf.train.FtrlOptimizer.md │ │ │ │ ├── tf.train.LooperThread.loop.md │ │ │ │ ├── tf.train.Optimizer.md │ │ │ │ ├── tf.train.Saver.md │ │ │ │ ├── tf.train.SessionManager.md │ │ │ │ ├── tf.train.replica_device_setter.md │ │ │ │ ├── tf.transpose.md │ │ │ │ ├── tf.truncated_normal_initializer.md │ │ │ │ ├── tf.variable_op_scope.md │ │ │ │ └── tf.verify_tensor_all_finite.md │ │ │ ├── shard6 │ │ │ │ ├── tf.Dimension.md │ │ │ │ ├── tf.FixedLenSequenceFeature.md │ │ │ │ ├── tf.QueueBase.md │ │ │ │ ├── tf.abs.md │ │ │ │ ├── tf.assert_positive.md │ │ │ │ ├── tf.batch_fft3d.md │ │ │ │ ├── tf.batch_ifft2d.md │ │ │ │ ├── tf.bitcast.md │ │ │ │ ├── tf.concat.md │ │ │ │ ├── tf.conj.md │ │ │ │ ├── tf.contrib.copy_graph.copy_variable_to_graph.md │ │ │ │ ├── tf.contrib.layers.summarize_activations.md │ │ │ │ ├── tf.contrib.learn.extract_dask_labels.md │ │ │ │ ├── tf.contrib.learn.read_batch_examples.md │ │ │ │ ├── tf.contrib.metrics.set_intersection.md │ │ │ │ ├── tf.contrib.metrics.streaming_recall.md │ │ │ │ ├── tf.contrib.metrics.streaming_root_mean_squared_error.md │ │ │ │ ├── tf.contrib.util.make_tensor_proto.md │ │ │ │ ├── tf.decode_json_example.md │ │ │ │ ├── tf.dynamic_partition.md │ │ │ │ ├── tf.erfc.md │ │ │ │ ├── tf.errors.AbortedError.md │ │ │ │ ├── tf.errors.InternalError.md │ │ │ │ ├── tf.errors.NotFoundError.md │ │ │ │ ├── tf.errors.UnimplementedError.md │ │ │ │ ├── tf.igamma.md │ │ │ │ ├── tf.image.extract_glimpse.md │ │ │ │ ├── tf.image.rgb_to_hsv.md │ │ │ │ ├── tf.import_graph_def.md │ │ │ │ ├── tf.load_op_library.md │ │ │ │ ├── tf.maximum.md │ │ │ │ ├── tf.moving_average_variables.md │ │ │ │ ├── tf.nn.elu.md │ │ │ │ ├── tf.nn.separable_conv2d.md │ │ │ │ ├── tf.nn.softmax.md │ │ │ │ ├── tf.one_hot.md │ │ │ │ ├── tf.op_scope.md │ │ │ │ ├── tf.parse_example.md │ │ │ │ ├── tf.pow.md │ │ │ │ ├── tf.python_io.tf_record_iterator.md │ │ │ │ ├── tf.random_crop.md │ │ │ │ ├── tf.random_normal_initializer.md │ │ │ │ ├── tf.rank.md │ │ │ │ ├── tf.self_adjoint_eig.md │ │ │ │ ├── tf.sigmoid.md │ │ │ │ ├── tf.slice.md │ │ │ │ ├── tf.space_to_depth.md │ │ │ │ ├── tf.sparse_reset_shape.md │ │ │ │ ├── tf.sparse_segment_mean.md │ │ │ │ ├── tf.sparse_segment_sum.md │ │ │ │ ├── tf.to_float.md │ │ │ │ ├── tf.train.AdamOptimizer.md │ │ │ │ ├── tf.train.Coordinator.md │ │ │ │ ├── tf.train.QueueRunner.from_proto.md │ │ │ │ ├── tf.train.RMSPropOptimizer.md │ │ │ │ ├── tf.train.Supervisor.md │ │ │ │ ├── tf.train.exponential_decay.md │ │ │ │ ├── tf.train.slice_input_producer.md │ │ │ │ ├── tf.trainable_variables.md │ │ │ │ └── tf.truncated_normal.md │ │ │ ├── shard7 │ │ │ │ ├── tf.DeviceSpec.from_string.md │ │ │ │ ├── tf.FixedLenFeature.md │ │ │ │ ├── tf.Operation.md │ │ │ │ ├── tf.QueueBase.from_list.md │ │ │ │ ├── tf.as_dtype.md │ │ │ │ ├── tf.assert_equal.md │ │ │ │ ├── tf.assert_variables_initialized.md │ │ │ │ ├── tf.batch_cholesky.md │ │ │ │ ├── tf.contrib.distributions.BaseDistribution.md │ │ │ │ ├── tf.contrib.distributions.DiscreteDistribution.md │ │ │ │ ├── tf.contrib.distributions.Normal.md │ │ │ │ ├── tf.contrib.learn.TensorFlowClassifier.md │ │ │ │ ├── tf.contrib.metrics.streaming_mean_absolute_error.md │ │ │ │ ├── tf.contrib.metrics.streaming_precision.md │ │ │ │ ├── tf.contrib.util.make_ndarray.md │ │ │ │ ├── tf.count_up_to.md │ │ │ │ ├── tf.dynamic_stitch.md │ │ │ │ ├── tf.fft3d.md │ │ │ │ ├── tf.get_collection.md │ │ │ │ ├── tf.get_collection_ref.md │ │ │ │ ├── tf.get_session_tensor.md │ │ │ │ ├── tf.ifft.md │ │ │ │ ├── tf.image.random_flip_left_right.md │ │ │ │ ├── tf.image.resize_area.md │ │ │ │ ├── tf.less.md │ │ │ │ ├── tf.lgamma.md │ │ │ │ ├── tf.logical_or.md │ │ │ │ ├── tf.matrix_solve.md │ │ │ │ ├── tf.matrix_solve_ls.md │ │ │ │ ├── tf.nn.atrous_conv2d.md │ │ │ │ ├── tf.nn.avg_pool.md │ │ │ │ ├── tf.nn.fixed_unigram_candidate_sampler.md │ │ │ │ ├── tf.nn.in_top_k.md │ │ │ │ ├── tf.nn.local_response_normalization.md │ │ │ │ ├── tf.nn.softmax_cross_entropy_with_logits.md │ │ │ │ ├── tf.ones_like.md │ │ │ │ ├── tf.polygamma.md │ │ │ │ ├── tf.python_io.TFRecordWriter.md │ │ │ │ ├── tf.random_normal.md │ │ │ │ ├── tf.reduce_max.md │ │ │ │ ├── tf.scatter_sub.md │ │ │ │ ├── tf.segment_prod.md │ │ │ │ ├── tf.segment_sum.md │ │ │ │ ├── tf.sparse_reduce_sum.md │ │ │ │ ├── tf.sparse_tensor_dense_matmul.md │ │ │ │ ├── tf.square.md │ │ │ │ ├── tf.string_to_hash_bucket.md │ │ │ │ ├── tf.train.MomentumOptimizer.md │ │ │ │ ├── tf.train.SummaryWriter.md │ │ │ │ ├── tf.train.export_meta_graph.md │ │ │ │ ├── tf.train.get_checkpoint_state.md │ │ │ │ ├── tf.truediv.md │ │ │ │ ├── tf.unique.md │ │ │ │ ├── tf.variable_scope.md │ │ │ │ └── tf.where.md │ │ │ ├── shard8 │ │ │ │ ├── tf.GraphKeys.md │ │ │ │ ├── tf.IndexedSlices.md │ │ │ │ ├── tf.RegisterShape.md │ │ │ │ ├── tf.Session.md │ │ │ │ ├── tf.VarLenFeature.md │ │ │ │ ├── tf.Variable.md │ │ │ │ ├── tf.argmax.md │ │ │ │ ├── tf.assert_negative.md │ │ │ │ ├── tf.assert_proper_iterable.md │ │ │ │ ├── tf.batch_matrix_diag.md │ │ │ │ ├── tf.batch_matrix_solve_ls.md │ │ │ │ ├── tf.contrib.distributions.normal_congugates_known_sigma_predictive.md │ │ │ │ ├── tf.contrib.layers.apply_regularization.md │ │ │ │ ├── tf.contrib.layers.summarize_tensor.md │ │ │ │ ├── tf.contrib.layers.xavier_initializer_conv2d.md │ │ │ │ ├── tf.contrib.learn.NanLossDuringTrainingError.md │ │ │ │ ├── tf.contrib.learn.TensorFlowRegressor.md │ │ │ │ ├── tf.contrib.learn.extract_pandas_labels.md │ │ │ │ ├── tf.contrib.metrics.confusion_matrix.md │ │ │ │ ├── tf.contrib.metrics.streaming_accuracy.md │ │ │ │ ├── tf.contrib.metrics.streaming_mean_cosine_distance.md │ │ │ │ ├── tf.cross.md │ │ │ │ ├── tf.equal.md │ │ │ │ ├── tf.image.crop_to_bounding_box.md │ │ │ │ ├── tf.image.draw_bounding_boxes.md │ │ │ │ ├── tf.image.resize_bilinear.md │ │ │ │ ├── tf.image.resize_images.md │ │ │ │ ├── tf.image.transpose_image.md │ │ │ │ ├── tf.is_inf.md │ │ │ │ ├── tf.lbeta.md │ │ │ │ ├── tf.less_equal.md │ │ │ │ ├── tf.matrix_inverse.md │ │ │ │ ├── tf.nn.batch_normalization.md │ │ │ │ ├── tf.nn.conv2d.md │ │ │ │ ├── tf.nn.learned_unigram_candidate_sampler.md │ │ │ │ ├── tf.nn.relu6.md │ │ │ │ ├── tf.nn.sufficient_statistics.md │ │ │ │ ├── tf.nn.weighted_cross_entropy_with_logits.md │ │ │ │ ├── tf.no_regularizer.md │ │ │ │ ├── tf.ones_initializer.md │ │ │ │ ├── tf.reduce_prod.md │ │ │ │ ├── tf.reset_default_graph.md │ │ │ │ ├── tf.reverse.md │ │ │ │ ├── tf.round.md │ │ │ │ ├── tf.rsqrt.md │ │ │ │ ├── tf.scatter_add.md │ │ │ │ ├── tf.set_random_seed.md │ │ │ │ ├── tf.sparse_fill_empty_rows.md │ │ │ │ ├── tf.sparse_reorder.md │ │ │ │ ├── tf.sparse_retain.md │ │ │ │ ├── tf.sparse_segment_sqrt_n.md │ │ │ │ ├── tf.sparse_to_dense.md │ │ │ │ ├── tf.train.batch.md │ │ │ │ ├── tf.train.import_meta_graph.md │ │ │ │ ├── tf.variable_axis_size_partitioner.md │ │ │ │ └── tf.zeta.md │ │ │ └── shard9 │ │ │ │ ├── tf.DeviceSpec.md │ │ │ │ ├── tf.audio_summary.md │ │ │ │ ├── tf.batch_fft2d.md │ │ │ │ ├── tf.clip_by_average_norm.md │ │ │ │ ├── tf.contrib.ffmpeg.decode_audio.md │ │ │ │ ├── tf.contrib.layers.l1_regularizer.md │ │ │ │ ├── tf.contrib.layers.xavier_initializer.md │ │ │ │ ├── tf.contrib.learn.TensorFlowLinearRegressor.md │ │ │ │ ├── tf.contrib.learn.TensorFlowRNNClassifier.md │ │ │ │ ├── tf.contrib.learn.infer.md │ │ │ │ ├── tf.errors.InvalidArgumentError.md │ │ │ │ ├── tf.errors.UnknownError.md │ │ │ │ ├── tf.fill.md │ │ │ │ ├── tf.foldr.md │ │ │ │ ├── tf.gather.md │ │ │ │ ├── tf.get_default_graph.md │ │ │ │ ├── tf.get_variable.md │ │ │ │ ├── tf.image.encode_png.md │ │ │ │ ├── tf.image.random_flip_up_down.md │ │ │ │ ├── tf.matrix_determinant.md │ │ │ │ ├── tf.matrix_triangular_solve.md │ │ │ │ ├── tf.nn.bias_add.md │ │ │ │ ├── tf.nn.max_pool_with_argmax.md │ │ │ │ ├── tf.nn.uniform_candidate_sampler.md │ │ │ │ ├── tf.nn.zero_fraction.md │ │ │ │ ├── tf.ones.md │ │ │ │ ├── tf.pad.md │ │ │ │ ├── tf.saturate_cast.md │ │ │ │ ├── tf.scalar_mul.md │ │ │ │ ├── tf.scan.md │ │ │ │ ├── tf.size.md │ │ │ │ ├── tf.space_to_batch.md │ │ │ │ ├── tf.sparse_mask.md │ │ │ │ ├── tf.sparse_merge.md │ │ │ │ ├── tf.squared_difference.md │ │ │ │ ├── tf.string_to_number.md │ │ │ │ ├── tf.tanh.md │ │ │ │ ├── tf.to_bfloat16.md │ │ │ │ ├── tf.train.input_producer.md │ │ │ │ ├── tf.train.string_input_producer.md │ │ │ │ └── tf.train.summary_iterator.md │ │ │ ├── histogram_ops.md │ │ │ ├── image.md │ │ │ ├── index.md │ │ │ ├── io_ops.md │ │ │ ├── math_ops.md │ │ │ ├── nn.md │ │ │ ├── python_io.md │ │ │ ├── script_ops.md │ │ │ ├── session_ops.md │ │ │ ├── sparse_ops.md │ │ │ ├── state_ops.md │ │ │ ├── string_ops.md │ │ │ ├── test.md │ │ │ └── train.md │ ├── contrib │ │ └── learn │ │ │ ├── get_started │ │ │ └── index.md │ │ │ └── index.md │ ├── extras │ │ └── README.txt │ ├── get_started │ │ ├── basic_usage.md │ │ ├── index.md │ │ ├── leftnav_files │ │ └── os_setup.md │ ├── how_tos │ │ ├── __init__.py │ │ ├── adding_an_op │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ ├── attr_examples.cc │ │ │ ├── cuda_op.py │ │ │ ├── cuda_op_kernel.cc │ │ │ ├── cuda_op_kernel.cu.cc │ │ │ ├── cuda_op_test.py │ │ │ ├── fact_test.py │ │ │ ├── index.md │ │ │ ├── zero_out_1_test.py │ │ │ ├── zero_out_2_test.py │ │ │ ├── zero_out_3_test.py │ │ │ ├── zero_out_grad_2.py │ │ │ ├── zero_out_op_1.py │ │ │ ├── zero_out_op_2.py │ │ │ ├── zero_out_op_3.py │ │ │ ├── zero_out_op_kernel_1.cc │ │ │ ├── zero_out_op_kernel_2.cc │ │ │ └── zero_out_op_kernel_3.cc │ │ ├── distributed │ │ │ └── index.md │ │ ├── documentation │ │ │ └── index.md │ │ ├── graph_viz │ │ │ └── index.md │ │ ├── image_retraining │ │ │ └── index.md │ │ ├── index.md │ │ ├── leftnav_files │ │ ├── meta_graph │ │ │ └── index.md │ │ ├── new_data_formats │ │ │ └── index.md │ │ ├── quantization │ │ │ └── index.md │ │ ├── reading_data │ │ │ └── index.md │ │ ├── style_guide.md │ │ ├── summaries_and_tensorboard │ │ │ └── index.md │ │ ├── threading_and_queues │ │ │ └── index.md │ │ ├── tool_developers │ │ │ └── index.md │ │ ├── using_gpu │ │ │ └── index.md │ │ ├── variable_scope │ │ │ └── index.md │ │ └── variables │ │ │ └── index.md │ ├── images │ │ └── getting_started.dot │ ├── index.md │ ├── resources │ │ ├── bib.md │ │ ├── dims_types.md │ │ ├── faq.md │ │ ├── glossary.md │ │ ├── index.md │ │ ├── leftnav_files │ │ ├── roadmap.md │ │ ├── uses.md │ │ └── versions.md │ └── tutorials │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── deep_cnn │ │ ├── cifar_tensorboard.html │ │ └── index.md │ │ ├── image_recognition │ │ └── index.md │ │ ├── index.md │ │ ├── leftnav_files │ │ ├── mandelbrot │ │ └── index.md │ │ ├── mnist │ │ ├── beginners │ │ │ └── index.md │ │ ├── download │ │ │ └── index.md │ │ ├── pros │ │ │ └── index.md │ │ └── tf │ │ │ └── index.md │ │ ├── pdes │ │ └── index.md │ │ ├── recurrent │ │ └── index.md │ │ ├── seq2seq │ │ └── index.md │ │ ├── syntaxnet │ │ └── index.md │ │ ├── tfserve │ │ └── index.md │ │ └── word2vec │ │ └── index.md ├── models │ ├── __init__.py │ ├── embedding │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── word2vec.py │ │ ├── word2vec_kernels.cc │ │ ├── word2vec_ops.cc │ │ ├── word2vec_optimized.py │ │ ├── word2vec_optimized_test.py │ │ └── word2vec_test.py │ ├── image │ │ ├── __init__.py │ │ ├── alexnet │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ └── alexnet_benchmark.py │ │ ├── cifar10 │ │ │ ├── BUILD │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── cifar10.py │ │ │ ├── cifar10_eval.py │ │ │ ├── cifar10_input.py │ │ │ ├── cifar10_input_test.py │ │ │ ├── cifar10_multi_gpu_train.py │ │ │ └── cifar10_train.py │ │ ├── imagenet │ │ │ ├── BUILD │ │ │ └── classify_image.py │ │ └── mnist │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ └── convolutional.py │ └── rnn │ │ ├── BUILD │ │ ├── README.md │ │ ├── __init__.py │ │ ├── linear.py │ │ ├── ptb │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── ptb_word_lm.py │ │ ├── reader.py │ │ └── reader_test.py │ │ ├── rnn.py │ │ ├── rnn_cell.py │ │ ├── seq2seq.py │ │ └── translate │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── data_utils.py │ │ ├── seq2seq_model.py │ │ └── translate.py ├── python │ ├── BUILD │ ├── __init__.py │ ├── client │ │ ├── __init__.py │ │ ├── client_lib.py │ │ ├── device_lib.i │ │ ├── device_lib.py │ │ ├── device_lib_test.py │ │ ├── events_writer.i │ │ ├── events_writer_test.py │ │ ├── graph_util.py │ │ ├── graph_util_test.py │ │ ├── notebook.py │ │ ├── session.py │ │ ├── session_test.py │ │ ├── test_construction_fails_op.cc │ │ ├── tf_session.i │ │ ├── tf_session_helper.cc │ │ ├── tf_session_helper.h │ │ ├── timeline.py │ │ └── timeline_test.py │ ├── framework │ │ ├── __init__.py │ │ ├── contrib_test.py │ │ ├── device.py │ │ ├── device_test.py │ │ ├── docs.py │ │ ├── dtypes.py │ │ ├── dtypes_test.py │ │ ├── errors.py │ │ ├── errors_test.py │ │ ├── file_system_test.py │ │ ├── framework_lib.py │ │ ├── function.py │ │ ├── function_test.py │ │ ├── gen_docs_combined.py │ │ ├── importer.py │ │ ├── importer_test.py │ │ ├── load_library.py │ │ ├── op_def_registry.py │ │ ├── ops.py │ │ ├── ops_test.py │ │ ├── proto_test.py │ │ ├── python_op_gen.cc │ │ ├── python_op_gen.h │ │ ├── python_op_gen.i │ │ ├── python_op_gen_main.cc │ │ ├── random_seed.py │ │ ├── registry.py │ │ ├── registry_test.py │ │ ├── tensor_shape.py │ │ ├── tensor_shape_div_test.py │ │ ├── tensor_shape_test.py │ │ ├── tensor_util.py │ │ ├── tensor_util_test.py │ │ ├── test_file_system.cc │ │ ├── test_ops.cc │ │ ├── test_util.py │ │ ├── test_util_test.py │ │ ├── versions.py │ │ └── versions_test.py │ ├── kernel_tests │ │ ├── __init__.py │ │ ├── argmax_op_test.py │ │ ├── array_ops_test.py │ │ ├── attention_ops_test.py │ │ ├── batch_matmul_op_test.py │ │ ├── batch_matrix_band_part_op_test.py │ │ ├── batchtospace_op_test.py │ │ ├── bcast_ops_test.py │ │ ├── benchmark_test.py │ │ ├── bias_op_test.py │ │ ├── bitcast_op_test.py │ │ ├── candidate_sampler_ops_test.py │ │ ├── cast_op_test.py │ │ ├── check_ops_test.py │ │ ├── cholesky_op_test.py │ │ ├── clip_ops_test.py │ │ ├── concat_op_test.py │ │ ├── constant_op_test.py │ │ ├── control_flow_ops_py_test.py │ │ ├── conv_ops_3d_test.py │ │ ├── conv_ops_test.py │ │ ├── cross_grad_test.py │ │ ├── cwise_ops_test.py │ │ ├── decode_csv_op_test.py │ │ ├── decode_raw_op_test.py │ │ ├── denormal_test.py │ │ ├── dense_update_ops_no_tsan_test.py │ │ ├── dense_update_ops_test.py │ │ ├── depthtospace_op_test.py │ │ ├── depthwise_conv_op_test.py │ │ ├── determinant_op_test.py │ │ ├── diag_op_test.py │ │ ├── division_future_test.py │ │ ├── division_past_test.py │ │ ├── dynamic_partition_op_test.py │ │ ├── dynamic_stitch_op_test.py │ │ ├── edit_distance_op_test.py │ │ ├── embedding_ops_test.py │ │ ├── fft_ops_test.py │ │ ├── fifo_queue_test.py │ │ ├── functional_ops_test.py │ │ ├── gather_nd_op_test.py │ │ ├── gather_op_test.py │ │ ├── gradient_checker.py │ │ ├── gradient_checker_test.py │ │ ├── gradient_correctness_test.py │ │ ├── identity_op_py_test.py │ │ ├── in_topk_op_test.py │ │ ├── init_ops_test.py │ │ ├── io_ops_test.py │ │ ├── linalg_grad_test.py │ │ ├── linalg_ops_test.py │ │ ├── listdiff_op_test.py │ │ ├── logging_ops_test.py │ │ ├── lrn_op_test.py │ │ ├── matmul_op_test.py │ │ ├── matrix_inverse_op_test.py │ │ ├── matrix_solve_ls_op_test.py │ │ ├── matrix_solve_op_test.py │ │ ├── matrix_triangular_solve_op_test.py │ │ ├── multinomial_op_test.py │ │ ├── numerics_test.py │ │ ├── one_hot_op_test.py │ │ ├── pack_op_test.py │ │ ├── pad_op_test.py │ │ ├── padding_fifo_queue_test.py │ │ ├── parsing_ops_test.py │ │ ├── partitioned_variables_test.py │ │ ├── pooling_ops_3d_test.py │ │ ├── pooling_ops_test.py │ │ ├── py_func_test.py │ │ ├── random_crop_test.py │ │ ├── random_ops_test.py │ │ ├── random_shuffle_queue_test.py │ │ ├── reader_ops_test.py │ │ ├── reduce_join_op_test.py │ │ ├── reduction_ops_test.py │ │ ├── relu_op_test.py │ │ ├── reshape_op_test.py │ │ ├── reverse_sequence_op_test.py │ │ ├── rnn_cell_test.py │ │ ├── rnn_test.py │ │ ├── save_restore_ops_test.py │ │ ├── scalar_strict_test.py │ │ ├── scatter_ops_test.py │ │ ├── segment_reduction_ops_test.py │ │ ├── self_adjoint_eig_op_test.py │ │ ├── seq2seq_test.py │ │ ├── session_ops_test.py │ │ ├── shape_ops_test.py │ │ ├── slice_op_test.py │ │ ├── softmax_op_test.py │ │ ├── softplus_op_test.py │ │ ├── softsign_op_test.py │ │ ├── spacetobatch_op_test.py │ │ ├── spacetodepth_op_test.py │ │ ├── sparse_add_op_test.py │ │ ├── sparse_concat_op_test.py │ │ ├── sparse_matmul_op_test.py │ │ ├── sparse_ops_test.py │ │ ├── sparse_reorder_op_test.py │ │ ├── sparse_serialization_ops_test.py │ │ ├── sparse_split_op_test.py │ │ ├── sparse_tensor_dense_matmul_grad_test.py │ │ ├── sparse_tensor_dense_matmul_op_test.py │ │ ├── sparse_to_dense_op_py_test.py │ │ ├── sparse_xent_op_test.py │ │ ├── sparsemask_op_test.py │ │ ├── split_op_test.py │ │ ├── stack_ops_test.py │ │ ├── string_to_hash_bucket_op_test.py │ │ ├── string_to_number_op_test.py │ │ ├── summary_audio_op_test.py │ │ ├── summary_image_op_test.py │ │ ├── summary_ops_test.py │ │ ├── template_test.py │ │ ├── tensor_array_ops_test.py │ │ ├── topk_op_test.py │ │ ├── trace_op_test.py │ │ ├── transpose_op_test.py │ │ ├── unique_op_test.py │ │ ├── unpack_op_test.py │ │ ├── variable_ops_test.py │ │ ├── variable_scope_test.py │ │ ├── variables_test.py │ │ ├── where_op_test.py │ │ ├── xent_op_test.py │ │ └── zero_division_test.py │ ├── lib │ │ ├── __init__.py │ │ ├── core │ │ │ ├── __init__.py │ │ │ ├── numpy.cc │ │ │ ├── numpy.h │ │ │ ├── py_func.cc │ │ │ ├── py_func.h │ │ │ ├── py_func.i │ │ │ ├── status_helper.i │ │ │ └── strings.i │ │ └── io │ │ │ ├── __init__.py │ │ │ ├── py_record_reader.cc │ │ │ ├── py_record_reader.h │ │ │ ├── py_record_reader.i │ │ │ ├── py_record_writer.cc │ │ │ ├── py_record_writer.h │ │ │ ├── py_record_writer.i │ │ │ ├── python_io.py │ │ │ └── tf_record.py │ ├── ops │ │ ├── __init__.py │ │ ├── array_grad.py │ │ ├── array_ops.py │ │ ├── batch_norm_benchmark.py │ │ ├── candidate_sampling_ops.py │ │ ├── check_ops.py │ │ ├── clip_ops.py │ │ ├── common_shapes.py │ │ ├── constant_op.py │ │ ├── control_flow_grad.py │ │ ├── control_flow_ops.py │ │ ├── control_flow_ops_test.py │ │ ├── data_flow_grad.py │ │ ├── data_flow_ops.py │ │ ├── embedding_ops.py │ │ ├── functional_ops.py │ │ ├── gradients.py │ │ ├── gradients_test.py │ │ ├── histogram_ops.py │ │ ├── histogram_ops_test.py │ │ ├── image_grad.py │ │ ├── image_grad_test.py │ │ ├── image_ops.py │ │ ├── image_ops_test.py │ │ ├── init_ops.py │ │ ├── io_ops.py │ │ ├── linalg_grad.py │ │ ├── linalg_ops.py │ │ ├── logging_ops.py │ │ ├── math_grad.py │ │ ├── math_grad_test.py │ │ ├── math_ops.py │ │ ├── math_ops_test.py │ │ ├── nn.py │ │ ├── nn_batchnorm_test.py │ │ ├── nn_conv_test.py │ │ ├── nn_grad.py │ │ ├── nn_ops.py │ │ ├── nn_test.py │ │ ├── nn_xent_test.py │ │ ├── numerics.py │ │ ├── op_def_library.py │ │ ├── op_def_library_test.py │ │ ├── parsing_ops.py │ │ ├── partitioned_variables.py │ │ ├── random_ops.py │ │ ├── rnn.py │ │ ├── rnn_cell.py │ │ ├── script_ops.py │ │ ├── seq2seq.py │ │ ├── session_ops.py │ │ ├── sparse_grad.py │ │ ├── sparse_ops.py │ │ ├── special_math_ops.py │ │ ├── special_math_ops_test.py │ │ ├── standard_ops.py │ │ ├── state_grad.py │ │ ├── state_ops.py │ │ ├── string_ops.py │ │ ├── template.py │ │ ├── tensor_array_grad.py │ │ ├── tensor_array_ops.py │ │ ├── variable_scope.py │ │ └── variables.py │ ├── platform │ │ ├── app.py │ │ ├── base.i │ │ ├── benchmark.py │ │ ├── control_imports.py │ │ ├── default │ │ │ ├── __init__.py │ │ │ ├── _app.py │ │ │ ├── _flags.py │ │ │ ├── _gfile.py │ │ │ ├── _googletest.py │ │ │ ├── _parameterized.py │ │ │ ├── _resource_loader.py │ │ │ ├── _resource_loader_test.py │ │ │ ├── _status_bar.py │ │ │ ├── flags_test.py │ │ │ ├── gfile_test.py │ │ │ └── logging_test.py │ │ ├── flags.py │ │ ├── flags_test.py │ │ ├── gfile.py │ │ ├── gfile_test.py │ │ ├── googletest.py │ │ ├── logging_test.py │ │ ├── numpy.i │ │ ├── parameterized.py │ │ ├── resource_loader.py │ │ ├── resource_loader_test.py │ │ ├── status_bar.py │ │ ├── sysconfig.py │ │ ├── test.py │ │ └── tf_logging.py │ ├── summary │ │ ├── README.md │ │ ├── __init__.py │ │ ├── event_accumulator.py │ │ ├── event_accumulator_test.py │ │ ├── event_file_inspector.py │ │ ├── event_file_inspector_test.py │ │ ├── event_multiplexer.py │ │ ├── event_multiplexer_test.py │ │ └── impl │ │ │ ├── __init__.py │ │ │ ├── directory_watcher.py │ │ │ ├── directory_watcher_test.py │ │ │ ├── event_file_loader.py │ │ │ ├── event_file_loader_test.py │ │ │ ├── gcs.py │ │ │ ├── gcs_file_loader.py │ │ │ ├── gcs_file_loader_test.py │ │ │ ├── io_wrapper.py │ │ │ ├── reservoir.py │ │ │ └── reservoir_test.py │ ├── tensorflow.i │ ├── tools │ │ ├── BUILD │ │ ├── freeze_graph.py │ │ ├── freeze_graph_test.py │ │ ├── graph_metrics.py │ │ ├── graph_metrics_test.py │ │ ├── inspect_checkpoint.py │ │ ├── strip_unused.py │ │ └── strip_unused_test.py │ ├── training │ │ ├── __init__.py │ │ ├── adadelta.py │ │ ├── adadelta_test.py │ │ ├── adagrad.py │ │ ├── adagrad_test.py │ │ ├── adam.py │ │ ├── adam_test.py │ │ ├── checkpoint_state.proto │ │ ├── coordinator.py │ │ ├── coordinator_test.py │ │ ├── device_setter.py │ │ ├── device_setter_test.py │ │ ├── ftrl.py │ │ ├── ftrl_test.py │ │ ├── gradient_descent.py │ │ ├── gradient_descent_test.py │ │ ├── input.py │ │ ├── input_test.py │ │ ├── learning_rate_decay.py │ │ ├── learning_rate_decay_test.py │ │ ├── momentum.py │ │ ├── momentum_test.py │ │ ├── moving_averages.py │ │ ├── moving_averages_test.py │ │ ├── optimizer.py │ │ ├── optimizer_test.py │ │ ├── queue_runner.py │ │ ├── queue_runner_test.py │ │ ├── rmsprop.py │ │ ├── rmsprop_test.py │ │ ├── saver.py │ │ ├── saver_io.i │ │ ├── saver_test.py │ │ ├── server_lib.i │ │ ├── server_lib.py │ │ ├── server_lib_test.py │ │ ├── session_manager.py │ │ ├── session_manager_test.py │ │ ├── slot_creator.py │ │ ├── slot_creator_test.py │ │ ├── summary_io.py │ │ ├── summary_writer_test.py │ │ ├── supervisor.py │ │ ├── supervisor_test.py │ │ ├── sync_replicas_optimizer.py │ │ ├── tensorboard_logging.py │ │ ├── tensorboard_logging_test.py │ │ ├── training.py │ │ ├── training_ops.py │ │ ├── training_ops_test.py │ │ └── training_util.py │ ├── user_ops │ │ ├── __init__.py │ │ └── user_ops.py │ └── util │ │ ├── __init__.py │ │ ├── all_util.py │ │ ├── compat.py │ │ ├── port.i │ │ ├── protobuf │ │ ├── __init__.py │ │ ├── compare.py │ │ ├── compare_test.proto │ │ └── compare_test.py │ │ └── py_checkpoint_reader.i ├── stream_executor │ ├── BUILD │ ├── blas.cc │ ├── blas.h │ ├── cuda │ │ ├── cuda_activation.cc │ │ ├── cuda_activation.h │ │ ├── cuda_blas.cc │ │ ├── cuda_blas.h │ │ ├── cuda_diagnostics.cc │ │ ├── cuda_diagnostics.h │ │ ├── cuda_dnn.cc │ │ ├── cuda_dnn.h │ │ ├── cuda_driver.cc │ │ ├── cuda_driver.h │ │ ├── cuda_event.cc │ │ ├── cuda_event.h │ │ ├── cuda_fft.cc │ │ ├── cuda_fft.h │ │ ├── cuda_gpu_executor.cc │ │ ├── cuda_gpu_executor.h │ │ ├── cuda_helpers.h │ │ ├── cuda_kernel.h │ │ ├── cuda_platform.cc │ │ ├── cuda_platform.h │ │ ├── cuda_platform_id.cc │ │ ├── cuda_platform_id.h │ │ ├── cuda_rng.cc │ │ ├── cuda_rng.h │ │ ├── cuda_stream.cc │ │ ├── cuda_stream.h │ │ ├── cuda_timer.cc │ │ ├── cuda_timer.h │ │ └── multi_op_activation.h │ ├── device_description.cc │ ├── device_description.h │ ├── device_memory.h │ ├── device_options.h │ ├── dnn.cc │ ├── dnn.h │ ├── dso_loader.cc │ ├── dso_loader.h │ ├── event.cc │ ├── event.h │ ├── executor_cache.cc │ ├── executor_cache.h │ ├── fft.h │ ├── gcuda.cc │ ├── gcuda.h │ ├── gpu_launch_dim.h │ ├── kernel.cc │ ├── kernel.h │ ├── kernel_cache_config.h │ ├── kernel_spec.cc │ ├── kernel_spec.h │ ├── launch_dim.h │ ├── lib │ │ ├── array_slice.h │ │ ├── casts.h │ │ ├── demangle.cc │ │ ├── demangle.h │ │ ├── env.h │ │ ├── error.h │ │ ├── human_readable.h │ │ ├── initialize.h │ │ ├── inlined_vector.h │ │ ├── mathutil.h │ │ ├── notification.h │ │ ├── numbers.cc │ │ ├── numbers.h │ │ ├── path.cc │ │ ├── path.h │ │ ├── process_state.cc │ │ ├── process_state.h │ │ ├── ptr_util.h │ │ ├── stacktrace.h │ │ ├── static_threadlocal.h │ │ ├── status.h │ │ ├── status_macros.h │ │ ├── statusor.h │ │ ├── str_util.h │ │ ├── strcat.h │ │ ├── stringpiece.h │ │ ├── stringprintf.h │ │ ├── thread_options.h │ │ └── threadpool.h │ ├── machine_manager.cc │ ├── machine_manager.h │ ├── multi_platform_manager.cc │ ├── multi_platform_manager.h │ ├── platform.cc │ ├── platform.h │ ├── platform │ │ ├── default │ │ │ └── mutex.h │ │ ├── logging.h │ │ ├── mutex.h │ │ ├── port.h │ │ └── thread_annotations.h │ ├── plugin.cc │ ├── plugin.h │ ├── plugin_registry.cc │ ├── plugin_registry.h │ ├── rng.cc │ ├── rng.h │ ├── scratch_allocator.cc │ ├── scratch_allocator.h │ ├── shared_memory_config.h │ ├── stream.cc │ ├── stream.h │ ├── stream_executor.h │ ├── stream_executor_internal.cc │ ├── stream_executor_internal.h │ ├── stream_executor_pimpl.cc │ ├── stream_executor_pimpl.h │ ├── temporary_device_memory.cc │ ├── temporary_device_memory.h │ ├── temporary_memory_manager.cc │ ├── temporary_memory_manager.h │ ├── timer.cc │ ├── timer.h │ └── trace_listener.h ├── tensorboard │ ├── .bowerrc │ ├── .gitignore │ ├── BUILD │ ├── CHANGES │ ├── DEVELOPMENT.md │ ├── README.md │ ├── TAG │ ├── __init__.py │ ├── app │ │ ├── BUILD │ │ └── analytics.js │ ├── backend │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── handler.py │ │ ├── handler_test.py │ │ ├── process_graph.py │ │ ├── server.py │ │ └── server_test.py │ ├── bower.json │ ├── bower │ │ └── BUILD │ ├── components │ │ ├── BUILD │ │ ├── index.html │ │ ├── tf-audio-dashboard │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ ├── test │ │ │ │ ├── audioDashboardTests.ts │ │ │ │ ├── data │ │ │ │ │ └── runs.json │ │ │ │ └── index.html │ │ │ ├── tf-audio-dashboard.html │ │ │ ├── tf-audio-grid.html │ │ │ └── tf-audio-loader.html │ │ ├── tf-backend │ │ │ ├── backend.ts │ │ │ ├── behavior.ts │ │ │ ├── requestManager.ts │ │ │ ├── router.ts │ │ │ ├── test │ │ │ │ ├── backendTests.ts │ │ │ │ ├── behaviorTests.ts │ │ │ │ ├── data │ │ │ │ │ ├── audio_run_run1_tag_audio1.json │ │ │ │ │ ├── compressedHistograms_run_run1_tag_histo1.json │ │ │ │ │ ├── example.json │ │ │ │ │ ├── histograms_run_run1_tag_histo1.json │ │ │ │ │ ├── images_run_run1_tag_im1.json │ │ │ │ │ ├── individualImage_index_0_tag_im1_run_run1.png │ │ │ │ │ ├── runs.json │ │ │ │ │ ├── scalars.json │ │ │ │ │ └── scalars_run_run1_tag_cross_entropy__281_29.json │ │ │ │ ├── index.html │ │ │ │ └── requestManagerTest.ts │ │ │ ├── tf-backend.html │ │ │ └── urlPathHelpers.ts │ │ ├── tf-categorizer │ │ │ ├── categorizer.ts │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ ├── test │ │ │ │ ├── categorizerTest.ts │ │ │ │ └── index.html │ │ │ └── tf-categorizer.html │ │ ├── tf-collapsable-pane │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ └── tf-collapsable-pane.html │ │ ├── tf-color-scale │ │ │ ├── colorScale.ts │ │ │ ├── demo │ │ │ │ ├── index.html │ │ │ │ └── style.css │ │ │ ├── palettes.ts │ │ │ ├── test │ │ │ │ ├── colorScaleTests.ts │ │ │ │ └── index.html │ │ │ └── tf-color-scale.html │ │ ├── tf-dashboard-common │ │ │ ├── dashboard-style.html │ │ │ ├── reload-behavior.ts │ │ │ ├── run-color-style.html │ │ │ ├── scrollbar-style.html │ │ │ ├── tensorboard-color.html │ │ │ ├── tf-dashboard-layout.html │ │ │ ├── tf-dashboard.html │ │ │ ├── tf-downloader.html │ │ │ └── tf-no-data-warning.html │ │ ├── tf-event-dashboard │ │ │ ├── demo │ │ │ │ ├── data │ │ │ │ │ ├── runs.json │ │ │ │ │ └── scalars │ │ │ │ │ │ ├── alpha │ │ │ │ │ │ ├── d1.json │ │ │ │ │ │ ├── d2.json │ │ │ │ │ │ ├── d3.json │ │ │ │ │ │ └── d4.json │ │ │ │ │ │ └── beta │ │ │ │ │ │ ├── d1.json │ │ │ │ │ │ ├── d2.json │ │ │ │ │ │ ├── d3.json │ │ │ │ │ │ └── d4.json │ │ │ │ └── index.html │ │ │ ├── dragZoomInteraction.ts │ │ │ ├── tf-chart.html │ │ │ ├── tf-chart.ts │ │ │ ├── tf-event-dashboard.html │ │ │ ├── tf-run-selector.html │ │ │ └── tf-x-type-selector.html │ │ ├── tf-graph-app │ │ │ └── tf-graph-app.html │ │ ├── tf-graph-board │ │ │ └── tf-graph-board.html │ │ ├── tf-graph-common │ │ │ ├── lib │ │ │ │ ├── colors.ts │ │ │ │ ├── common.ts │ │ │ │ ├── externs.ts │ │ │ │ ├── graph.ts │ │ │ │ ├── hierarchy.ts │ │ │ │ ├── layout.ts │ │ │ │ ├── parser.ts │ │ │ │ ├── proto.ts │ │ │ │ ├── render.ts │ │ │ │ ├── scene │ │ │ │ │ ├── annotation.ts │ │ │ │ │ ├── contextmenu.ts │ │ │ │ │ ├── edge.ts │ │ │ │ │ ├── minimap.ts │ │ │ │ │ ├── node.ts │ │ │ │ │ └── scene.ts │ │ │ │ ├── template.ts │ │ │ │ └── util.ts │ │ │ ├── test │ │ │ │ ├── graph-test.ts │ │ │ │ ├── hierarchy-test.ts │ │ │ │ ├── index.html │ │ │ │ ├── layout-test.ts │ │ │ │ └── parser-test.ts │ │ │ └── tf-graph-common.html │ │ ├── tf-graph-dashboard │ │ │ └── tf-graph-dashboard.html │ │ ├── tf-graph-info │ │ │ ├── tf-graph-info.html │ │ │ ├── tf-node-info.html │ │ │ └── tf-node-list-item.html │ │ ├── tf-graph-loader │ │ │ ├── test │ │ │ │ ├── index.html │ │ │ │ └── loader.ts │ │ │ └── tf-graph-loader.html │ │ ├── tf-graph │ │ │ ├── demo │ │ │ │ ├── index.html │ │ │ │ └── tf-graph-demo.html │ │ │ ├── tf-graph-controls.html │ │ │ ├── tf-graph-icon.html │ │ │ ├── tf-graph-minimap.html │ │ │ ├── tf-graph-scene.html │ │ │ └── tf-graph.html │ │ ├── tf-histogram-dashboard │ │ │ ├── rebin.ts │ │ │ ├── test │ │ │ │ ├── index.html │ │ │ │ └── rebinTests.ts │ │ │ ├── tf-histogram-dashboard.html │ │ │ └── tf-vz-histogram-series.html │ │ ├── tf-image-dashboard │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ ├── test │ │ │ │ ├── data │ │ │ │ │ └── runs.json │ │ │ │ ├── imageDashboardTests.ts │ │ │ │ └── index.html │ │ │ ├── tf-image-dashboard.html │ │ │ ├── tf-image-grid.html │ │ │ └── tf-image-loader.html │ │ ├── tf-imports │ │ │ ├── README.md │ │ │ ├── d3.html │ │ │ ├── dagre.html │ │ │ ├── google │ │ │ │ ├── README.md │ │ │ │ ├── d3.html │ │ │ │ ├── dagre.html │ │ │ │ ├── graphlib.html │ │ │ │ ├── lodash.html │ │ │ │ └── plottable.html │ │ │ ├── graphlib.html │ │ │ ├── lodash.html │ │ │ └── plottable.html │ │ ├── tf-multi-checkbox │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ └── tf-multi-checkbox.html │ │ ├── tf-regex-group │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ └── tf-regex-group.html │ │ └── tf-tensorboard │ │ │ ├── autoReloadBehavior.ts │ │ │ ├── tensorboard.ts │ │ │ ├── test │ │ │ ├── autoReloadTests.ts │ │ │ ├── data │ │ │ │ ├── graph_run_run1.pbtxt │ │ │ │ ├── graph_run_run2.pbtxt │ │ │ │ └── runs.json │ │ │ ├── e2eTests.html │ │ │ ├── e2eTests.ts │ │ │ ├── fastTabSwitch.html │ │ │ ├── fastTabSwitch.ts │ │ │ ├── index.html │ │ │ ├── tensorboardTests.html │ │ │ └── tensorboardTests.ts │ │ │ ├── tf-tensorboard-demo.html │ │ │ └── tf-tensorboard.html │ ├── demo │ │ ├── data │ │ │ ├── audio_run_run1_tag_au1_2Faudio_2F0.json │ │ │ ├── audio_run_run2_tag_au2_2Faudio_2F0.json │ │ │ ├── compressedHistograms_run_run1_tag_histo1.json │ │ │ ├── compressedHistograms_run_run2_tag_histo1.json │ │ │ ├── compressedHistograms_run_run2_tag_histo2.json │ │ │ ├── graph_run_run1.pbtxt │ │ │ ├── graph_run_run2.pbtxt │ │ │ ├── histograms_run_run1_tag_histo1.json │ │ │ ├── histograms_run_run2_tag_histo1.json │ │ │ ├── histograms_run_run2_tag_histo2.json │ │ │ ├── images_run_run1_tag_im1_2Fimage_2F0.json │ │ │ ├── images_run_run1_tag_im2_2Fimage_2F0.json │ │ │ ├── images_run_run2_tag_im1_2Fimage_2F0.json │ │ │ ├── individualAudio_index_0_tag_au1_2Faudio_2F0_run_run1.wav │ │ │ ├── individualAudio_index_0_tag_au2_2Faudio_2F0_run_run2.wav │ │ │ ├── individualImage_tag_im1_2Fimage_2F0_index_0_run_run1.png │ │ │ ├── individualImage_tag_im1_2Fimage_2F0_index_0_run_run2.png │ │ │ ├── individualImage_tag_im2_2Fimage_2F0_index_0_run_run1.png │ │ │ ├── runs.json │ │ │ ├── scalars.json │ │ │ ├── scalars_run_run1_tag_bar_2Fsquare.json │ │ │ ├── scalars_run_run1_tag_foo_2Fcos.json │ │ │ ├── scalars_run_run1_tag_foo_2Fsin.json │ │ │ ├── scalars_run_run1_tag_foo_2Fsquare.json │ │ │ ├── scalars_run_run2_tag_bar_2Fsquare.json │ │ │ ├── scalars_run_run2_tag_foo_2Fcos.json │ │ │ └── scalars_run_run2_tag_foo_2Fsquare.json │ │ └── index.html │ ├── dist │ │ ├── index.html │ │ └── tf-tensorboard.html │ ├── gulp_tasks │ │ ├── bower.js │ │ ├── compile.js │ │ ├── test.js │ │ ├── tslint.js │ │ └── vulcanize.js │ ├── gulpfile.js │ ├── http_api.md │ ├── lib │ │ ├── BUILD │ │ ├── css │ │ │ └── global.css │ │ ├── js │ │ │ ├── BUILD │ │ │ ├── nanite │ │ │ │ ├── nanite.ts │ │ │ │ └── test │ │ │ │ │ ├── index.html │ │ │ │ │ └── naniteTest.ts │ │ │ └── node-radar │ │ │ │ ├── demo │ │ │ │ └── index.html │ │ │ │ ├── nodeRadar.ts │ │ │ │ └── test │ │ │ │ ├── index.html │ │ │ │ └── nodeRadarTest.ts │ │ └── python │ │ │ ├── BUILD │ │ │ ├── __init__.py │ │ │ ├── json_util.py │ │ │ └── json_util_test.py │ ├── package.json │ ├── scripts │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── generate_testdata.py │ │ └── serialize_tensorboard.py │ ├── tensorboard.py │ ├── tsconfig.json │ ├── tslint.json │ ├── typings.json │ └── wct.conf.json ├── tensorflow.bzl ├── tf_exported_symbols.lds ├── tf_version_script.lds ├── tools │ ├── __init__.py │ ├── benchmark │ │ ├── BUILD │ │ ├── README.md │ │ ├── benchmark_model.cc │ │ ├── benchmark_model.h │ │ ├── benchmark_model_main.cc │ │ └── benchmark_model_test.cc │ ├── ci_build │ │ ├── Dockerfile.android │ │ ├── Dockerfile.cpu │ │ ├── Dockerfile.debian.jessie.cpu │ │ ├── Dockerfile.gpu │ │ ├── Dockerfile.tensorboard │ │ ├── README.md │ │ ├── builds │ │ │ ├── android.sh │ │ │ ├── benchmark.sh │ │ │ ├── builds_common.sh │ │ │ ├── cmake.sh │ │ │ ├── configured │ │ │ ├── docker_test.sh │ │ │ ├── integration_tests.sh │ │ │ ├── pip.sh │ │ │ ├── print_build_info.sh │ │ │ ├── py_test_delegate.sh │ │ │ ├── tensorboard.sh │ │ │ ├── test_installation.sh │ │ │ ├── test_tutorials.sh │ │ │ ├── test_user_ops.sh │ │ │ └── with_the_same_user │ │ ├── ci_build.sh │ │ ├── ci_parameterized_build.sh │ │ ├── ci_sanity.sh │ │ ├── install │ │ │ ├── .bazelrc │ │ │ ├── install_bazel.sh │ │ │ ├── install_bootstrap_deb_packages.sh │ │ │ ├── install_deb_packages.sh │ │ │ ├── install_pip_packages.sh │ │ │ ├── install_proto3.sh │ │ │ ├── install_python3.5_pip_packages.sh │ │ │ └── install_tensorboard_packages.sh │ │ ├── pylintrc │ │ └── update_version.sh │ ├── dist_test │ │ ├── Dockerfile │ │ ├── Dockerfile.local │ │ ├── README.md │ │ ├── __init__.py │ │ ├── build_server.sh │ │ ├── local │ │ │ ├── Dockerfile │ │ │ ├── start_local_k8s_service.sh │ │ │ ├── start_tf_cluster_container.sh │ │ │ └── test_local_tf_cluster.sh │ │ ├── local_test.sh │ │ ├── python │ │ │ └── mnist_replica.py │ │ ├── remote_test.sh │ │ ├── scripts │ │ │ ├── create_tf_cluster.sh │ │ │ ├── delete_tf_cluster.sh │ │ │ ├── dist_mnist_test.sh │ │ │ ├── dist_test.sh │ │ │ ├── k8s_tensorflow.py │ │ │ └── utils.sh │ │ └── server │ │ │ ├── BUILD │ │ │ ├── Dockerfile │ │ │ ├── Dockerfile.test │ │ │ ├── __init__.py │ │ │ ├── grpc_tensorflow_server.py │ │ │ ├── grpc_tensorflow_server_wrapper.sh │ │ │ └── parse_cluster_spec_test.py │ ├── docker │ │ ├── BUILD │ │ ├── Dockerfile │ │ ├── Dockerfile.devel │ │ ├── Dockerfile.devel-gpu │ │ ├── Dockerfile.gpu │ │ ├── LICENSE │ │ ├── README.md │ │ ├── __init__.py │ │ ├── docker_run_gpu.sh │ │ ├── jupyter_notebook_config.py │ │ ├── notebooks │ │ │ ├── 1_hello_tensorflow.ipynb │ │ │ ├── 2_getting_started.ipynb │ │ │ ├── 3_mnist_from_scratch.ipynb │ │ │ ├── BUILD │ │ │ └── LICENSE │ │ ├── parameterized_docker_build.sh │ │ ├── run_jupyter.sh │ │ └── simple_console.py │ ├── docs │ │ ├── BUILD │ │ ├── gen_cc_md.py │ │ ├── gen_docs.sh │ │ ├── gen_docs_test.sh │ │ └── tf-doxy_for_md-config │ ├── pip_package │ │ ├── BUILD │ │ ├── MANIFEST.in │ │ ├── README │ │ ├── build_pip_package.sh │ │ ├── setup.py │ │ └── simple_console.py │ ├── proto_text │ │ ├── BUILD │ │ ├── gen_proto_text_functions.cc │ │ ├── gen_proto_text_functions_lib.cc │ │ ├── gen_proto_text_functions_lib.h │ │ ├── gen_proto_text_functions_lib_test.cc │ │ ├── placeholder.txt │ │ └── test.proto │ ├── swig │ │ ├── .gitignore │ │ └── swig.sh │ └── test │ │ ├── BUILD │ │ ├── __init__.py │ │ ├── check_futures_test.py │ │ ├── gpu_info_lib.py │ │ ├── performance.bzl │ │ ├── run_and_gather_logs.py │ │ ├── run_and_gather_logs_lib.py │ │ ├── system_info.py │ │ └── system_info_lib.py ├── user_ops │ ├── BUILD │ ├── ackermann_op.cc │ └── ackermann_test.py └── workspace.bzl ├── third_party ├── avro │ ├── BUILD │ └── build_defs.bzl ├── boringssl │ ├── BUILD │ └── err_data.c ├── eigen3 │ ├── BUILD │ ├── Eigen │ │ ├── Cholesky │ │ ├── Core │ │ ├── Eigenvalues │ │ ├── LU │ │ └── QR │ ├── LICENSE │ └── unsupported │ │ └── Eigen │ │ └── CXX11 │ │ ├── Core │ │ ├── FixedPoint │ │ ├── NeuralNetworks │ │ ├── Tensor │ │ └── src │ │ ├── FixedPoint │ │ ├── FixedPointTypes.h │ │ ├── MatMatProduct.h │ │ ├── MatMatProductAVX2.h │ │ ├── MatMatProductNEON.h │ │ ├── MatVecProduct.h │ │ ├── PacketMathAVX2.h │ │ └── TypeCastingAVX2.h │ │ └── NeuralNetworks │ │ ├── Activations.h │ │ ├── Attention.h │ │ ├── BackwardCuboidConvolutions.h │ │ ├── BackwardSpatialConvolutions.h │ │ ├── CuboidConvolution.h │ │ ├── Patch3d.h │ │ ├── Pooling.h │ │ ├── SoftMax.h │ │ ├── SpatialConvolutions.h │ │ └── TensorConvolutionByFFT.h ├── gpus │ ├── crosstool │ │ ├── BUILD │ │ ├── CROSSTOOL │ │ ├── LICENSE │ │ └── clang │ │ │ └── bin │ │ │ └── crosstool_wrapper_driver_is_not_gcc │ └── cuda │ │ ├── BUILD │ │ ├── LICENSE │ │ ├── build_defs.bzl │ │ ├── cuda_config.sh │ │ └── platform.bzl └── py │ └── numpy │ └── BUILD ├── tools └── bazel.rc.template ├── util └── python │ ├── BUILD │ └── python_config.sh └── zlib.BUILD /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | .ipynb_checkpoints 3 | node_modules 4 | /bazel-bin 5 | /bazel-ci_build-cache 6 | /bazel-genfiles 7 | /bazel-out 8 | /bazel-tensorflow 9 | /bazel-testlogs 10 | /bazel-tf 11 | /tensorflow/contrib/cmake/build 12 | /third_party/gpus/cuda/bin 13 | /third_party/gpus/cuda/cuda.config 14 | /third_party/gpus/cuda/extras 15 | /third_party/gpus/cuda/include 16 | /third_party/gpus/cuda/lib 17 | /third_party/gpus/cuda/lib64 18 | /third_party/gpus/cuda/nvvm 19 | /third_party/py/numpy/numpy_include 20 | /tools/bazel.rc 21 | /tools/python_bin_path.sh 22 | /util/python/python_include 23 | /util/python/python_lib 24 | /pip_test 25 | /_python_build 26 | *.pyc 27 | __pycache__ 28 | -------------------------------------------------------------------------------- /.gitmodules: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/.gitmodules -------------------------------------------------------------------------------- /AUTHORS: -------------------------------------------------------------------------------- 1 | # This is the official list of TensorFlow authors for copyright purposes. 2 | # This file is distinct from the CONTRIBUTORS files. 3 | # See the latter for an explanation. 4 | 5 | # Names should be added to this file as: 6 | # Name or Organization 7 | # The email address is not required for organizations. 8 | 9 | Google Inc. 10 | -------------------------------------------------------------------------------- /ISSUE_TEMPLATE.md: -------------------------------------------------------------------------------- 1 | Feel free to use the issue tracker not just to report bugs, but also to ask general questions. 2 | -------------------------------------------------------------------------------- /build_pip_package.sh: -------------------------------------------------------------------------------- 1 | bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package -------------------------------------------------------------------------------- /build_user_op.sh: -------------------------------------------------------------------------------- 1 | bazel build -c opt --config=cuda //tensorflow/core/user_ops:roi_pooling_op.so 2 | bazel build -c opt --config=cuda //tensorflow/core/user_ops:roi_pooling_op_grad.so -------------------------------------------------------------------------------- /eigen.BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//visibility:public"]) 2 | 3 | archive_dir = "eigen-eigen-f3a13643ac1f" 4 | 5 | cc_library( 6 | name = "eigen", 7 | hdrs = glob([archive_dir+"/**/*.h", archive_dir+"/unsupported/Eigen/CXX11/*", archive_dir+"/Eigen/*"]), 8 | includes = [ archive_dir ], 9 | visibility = ["//visibility:public"], 10 | ) 11 | -------------------------------------------------------------------------------- /gmock.BUILD: -------------------------------------------------------------------------------- 1 | cc_library( 2 | name = "gtest", 3 | srcs = [ 4 | "gmock-1.7.0/gtest/src/gtest-all.cc", 5 | "gmock-1.7.0/src/gmock-all.cc", 6 | ], 7 | hdrs = glob([ 8 | "gmock-1.7.0/**/*.h", 9 | "gmock-1.7.0/gtest/src/*.cc", 10 | "gmock-1.7.0/src/*.cc", 11 | ]), 12 | includes = [ 13 | "gmock-1.7.0", 14 | "gmock-1.7.0/gtest", 15 | "gmock-1.7.0/gtest/include", 16 | "gmock-1.7.0/include", 17 | ], 18 | linkopts = ["-pthread"], 19 | visibility = ["//visibility:public"], 20 | ) 21 | 22 | cc_library( 23 | name = "gtest_main", 24 | srcs = ["gmock-1.7.0/src/gmock_main.cc"], 25 | linkopts = ["-pthread"], 26 | visibility = ["//visibility:public"], 27 | deps = [":gtest"], 28 | ) 29 | -------------------------------------------------------------------------------- /navbar.md: -------------------------------------------------------------------------------- 1 | # TensorFlow 2 | 3 | * [Home][home] 4 | * [Getting Started](/tensorflow/g3doc/get_started/index.md) 5 | * [Mechanics](/tensorflow/g3doc/how_tos/index.md) 6 | * [Tutorials](/tensorflow/g3doc/tutorials/index.md) 7 | * [Python API](/tensorflow/g3doc/api_docs/python/index.md) 8 | * [C++ API](/tensorflow/g3doc/api_docs/cc/index.md) 9 | * [Other Resources](/tensorflow/g3doc/resources/index.md) 10 | 11 | [home]: /tensorflow/g3doc/index.md 12 | -------------------------------------------------------------------------------- /six.BUILD: -------------------------------------------------------------------------------- 1 | genrule( 2 | name = "copy_six", 3 | srcs = ["six-1.10.0/six.py"], 4 | outs = ["six.py"], 5 | cmd = "cp $< $(@)", 6 | ) 7 | 8 | py_library( 9 | name = "six", 10 | srcs = ["six.py"], 11 | visibility = ["//visibility:public"], 12 | srcs_version = "PY2AND3", 13 | ) 14 | -------------------------------------------------------------------------------- /tensorflow/contrib/avro/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Contains ops for reading and writing Apache Avro files. 3 | # (https://avro.apache.org/) 4 | 5 | licenses(["notice"]) # Apache 2.0 6 | 7 | exports_files(["LICENSE"]) 8 | 9 | package(default_visibility = ["//tensorflow:__subpackages__"]) 10 | 11 | load("//third_party/avro:build_defs.bzl", "avro_gen_cpp") 12 | 13 | avro_gen_cpp( 14 | name = "example_h", 15 | srcs = ["example.json"], 16 | outs = ["example.h"], 17 | namespace = "tensorflow", 18 | ) 19 | 20 | filegroup( 21 | name = "all_files", 22 | srcs = glob( 23 | ["**/*"], 24 | exclude = [ 25 | "**/METADATA", 26 | "**/OWNERS", 27 | ], 28 | ), 29 | visibility = ["//tensorflow:__subpackages__"], 30 | ) 31 | -------------------------------------------------------------------------------- /tensorflow/contrib/avro/README.md: -------------------------------------------------------------------------------- 1 | # TensorFlow Avro support 2 | 3 | This directory contains code for reading and writing 4 | [Apache Avro](https://avro.apache.org/) data in TensorFlow. -------------------------------------------------------------------------------- /tensorflow/contrib/avro/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/contrib/avro/__init__.py -------------------------------------------------------------------------------- /tensorflow/contrib/cmake/install.cmake: -------------------------------------------------------------------------------- 1 | # [TODO] -------------------------------------------------------------------------------- /tensorflow/contrib/cmake/tests.cmake: -------------------------------------------------------------------------------- 1 | # 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/tensorflow/contrib/framework/README.md: -------------------------------------------------------------------------------- 1 | # TensorFlow contrib framework. 2 | 3 | Common TensorFlow utilities, mostly used by tf.contrib.layers and 4 | tf.contrib.losses. 5 | -------------------------------------------------------------------------------- /tensorflow/contrib/ios_example/data/grace_hopper.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/contrib/ios_example/data/grace_hopper.jpg -------------------------------------------------------------------------------- /tensorflow/contrib/losses/README.md: -------------------------------------------------------------------------------- 1 | # TensorFlow contrib losses. 2 | 3 | ## losses 4 | 5 | Loss operations, typically with the following signatures. `predicted` and 6 | `target` generally have the same dimensions, and dim 0 is assumed to be batch. 7 | 8 | `squared(predicted, target, name=None) : Tensor` 9 | 10 | Other examples of foo are `absolute`, `logistic`, and `softmax`. 11 | 12 | Any parameter named `logit` should be the raw model outputs, not a normalized 13 | probablility distribution (i.e., `[0.0, 1.0]`). `target` for losses taking 14 | `logit` _should_ be a normalized probability distribution. 15 | -------------------------------------------------------------------------------- /tensorflow/contrib/metrics/README.md: -------------------------------------------------------------------------------- 1 | # TensorFlow evaluation metrics and summary statistics 2 | 3 | ## Evaluation metrics 4 | 5 | Compare predictions and labels, producing an aggregate loss. Typically produce 6 | a `value` and an `update_op`. The `update_op` is run with every batch to update 7 | internal state (e.g. accumulated right/wrong predictions). 8 | The `value` is extracted after all batches have been read (e.g. precision = 9 | number correct / total). 10 | 11 | ```python 12 | predictions = ... 13 | labels = ... 14 | value, update_op = some_metric(predictions, labels) 15 | 16 | for step_num in range(max_steps): 17 | update_op.run() 18 | 19 | print "evaluation score: ", value.eval() 20 | ``` 21 | -------------------------------------------------------------------------------- /tensorflow/contrib/metrics/kernels/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Contains kernels for evaluation metrics and summary statistics. 3 | 4 | licenses(["notice"]) # Apache 2.0 5 | 6 | exports_files(["LICENSE"]) 7 | 8 | package(default_visibility = ["//tensorflow:__subpackages__"]) 9 | 10 | cc_library( 11 | name = "set_kernels", 12 | srcs = ["set_kernels.cc"], 13 | deps = [ 14 | "@protobuf//:protobuf", 15 | "//tensorflow/core:framework_headers_lib", 16 | "//third_party/eigen3", 17 | ], 18 | alwayslink = 1, 19 | ) 20 | 21 | filegroup( 22 | name = "all_files", 23 | srcs = glob( 24 | ["**/*"], 25 | exclude = [ 26 | "**/METADATA", 27 | "**/OWNERS", 28 | ], 29 | ), 30 | ) 31 | -------------------------------------------------------------------------------- /tensorflow/contrib/opt/README.md: -------------------------------------------------------------------------------- 1 | # Optimization package 2 | 3 | Contains the following experimental optimization functionality: 4 | 5 | * Support for controlling a TensorFlow session using external optimization 6 | algorithms. 7 | 8 | Maintainer: joshburkart 9 | -------------------------------------------------------------------------------- /tensorflow/contrib/skflow/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # This is a old build rule for Scikit Flow (moved to learn). 3 | 4 | licenses(["notice"]) # Apache 2.0 5 | 6 | exports_files(["LICENSE"]) 7 | 8 | package(default_visibility = ["//tensorflow:__subpackages__"]) 9 | 10 | py_library( 11 | name = "skflow", 12 | srcs = ["__init__.py"], 13 | srcs_version = "PY2AND3", 14 | deps = [ 15 | "//tensorflow/contrib/learn", 16 | ], 17 | ) 18 | 19 | filegroup( 20 | name = "all_files", 21 | srcs = glob( 22 | ["**/*"], 23 | exclude = [ 24 | "**/METADATA", 25 | "**/OWNERS", 26 | ], 27 | ), 28 | visibility = ["//tensorflow:__subpackages__"], 29 | ) 30 | -------------------------------------------------------------------------------- /tensorflow/contrib/testing/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # contains parts of TensorFlow that are experimental or unstable and which are not supported. 3 | 4 | licenses(["notice"]) # Apache 2.0 5 | 6 | exports_files(["LICENSE"]) 7 | 8 | package(default_visibility = ["//tensorflow:__subpackages__"]) 9 | 10 | py_library( 11 | name = "testing_py", 12 | srcs = [ 13 | "__init__.py", 14 | "python/framework/test_util.py", 15 | ], 16 | srcs_version = "PY2AND3", 17 | ) 18 | 19 | filegroup( 20 | name = "all_files", 21 | srcs = glob( 22 | ["**/*"], 23 | exclude = [ 24 | "**/METADATA", 25 | "**/OWNERS", 26 | ], 27 | ), 28 | visibility = ["//tensorflow:__subpackages__"], 29 | ) 30 | -------------------------------------------------------------------------------- /tensorflow/core/distributed_runtime/README.md: -------------------------------------------------------------------------------- 1 | # Distributed TensorFlow 2 | 3 | This directory contains the initial open-source implementation of the 4 | distributed TensorFlow runtime, using [gRPC](http://grpc.io) for inter-process 5 | communication. 6 | 7 | To learn how to use the distributed runtime to create a TensorFlow cluster, 8 | see the "Distributed TensorFlow" How To, which is available [in this 9 | repository](../../g3doc/how_tos/distributed/index.md), and will be available 10 | on the TensorFlow website after the next version is released. 11 | -------------------------------------------------------------------------------- /tensorflow/core/framework/tensor_description.proto: -------------------------------------------------------------------------------- 1 | syntax = "proto3"; 2 | 3 | package tensorflow; 4 | // option cc_enable_arenas = true; 5 | option java_outer_classname = "TensorDescriptionProtos"; 6 | option java_multiple_files = true; 7 | option java_package = "org.tensorflow.framework"; 8 | 9 | import "tensorflow/core/framework/types.proto"; 10 | import "tensorflow/core/framework/tensor_shape.proto"; 11 | import "tensorflow/core/framework/allocation_description.proto"; 12 | 13 | message TensorDescription { 14 | // Data type of tensor elements 15 | DataType dtype = 1; 16 | 17 | // Shape of the tensor. 18 | TensorShapeProto shape = 2; 19 | 20 | // Information about the size and allocator used for the data 21 | AllocationDescription allocation_description = 4; 22 | }; 23 | -------------------------------------------------------------------------------- /tensorflow/core/kernels/reader_base.proto: -------------------------------------------------------------------------------- 1 | syntax = "proto3"; 2 | 3 | package tensorflow; 4 | // option cc_enable_arenas = true; 5 | option java_outer_classname = "ReaderBaseProtos"; 6 | option java_multiple_files = true; 7 | option java_package = "org.tensorflow.kernels"; 8 | 9 | // For serializing and restoring the state of ReaderBase, see 10 | // reader_base.h for details. 11 | message ReaderBaseState { 12 | int64 work_started = 1; 13 | int64 work_finished = 2; 14 | int64 num_records_produced = 3; 15 | bytes current_work = 4; 16 | }; 17 | -------------------------------------------------------------------------------- /tensorflow/core/lib/io/table_format.txt: -------------------------------------------------------------------------------- 1 | File format 2 | =========== 3 | 4 | The table format is similar to the table format for the LevelDB 5 | open source key/value store, with the exception that our tables 6 | do not support "filter" meta blocks (Bloom Filters). See: 7 | 8 | https://github.com/google/leveldb/blob/master/doc/table_format.txt 9 | -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/bad_huffman.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/bad_huffman.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/corrupt.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/corrupt.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/corrupt34_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/corrupt34_2.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/corrupt34_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/corrupt34_3.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/corrupt34_4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/corrupt34_4.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/jpeg_merge_test1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/jpeg_merge_test1.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/jpeg/testdata/jpeg_merge_test1_cmyk.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/jpeg/testdata/jpeg_merge_test1_cmyk.jpg -------------------------------------------------------------------------------- /tensorflow/core/lib/png/testdata/lena_gray.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/png/testdata/lena_gray.png -------------------------------------------------------------------------------- /tensorflow/core/lib/png/testdata/lena_rgba.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/core/lib/png/testdata/lena_rgba.png -------------------------------------------------------------------------------- /tensorflow/core/platform/cloud/testdata/application_default_credentials.json: -------------------------------------------------------------------------------- 1 | { 2 | "client_id": "fake-client-id.apps.googleusercontent.com", 3 | "client_secret": "fake-client-secret", 4 | "refresh_token": "fake-refresh-token", 5 | "type": "authorized_user" 6 | } 7 | -------------------------------------------------------------------------------- /tensorflow/core/platform/cloud/testdata/service_account_public_key.txt: -------------------------------------------------------------------------------- 1 | -----BEGIN PUBLIC KEY----- 2 | MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwrEZE6PWQYAy68mWPMuC 3 | 6KAD02Sb9Pv/FHWpGKe8MxxdDiz/spb2KIrWxxZolStHgDXAOoElbAv4GbRLJiiv 4 | El8k0gSP9YpIE56nSxfXxRIDH25NI3fhRIs5hSG+/p3lLV5NsdNrm1CYHnEbTY7O 5 | w7gpyxl0n+6q+ngguZTOGtBIMqVS4KIJlzTlJgeqvLFbtLP6uFc4OuGL6UZ+s4I7 6 | zSJVPBRxrFA+mOhBEPz/QjANBHBdIEhgh5VlmX/oRUK+D3zR/MnRTYtD8skiZSFM 7 | Uix1eWvKw/1wX0mieH1rUQbpIYdJTgFhROKuAJWVU7c+T6JHZwm8DqXaVz6oCJPl 8 | zwIDAQAB 9 | -----END PUBLIC KEY----- -------------------------------------------------------------------------------- /tensorflow/core/platform/default/build_config_root.bzl: -------------------------------------------------------------------------------- 1 | # Lower-level functionality for build config. 2 | # The functions in this file might be referred by tensorflow.bzl. They have to 3 | # be separate to avoid cyclic references. 4 | 5 | def tf_cuda_tests_tags(): 6 | return ["local"] 7 | -------------------------------------------------------------------------------- /tensorflow/core/protobuf/queue_runner.proto: -------------------------------------------------------------------------------- 1 | syntax = "proto3"; 2 | 3 | package tensorflow; 4 | // option cc_enable_arenas = true; 5 | option java_outer_classname = "QueueRunnerProtos"; 6 | option java_multiple_files = true; 7 | option java_package = "org.tensorflow.framework"; 8 | 9 | // Protocol buffer representing a QueueRunner. 10 | message QueueRunnerDef { 11 | // Queue name. 12 | string queue_name = 1; 13 | 14 | // A list of enqueue operations. 15 | repeated string enqueue_op_name = 2; 16 | 17 | // The operation to run to close the queue. 18 | string close_op_name = 3; 19 | 20 | // The operation to run to cancel the queue. 21 | string cancel_op_name = 4; 22 | } 23 | 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| name = "all_files", 23 | srcs = glob( 24 | ["**/*"], 25 | exclude = [ 26 | "**/METADATA", 27 | "**/OWNERS", 28 | ], 29 | ), 30 | ) 31 | -------------------------------------------------------------------------------- /tensorflow/examples/tutorials/word2vec/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/examples/tutorials/word2vec/__init__.py -------------------------------------------------------------------------------- /tensorflow/examples/udacity/.gitignore: -------------------------------------------------------------------------------- 1 | notMNIST_large* 2 | notMNIST_small* 3 | -------------------------------------------------------------------------------- /tensorflow/examples/udacity/Dockerfile: -------------------------------------------------------------------------------- 1 | FROM gcr.io/tensorflow/tensorflow:latest 2 | MAINTAINER Vincent Vanhoucke 3 | RUN pip install scikit-learn 4 | RUN rm -rf /notebooks/* 5 | ADD *.ipynb /notebooks/ 6 | WORKDIR /notebooks 7 | CMD ["/run_jupyter.sh"] 8 | -------------------------------------------------------------------------------- /tensorflow/g3doc/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/g3doc/__init__.py -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/ClassPartialTensorShapeUtils.md: -------------------------------------------------------------------------------- 1 | # `class tensorflow::PartialTensorShapeUtils` 2 | 3 | Static helper routines for ` PartialTensorShape `. Includes a few common predicates on a partially known tensor shape. 4 | 5 | 6 | 7 | ###Member Details 8 | 9 | #### `string tensorflow::PartialTensorShapeUtils::PartialShapeListString(const gtl::ArraySlice< PartialTensorShape > &shapes)` {#string_tensorflow_PartialTensorShapeUtils_PartialShapeListString} 10 | 11 | 12 | 13 | 14 | 15 | #### `bool tensorflow::PartialTensorShapeUtils::AreCompatible(const gtl::ArraySlice< PartialTensorShape > &shapes0, const gtl::ArraySlice< PartialTensorShape > &shapes1)` {#bool_tensorflow_PartialTensorShapeUtils_AreCompatible} 16 | 17 | 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/ClassThread.md: -------------------------------------------------------------------------------- 1 | # `class tensorflow::Thread` 2 | 3 | 4 | 5 | 6 | 7 | ###Member Details 8 | 9 | #### `tensorflow::Thread::Thread()` {#tensorflow_Thread_Thread} 10 | 11 | 12 | 13 | 14 | 15 | #### `tensorflow::Thread::~Thread()` {#tensorflow_Thread_Thread} 16 | 17 | Blocks until the thread of control stops running. 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/StructState.md: -------------------------------------------------------------------------------- 1 | # `struct tensorflow::Status::State` 2 | 3 | 4 | 5 | 6 | 7 | ###Member Details 8 | 9 | #### `tensorflow::error::Code tensorflow::Status::State::code` {#tensorflow_error_Code_tensorflow_Status_State_code} 10 | 11 | 12 | 13 | 14 | 15 | #### `string tensorflow::Status::State::msg` {#string_tensorflow_Status_State_msg} 16 | 17 | 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/StructTF_Buffer.md: -------------------------------------------------------------------------------- 1 | # `struct TF_Buffer` 2 | 3 | 4 | 5 | 6 | 7 | ###Member Details 8 | 9 | #### `const void* TF_Buffer::data` {#const_void_TF_Buffer_data} 10 | 11 | 12 | 13 | 14 | 15 | #### `size_t TF_Buffer::length` {#size_t_TF_Buffer_length} 16 | 17 | 18 | 19 | 20 | 21 | #### `void(* TF_Buffer::data_deallocator) (void *data, size_t length))(void *data, size_t length)` {#void_TF_Buffer_data_deallocator_void_data_size_t_length_} 22 | 23 | 24 | 25 | 26 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/StructTensorShapeDim.md: -------------------------------------------------------------------------------- 1 | # `struct tensorflow::TensorShapeDim` 2 | 3 | 4 | 5 | 6 | 7 | ###Member Details 8 | 9 | #### `int64 tensorflow::TensorShapeDim::size` {#int64_tensorflow_TensorShapeDim_size} 10 | 11 | 12 | 13 | 14 | 15 | #### `tensorflow::TensorShapeDim::TensorShapeDim(int64 s)` {#tensorflow_TensorShapeDim_TensorShapeDim} 16 | 17 | 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/cc/StructThreadOptions.md: -------------------------------------------------------------------------------- 1 | # `struct tensorflow::ThreadOptions` 2 | 3 | Options to configure a Thread . 4 | 5 | Note that the options are all hints, and the underlying implementation may choose to ignore it. 6 | 7 | ###Member Details 8 | 9 | #### `size_t tensorflow::ThreadOptions::stack_size` {#size_t_tensorflow_ThreadOptions_stack_size} 10 | 11 | Thread stack size to use (in bytes). 12 | 13 | 14 | 15 | #### `size_t tensorflow::ThreadOptions::guard_size` {#size_t_tensorflow_ThreadOptions_guard_size} 16 | 17 | Guard area size to use near thread stacks to use (in bytes) 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.SparseTensorValue.md: -------------------------------------------------------------------------------- 1 | SparseTensorValue(indices, values, shape) 2 | - - - 3 | 4 | #### `tf.SparseTensorValue.indices` {#SparseTensorValue.indices} 5 | 6 | Alias for field number 0 7 | 8 | 9 | - - - 10 | 11 | #### `tf.SparseTensorValue.shape` {#SparseTensorValue.shape} 12 | 13 | Alias for field number 2 14 | 15 | 16 | - - - 17 | 18 | #### `tf.SparseTensorValue.values` {#SparseTensorValue.values} 19 | 20 | Alias for field number 1 21 | 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.add_check_numerics_ops.md: -------------------------------------------------------------------------------- 1 | ### `tf.add_check_numerics_ops()` {#add_check_numerics_ops} 2 | 3 | Connect a `check_numerics` to every floating point tensor. 4 | 5 | `check_numerics` operations themselves are added for each `float` or `double` 6 | tensor in the graph. For all ops in the graph, the `check_numerics` op for 7 | all of its (`float` or `double`) inputs is guaranteed to run before the 8 | `check_numerics` op on any of its outputs. 9 | 10 | ##### Returns: 11 | 12 | A `group` op depending on all `check_numerics` ops added. 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.add_n.md: -------------------------------------------------------------------------------- 1 | ### `tf.add_n(inputs, name=None)` {#add_n} 2 | 3 | Add all input tensors element wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `inputs`: A list of at least 1 `Tensor` objects of the same type in: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`. 9 | Must all be the same size and shape. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `inputs`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.add_to_collection.md: -------------------------------------------------------------------------------- 1 | ### `tf.add_to_collection(name, value)` {#add_to_collection} 2 | 3 | Wrapper for `Graph.add_to_collection()` using the default graph. 4 | 5 | See [`Graph.add_to_collection()`](../../api_docs/python/framework.md#Graph.add_to_collection) 6 | for more details. 7 | 8 | ##### Args: 9 | 10 | 11 | * `name`: The key for the collection. For example, the `GraphKeys` class 12 | contains many standard names for collections. 13 | * `value`: The value to add to the collection. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.layers.l2_regularizer.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.l2_regularizer(scale)` {#l2_regularizer} 2 | 3 | Returns a function that can be used to apply L2 regularization to weights. 4 | 5 | Small values of L2 can help prevent overfitting the training data. 6 | 7 | ##### Args: 8 | 9 | 10 | * `scale`: A scalar multiplier `Tensor`. 0.0 disables the regularizer. 11 | 12 | ##### Returns: 13 | 14 | A function with signature `l2(weights, name=None)` that applies L2 15 | regularization. 16 | 17 | ##### Raises: 18 | 19 | 20 | * `ValueError`: If scale is outside of the range [0.0, 1.0] or if scale is not a 21 | float. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.learn.extract_pandas_matrix.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.extract_pandas_matrix(data)` {#extract_pandas_matrix} 2 | 3 | Extracts numpy matrix from pandas DataFrame. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.metrics.set_size.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.metrics.set_size(a, validate_indices=True)` {#set_size} 2 | 3 | Compute number of unique elements along last dimension of `a`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `a`: `SparseTensor`, with indices sorted in row-major order. 9 | * `validate_indices`: Whether to validate the order and range of sparse indices 10 | in `a`. 11 | 12 | ##### Returns: 13 | 14 | For `a` ranked `n`, this is a `Tensor` with rank `n-1`, and the same 1st 15 | `n-1` dimensions as `a`. Each value is the number of unique elements in 16 | the corresponding `[0...n-1]` dimension of `a`. 17 | 18 | ##### Raises: 19 | 20 | 21 | * `TypeError`: If `a` is an invalid types. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.contrib.util.ops_used_by_graph_def.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.util.ops_used_by_graph_def(graph_def)` {#ops_used_by_graph_def} 2 | 3 | Collect the list of ops used by a graph. 4 | 5 | Does not validate that the ops are all registered. 6 | 7 | ##### Args: 8 | 9 | 10 | * `graph_def`: A `GraphDef` proto, as from `graph.as_graph_def()`. 11 | 12 | ##### Returns: 13 | 14 | A list of strings, each naming an op used by the graph. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.delete_session_tensor.md: -------------------------------------------------------------------------------- 1 | ### `tf.delete_session_tensor(name=None)` {#delete_session_tensor} 2 | 3 | Delete the tensor by feeding a tensor handle. 4 | 5 | This is EXPERIMENTAL and subject to change. 6 | 7 | Delete the tensor of a given tensor handle. The tensor is produced 8 | in a previous run() and stored in the state of the session. 9 | 10 | ##### Args: 11 | 12 | 13 | * `name`: Optional name prefix for the return tensor. 14 | 15 | ##### Returns: 16 | 17 | A pair of graph elements. The first is a placeholder for feeding a 18 | tensor handle and the second is a deletion operation. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.device.md: -------------------------------------------------------------------------------- 1 | ### `tf.device(device_name_or_function)` {#device} 2 | 3 | Wrapper for `Graph.device()` using the default graph. 4 | 5 | See 6 | [`Graph.device()`](../../api_docs/python/framework.md#Graph.device) 7 | for more details. 8 | 9 | ##### Args: 10 | 11 | 12 | * `device_name_or_function`: The device name or function to use in 13 | the context. 14 | 15 | ##### Returns: 16 | 17 | A context manager that specifies the default device to use for newly 18 | created ops. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.errors.CancelledError.md: -------------------------------------------------------------------------------- 1 | Raised when an operation or step is cancelled. 2 | 3 | For example, a long-running operation (e.g. 4 | [`queue.enqueue()`](../../api_docs/python/io_ops.md#QueueBase.enqueue) may be 5 | cancelled by running another operation (e.g. 6 | [`queue.close(cancel_pending_enqueues=True)`](../../api_docs/python/io_ops.md#QueueBase.close), 7 | or by [closing the session](../../api_docs/python/client.md#Session.close). 8 | A step that is running such a long-running operation will fail by raising 9 | `CancelledError`. 10 | 11 | - - - 12 | 13 | #### `tf.errors.CancelledError.__init__(node_def, op, message)` {#CancelledError.__init__} 14 | 15 | Creates a `CancelledError`. 16 | 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.errors.DataLossError.md: -------------------------------------------------------------------------------- 1 | Raised when unrecoverable data loss or corruption is encountered. 2 | 3 | For example, this may be raised by running a 4 | [`tf.WholeFileReader.read()`](../../api_docs/python/io_ops.md#WholeFileReader) 5 | operation, if the file is truncated while it is being read. 6 | 7 | - - - 8 | 9 | #### `tf.errors.DataLossError.__init__(node_def, op, message)` {#DataLossError.__init__} 10 | 11 | Creates a `DataLossError`. 12 | 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.errors.DeadlineExceededError.md: -------------------------------------------------------------------------------- 1 | Raised when a deadline expires before an operation could complete. 2 | 3 | This exception is not currently used. 4 | 5 | - - - 6 | 7 | #### `tf.errors.DeadlineExceededError.__init__(node_def, op, message)` {#DeadlineExceededError.__init__} 8 | 9 | Creates a `DeadlineExceededError`. 10 | 11 | 12 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.fft.md: -------------------------------------------------------------------------------- 1 | ### `tf.fft(input, name=None)` {#fft} 2 | 3 | Compute the 1-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 vector. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. The 1D Fourier Transform of `input`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.fft2d.md: -------------------------------------------------------------------------------- 1 | ### `tf.fft2d(input, name=None)` {#fft2d} 2 | 3 | Compute the 2-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 matrix. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. The 2D Fourier Transform of `input`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.ifft3d.md: -------------------------------------------------------------------------------- 1 | ### `tf.ifft3d(input, name=None)` {#ifft3d} 2 | 3 | Compute the inverse 3-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 3-D tensor. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. 14 | The inverse 3D Fourier Transform of `input`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.image.grayscale_to_rgb.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.grayscale_to_rgb(images, name=None)` {#grayscale_to_rgb} 2 | 3 | Converts one or more images from Grayscale to RGB. 4 | 5 | Outputs a tensor of the same `DType` and rank as `images`. The size of the 6 | last dimension of the output is 3, containing the RGB value of the pixels. 7 | 8 | ##### Args: 9 | 10 | 11 | * `images`: The Grayscale tensor to convert. Last dimension must be size 1. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | The converted grayscale image(s). 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.image.rgb_to_grayscale.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.rgb_to_grayscale(images, name=None)` {#rgb_to_grayscale} 2 | 3 | Converts one or more images from RGB to Grayscale. 4 | 5 | Outputs a tensor of the same `DType` and rank as `images`. The size of the 6 | last dimension of the output is 1, containing the Grayscale value of the 7 | pixels. 8 | 9 | ##### Args: 10 | 11 | 12 | * `images`: The RGB tensor to convert. Last dimension must have size 3 and 13 | should contain RGB values. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | The converted grayscale image(s). 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.is_finite.md: -------------------------------------------------------------------------------- 1 | ### `tf.is_finite(x, name=None)` {#is_finite} 2 | 3 | Returns which elements of x are finite. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `bool`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.is_nan.md: -------------------------------------------------------------------------------- 1 | ### `tf.is_nan(x, name=None)` {#is_nan} 2 | 3 | Returns which elements of x are NaN. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `bool`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.is_numeric_tensor.md: -------------------------------------------------------------------------------- 1 | ### `tf.is_numeric_tensor(tensor)` {#is_numeric_tensor} 2 | 3 | 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.mod.md: -------------------------------------------------------------------------------- 1 | ### `tf.mod(x, y, name=None)` {#mod} 2 | 3 | Returns element-wise remainder of division. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `int32`, `int64`, `float32`, `float64`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.mul.md: -------------------------------------------------------------------------------- 1 | ### `tf.mul(x, y, name=None)` {#mul} 2 | 3 | Returns x * y element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.name_scope.md: -------------------------------------------------------------------------------- 1 | ### `tf.name_scope(name)` {#name_scope} 2 | 3 | Wrapper for `Graph.name_scope()` using the default graph. 4 | 5 | See 6 | [`Graph.name_scope()`](../../api_docs/python/framework.md#Graph.name_scope) 7 | for more details. 8 | 9 | ##### Args: 10 | 11 | 12 | * `name`: A name for the scope. 13 | 14 | ##### Returns: 15 | 16 | A context manager that installs `name` as a new name scope in the 17 | default graph. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.not_equal.md: -------------------------------------------------------------------------------- 1 | ### `tf.not_equal(x, y, name=None)` {#not_equal} 2 | 3 | Returns the truth value of (x != y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `quint8`, `qint8`, `qint32`, `string`, `bool`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.sqrt.md: -------------------------------------------------------------------------------- 1 | ### `tf.sqrt(x, name=None)` {#sqrt} 2 | 3 | Computes square root of x element-wise. 4 | 5 | I.e., \\(y = \sqrt{x} = x^{1/2}\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.train.limit_epochs.md: -------------------------------------------------------------------------------- 1 | ### `tf.train.limit_epochs(tensor, num_epochs=None, name=None)` {#limit_epochs} 2 | 3 | Returns tensor `num_epochs` times and then raises an `OutOfRange` error. 4 | 5 | ##### Args: 6 | 7 | 8 | * `tensor`: Any `Tensor`. 9 | * `num_epochs`: A positive integer (optional). If specified, limits the number 10 | of steps the output tensor may be evaluated. 11 | * `name`: A name for the operations (optional). 12 | 13 | ##### Returns: 14 | 15 | tensor or `OutOfRange`. 16 | 17 | ##### Raises: 18 | 19 | 20 | * `ValueError`: if `num_epochs` is invalid. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.zeros_initializer.md: -------------------------------------------------------------------------------- 1 | ### `tf.zeros_initializer(shape, dtype=tf.float32)` {#zeros_initializer} 2 | 3 | An adaptor for zeros() to match the Initializer spec. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.AggregationMethod.md: -------------------------------------------------------------------------------- 1 | A class listing aggregation methods used to combine gradients. 2 | 3 | Computing partial derivatives can require aggregating gradient 4 | contributions. This class lists the various methods that can 5 | be used to combine gradients in the graph: 6 | 7 | * `ADD_N`: All of the gradient terms are summed as part of one 8 | operation using the "AddN" op. It has the property that all 9 | gradients must be ready before any aggregation is performed. 10 | * `DEFAULT`: The system-chosen default aggregation method. 11 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.NoGradient.md: -------------------------------------------------------------------------------- 1 | ### `tf.NoGradient(op_type)` {#NoGradient} 2 | 3 | Specifies that ops of type `op_type` do not have a defined gradient. 4 | 5 | This function is only used when defining a new op type. It may be 6 | used for ops such as `tf.size()` that are not differentiable. For 7 | example: 8 | 9 | ```python 10 | tf.NoGradient("Size") 11 | ``` 12 | 13 | ##### Args: 14 | 15 | 16 | * `op_type`: The string type of an operation. This corresponds to the 17 | `OpDef.name` field for the proto that defines the operation. 18 | 19 | ##### Raises: 20 | 21 | 22 | * `TypeError`: If `op_type` is not a string. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.Variable.from_proto.md: -------------------------------------------------------------------------------- 1 | #### `tf.Variable.from_proto(variable_def)` {#Variable.from_proto} 2 | 3 | Returns a `Variable` object created from `variable_def`. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.all_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.all_variables()` {#all_variables} 2 | 3 | Returns all variables that must be saved/restored. 4 | 5 | The `Variable()` constructor automatically adds new variables to the graph 6 | collection `GraphKeys.VARIABLES`. This convenience function returns the 7 | contents of that collection. 8 | 9 | ##### Returns: 10 | 11 | A list of `Variable` objects. 12 | 13 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.batch_fft.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_fft(input, name=None)` {#batch_fft} 2 | 3 | Compute the 1-dimensional discrete Fourier Transform over the inner-most 4 | 5 | dimension of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 17 | dimension of `input` is replaced with its 1D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.constant_initializer.md: -------------------------------------------------------------------------------- 1 | ### `tf.constant_initializer(value=0.0, dtype=tf.float32)` {#constant_initializer} 2 | 3 | Returns an initializer that generates tensors with a single value. 4 | 5 | ##### Args: 6 | 7 | 8 | * `value`: A Python scalar. All elements of the initialized variable 9 | will be set to this value. 10 | * `dtype`: The data type. Only floating point types are supported. 11 | 12 | ##### Returns: 13 | 14 | An initializer that generates tensors with a single value. 15 | 16 | ##### Raises: 17 | 18 | 19 | * `ValueError`: if `dtype` is not a floating point type. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.contrib.layers.summarize_tensors.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.summarize_tensors(tensors, summarizer=summarize_tensor)` {#summarize_tensors} 2 | 3 | Summarize a set of tensors. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.contrib.learn.extract_pandas_data.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.extract_pandas_data(data)` {#extract_pandas_data} 2 | 3 | Extract data from pandas.DataFrame for predictors. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.erf.md: -------------------------------------------------------------------------------- 1 | ### `tf.erf(x, name=None)` {#erf} 2 | 3 | Computes the Gauss error function of `x` element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.errors.AlreadyExistsError.md: -------------------------------------------------------------------------------- 1 | Raised when an entity that we attempted to create already exists. 2 | 3 | For example, running an operation that saves a file 4 | (e.g. [`tf.train.Saver.save()`](../../api_docs/python/train.md#Saver.save)) 5 | could potentially raise this exception if an explicit filename for an 6 | existing file was passed. 7 | 8 | - - - 9 | 10 | #### `tf.errors.AlreadyExistsError.__init__(node_def, op, message)` {#AlreadyExistsError.__init__} 11 | 12 | Creates an `AlreadyExistsError`. 13 | 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.get_default_session.md: -------------------------------------------------------------------------------- 1 | ### `tf.get_default_session()` {#get_default_session} 2 | 3 | Returns the default session for the current thread. 4 | 5 | The returned `Session` will be the innermost session on which a 6 | `Session` or `Session.as_default()` context has been entered. 7 | 8 | NOTE: The default session is a property of the current thread. If you 9 | create a new thread, and wish to use the default session in that 10 | thread, you must explicitly add a `with sess.as_default():` in that 11 | thread's function. 12 | 13 | ##### Returns: 14 | 15 | The default `Session` being used in the current thread. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.greater_equal.md: -------------------------------------------------------------------------------- 1 | ### `tf.greater_equal(x, y, name=None)` {#greater_equal} 2 | 3 | Returns the truth value of (x >= y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.matching_files.md: -------------------------------------------------------------------------------- 1 | ### `tf.matching_files(pattern, name=None)` {#matching_files} 2 | 3 | Returns the set of files matching a pattern. 4 | 5 | Note that this routine only supports wildcard characters in the 6 | basename portion of the pattern, not in the directory portion. 7 | 8 | ##### Args: 9 | 10 | 11 | * `pattern`: A `Tensor` of type `string`. A (scalar) shell wildcard pattern. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A `Tensor` of type `string`. A vector of matching filenames. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.merge_all_summaries.md: -------------------------------------------------------------------------------- 1 | ### `tf.merge_all_summaries(key='summaries')` {#merge_all_summaries} 2 | 3 | Merges all summaries collected in the default graph. 4 | 5 | ##### Args: 6 | 7 | 8 | * `key`: `GraphKey` used to collect the summaries. Defaults to 9 | `GraphKeys.SUMMARIES`. 10 | 11 | ##### Returns: 12 | 13 | If no summaries were collected, returns None. Otherwise returns a scalar 14 | `Tensor` of type `string` containing the serialized `Summary` protocol 15 | buffer resulting from the merging. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.read_file.md: -------------------------------------------------------------------------------- 1 | ### `tf.read_file(filename, name=None)` {#read_file} 2 | 3 | Reads and outputs the entire contents of the input filename. 4 | 5 | ##### Args: 6 | 7 | 8 | * `filename`: A `Tensor` of type `string`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `string`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.test.get_temp_dir.md: -------------------------------------------------------------------------------- 1 | ### `tf.test.get_temp_dir()` {#get_temp_dir} 2 | 3 | Returns a temporary directory for use during tests. 4 | 5 | There is no need to delete the directory after the test. 6 | 7 | ##### Returns: 8 | 9 | The temporary directory. 10 | 11 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.train.GradientDescentOptimizer.md: -------------------------------------------------------------------------------- 1 | Optimizer that implements the gradient descent algorithm. 2 | 3 | - - - 4 | 5 | #### `tf.train.GradientDescentOptimizer.__init__(learning_rate, use_locking=False, name='GradientDescent')` {#GradientDescentOptimizer.__init__} 6 | 7 | Construct a new gradient descent optimizer. 8 | 9 | ##### Args: 10 | 11 | 12 | * `learning_rate`: A Tensor or a floating point value. The learning 13 | rate to use. 14 | * `use_locking`: If True use locks for update operations. 15 | * `name`: Optional name prefix for the operations created when applying 16 | gradients. Defaults to "GradientDescent". 17 | 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.train.Server.create_local_server.md: -------------------------------------------------------------------------------- 1 | #### `tf.train.Server.create_local_server(start=True)` {#Server.create_local_server} 2 | 3 | Creates a new single-process cluster running on the local host. 4 | 5 | This method is a convenience wrapper for creating a 6 | `tf.train.Server` with a `tf.train.ServerDef` that specifies a 7 | single-process cluster containing a single task in a job called 8 | `"local"`. 9 | 10 | ##### Args: 11 | 12 | 13 | * `start`: (Optional.) Boolean, indicating whether to start the server after 14 | creating it. Defaults to `True`. 15 | 16 | ##### Returns: 17 | 18 | A local `tf.train.Server`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.zeros.md: -------------------------------------------------------------------------------- 1 | ### `tf.zeros(shape, dtype=tf.float32, name=None)` {#zeros} 2 | 3 | Creates a tensor with all elements set to zero. 4 | 5 | This operation returns a tensor of type `dtype` with shape `shape` and 6 | all elements set to zero. 7 | 8 | For example: 9 | 10 | ```python 11 | tf.zeros([3, 4], int32) ==> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]] 12 | ``` 13 | 14 | ##### Args: 15 | 16 | 17 | * `shape`: Either a list of integers, or a 1-D `Tensor` of type `int32`. 18 | * `dtype`: The type of an element in the resulting `Tensor`. 19 | * `name`: A name for the operation (optional). 20 | 21 | ##### Returns: 22 | 23 | A `Tensor` with all elements set to zero. 24 | 25 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.batch_matrix_determinant.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_matrix_determinant(input, name=None)` {#batch_matrix_determinant} 2 | 3 | Calculates the determinants for a batch of square matrices. 4 | 5 | The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions 6 | form square matrices. The output is a 1-D tensor containing the determinants 7 | for all input submatrices `[..., :, :]`. 8 | 9 | ##### Args: 10 | 11 | 12 | * `input`: A `Tensor`. Must be one of the following types: `float32`, `float64`. 13 | Shape is `[..., M, M]`. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | A `Tensor`. Has the same type as `input`. Shape is `[...]`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.copy_graph.get_copied_op.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.copy_graph.get_copied_op(org_instance, graph, scope='')` {#get_copied_op} 2 | 3 | Given an `Operation` instance from some `Graph`, returns 4 | its namesake from `graph`, under the specified scope 5 | (default `""`). 6 | 7 | If a copy of `org_instance` is present in `graph` under the given 8 | `scope`, it will be returned. 9 | 10 | Args: 11 | org_instance: An `Operation` from some `Graph`. 12 | graph: The `Graph` to be searched for a copr of `org_instance`. 13 | scope: The scope `org_instance` is present in. 14 | 15 | ##### Returns: 16 | 17 | The `Operation` copy from `graph`. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.contrib.learn.ModeKeys.md: -------------------------------------------------------------------------------- 1 | Standard names for model modes. 2 | 3 | The following standard keys are defined: 4 | 5 | * `TRAIN`: training mode. 6 | * `EVAL`: evaluation mode. 7 | * `INFER`: inference mode. 8 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.digamma.md: -------------------------------------------------------------------------------- 1 | ### `tf.digamma(x, name=None)` {#digamma} 2 | 3 | Computes Psi, the derivative of Lgamma (the log of the absolute value of 4 | 5 | `Gamma(x)`), element-wise. 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.errors.ResourceExhaustedError.md: -------------------------------------------------------------------------------- 1 | Some resource has been exhausted. 2 | 3 | For example, this error might be raised if a per-user quota is 4 | exhausted, or perhaps the entire file system is out of space. 5 | 6 | - - - 7 | 8 | #### `tf.errors.ResourceExhaustedError.__init__(node_def, op, message)` {#ResourceExhaustedError.__init__} 9 | 10 | Creates a `ResourceExhaustedError`. 11 | 12 | 13 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.get_variable_scope.md: -------------------------------------------------------------------------------- 1 | ### `tf.get_variable_scope()` {#get_variable_scope} 2 | 3 | Returns the current variable scope. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.identity.md: -------------------------------------------------------------------------------- 1 | ### `tf.identity(input, name=None)` {#identity} 2 | 3 | Return a tensor with the same shape and contents as the input tensor or value. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `input`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.initialize_all_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.initialize_all_variables()` {#initialize_all_variables} 2 | 3 | Returns an Op that initializes all variables. 4 | 5 | This is just a shortcut for `initialize_variables(all_variables())` 6 | 7 | ##### Returns: 8 | 9 | An Op that initializes all variables in the graph. 10 | 11 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.initialize_local_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.initialize_local_variables()` {#initialize_local_variables} 2 | 3 | Returns an Op that initializes all local variables. 4 | 5 | This is just a shortcut for `initialize_variables(local_variables())` 6 | 7 | ##### Returns: 8 | 9 | An Op that initializes all local variables in the graph. 10 | 11 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.is_variable_initialized.md: -------------------------------------------------------------------------------- 1 | ### `tf.is_variable_initialized(variable)` {#is_variable_initialized} 2 | 3 | Tests if a variable has been initialized. 4 | 5 | ##### Args: 6 | 7 | 8 | * `variable`: A `Variable`. 9 | 10 | ##### Returns: 11 | 12 | Returns a scalar boolean Tensor, `True` if the variable has been 13 | initialized, `False` otherwise. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.minimum.md: -------------------------------------------------------------------------------- 1 | ### `tf.minimum(x, y, name=None)` {#minimum} 2 | 3 | Returns the min of x and y (i.e. x < y ? x : y) element-wise, broadcasts. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.neg.md: -------------------------------------------------------------------------------- 1 | ### `tf.neg(x, name=None)` {#neg} 2 | 3 | Computes numerical negative value element-wise. 4 | 5 | I.e., \\(y = -x\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.nn.relu.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.relu(features, name=None)` {#relu} 2 | 3 | Computes rectified linear: `max(features, 0)`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `features`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `features`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.shape_n.md: -------------------------------------------------------------------------------- 1 | ### `tf.shape_n(input, name=None)` {#shape_n} 2 | 3 | Returns shape of tensors. 4 | 5 | This operation returns N 1-D integer tensors representing shape of `input[i]s`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A list of at least 1 `Tensor` objects of the same type. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A list with the same number of `Tensor` objects as `input` of `Tensor` objects of type `int32`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.sin.md: -------------------------------------------------------------------------------- 1 | ### `tf.sin(x, name=None)` {#sin} 2 | 3 | Computes sin of x element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.assert_equal_graph_def.md: -------------------------------------------------------------------------------- 1 | ### `tf.test.assert_equal_graph_def(actual, expected)` {#assert_equal_graph_def} 2 | 3 | Asserts that two `GraphDef`s are (mostly) the same. 4 | 5 | Compares two `GraphDef` protos for equality, ignoring versions and ordering of 6 | nodes, attrs, and control inputs. Node names are used to match up nodes 7 | between the graphs, so the naming of nodes must be consistent. 8 | 9 | ##### Args: 10 | 11 | 12 | * `actual`: The `GraphDef` we have. 13 | * `expected`: The `GraphDef` we expected. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `AssertionError`: If the `GraphDef`s do not match. 19 | * `TypeError`: If either argument is not a `GraphDef`. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.test.is_built_with_cuda.md: -------------------------------------------------------------------------------- 1 | ### `tf.test.is_built_with_cuda()` {#is_built_with_cuda} 2 | 3 | Returns whether TensorFlow was built with CUDA (GPU) support. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.to_int32.md: -------------------------------------------------------------------------------- 1 | ### `tf.to_int32(x, name='ToInt32')` {#to_int32} 2 | 3 | Casts a tensor to type `int32`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` or `SparseTensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` or `SparseTensor` with same shape as `x` with type `int32`. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `TypeError`: If `x` cannot be cast to the `int32`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.train.Saver.from_proto.md: -------------------------------------------------------------------------------- 1 | #### `tf.train.Saver.from_proto(saver_def)` {#Saver.from_proto} 2 | 3 | Returns a `Saver` object created from `saver_def`. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.train.latest_checkpoint.md: -------------------------------------------------------------------------------- 1 | ### `tf.train.latest_checkpoint(checkpoint_dir, latest_filename=None)` {#latest_checkpoint} 2 | 3 | Finds the filename of latest saved checkpoint file. 4 | 5 | ##### Args: 6 | 7 | 8 | * `checkpoint_dir`: Directory where the variables were saved. 9 | * `latest_filename`: Optional name for the protocol buffer file that 10 | contains the list of most recent checkpoint filenames. 11 | See the corresponding argument to `Saver.save()`. 12 | 13 | ##### Returns: 14 | 15 | The full path to the latest checkpoint or `None` if no checkpoint was found. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.assert_type.md: -------------------------------------------------------------------------------- 1 | ### `tf.assert_type(tensor, tf_type)` {#assert_type} 2 | 3 | Asserts that the given `Tensor` is of the specified type. 4 | 5 | ##### Args: 6 | 7 | 8 | * `tensor`: A tensorflow `Tensor`. 9 | * `tf_type`: A tensorflow type (dtypes.float32, tf.int64, dtypes.bool, etc). 10 | 11 | ##### Raises: 12 | 13 | 14 | * `ValueError`: If the tensors data type doesn't match tf_type. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.batch_ifft3d.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_ifft3d(input, name=None)` {#batch_ifft3d} 2 | 3 | Compute the inverse 3-dimensional discrete Fourier Transform over the inner-most 4 | 5 | 3 dimensions of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 3 17 | dimensions of `input` are replaced with their inverse 3D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.ceil.md: -------------------------------------------------------------------------------- 1 | ### `tf.ceil(x, name=None)` {#ceil} 2 | 3 | Returns element-wise smallest integer in not less than x. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.check_numerics.md: -------------------------------------------------------------------------------- 1 | ### `tf.check_numerics(tensor, message, name=None)` {#check_numerics} 2 | 3 | Checks a tensor for NaN and Inf values. 4 | 5 | When run, reports an `InvalidArgument` error if `tensor` has any values 6 | that are not a number (NaN) or infinity (Inf). Otherwise, passes `tensor` as-is. 7 | 8 | ##### Args: 9 | 10 | 11 | * `tensor`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 12 | * `message`: A `string`. Prefix of the error message. 13 | * `name`: A name for the operation (optional). 14 | 15 | ##### Returns: 16 | 17 | A `Tensor`. Has the same type as `tensor`. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.layers.summarize_activation.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.summarize_activation(op)` {#summarize_activation} 2 | 3 | Summarize an activation. 4 | 5 | This applies the given activation and adds useful summaries specific to the 6 | activation. 7 | 8 | ##### Args: 9 | 10 | 11 | * `op`: The tensor to summarize (assumed to be a layer activation). 12 | 13 | ##### Returns: 14 | 15 | The summary op created to summarize `op`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.contrib.learn.extract_dask_data.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.extract_dask_data(data)` {#extract_dask_data} 2 | 3 | Extract data from dask.Series or dask.DataFrame for predictors. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.control_dependencies.md: -------------------------------------------------------------------------------- 1 | ### `tf.control_dependencies(control_inputs)` {#control_dependencies} 2 | 3 | Wrapper for `Graph.control_dependencies()` using the default graph. 4 | 5 | See [`Graph.control_dependencies()`](../../api_docs/python/framework.md#Graph.control_dependencies) 6 | for more details. 7 | 8 | ##### Args: 9 | 10 | 11 | * `control_inputs`: A list of `Operation` or `Tensor` objects which 12 | must be executed or computed before running the operations 13 | defined in the context. Can also be `None` to clear the control 14 | dependencies. 15 | 16 | ##### Returns: 17 | 18 | A context manager that specifies control dependencies for all 19 | operations constructed within the context. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.errors.OutOfRangeError.md: -------------------------------------------------------------------------------- 1 | Raised when an operation iterates past the valid input range. 2 | 3 | This exception is raised in "end-of-file" conditions, such as when a 4 | [`queue.dequeue()`](../../api_docs/python/io_ops.md#QueueBase.dequeue) 5 | operation is blocked on an empty queue, and a 6 | [`queue.close()`](../../api_docs/python/io_ops.md#QueueBase.close) 7 | operation executes. 8 | 9 | - - - 10 | 11 | #### `tf.errors.OutOfRangeError.__init__(node_def, op, message)` {#OutOfRangeError.__init__} 12 | 13 | Creates an `OutOfRangeError`. 14 | 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.errors.UnauthenticatedError.md: -------------------------------------------------------------------------------- 1 | The request does not have valid authentication credentials. 2 | 3 | This exception is not currently used. 4 | 5 | - - - 6 | 7 | #### `tf.errors.UnauthenticatedError.__init__(node_def, op, message)` {#UnauthenticatedError.__init__} 8 | 9 | Creates an `UnauthenticatedError`. 10 | 11 | 12 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.exp.md: -------------------------------------------------------------------------------- 1 | ### `tf.exp(x, name=None)` {#exp} 2 | 3 | Computes exponential of x element-wise. \\(y = e^x\\). 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.group.md: -------------------------------------------------------------------------------- 1 | ### `tf.group(*inputs, **kwargs)` {#group} 2 | 3 | Create an op that groups multiple operations. 4 | 5 | When this op finishes, all ops in `input` have finished. This op has no 6 | output. 7 | 8 | See also `tuple` and `with_dependencies`. 9 | 10 | ##### Args: 11 | 12 | 13 | * `*inputs`: Zero or more tensors to group. 14 | * `**kwargs`: Optional parameters to pass when constructing the NodeDef. 15 | * `name`: A name for this operation (optional). 16 | 17 | ##### Returns: 18 | 19 | An Operation that executes all its inputs. 20 | 21 | ##### Raises: 22 | 23 | 24 | * `ValueError`: If an unknown keyword argument is provided. 25 | 26 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.ifft2d.md: -------------------------------------------------------------------------------- 1 | ### `tf.ifft2d(input, name=None)` {#ifft2d} 2 | 3 | Compute the inverse 2-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 matrix. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. 14 | The inverse 2D Fourier Transform of `input`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.local_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.local_variables()` {#local_variables} 2 | 3 | Returns all variables created with collection=[LOCAL_VARIABLES]. 4 | 5 | ##### Returns: 6 | 7 | A list of local Variable objects. 8 | 9 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.logical_xor.md: -------------------------------------------------------------------------------- 1 | ### `tf.logical_xor(x, y, name='LogicalXor')` {#logical_xor} 2 | 3 | x ^ y = (x | y) & ~(x & y). 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.nn.log_softmax.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.log_softmax(logits, name=None)` {#log_softmax} 2 | 3 | Computes log softmax activations. 4 | 5 | For each batch `i` and class `j` we have 6 | 7 | logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i]))) 8 | 9 | ##### Args: 10 | 11 | 12 | * `logits`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 13 | 2-D with shape `[batch_size, num_classes]`. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | A `Tensor`. Has the same type as `logits`. Same shape as `logits`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.nn.softsign.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.softsign(features, name=None)` {#softsign} 2 | 3 | Computes softsign: `features / (abs(features) + 1)`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `features`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `features`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.shape.md: -------------------------------------------------------------------------------- 1 | ### `tf.shape(input, name=None)` {#shape} 2 | 3 | Returns the shape of a tensor. 4 | 5 | This operation returns a 1-D integer tensor representing the shape of `input`. 6 | 7 | For example: 8 | 9 | ```prettyprint 10 | # 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] 11 | shape(t) ==> [2, 2, 3] 12 | ``` 13 | 14 | ##### Args: 15 | 16 | 17 | * `input`: A `Tensor`. 18 | * `name`: A name for the operation (optional). 19 | 20 | ##### Returns: 21 | 22 | A `Tensor` of type `int32`. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.to_double.md: -------------------------------------------------------------------------------- 1 | ### `tf.to_double(x, name='ToDouble')` {#to_double} 2 | 3 | Casts a tensor to type `float64`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` or `SparseTensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` or `SparseTensor` with same shape as `x` with type `float64`. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `TypeError`: If `x` cannot be cast to the `float64`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard3/tf.trace.md: -------------------------------------------------------------------------------- 1 | ### `tf.trace(x, name=None)` {#trace} 2 | 3 | Compute the trace of a tensor `x`. 4 | 5 | `trace(x)` returns the sum of along the diagonal. 6 | 7 | For example: 8 | 9 | ```python 10 | # 'x' is [[1, 1], 11 | # [1, 1]] 12 | tf.trace(x) ==> 2 13 | 14 | # 'x' is [[1,2,3], 15 | # [4,5,6], 16 | # [7,8,9]] 17 | tf.trace(x) ==> 15 18 | ``` 19 | 20 | ##### Args: 21 | 22 | 23 | * `x`: 2-D tensor. 24 | * `name`: A name for the operation (optional). 25 | 26 | ##### Returns: 27 | 28 | The trace of input tensor. 29 | 30 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.argmin.md: -------------------------------------------------------------------------------- 1 | ### `tf.argmin(input, dimension, name=None)` {#argmin} 2 | 3 | Returns the index with the smallest value across dimensions of a tensor. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`. 9 | * `dimension`: A `Tensor` of type `int32`. 10 | int32, 0 <= dimension < rank(input). Describes which dimension 11 | of the input Tensor to reduce across. For vectors, use dimension = 0. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A `Tensor` of type `int64`. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.batch_ifft.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_ifft(input, name=None)` {#batch_ifft} 2 | 3 | Compute the inverse 1-dimensional discrete Fourier Transform over the inner-most 4 | 5 | dimension of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 17 | dimension of `input` is replaced with its inverse 1D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.errors.FailedPreconditionError.md: -------------------------------------------------------------------------------- 1 | Operation was rejected because the system is not in a state to execute it. 2 | 3 | This exception is most commonly raised when running an operation 4 | that reads a [`tf.Variable`](../../api_docs/python/state_ops.md#Variable) 5 | before it has been initialized. 6 | 7 | - - - 8 | 9 | #### `tf.errors.FailedPreconditionError.__init__(node_def, op, message)` {#FailedPreconditionError.__init__} 10 | 11 | Creates a `FailedPreconditionError`. 12 | 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.floor.md: -------------------------------------------------------------------------------- 1 | ### `tf.floor(x, name=None)` {#floor} 2 | 3 | Returns element-wise largest integer not greater than x. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.greater.md: -------------------------------------------------------------------------------- 1 | ### `tf.greater(x, y, name=None)` {#greater} 2 | 3 | Returns the truth value of (x > y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.image.hsv_to_rgb.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.hsv_to_rgb(images, name=None)` {#hsv_to_rgb} 2 | 3 | Convert one or more images from HSV to RGB. 4 | 5 | Outputs a tensor of the same shape as the `images` tensor, containing the RGB 6 | value of the pixels. The output is only well defined if the value in `images` 7 | are in `[0,1]`. 8 | 9 | See `rgb_to_hsv` for a description of the HSV encoding. 10 | 11 | ##### Args: 12 | 13 | 14 | * `images`: A `Tensor` of type `float32`. 15 | 1-D or higher rank. HSV data to convert. Last dimension must be size 3. 16 | * `name`: A name for the operation (optional). 17 | 18 | ##### Returns: 19 | 20 | A `Tensor` of type `float32`. `images` converted to RGB. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.log.md: -------------------------------------------------------------------------------- 1 | ### `tf.log(x, name=None)` {#log} 2 | 3 | Computes natural logarithm of x element-wise. 4 | 5 | I.e., \\(y = \log_e x\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.nn.l2_loss.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.l2_loss(t, name=None)` {#l2_loss} 2 | 3 | L2 Loss. 4 | 5 | Computes half the L2 norm of a tensor without the `sqrt`: 6 | 7 | output = sum(t ** 2) / 2 8 | 9 | ##### Args: 10 | 11 | 12 | * `t`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`. 13 | Typically 2-D, but may have any dimensions. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | A `Tensor`. Has the same type as `t`. 0-D. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.nn.softplus.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.softplus(features, name=None)` {#softplus} 2 | 3 | Computes softplus: `log(exp(features) + 1)`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `features`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `features`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.placeholder_with_default.md: -------------------------------------------------------------------------------- 1 | ### `tf.placeholder_with_default(input, shape, name=None)` {#placeholder_with_default} 2 | 3 | A placeholder op that passes though `input` when its output is not fed. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor`. The default value to produce when `output` is not fed. 9 | * `shape`: A `tf.TensorShape` or list of `ints`. 10 | The (possibly partial) shape of the tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `input`. 16 | A placeholder tensor that defaults to `input` if it is not fed. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.sub.md: -------------------------------------------------------------------------------- 1 | ### `tf.sub(x, y, name=None)` {#sub} 2 | 3 | Returns x - y element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard4/tf.train.match_filenames_once.md: -------------------------------------------------------------------------------- 1 | ### `tf.train.match_filenames_once(pattern, name=None)` {#match_filenames_once} 2 | 3 | Save the list of files matching pattern, so it is only computed once. 4 | 5 | ##### Args: 6 | 7 | 8 | * `pattern`: A file pattern (glob). 9 | * `name`: A name for the operations (optional). 10 | 11 | ##### Returns: 12 | 13 | A variable that is initialized to the list of files matching pattern. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.add.md: -------------------------------------------------------------------------------- 1 | ### `tf.add(x, y, name=None)` {#add} 2 | 3 | Returns x + y element-wise. 4 | 5 | *NOTE*: Add supports broadcasting. AddN does not. 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`, `string`. 11 | * `y`: A `Tensor`. Must have the same type as `x`. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A `Tensor`. Has the same type as `x`. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.bytes.md: -------------------------------------------------------------------------------- 1 | str(object='') -> string 2 | 3 | Return a nice string representation of the object. 4 | If the argument is a string, the return value is the same object. 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.contrib.layers.sum_regularizer.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.sum_regularizer(regularizer_list)` {#sum_regularizer} 2 | 3 | Returns a function that applies the sum of multiple regularizers. 4 | 5 | ##### Args: 6 | 7 | 8 | * `regularizer_list`: A list of regularizers to apply. 9 | 10 | ##### Returns: 11 | 12 | A function with signature `sum_reg(weights, name=None)` that applies the 13 | sum of all the input regularizers. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.contrib.layers.summarize_collection.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.summarize_collection(collection, name_filter=None, summarizer=summarize_tensor)` {#summarize_collection} 2 | 3 | Summarize a graph collection of tensors, possibly filtered by name. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.contrib.learn.run_n.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.run_n(output_dict, feed_dict=None, restore_checkpoint_path=None, n=1)` {#run_n} 2 | 3 | Run `output_dict` tensors `n` times, with the same `feed_dict` each run. 4 | 5 | ##### Args: 6 | 7 | 8 | * `output_dict`: A `dict` mapping string names to tensors to run. Must all be 9 | from the same graph. 10 | * `feed_dict`: `dict` of input values to feed each run. 11 | * `restore_checkpoint_path`: A string containing the path to a checkpoint to 12 | restore. 13 | * `n`: Number of times to repeat. 14 | 15 | ##### Returns: 16 | 17 | A list of `n` `dict` objects, each containing values read from `output_dict` 18 | tensors. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.cos.md: -------------------------------------------------------------------------------- 1 | ### `tf.cos(x, name=None)` {#cos} 2 | 3 | Computes cos of x element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.div.md: -------------------------------------------------------------------------------- 1 | ### `tf.div(x, y, name=None)` {#div} 2 | 3 | Returns x / y element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.errors.PermissionDeniedError.md: -------------------------------------------------------------------------------- 1 | Raised when the caller does not have permission to run an operation. 2 | 3 | For example, running the 4 | [`tf.WholeFileReader.read()`](../../api_docs/python/io_ops.md#WholeFileReader) 5 | operation could raise `PermissionDeniedError` if it receives the name of a 6 | file for which the user does not have the read file permission. 7 | 8 | - - - 9 | 10 | #### `tf.errors.PermissionDeniedError.__init__(node_def, op, message)` {#PermissionDeniedError.__init__} 11 | 12 | Creates a `PermissionDeniedError`. 13 | 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.errors.UnavailableError.md: -------------------------------------------------------------------------------- 1 | Raised when the runtime is currently unavailable. 2 | 3 | This exception is not currently used. 4 | 5 | - - - 6 | 7 | #### `tf.errors.UnavailableError.__init__(node_def, op, message)` {#UnavailableError.__init__} 8 | 9 | Creates an `UnavailableError`. 10 | 11 | 12 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.image.flip_left_right.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.flip_left_right(image)` {#flip_left_right} 2 | 3 | Flip an image horizontally (left to right). 4 | 5 | Outputs the contents of `image` flipped along the second dimension, which is 6 | `width`. 7 | 8 | See also `reverse()`. 9 | 10 | ##### Args: 11 | 12 | 13 | * `image`: A 3-D tensor of shape `[height, width, channels].` 14 | 15 | ##### Returns: 16 | 17 | A 3-D tensor of the same type and shape as `image`. 18 | 19 | ##### Raises: 20 | 21 | 22 | * `ValueError`: if the shape of `image` not supported. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.image.flip_up_down.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.flip_up_down(image)` {#flip_up_down} 2 | 3 | Flip an image horizontally (upside down). 4 | 5 | Outputs the contents of `image` flipped along the first dimension, which is 6 | `height`. 7 | 8 | See also `reverse()`. 9 | 10 | ##### Args: 11 | 12 | 13 | * `image`: A 3-D tensor of shape `[height, width, channels].` 14 | 15 | ##### Returns: 16 | 17 | A 3-D tensor of the same type and shape as `image`. 18 | 19 | ##### Raises: 20 | 21 | 22 | * `ValueError`: if the shape of `image` not supported. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.inv.md: -------------------------------------------------------------------------------- 1 | ### `tf.inv(x, name=None)` {#inv} 2 | 3 | Computes the reciprocal of x element-wise. 4 | 5 | I.e., \\(y = 1 / x\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.load_file_system_library.md: -------------------------------------------------------------------------------- 1 | ### `tf.load_file_system_library(library_filename)` {#load_file_system_library} 2 | 3 | Loads a TensorFlow plugin, containing file system implementation. 4 | 5 | Pass `library_filename` to a platform-specific mechanism for dynamically 6 | loading a library. The rules for determining the exact location of the 7 | library are platform-specific and are not documented here. 8 | 9 | ##### Args: 10 | 11 | 12 | * `library_filename`: Path to the plugin. 13 | Relative or absolute filesystem path to a dynamic library file. 14 | 15 | ##### Returns: 16 | 17 | None. 18 | 19 | ##### Raises: 20 | 21 | 22 | * `RuntimeError`: when unable to load the library. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.logical_and.md: -------------------------------------------------------------------------------- 1 | ### `tf.logical_and(x, y, name=None)` {#logical_and} 2 | 3 | Returns the truth value of x AND y element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` of type `bool`. 9 | * `y`: A `Tensor` of type `bool`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.logical_not.md: -------------------------------------------------------------------------------- 1 | ### `tf.logical_not(x, name=None)` {#logical_not} 2 | 3 | Returns the truth value of NOT x element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` of type `bool`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `bool`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.no_op.md: -------------------------------------------------------------------------------- 1 | ### `tf.no_op(name=None)` {#no_op} 2 | 3 | Does nothing. Only useful as a placeholder for control edges. 4 | 5 | ##### Args: 6 | 7 | 8 | * `name`: A name for the operation (optional). 9 | 10 | ##### Returns: 11 | 12 | The created Operation. 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.sign.md: -------------------------------------------------------------------------------- 1 | ### `tf.sign(x, name=None)` {#sign} 2 | 3 | Returns an element-wise indication of the sign of a number. 4 | 5 | `y = sign(x) = -1` if `x < 0`; 0 if `x == 0`; 1 if `x > 0`. 6 | 7 | For complex numbers, `y = sign(x) = x / |x|` if `x != 0`, otherwise `y = 0`. 8 | 9 | ##### Args: 10 | 11 | 12 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 13 | * `name`: A name for the operation (optional). 14 | 15 | ##### Returns: 16 | 17 | A `Tensor`. Has the same type as `x`. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.test.main.md: -------------------------------------------------------------------------------- 1 | ### `tf.test.main()` {#main} 2 | 3 | Runs all unit tests. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.to_int64.md: -------------------------------------------------------------------------------- 1 | ### `tf.to_int64(x, name='ToInt64')` {#to_int64} 2 | 3 | Casts a tensor to type `int64`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` or `SparseTensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` or `SparseTensor` with same shape as `x` with type `int64`. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `TypeError`: If `x` cannot be cast to the `int64`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.verify_tensor_all_finite.md: -------------------------------------------------------------------------------- 1 | ### `tf.verify_tensor_all_finite(t, msg, name=None)` {#verify_tensor_all_finite} 2 | 3 | Assert that the tensor does not contain any NaN's or Inf's. 4 | 5 | ##### Args: 6 | 7 | 8 | * `t`: Tensor to check. 9 | * `msg`: Message to log on failure. 10 | * `name`: A name for this operation (optional). 11 | 12 | ##### Returns: 13 | 14 | Same tensor as `t`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.abs.md: -------------------------------------------------------------------------------- 1 | ### `tf.abs(x, name=None)` {#abs} 2 | 3 | Computes the absolute value of a tensor. 4 | 5 | Given a tensor of real numbers `x`, this operation returns a tensor 6 | containing the absolute value of each element in `x`. For example, if x is 7 | an input element and y is an output element, this operation computes 8 | \\(y = |x|\\). 9 | 10 | See [`tf.complex_abs()`](#tf_complex_abs) to compute the absolute value of a complex 11 | number. 12 | 13 | ##### Args: 14 | 15 | 16 | * `x`: A `Tensor` of type `float`, `double`, `int32`, or `int64`. 17 | * `name`: A name for the operation (optional). 18 | 19 | ##### Returns: 20 | 21 | A `Tensor` the same size and type as `x` with absolute values. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.batch_fft3d.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_fft3d(input, name=None)` {#batch_fft3d} 2 | 3 | Compute the 3-dimensional discrete Fourier Transform over the inner-most 3 4 | 5 | dimensions of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 3 17 | dimensions of `input` are replaced with their 3D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.batch_ifft2d.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_ifft2d(input, name=None)` {#batch_ifft2d} 2 | 3 | Compute the inverse 2-dimensional discrete Fourier Transform over the inner-most 4 | 5 | 2 dimensions of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 2 17 | dimensions of `input` are replaced with their inverse 2D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.copy_graph.copy_variable_to_graph.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.copy_graph.copy_variable_to_graph(org_instance, to_graph, scope='')` {#copy_variable_to_graph} 2 | 3 | Given a `Variable` instance from one `Graph`, initializes and returns 4 | a copy of it from another `Graph`, under the specified scope 5 | (default `""`). 6 | 7 | Args: 8 | org_instance: A `Variable` from some `Graph`. 9 | to_graph: The `Graph` to copy the `Variable` to. 10 | scope: A scope for the new `Variable` (default `""`). 11 | 12 | ##### Returns: 13 | 14 | The copied `Variable` from `to_graph`. 15 | 16 | ##### Raises: 17 | 18 | 19 | * `TypeError`: If `org_instance` is not a `Variable`. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.layers.summarize_activations.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.summarize_activations(name_filter=None, summarizer=summarize_activation)` {#summarize_activations} 2 | 3 | Summarize activations, using `summarize_activation` to summarize. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.contrib.learn.extract_dask_labels.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.extract_dask_labels(labels)` {#extract_dask_labels} 2 | 3 | Extract data from dask.Series for labels. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.erfc.md: -------------------------------------------------------------------------------- 1 | ### `tf.erfc(x, name=None)` {#erfc} 2 | 3 | Computes the complementary error function of `x` element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.errors.AbortedError.md: -------------------------------------------------------------------------------- 1 | The operation was aborted, typically due to a concurrent action. 2 | 3 | For example, running a 4 | [`queue.enqueue()`](../../api_docs/python/io_ops.md#QueueBase.enqueue) 5 | operation may raise `AbortedError` if a 6 | [`queue.close()`](../../api_docs/python/io_ops.md#QueueBase.close) operation 7 | previously ran. 8 | 9 | - - - 10 | 11 | #### `tf.errors.AbortedError.__init__(node_def, op, message)` {#AbortedError.__init__} 12 | 13 | Creates an `AbortedError`. 14 | 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.errors.InternalError.md: -------------------------------------------------------------------------------- 1 | Raised when the system experiences an internal error. 2 | 3 | This exception is raised when some invariant expected by the runtime 4 | has been broken. Catching this exception is not recommended. 5 | 6 | - - - 7 | 8 | #### `tf.errors.InternalError.__init__(node_def, op, message)` {#InternalError.__init__} 9 | 10 | Creates an `InternalError`. 11 | 12 | 13 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.errors.NotFoundError.md: -------------------------------------------------------------------------------- 1 | Raised when a requested entity (e.g., a file or directory) was not found. 2 | 3 | For example, running the 4 | [`tf.WholeFileReader.read()`](../../api_docs/python/io_ops.md#WholeFileReader) 5 | operation could raise `NotFoundError` if it receives the name of a file that 6 | does not exist. 7 | 8 | - - - 9 | 10 | #### `tf.errors.NotFoundError.__init__(node_def, op, message)` {#NotFoundError.__init__} 11 | 12 | Creates a `NotFoundError`. 13 | 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.errors.UnimplementedError.md: -------------------------------------------------------------------------------- 1 | Raised when an operation has not been implemented. 2 | 3 | Some operations may raise this error when passed otherwise-valid 4 | arguments that it does not currently support. For example, running 5 | the [`tf.nn.max_pool()`](../../api_docs/python/nn.md#max_pool) operation 6 | would raise this error if pooling was requested on the batch dimension, 7 | because this is not yet supported. 8 | 9 | - - - 10 | 11 | #### `tf.errors.UnimplementedError.__init__(node_def, op, message)` {#UnimplementedError.__init__} 12 | 13 | Creates an `UnimplementedError`. 14 | 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.maximum.md: -------------------------------------------------------------------------------- 1 | ### `tf.maximum(x, y, name=None)` {#maximum} 2 | 3 | Returns the max of x and y (i.e. x > y ? x : y) element-wise, broadcasts. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.moving_average_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.moving_average_variables()` {#moving_average_variables} 2 | 3 | Returns all variables that maintain their moving averages. 4 | 5 | If an `ExponentialMovingAverage` object is created and the `apply()` 6 | method is called on a list of variables, these variables will 7 | be added to the `GraphKeys.MOVING_AVERAGE_VARIABLES` collection. 8 | This convenience function returns the contents of that collection. 9 | 10 | ##### Returns: 11 | 12 | A list of Variable objects. 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.nn.elu.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.elu(features, name=None)` {#elu} 2 | 3 | Computes exponential linear: `exp(features) - 1` if < 0, `features` otherwise. 4 | 5 | See [Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) 6 | ](http://arxiv.org/abs/1511.07289) 7 | 8 | ##### Args: 9 | 10 | 11 | * `features`: A `Tensor`. Must be one of the following types: `float32`, `float64`. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A `Tensor`. Has the same type as `features`. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.nn.softmax.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.softmax(logits, name=None)` {#softmax} 2 | 3 | Computes softmax activations. 4 | 5 | For each batch `i` and class `j` we have 6 | 7 | softmax[i, j] = exp(logits[i, j]) / sum(exp(logits[i])) 8 | 9 | ##### Args: 10 | 11 | 12 | * `logits`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 13 | 2-D with shape `[batch_size, num_classes]`. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | A `Tensor`. Has the same type as `logits`. Same shape as `logits`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.pow.md: -------------------------------------------------------------------------------- 1 | ### `tf.pow(x, y, name=None)` {#pow} 2 | 3 | Computes the power of one value to another. 4 | 5 | Given a tensor `x` and a tensor `y`, this operation computes \\(x^y\\) for 6 | corresponding elements in `x` and `y`. For example: 7 | 8 | ``` 9 | # tensor 'x' is [[2, 2], [3, 3]] 10 | # tensor 'y' is [[8, 16], [2, 3]] 11 | tf.pow(x, y) ==> [[256, 65536], [9, 27]] 12 | ``` 13 | 14 | ##### Args: 15 | 16 | 17 | * `x`: A `Tensor` of type `float`, `double`, `int32`, `complex64`, or `int64`. 18 | * `y`: A `Tensor` of type `float`, `double`, `int32`, `complex64`, or `int64`. 19 | * `name`: A name for the operation (optional). 20 | 21 | ##### Returns: 22 | 23 | A `Tensor`. 24 | 25 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.python_io.tf_record_iterator.md: -------------------------------------------------------------------------------- 1 | ### `tf.python_io.tf_record_iterator(path)` {#tf_record_iterator} 2 | 3 | An iterator that read the records from a TFRecords file. 4 | 5 | ##### Args: 6 | 7 | 8 | * `path`: The path to the TFRecords file. 9 | 10 | ##### Yields: 11 | 12 | Strings. 13 | 14 | ##### Raises: 15 | 16 | 17 | * `IOError`: If `path` cannot be opened for reading. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.self_adjoint_eig.md: -------------------------------------------------------------------------------- 1 | ### `tf.self_adjoint_eig(input, name=None)` {#self_adjoint_eig} 2 | 3 | Calculates the Eigen Decomposition of a square Self-Adjoint matrix. 4 | 5 | Only the lower-triangular part of the input will be used in this case. The 6 | upper-triangular part will not be read. 7 | 8 | The result is a M+1 x M matrix whose first row is the eigenvalues, and 9 | subsequent rows are eigenvectors. 10 | 11 | ##### Args: 12 | 13 | 14 | * `input`: A `Tensor`. Must be one of the following types: `float64`, `float32`. 15 | Shape is `[M, M]`. 16 | * `name`: A name for the operation (optional). 17 | 18 | ##### Returns: 19 | 20 | A `Tensor`. Has the same type as `input`. Shape is `[M+1, M]`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.sigmoid.md: -------------------------------------------------------------------------------- 1 | ### `tf.sigmoid(x, name=None)` {#sigmoid} 2 | 3 | Computes sigmoid of `x` element-wise. 4 | 5 | Specifically, `y = 1 / (1 + exp(-x))`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A Tensor with type `float`, `double`, `int32`, `complex64`, `int64`, 11 | or `qint32`. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A Tensor with the same type as `x` if `x.dtype != qint32` 17 | otherwise the return type is `quint8`. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.to_float.md: -------------------------------------------------------------------------------- 1 | ### `tf.to_float(x, name='ToFloat')` {#to_float} 2 | 3 | Casts a tensor to type `float32`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` or `SparseTensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` or `SparseTensor` with same shape as `x` with type `float32`. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `TypeError`: If `x` cannot be cast to the `float32`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.train.QueueRunner.from_proto.md: -------------------------------------------------------------------------------- 1 | #### `tf.train.QueueRunner.from_proto(queue_runner_def)` {#QueueRunner.from_proto} 2 | 3 | Returns a `QueueRunner` object created from `queue_runner_def`. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard6/tf.trainable_variables.md: -------------------------------------------------------------------------------- 1 | ### `tf.trainable_variables()` {#trainable_variables} 2 | 3 | Returns all variables created with `trainable=True`. 4 | 5 | When passed `trainable=True`, the `Variable()` constructor automatically 6 | adds new variables to the graph collection 7 | `GraphKeys.TRAINABLE_VARIABLES`. This convenience function returns the 8 | contents of that collection. 9 | 10 | ##### Returns: 11 | 12 | A list of Variable objects. 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.DeviceSpec.from_string.md: -------------------------------------------------------------------------------- 1 | #### `tf.DeviceSpec.from_string(spec)` {#DeviceSpec.from_string} 2 | 3 | Construct a `DeviceSpec` from a string. 4 | 5 | ##### Args: 6 | 7 | 8 | * `spec`: a string of the form 9 | /job:/replica:/task:/device:CPU: 10 | or 11 | /job:/replica:/task:/device:GPU: 12 | as cpu and gpu are mutually exclusive. 13 | All entries are optional. 14 | 15 | ##### Returns: 16 | 17 | A DeviceSpec. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.QueueBase.from_list.md: -------------------------------------------------------------------------------- 1 | #### `tf.QueueBase.from_list(index, queues)` {#QueueBase.from_list} 2 | 3 | Create a queue using the queue reference from `queues[index]`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `index`: An integer scalar tensor that determines the input that gets 9 | selected. 10 | * `queues`: A list of `QueueBase` objects. 11 | 12 | ##### Returns: 13 | 14 | A `QueueBase` object. 15 | 16 | ##### Raises: 17 | 18 | 19 | * `TypeError`: When `queues` is not a list of `QueueBase` objects, 20 | or when the data types of `queues` are not all the same. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.as_dtype.md: -------------------------------------------------------------------------------- 1 | ### `tf.as_dtype(type_value)` {#as_dtype} 2 | 3 | Converts the given `type_value` to a `DType`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `type_value`: A value that can be converted to a `tf.DType` 9 | object. This may currently be a `tf.DType` object, a 10 | [`DataType` enum](https://www.tensorflow.org/code/tensorflow/core/framework/types.proto), 11 | a string type name, or a `numpy.dtype`. 12 | 13 | ##### Returns: 14 | 15 | A `DType` corresponding to `type_value`. 16 | 17 | ##### Raises: 18 | 19 | 20 | * `TypeError`: If `type_value` cannot be converted to a `DType`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.contrib.util.make_ndarray.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.util.make_ndarray(tensor)` {#make_ndarray} 2 | 3 | Create a numpy ndarray from a tensor. 4 | 5 | Create a numpy ndarray with the same shape and data as the tensor. 6 | 7 | ##### Args: 8 | 9 | 10 | * `tensor`: A TensorProto. 11 | 12 | ##### Returns: 13 | 14 | A numpy array with the tensor contents. 15 | 16 | ##### Raises: 17 | 18 | 19 | * `TypeError`: if tensor has unsupported type. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.fft3d.md: -------------------------------------------------------------------------------- 1 | ### `tf.fft3d(input, name=None)` {#fft3d} 2 | 3 | Compute the 3-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 3-D tensor. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. The 3D Fourier Transform of `input`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.get_session_tensor.md: -------------------------------------------------------------------------------- 1 | ### `tf.get_session_tensor(dtype, name=None)` {#get_session_tensor} 2 | 3 | Get the tensor of type `dtype` by feeding a tensor handle. 4 | 5 | This is EXPERIMENTAL and subject to change. 6 | 7 | Get the value of the tensor from a tensor handle. The tensor 8 | is produced in a previous run() and stored in the state of the 9 | session. 10 | 11 | ##### Args: 12 | 13 | 14 | * `dtype`: The type of the output tensor. 15 | * `name`: Optional name prefix for the return tensor. 16 | 17 | ##### Returns: 18 | 19 | A pair of tensors. The first is a placeholder for feeding a 20 | tensor handle and the second is the tensor in the session state 21 | keyed by the tensor handle. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.ifft.md: -------------------------------------------------------------------------------- 1 | ### `tf.ifft(input, name=None)` {#ifft} 2 | 3 | Compute the inverse 1-dimensional discrete Fourier Transform. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor` of type `complex64`. A complex64 vector. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `complex64`. 14 | The inverse 1D Fourier Transform of `input`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.less.md: -------------------------------------------------------------------------------- 1 | ### `tf.less(x, y, name=None)` {#less} 2 | 3 | Returns the truth value of (x < y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.lgamma.md: -------------------------------------------------------------------------------- 1 | ### `tf.lgamma(x, name=None)` {#lgamma} 2 | 3 | Computes the log of the absolute value of `Gamma(x)` element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor`. Has the same type as `x`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.logical_or.md: -------------------------------------------------------------------------------- 1 | ### `tf.logical_or(x, y, name=None)` {#logical_or} 2 | 3 | Returns the truth value of x OR y element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` of type `bool`. 9 | * `y`: A `Tensor` of type `bool`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.polygamma.md: -------------------------------------------------------------------------------- 1 | ### `tf.polygamma(a, x, name=None)` {#polygamma} 2 | 3 | Compute the polygamma function \\(\psi^{(n)}(x)\\). 4 | 5 | The polygamma function is defined as: 6 | 7 | ``` 8 | \psi^{(n)}(x) = \frac{d^n}{dx^n} \psi(x) 9 | ``` 10 | where \\(\psi(x)\\) is the digamma function. 11 | 12 | ##### Args: 13 | 14 | 15 | * `a`: A `Tensor`. Must be one of the following types: `float32`, `float64`. 16 | * `x`: A `Tensor`. Must have the same type as `a`. 17 | * `name`: A name for the operation (optional). 18 | 19 | ##### Returns: 20 | 21 | A `Tensor`. Has the same type as `a`. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.square.md: -------------------------------------------------------------------------------- 1 | ### `tf.square(x, name=None)` {#square} 2 | 3 | Computes square of x element-wise. 4 | 5 | I.e., \\(y = x * x = x^2\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.string_to_hash_bucket.md: -------------------------------------------------------------------------------- 1 | ### `tf.string_to_hash_bucket(string_tensor, num_buckets, name=None)` {#string_to_hash_bucket} 2 | 3 | Converts each string in the input Tensor to its hash mod by a number of buckets. 4 | 5 | The hash function is deterministic on the content of the string within the 6 | process. 7 | 8 | Note that the hash function may change from time to time. 9 | 10 | ##### Args: 11 | 12 | 13 | * `string_tensor`: A `Tensor` of type `string`. 14 | * `num_buckets`: An `int` that is `>= 1`. The number of buckets. 15 | * `name`: A name for the operation (optional). 16 | 17 | ##### Returns: 18 | 19 | A `Tensor` of type `int64`. 20 | A Tensor of the same shape as the input `string_tensor`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.MomentumOptimizer.md: -------------------------------------------------------------------------------- 1 | Optimizer that implements the Momentum algorithm. 2 | 3 | - - - 4 | 5 | #### `tf.train.MomentumOptimizer.__init__(learning_rate, momentum, use_locking=False, name='Momentum')` {#MomentumOptimizer.__init__} 6 | 7 | Construct a new Momentum optimizer. 8 | 9 | ##### Args: 10 | 11 | 12 | * `learning_rate`: A `Tensor` or a floating point value. The learning rate. 13 | * `momentum`: A `Tensor` or a floating point value. The momentum. 14 | * `use_locking`: If `True` use locks for update operations. 15 | * `name`: Optional name prefix for the operations created when applying 16 | gradients. Defaults to "Momentum". 17 | 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard7/tf.train.get_checkpoint_state.md: -------------------------------------------------------------------------------- 1 | ### `tf.train.get_checkpoint_state(checkpoint_dir, latest_filename=None)` {#get_checkpoint_state} 2 | 3 | Returns CheckpointState proto from the "checkpoint" file. 4 | 5 | If the "checkpoint" file contains a valid CheckpointState 6 | proto, returns it. 7 | 8 | ##### Args: 9 | 10 | 11 | * `checkpoint_dir`: The directory of checkpoints. 12 | * `latest_filename`: Optional name of the checkpoint file. Default to 13 | 'checkpoint'. 14 | 15 | ##### Returns: 16 | 17 | A CheckpointState if the state was available, None 18 | otherwise. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.VarLenFeature.md: -------------------------------------------------------------------------------- 1 | Configuration for parsing a variable-length input feature. 2 | 3 | Fields: 4 | dtype: Data type of input. 5 | - - - 6 | 7 | #### `tf.VarLenFeature.dtype` {#VarLenFeature.dtype} 8 | 9 | Alias for field number 0 10 | 11 | 12 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.argmax.md: -------------------------------------------------------------------------------- 1 | ### `tf.argmax(input, dimension, name=None)` {#argmax} 2 | 3 | Returns the index with the largest value across dimensions of a tensor. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`. 9 | * `dimension`: A `Tensor` of type `int32`. 10 | int32, 0 <= dimension < rank(input). Describes which dimension 11 | of the input Tensor to reduce across. For vectors, use dimension = 0. 12 | * `name`: A name for the operation (optional). 13 | 14 | ##### Returns: 15 | 16 | A `Tensor` of type `int64`. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.assert_proper_iterable.md: -------------------------------------------------------------------------------- 1 | ### `tf.assert_proper_iterable(values)` {#assert_proper_iterable} 2 | 3 | Static assert that values is a "proper" iterable. 4 | 5 | `Ops` that expect iterables of `Tensor` can call this to validate input. 6 | Useful since `Tensor`, `ndarray`, byte/text type are all iterables themselves. 7 | 8 | ##### Args: 9 | 10 | 11 | * `values`: Object to be checked. 12 | 13 | ##### Raises: 14 | 15 | 16 | * `TypeError`: If `values` is not iterable or is one of 17 | `Tensor`, `SparseTensor`, `np.array`, `tf.compat.bytes_or_text_types`. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.layers.summarize_tensor.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.summarize_tensor(tensor, tag=None)` {#summarize_tensor} 2 | 3 | Summarize a tensor using a suitable summary type. 4 | 5 | This function adds a summary op for `tensor`. The type of summary depends on 6 | the shape of `tensor`. For scalars, a `scalar_summary` is created, for all 7 | other tensors, `histogram_summary` is used. 8 | 9 | ##### Args: 10 | 11 | 12 | * `tensor`: The tensor to summarize 13 | * `tag`: The tag to use, if None then use tensor's op's name. 14 | 15 | ##### Returns: 16 | 17 | The summary op created or None for string tensors. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.NanLossDuringTrainingError.md: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.contrib.learn.extract_pandas_labels.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.extract_pandas_labels(labels)` {#extract_pandas_labels} 2 | 3 | Extract data from pandas.DataFrame for labels. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.equal.md: -------------------------------------------------------------------------------- 1 | ### `tf.equal(x, y, name=None)` {#equal} 2 | 3 | Returns the truth value of (x == y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `quint8`, `qint8`, `qint32`, `string`, `bool`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.image.transpose_image.md: -------------------------------------------------------------------------------- 1 | ### `tf.image.transpose_image(image)` {#transpose_image} 2 | 3 | Transpose an image by swapping the first and second dimension. 4 | 5 | See also `transpose()`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `image`: 3-D tensor of shape `[height, width, channels]` 11 | 12 | ##### Returns: 13 | 14 | A 3-D tensor of shape `[width, height, channels]` 15 | 16 | ##### Raises: 17 | 18 | 19 | * `ValueError`: if the shape of `image` not supported. 20 | 21 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.is_inf.md: -------------------------------------------------------------------------------- 1 | ### `tf.is_inf(x, name=None)` {#is_inf} 2 | 3 | Returns which elements of x are Inf. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` of type `bool`. 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.less_equal.md: -------------------------------------------------------------------------------- 1 | ### `tf.less_equal(x, y, name=None)` {#less_equal} 2 | 3 | Returns the truth value of (x <= y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`, `int8`, `uint16`, `half`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` of type `bool`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.nn.relu6.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.relu6(features, name=None)` {#relu6} 2 | 3 | Computes Rectified Linear 6: `min(max(features, 0), 6)`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `features`: A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`, 9 | `int16`, or `int8`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor` with the same type as `features`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.no_regularizer.md: -------------------------------------------------------------------------------- 1 | ### `tf.no_regularizer(_)` {#no_regularizer} 2 | 3 | Use this function to prevent regularization of variables. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.ones_initializer.md: -------------------------------------------------------------------------------- 1 | ### `tf.ones_initializer(shape, dtype=tf.float32)` {#ones_initializer} 2 | 3 | An adaptor for ones() to match the Initializer spec. 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.reset_default_graph.md: -------------------------------------------------------------------------------- 1 | ### `tf.reset_default_graph()` {#reset_default_graph} 2 | 3 | Clears the default graph stack and resets the global default graph. 4 | 5 | NOTE: The default graph is a property of the current thread. This 6 | function applies only to the current thread. Calling this function while 7 | a `tf.Session` or `tf.InteractiveSession` is active will result in undefined 8 | behavior. Using any previously created `tf.Operation` or `tf.Tensor` objects 9 | after calling this function will result in undefined behavior. 10 | 11 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.round.md: -------------------------------------------------------------------------------- 1 | ### `tf.round(x, name=None)` {#round} 2 | 3 | Rounds the values of a tensor to the nearest integer, element-wise. 4 | 5 | For example: 6 | 7 | ```python 8 | # 'a' is [0.9, 2.5, 2.3, -4.4] 9 | tf.round(a) ==> [ 1.0, 3.0, 2.0, -4.0 ] 10 | ``` 11 | 12 | ##### Args: 13 | 14 | 15 | * `x`: A `Tensor` of type `float` or `double`. 16 | * `name`: A name for the operation (optional). 17 | 18 | ##### Returns: 19 | 20 | A `Tensor` of same shape and type as `x`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.rsqrt.md: -------------------------------------------------------------------------------- 1 | ### `tf.rsqrt(x, name=None)` {#rsqrt} 2 | 3 | Computes reciprocal of square root of x element-wise. 4 | 5 | I.e., \\(y = 1 / \sqrt{x}\\). 6 | 7 | ##### Args: 8 | 9 | 10 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `complex64`, `complex128`. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor`. Has the same type as `x`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard8/tf.zeta.md: -------------------------------------------------------------------------------- 1 | ### `tf.zeta(x, q, name=None)` {#zeta} 2 | 3 | Compute the Hurwitz zeta function \\(\zeta(x, q)\\). 4 | 5 | The Hurwitz zeta function is defined as: 6 | 7 | ``` 8 | \zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x} 9 | ``` 10 | 11 | ##### Args: 12 | 13 | 14 | * `x`: A `Tensor`. Must be one of the following types: `float32`, `float64`. 15 | * `q`: A `Tensor`. Must have the same type as `x`. 16 | * `name`: A name for the operation (optional). 17 | 18 | ##### Returns: 19 | 20 | A `Tensor`. Has the same type as `x`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.batch_fft2d.md: -------------------------------------------------------------------------------- 1 | ### `tf.batch_fft2d(input, name=None)` {#batch_fft2d} 2 | 3 | Compute the 2-dimensional discrete Fourier Transform over the inner-most 4 | 5 | 2 dimensions of `input`. 6 | 7 | ##### Args: 8 | 9 | 10 | * `input`: A `Tensor` of type `complex64`. A complex64 tensor. 11 | * `name`: A name for the operation (optional). 12 | 13 | ##### Returns: 14 | 15 | A `Tensor` of type `complex64`. 16 | A complex64 tensor of the same shape as `input`. The inner-most 2 17 | dimensions of `input` are replaced with their 2D Fourier Transform. 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.layers.l1_regularizer.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.layers.l1_regularizer(scale)` {#l1_regularizer} 2 | 3 | Returns a function that can be used to apply L1 regularization to weights. 4 | 5 | L1 regularization encourages sparsity. 6 | 7 | ##### Args: 8 | 9 | 10 | * `scale`: A scalar multiplier `Tensor`. 0.0 disables the regularizer. 11 | 12 | ##### Returns: 13 | 14 | A function with signature `l1(weights, name=None)` that apply L1 15 | regularization. 16 | 17 | ##### Raises: 18 | 19 | 20 | * `ValueError`: If scale is outside of the range [0.0, 1.0] or if scale is not a 21 | float. 22 | 23 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.contrib.learn.infer.md: -------------------------------------------------------------------------------- 1 | ### `tf.contrib.learn.infer(restore_checkpoint_path, output_dict, feed_dict=None)` {#infer} 2 | 3 | 4 | 5 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.errors.InvalidArgumentError.md: -------------------------------------------------------------------------------- 1 | Raised when an operation receives an invalid argument. 2 | 3 | This may occur, for example, if an operation is receives an input 4 | tensor that has an invalid value or shape. For example, the 5 | [`tf.matmul()`](../../api_docs/python/math_ops.md#matmul) op will raise this 6 | error if it receives an input that is not a matrix, and the 7 | [`tf.reshape()`](../../api_docs/python/array_ops.md#reshape) op will raise 8 | this error if the new shape does not match the number of elements in the input 9 | tensor. 10 | 11 | - - - 12 | 13 | #### `tf.errors.InvalidArgumentError.__init__(node_def, op, message)` {#InvalidArgumentError.__init__} 14 | 15 | Creates an `InvalidArgumentError`. 16 | 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.errors.UnknownError.md: -------------------------------------------------------------------------------- 1 | Unknown error. 2 | 3 | An example of where this error may be returned is if a Status value 4 | received from another address space belongs to an error-space that 5 | is not known to this address space. Also errors raised by APIs that 6 | do not return enough error information may be converted to this 7 | error. 8 | 9 | - - - 10 | 11 | #### `tf.errors.UnknownError.__init__(node_def, op, message, error_code=2)` {#UnknownError.__init__} 12 | 13 | Creates an `UnknownError`. 14 | 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.fill.md: -------------------------------------------------------------------------------- 1 | ### `tf.fill(dims, value, name=None)` {#fill} 2 | 3 | Creates a tensor filled with a scalar value. 4 | 5 | This operation creates a tensor of shape `dims` and fills it with `value`. 6 | 7 | For example: 8 | 9 | ```prettyprint 10 | # Output tensor has shape [2, 3]. 11 | fill([2, 3], 9) ==> [[9, 9, 9] 12 | [9, 9, 9]] 13 | ``` 14 | 15 | ##### Args: 16 | 17 | 18 | * `dims`: A `Tensor` of type `int32`. 19 | 1-D. Represents the shape of the output tensor. 20 | * `value`: A `Tensor`. 0-D (scalar). Value to fill the returned tensor. 21 | * `name`: A name for the operation (optional). 22 | 23 | ##### Returns: 24 | 25 | A `Tensor`. Has the same type as `value`. 26 | 27 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.get_default_graph.md: -------------------------------------------------------------------------------- 1 | ### `tf.get_default_graph()` {#get_default_graph} 2 | 3 | Returns the default graph for the current thread. 4 | 5 | The returned graph will be the innermost graph on which a 6 | `Graph.as_default()` context has been entered, or a global default 7 | graph if none has been explicitly created. 8 | 9 | NOTE: The default graph is a property of the current thread. If you 10 | create a new thread, and wish to use the default graph in that 11 | thread, you must explicitly add a `with g.as_default():` in that 12 | thread's function. 13 | 14 | ##### Returns: 15 | 16 | The default `Graph` being used in the current thread. 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.matrix_determinant.md: -------------------------------------------------------------------------------- 1 | ### `tf.matrix_determinant(input, name=None)` {#matrix_determinant} 2 | 3 | Calculates the determinant of a square matrix. 4 | 5 | ##### Args: 6 | 7 | 8 | * `input`: A `Tensor`. Must be one of the following types: `float32`, `float64`. 9 | A tensor of shape `[M, M]`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `input`. 15 | A scalar, equal to the determinant of the input. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.nn.zero_fraction.md: -------------------------------------------------------------------------------- 1 | ### `tf.nn.zero_fraction(value, name=None)` {#zero_fraction} 2 | 3 | Returns the fraction of zeros in `value`. 4 | 5 | If `value` is empty, the result is `nan`. 6 | 7 | This is useful in summaries to measure and report sparsity. For example, 8 | 9 | z = tf.Relu(...) 10 | summ = tf.scalar_summary('sparsity', tf.nn.zero_fraction(z)) 11 | 12 | ##### Args: 13 | 14 | 15 | * `value`: A tensor of numeric type. 16 | * `name`: A name for the operation (optional). 17 | 18 | ##### Returns: 19 | 20 | The fraction of zeros in `value`, with type `float32`. 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.ones.md: -------------------------------------------------------------------------------- 1 | ### `tf.ones(shape, dtype=tf.float32, name=None)` {#ones} 2 | 3 | Creates a tensor with all elements set to 1. 4 | 5 | This operation returns a tensor of type `dtype` with shape `shape` and all 6 | elements set to 1. 7 | 8 | For example: 9 | 10 | ```python 11 | tf.ones([2, 3], int32) ==> [[1, 1, 1], [1, 1, 1]] 12 | ``` 13 | 14 | ##### Args: 15 | 16 | 17 | * `shape`: Either a list of integers, or a 1-D `Tensor` of type `int32`. 18 | * `dtype`: The type of an element in the resulting `Tensor`. 19 | * `name`: A name for the operation (optional). 20 | 21 | ##### Returns: 22 | 23 | A `Tensor` with all elements set to 1. 24 | 25 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.saturate_cast.md: -------------------------------------------------------------------------------- 1 | ### `tf.saturate_cast(value, dtype, name=None)` {#saturate_cast} 2 | 3 | Performs a safe saturating cast of `value` to `dtype`. 4 | 5 | This function casts the input to `dtype` without applying any scaling. If 6 | there is a danger that values would over or underflow in the cast, this op 7 | applies the appropriate clamping before the cast. 8 | 9 | ##### Args: 10 | 11 | 12 | * `value`: A `Tensor`. 13 | * `dtype`: The desired output `DType`. 14 | * `name`: A name for the operation (optional). 15 | 16 | ##### Returns: 17 | 18 | `value` safely cast to `dtype`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.scalar_mul.md: -------------------------------------------------------------------------------- 1 | ### `tf.scalar_mul(scalar, x)` {#scalar_mul} 2 | 3 | Multiplies a scalar times a `Tensor` or `IndexedSlices` object. 4 | 5 | Intended for use in gradient code which might deal with `IndexedSlices` 6 | objects, which are easy to multiply by a scalar but more expensive to 7 | multiply with arbitrary tensors. 8 | 9 | ##### Args: 10 | 11 | 12 | * `scalar`: A 0-D scalar `Tensor`. Must have known shape. 13 | * `x`: A `Tensor` or `IndexedSlices` to be scaled. 14 | 15 | ##### Returns: 16 | 17 | `scalar * x` of the same type (`Tensor` or `IndexedSlices`) as `x`. 18 | 19 | ##### Raises: 20 | 21 | 22 | * `ValueError`: if scalar is not a 0-D `scalar`. 23 | 24 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.size.md: -------------------------------------------------------------------------------- 1 | ### `tf.size(input, name=None)` {#size} 2 | 3 | Returns the size of a tensor. 4 | 5 | This operation returns an integer representing the number of elements in 6 | `input`. 7 | 8 | For example: 9 | 10 | ```prettyprint 11 | # 't' is [[[1, 1,, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]] 12 | size(t) ==> 12 13 | ``` 14 | 15 | ##### Args: 16 | 17 | 18 | * `input`: A `Tensor`. 19 | * `name`: A name for the operation (optional). 20 | 21 | ##### Returns: 22 | 23 | A `Tensor` of type `int32`. 24 | 25 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.squared_difference.md: -------------------------------------------------------------------------------- 1 | ### `tf.squared_difference(x, y, name=None)` {#squared_difference} 2 | 3 | Returns (x - y)(x - y) element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`. 9 | * `y`: A `Tensor`. Must have the same type as `x`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A `Tensor`. Has the same type as `x`. 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.tanh.md: -------------------------------------------------------------------------------- 1 | ### `tf.tanh(x, name=None)` {#tanh} 2 | 3 | Computes hyperbolic tangent of `x` element-wise. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A Tensor with type `float`, `double`, `int32`, `complex64`, `int64`, 9 | or `qint32`. 10 | * `name`: A name for the operation (optional). 11 | 12 | ##### Returns: 13 | 14 | A Tensor with the same type as `x` if `x.dtype != qint32` otherwise 15 | the return type is `quint8`. 16 | 17 | -------------------------------------------------------------------------------- /tensorflow/g3doc/api_docs/python/functions_and_classes/shard9/tf.to_bfloat16.md: -------------------------------------------------------------------------------- 1 | ### `tf.to_bfloat16(x, name='ToBFloat16')` {#to_bfloat16} 2 | 3 | Casts a tensor to type `bfloat16`. 4 | 5 | ##### Args: 6 | 7 | 8 | * `x`: A `Tensor` or `SparseTensor`. 9 | * `name`: A name for the operation (optional). 10 | 11 | ##### Returns: 12 | 13 | A `Tensor` or `SparseTensor` with same shape as `x` with type `bfloat16`. 14 | 15 | ##### Raises: 16 | 17 | 18 | * `TypeError`: If `x` cannot be cast to the `bfloat16`. 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/extras/README.txt: -------------------------------------------------------------------------------- 1 | This directory holds extra files we'd like to be able 2 | to link to and serve from within tensorflow.org. 3 | They are excluded from versioning. -------------------------------------------------------------------------------- /tensorflow/g3doc/get_started/leftnav_files: -------------------------------------------------------------------------------- 1 | index.md 2 | os_setup.md 3 | basic_usage.md -------------------------------------------------------------------------------- /tensorflow/g3doc/how_tos/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/g3doc/how_tos/__init__.py -------------------------------------------------------------------------------- /tensorflow/g3doc/how_tos/adding_an_op/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/g3doc/how_tos/adding_an_op/__init__.py -------------------------------------------------------------------------------- /tensorflow/g3doc/how_tos/leftnav_files: -------------------------------------------------------------------------------- 1 | variables/index.md 2 | ../tutorials/mnist/tf/index.md 3 | summaries_and_tensorboard/index.md 4 | graph_viz/index.md 5 | reading_data/index.md 6 | threading_and_queues/index.md 7 | distributed/index.md 8 | adding_an_op/index.md 9 | new_data_formats/index.md 10 | using_gpu/index.md 11 | variable_scope/index.md -------------------------------------------------------------------------------- /tensorflow/g3doc/images/getting_started.dot: -------------------------------------------------------------------------------- 1 | digraph Dependencies { 2 | node [shape = oval]; 3 | "predictions: MatMul()" -> "data: Concat()" 4 | "data: Concat()" -> data_left 5 | "data: Concat()" -> data_right 6 | "predictions: MatMul()" -> "weight_matrix: Reshape()" 7 | "weight_matrix: Reshape()" -> "new_weights: Add()" 8 | "new_weights: Add()" -> weights 9 | "new_weights: Add()" -> deltas 10 | "update: Assign()" -> weights 11 | "update: Assign()" -> "new_weights: Add()" 12 | "InitializeAllVariables()" -> weights 13 | "InitializeAllVariables()" -> init_value 14 | } -------------------------------------------------------------------------------- /tensorflow/g3doc/resources/leftnav_files: -------------------------------------------------------------------------------- 1 | bib.md 2 | uses.md 3 | faq.md 4 | glossary.md 5 | dims_types.md 6 | versions.md 7 | roadmap.md -------------------------------------------------------------------------------- /tensorflow/g3doc/tutorials/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Top-level tutorials files 3 | 4 | package(default_visibility = ["//tensorflow:internal"]) 5 | 6 | licenses(["notice"]) # Apache 2.0 7 | 8 | exports_files(["LICENSE"]) 9 | 10 | filegroup( 11 | name = "all_files", 12 | srcs = glob( 13 | ["**/*"], 14 | exclude = [ 15 | "**/METADATA", 16 | "**/OWNERS", 17 | ], 18 | ), 19 | ) 20 | -------------------------------------------------------------------------------- /tensorflow/g3doc/tutorials/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/g3doc/tutorials/__init__.py -------------------------------------------------------------------------------- /tensorflow/g3doc/tutorials/deep_cnn/cifar_tensorboard.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | TensorBoard Demo 5 | 6 | 7 | 17 | 18 | 19 | 20 | 21 | 22 | -------------------------------------------------------------------------------- /tensorflow/g3doc/tutorials/leftnav_files: -------------------------------------------------------------------------------- 1 | mnist/beginners/index.md 2 | mnist/pros/index.md 3 | mnist/tf/index.md 4 | tfserve/index.md 5 | deep_cnn/index.md 6 | word2vec/index.md 7 | recurrent/index.md 8 | seq2seq/index.md 9 | mandelbrot/index.md 10 | pdes/index.md 11 | mnist/download/index.md 12 | image_recognition/index.md -------------------------------------------------------------------------------- /tensorflow/g3doc/tutorials/syntaxnet/index.md: -------------------------------------------------------------------------------- 1 | # SyntaxNet 2 | 3 | ## Introduction 4 | 5 | SyntaxNet is a neural-network Natural Language Processing framework for 6 | TensorFlow. 7 | 8 | ## Basic SyntaxNet Tutorial 9 | 10 | The [tutorial]( 11 | https://github.com/tensorflow/models/tree/master/syntaxnet#installation) 12 | shows you how to: 13 | 14 | * Install SyntaxNet. 15 | * Use the included, pretrained Parsey McParseface parser. 16 | * Train your own part-of-speech tagger. 17 | * Train your own parser. -------------------------------------------------------------------------------- /tensorflow/models/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/models/__init__.py -------------------------------------------------------------------------------- /tensorflow/models/image/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/models/image/__init__.py -------------------------------------------------------------------------------- /tensorflow/models/image/alexnet/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Benchmark for AlexNet. 3 | 4 | licenses(["notice"]) # Apache 2.0 5 | 6 | exports_files(["LICENSE"]) 7 | 8 | py_binary( 9 | name = "alexnet_benchmark", 10 | srcs = [ 11 | "alexnet_benchmark.py", 12 | ], 13 | srcs_version = "PY2AND3", 14 | deps = [ 15 | "//tensorflow:tensorflow_py", 16 | ], 17 | ) 18 | 19 | filegroup( 20 | name = "all_files", 21 | srcs = glob( 22 | ["**/*"], 23 | exclude = [ 24 | "**/METADATA", 25 | "**/OWNERS", 26 | ], 27 | ), 28 | visibility = ["//tensorflow:__subpackages__"], 29 | ) 30 | -------------------------------------------------------------------------------- /tensorflow/models/image/alexnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/models/image/alexnet/__init__.py -------------------------------------------------------------------------------- /tensorflow/models/image/cifar10/README.md: -------------------------------------------------------------------------------- 1 | CIFAR-10 is a common benchmark in machine learning for image recognition. 2 | 3 | http://www.cs.toronto.edu/~kriz/cifar.html 4 | 5 | Code in this directory demonstrates how to use TensorFlow to train and evaluate a convolutional neural network (CNN) on both CPU and GPU. We also demonstrate how to train a CNN over multiple GPUs. 6 | 7 | Detailed instructions on how to get started available at: 8 | 9 | http://tensorflow.org/tutorials/deep_cnn/ 10 | 11 | -------------------------------------------------------------------------------- /tensorflow/models/image/imagenet/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Example TensorFlow models for ImageNet. 3 | 4 | licenses(["notice"]) # Apache 2.0 5 | 6 | exports_files(["LICENSE"]) 7 | 8 | py_binary( 9 | name = "classify_image", 10 | srcs = [ 11 | "classify_image.py", 12 | ], 13 | srcs_version = "PY2AND3", 14 | visibility = ["//tensorflow:__subpackages__"], 15 | deps = [ 16 | "//tensorflow:tensorflow_py", 17 | ], 18 | ) 19 | 20 | filegroup( 21 | name = "all_files", 22 | srcs = glob( 23 | ["**/*"], 24 | exclude = [ 25 | "**/METADATA", 26 | "**/OWNERS", 27 | ], 28 | ), 29 | visibility = ["//tensorflow:__subpackages__"], 30 | ) 31 | -------------------------------------------------------------------------------- /tensorflow/models/image/mnist/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/models/image/mnist/__init__.py -------------------------------------------------------------------------------- /tensorflow/models/rnn/README.md: -------------------------------------------------------------------------------- 1 | This directory contains functions for creating recurrent neural networks 2 | and sequence-to-sequence models. Detailed instructions on how to get started 3 | and use them are available in the tutorials. 4 | 5 | * [RNN Tutorial](http://tensorflow.org/tutorials/recurrent/index.md) 6 | * [Sequence-to-Sequence Tutorial](http://tensorflow.org/tutorials/seq2seq/index.md) 7 | 8 | Here is a short overview of what is in this directory. 9 | 10 | File | What's in it? 11 | --- | --- 12 | `ptb/` | PTB language model, see the [RNN Tutorial](http://tensorflow.org/tutorials/recurrent/) 13 | `translate/` | Translation model, see the [Sequence-to-Sequence Tutorial](http://tensorflow.org/tutorials/seq2seq/) 14 | -------------------------------------------------------------------------------- /tensorflow/python/client/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/client/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/framework/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/framework/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/kernel_tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/kernel_tests/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/lib/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/lib/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/lib/core/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/lib/core/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/lib/io/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/lib/io/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/ops/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/ops/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/platform/default/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/platform/default/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/summary/README.md: -------------------------------------------------------------------------------- 1 | # TensorFlow Event Processing 2 | 3 | This folder contains classes useful for analyzing and visualizing TensorFlow 4 | events files. The code is primarily being developed to support TensorBoard, 5 | but it can be used by anyone who wishes to analyze or visualize TensorFlow 6 | events files. 7 | 8 | If you wish to load TensorFlow events, you should use an EventAccumulator 9 | (to load from a single events file) or an EventMultiplexer (to load from 10 | multiple events files). 11 | 12 | The API around these tools has not solidified, and we may make backwards- 13 | incompatible changes without warning. 14 | 15 | If you have questions or requests, please contact danmane@google.com 16 | -------------------------------------------------------------------------------- /tensorflow/python/summary/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/summary/__init__.py -------------------------------------------------------------------------------- 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TODO(touts): Add other attributes as needed. 9 | message CheckpointState { 10 | // Path to the most-recent model checkpoint. 11 | string model_checkpoint_path = 1; 12 | 13 | // Paths to all not-yet-deleted model checkpoints, sorted from oldest to 14 | // newest. 15 | // Note that the value of model_checkpoint_path should be the last item in 16 | // this list. 17 | repeated string all_model_checkpoint_paths = 2; 18 | } 19 | -------------------------------------------------------------------------------- /tensorflow/python/user_ops/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/python/user_ops/__init__.py -------------------------------------------------------------------------------- /tensorflow/python/util/__init__.py: -------------------------------------------------------------------------------- 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5 | Change default # of scalar values to 1000 6 | Fix bug where TensorBoard discards all values after a restart. 7 | 8 | --- 4 --- 9 | Fix another case where TensorBoard discards values after a restart. 10 | Add a "toggle all runs" button. -------------------------------------------------------------------------------- /tensorflow/tensorboard/TAG: -------------------------------------------------------------------------------- 1 | 21 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/__init__.py -------------------------------------------------------------------------------- /tensorflow/tensorboard/app/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Build rules for building the HTML/JS necessary for TensorBoard. 3 | package(default_visibility = ["//tensorflow:internal"]) 4 | 5 | licenses(["notice"]) # Apache 2.0 6 | 7 | exports_files(["LICENSE"]) 8 | 9 | filegroup( 10 | name = "all_files", 11 | srcs = glob( 12 | ["**/*"], 13 | exclude = [ 14 | "**/METADATA", 15 | "**/OWNERS", 16 | ], 17 | ), 18 | visibility = ["//tensorflow:__subpackages__"], 19 | ) 20 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/backend/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/backend/__init__.py -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//tensorflow:internal"]) 2 | 3 | licenses(["notice"]) # Apache 2.0 4 | 5 | exports_files(["LICENSE"]) 6 | 7 | filegroup( 8 | name = "all_files", 9 | srcs = glob( 10 | ["tf-*/**/*"], 11 | exclude = [ 12 | "**/tf_model_zoo/*", 13 | "**/METADATA", 14 | "**/OWNERS", 15 | ], 16 | ), 17 | visibility = ["//tensorflow:__subpackages__"], 18 | ) 19 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-audio-dashboard/test/data/runs.json: -------------------------------------------------------------------------------- 1 | {"run1": {"audio": ["foo", "bar"]}, "run2": {"audio": ["bar", "zod"]}} 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-audio-dashboard/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 15 | 16 | 17 | 18 | 19 | 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| } 29 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-backend/test/data/scalars.json: -------------------------------------------------------------------------------- 1 | {"run1": {"cross_entropy (1)": [[0, 0, 0.0], [10.0, 1, 1.0], [20.0, 2, 4.0], [30.0, 3, 9.0], [40.0, 4, 16.0]]}} -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-backend/test/data/scalars_run_run1_tag_cross_entropy__281_29.json: -------------------------------------------------------------------------------- 1 | [[0, 0, 0.0], [10.0, 1, 1.0], [20.0, 2, 4.0], [30.0, 3, 9.0], [40.0, 4, 16.0]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-backend/tf-backend.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-categorizer/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-collapsable-pane/demo/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 10 | 11 |

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12 | 13 | 14 | 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-dashboard-common/tensorboard-color.html: -------------------------------------------------------------------------------- 1 | 2 | 15 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-dashboard-common/tf-dashboard.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-event-dashboard/demo/data/runs.json: -------------------------------------------------------------------------------- 1 | { 2 | "alpha": { 3 | "scalars": [ 4 | "d1", 5 | "d2", 6 | "d3", 7 | "d4" 8 | ], 9 | "histograms": [], 10 | "images": [], 11 | "audio": [] 12 | }, 13 | "beta": { 14 | "scalars": [ 15 | "d1", 16 | "d2", 17 | "d3", 18 | "d4" 19 | ], 20 | "histograms": [], 21 | "images": [], 22 | "audio": [] 23 | } 24 | } 25 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-graph-common/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-graph-loader/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-histogram-dashboard/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-image-dashboard/test/data/runs.json: -------------------------------------------------------------------------------- 1 | {"run1": {"images": ["foo", "bar"]}, "run2": {"images": ["bar", "zod"]}} 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-image-dashboard/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 15 | 16 | 17 | 18 | 19 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/README.md: -------------------------------------------------------------------------------- 1 | This file acts as import routers for third party javascript libraries, 2 | e.g. Plottable and D3. 3 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/d3.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/dagre.html: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/README.md: -------------------------------------------------------------------------------- 1 | This file acts as import routers for third party javascript libraries, 2 | e.g. Plottable and D3 from `g3/third_party`; it exists to facilitate development 3 | inside google. 4 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/d3.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/dagre.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/graphlib.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/lodash.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/google/plottable.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/graphlib.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/lodash.html: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-imports/plottable.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/data/graph_run_run1.pbtxt: -------------------------------------------------------------------------------- 1 | node { 2 | name: "a" 3 | op: "matmul" 4 | } 5 | node { 6 | name: "b" 7 | op: "matmul" 8 | input: "a:0" 9 | } 10 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/data/graph_run_run2.pbtxt: -------------------------------------------------------------------------------- 1 | node { 2 | name: "a" 3 | op: "matmul" 4 | } 5 | node { 6 | name: "b" 7 | op: "matmul" 8 | input: "a:0" 9 | } 10 | node { 11 | name: "c" 12 | op: "matmul" 13 | input: "a:0" 14 | input: "b:0" 15 | } 16 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/data/runs.json: -------------------------------------------------------------------------------- 1 | {"run2": {"graph": true, "histograms": [], "scalars": [], "compressedHistograms": [], "images": []}, "run1": {"graph": true, "histograms": [], "scalars": [], "compressedHistograms": [], "images": []}} 2 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/e2eTests.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/fastTabSwitch.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/components/tf-tensorboard/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 16 | 17 | 18 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/audio_run_run1_tag_au1_2Faudio_2F0.json: -------------------------------------------------------------------------------- 1 | [{"query": "index=0&tag=au1%2Faudio%2F0&run=run1", "step": 0, "wall_time": 1461795049.203407, "content_type": "audio/wav"}] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/audio_run_run2_tag_au2_2Faudio_2F0.json: -------------------------------------------------------------------------------- 1 | [{"query": "index=0&tag=au2%2Faudio%2F0&run=run2", "step": 0, "wall_time": 1461795049.212815, "content_type": "audio/wav"}] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/graph_run_run1.pbtxt: -------------------------------------------------------------------------------- 1 | node { 2 | name: "a" 3 | op: "matmul" 4 | } 5 | node { 6 | name: "b" 7 | op: "matmul" 8 | input: "a:0" 9 | } 10 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/graph_run_run2.pbtxt: -------------------------------------------------------------------------------- 1 | node { 2 | name: "a" 3 | op: "matmul" 4 | } 5 | node { 6 | name: "b" 7 | op: "matmul" 8 | input: "a:0" 9 | } 10 | node { 11 | name: "c" 12 | op: "matmul" 13 | input: "a:0" 14 | input: "b:0" 15 | } 16 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/histograms_run_run1_tag_histo1.json: -------------------------------------------------------------------------------- 1 | [[400.0, 40, [-0.3584790755077172, 3.0267252195784047, 20.0, 24.012225532303315, 48.29045006426564, [-0.35363819004775493, 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1.3429404381931362, 1.624957930213695, 1.7874537232350647, 2.1628190051144287, 2.6170109961884593, 2.8787120958073054, 3.8315657995195243], [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 2.0, 1.0, 1.0]]]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/histograms_run_run2_tag_histo2.json: -------------------------------------------------------------------------------- 1 | [[400.0, 40, [-0.8286852465281818, 2.0954239138728523, 20.0, 13.546880465642861, 24.14836803774091, [-0.7580548669750213, -0.38900200905253046, -0.06996543062044111, 0.07696197368248522, 0.19961953895336082, 0.2656936063469233, 0.29226296698161564, 0.5177616740489182, 0.7580548669750213, 0.917246389039776, 1.109868130738129, 1.220854943811942, 1.624957930213695, 2.1628190051144287], [2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 2.0, 1.0, 1.0, 1.0, 2.0, 3.0]]]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/images_run_run1_tag_im1_2Fimage_2F0.json: -------------------------------------------------------------------------------- 1 | [{"wall_time": 1459200389.088045, "width": 4, "height": 4, "step": 0, "query": "tag=im1%2Fimage%2F0&index=0&run=run1"}] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/images_run_run1_tag_im2_2Fimage_2F0.json: -------------------------------------------------------------------------------- 1 | [{"wall_time": 1459200389.093653, "width": 4, "height": 4, "step": 0, "query": "tag=im2%2Fimage%2F0&index=0&run=run1"}] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/images_run_run2_tag_im1_2Fimage_2F0.json: -------------------------------------------------------------------------------- 1 | [{"wall_time": 1459200389.117463, "width": 4, "height": 4, "step": 0, "query": "tag=im1%2Fimage%2F0&index=0&run=run2"}] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/individualAudio_index_0_tag_au1_2Faudio_2F0_run_run1.wav: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/demo/data/individualAudio_index_0_tag_au1_2Faudio_2F0_run_run1.wav -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/individualAudio_index_0_tag_au2_2Faudio_2F0_run_run2.wav: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/demo/data/individualAudio_index_0_tag_au2_2Faudio_2F0_run_run2.wav 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/tensorflow/tensorboard/demo/data/individualImage_tag_im2_2Fimage_2F0_index_0_run_run1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/demo/data/individualImage_tag_im2_2Fimage_2F0_index_0_run_run1.png -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/runs.json: -------------------------------------------------------------------------------- 1 | {"run1": {"scalars": ["foo/sin", "foo/cos", "foo/square", "bar/square"], "run_metadata": [], "compressedHistograms": ["histo1"], "images": ["im1/image/0", "im2/image/0"], "histograms": ["histo1"], "graph": true, "audio": ["au1/audio/0"]}, "run2": {"scalars": ["foo/cos", "foo/square", "bar/square"], "run_metadata": [], "compressedHistograms": ["histo2", "histo1"], "images": ["im1/image/0"], "histograms": ["histo2", "histo1"], "graph": true, "audio": ["au2/audio/0"]}} -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run1_tag_bar_2Fsquare.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 0.0], [10.0, 1, 1.0], [20.0, 2, 4.0], [30.0, 3, 9.0], [40.0, 4, 16.0]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run1_tag_foo_2Fcos.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 1.0], [10.0, 1, 0.5403022766113281], [20.0, 2, -0.416146844625473], [30.0, 3, -0.9899924993515015], [40.0, 4, -0.6536436080932617]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run1_tag_foo_2Fsin.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 0.0], [10.0, 1, 0.8414709568023682], [20.0, 2, 0.9092974066734314], [30.0, 3, 0.14112000167369843], [40.0, 4, -0.756802499294281]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run1_tag_foo_2Fsquare.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 0.0], [10.0, 1, 1.0], [20.0, 2, 4.0], [30.0, 3, 9.0], [40.0, 4, 16.0]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run2_tag_bar_2Fsquare.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 0.0], [10.0, 1, 1.0], [20.0, 2, 4.0], [30.0, 3, 9.0], [40.0, 4, 16.0]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run2_tag_foo_2Fcos.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 2.0], [10.0, 1, 1.0806045532226562], [20.0, 2, -0.832293689250946], [30.0, 3, -1.979984998703003], [40.0, 4, -1.3072872161865234]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/demo/data/scalars_run_run2_tag_foo_2Fsquare.json: -------------------------------------------------------------------------------- 1 | [[0.0, 0, 0.0], [10.0, 1, 2.0], [20.0, 2, 8.0], [30.0, 3, 18.0], [40.0, 4, 32.0]] -------------------------------------------------------------------------------- /tensorflow/tensorboard/lib/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # BUILD rules for the static resources in TensorBoard. 3 | 4 | package(default_visibility = [ 5 | "//tensorflow:internal", 6 | ]) 7 | 8 | licenses(["notice"]) # Apache 2.0 9 | 10 | exports_files([ 11 | "LICENSE", 12 | ]) 13 | 14 | filegroup( 15 | name = "all_files", 16 | srcs = glob( 17 | [ 18 | "**/*", 19 | ], 20 | ), 21 | visibility = ["//tensorflow:__subpackages__"], 22 | ) 23 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/lib/css/global.css: -------------------------------------------------------------------------------- 1 | html,body { 2 | margin: 0; 3 | padding: 0; 4 | height: 100%; 5 | font-family: "RobotoDraft","Roboto",sans-serif; 6 | } 7 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/lib/js/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # BUILD rules for the frontend libraries in TensorBoard. 3 | 4 | package(default_visibility = [ 5 | "//tensorflow:internal", 6 | ]) 7 | 8 | licenses(["notice"]) # Apache 2.0 9 | 10 | exports_files([ 11 | "LICENSE", 12 | ]) 13 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/lib/js/nanite/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 16 | 17 | 18 | 19 | 20 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/lib/js/node-radar/test/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/scripts/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tensorboard/scripts/__init__.py -------------------------------------------------------------------------------- /tensorflow/tensorboard/tsconfig.json: -------------------------------------------------------------------------------- 1 | { 2 | "compilerOptions": { 3 | "noImplicitAny": false, 4 | "noEmitOnError": true, 5 | "target": "ES5" 6 | }, 7 | "compileOnSave": false, 8 | "exclude": [ 9 | "node_modules", 10 | "typings/main.d.ts", 11 | "typings/main", 12 | "lib" 13 | ] 14 | } 15 | -------------------------------------------------------------------------------- /tensorflow/tensorboard/wct.conf.json: -------------------------------------------------------------------------------- 1 | { 2 | "suites": [ 3 | "components/tf-*/test", 4 | "lib/js/*/test" 5 | ], 6 | "plugins": ["local"], 7 | "webserver": { 8 | "pathMappings": [ 9 | {"/components//lib/js": "components"} 10 | ] 11 | } 12 | } -------------------------------------------------------------------------------- /tensorflow/tf_exported_symbols.lds: -------------------------------------------------------------------------------- 1 | *tensorflow* 2 | -------------------------------------------------------------------------------- /tensorflow/tf_version_script.lds: -------------------------------------------------------------------------------- 1 | tensorflow { 2 | global: 3 | *tensorflow*; 4 | local: 5 | *; 6 | }; 7 | -------------------------------------------------------------------------------- /tensorflow/tools/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tools/__init__.py -------------------------------------------------------------------------------- /tensorflow/tools/ci_build/Dockerfile.cpu: -------------------------------------------------------------------------------- 1 | FROM ubuntu:14.04 2 | 3 | MAINTAINER Jan Prach 4 | 5 | # Copy and run the install scripts. 6 | COPY install/*.sh /install/ 7 | RUN /install/install_bootstrap_deb_packages.sh 8 | RUN add-apt-repository -y ppa:openjdk-r/ppa && \ 9 | add-apt-repository -y ppa:mc3man/trusty-media && \ 10 | add-apt-repository -y ppa:george-edison55/cmake-3.x 11 | RUN /install/install_deb_packages.sh 12 | RUN /install/install_pip_packages.sh 13 | RUN /install/install_bazel.sh 14 | RUN /install/install_proto3.sh 15 | 16 | # Set up bazelrc. 17 | COPY install/.bazelrc /root/.bazelrc 18 | ENV BAZELRC /root/.bazelrc 19 | -------------------------------------------------------------------------------- /tensorflow/tools/ci_build/Dockerfile.debian.jessie.cpu: -------------------------------------------------------------------------------- 1 | FROM debian:jessie 2 | 3 | MAINTAINER Jan Prach 4 | 5 | # Copy and run the install scripts. 6 | COPY install/*.sh /install/ 7 | RUN /install/install_bootstrap_deb_packages.sh 8 | RUN echo "deb http://http.debian.net/debian jessie-backports main" | tee -a /etc/apt/sources.list 9 | RUN /install/install_deb_packages.sh 10 | RUN /install/install_pip_packages.sh 11 | RUN /install/install_bazel.sh 12 | 13 | # Set up bazelrc. 14 | COPY install/.bazelrc /root/.bazelrc 15 | ENV BAZELRC /root/.bazelrc 16 | -------------------------------------------------------------------------------- /tensorflow/tools/ci_build/Dockerfile.tensorboard: -------------------------------------------------------------------------------- 1 | FROM ubuntu:14.04 2 | 3 | MAINTAINER Jan Prach 4 | 5 | # Copy and run the install scripts. 6 | COPY install/*.sh /install/ 7 | RUN /install/install_bootstrap_deb_packages.sh 8 | RUN add-apt-repository -y ppa:openjdk-r/ppa && \ 9 | add-apt-repository -y ppa:mc3man/trusty-media && \ 10 | add-apt-repository -y ppa:george-edison55/cmake-3.x 11 | RUN /install/install_deb_packages.sh 12 | RUN /install/install_tensorboard_packages.sh 13 | -------------------------------------------------------------------------------- /tensorflow/tools/ci_build/install/.bazelrc: -------------------------------------------------------------------------------- 1 | # Running bazel inside a `docker build` command causes trouble, cf: 2 | # https://github.com/bazelbuild/bazel/issues/134 3 | # The easiest solution is to set up a bazelrc file forcing --batch. 4 | startup --batch 5 | 6 | # Similarly, we need to workaround sandboxing issues: 7 | # https://github.com/bazelbuild/bazel/issues/418 8 | build --spawn_strategy=standalone --genrule_strategy=standalone 9 | test --spawn_strategy=standalone 10 | 11 | build --color=yes --verbose_failures 12 | test --color=yes --verbose_failures --test_output=errors --test_verbose_timeout_warnings 13 | -------------------------------------------------------------------------------- /tensorflow/tools/dist_test/Dockerfile.local: -------------------------------------------------------------------------------- 1 | FROM jpetazzo/dind 2 | 3 | MAINTAINER Shanqing Cai 4 | 5 | RUN apt-get update 6 | 7 | RUN apt-get install -y \ 8 | build-essential \ 9 | dbus \ 10 | git \ 11 | software-properties-common 12 | 13 | # Install the latest golang 14 | RUN wget https://storage.googleapis.com/golang/go1.4.2.linux-amd64.tar.gz 15 | RUN tar -C /usr/local -xzf go1.4.2.linux-amd64.tar.gz 16 | RUN rm -f go1.4.2.linux-amd64.tar.gz 17 | RUN echo 'PATH=/usr/local/go/bin:${PATH}' >> /root/.bashrc 18 | 19 | ADD . /var/tf-k8s 20 | -------------------------------------------------------------------------------- /tensorflow/tools/dist_test/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tools/dist_test/__init__.py -------------------------------------------------------------------------------- /tensorflow/tools/dist_test/local/Dockerfile: -------------------------------------------------------------------------------- 1 | FROM jpetazzo/dind 2 | 3 | MAINTAINER Shanqing Cai 4 | 5 | RUN apt-get update 6 | 7 | RUN apt-get install -y \ 8 | build-essential \ 9 | git \ 10 | software-properties-common 11 | 12 | # Install the latest golang 13 | RUN wget https://storage.googleapis.com/golang/go1.4.2.linux-amd64.tar.gz 14 | RUN tar -C /usr/local -xzf go1.4.2.linux-amd64.tar.gz 15 | RUN rm -f go1.4.2.linux-amd64.tar.gz 16 | RUN echo 'PATH=/usr/local/go/bin:${PATH}' >> /root/.bashrc 17 | 18 | ADD start_local_k8s_cluster.sh /var/k8s/start_local_k8s_cluster.sh 19 | ADD ../scripts /var/k8s/dist_test/scripts 20 | ADD ../python /var/k8s/dist_test/python 21 | -------------------------------------------------------------------------------- /tensorflow/tools/docker/BUILD: -------------------------------------------------------------------------------- 1 | # Description: 2 | # Various tools and rules related to the TensorFlow docker container. 3 | 4 | package(default_visibility = ["//visibility:private"]) 5 | 6 | licenses(["notice"]) # Apache 2.0 7 | 8 | exports_files(["LICENSE"]) 9 | 10 | py_binary( 11 | name = "simple_console", 12 | srcs = ["simple_console.py"], 13 | srcs_version = "PY2AND3", 14 | deps = ["//tensorflow:tensorflow_py"], 15 | ) 16 | 17 | filegroup( 18 | name = "all_files", 19 | srcs = glob( 20 | ["**/*"], 21 | exclude = [ 22 | "**/METADATA", 23 | "**/OWNERS", 24 | ], 25 | ), 26 | visibility = ["//tensorflow:__subpackages__"], 27 | ) 28 | -------------------------------------------------------------------------------- /tensorflow/tools/docker/LICENSE: -------------------------------------------------------------------------------- 1 | Copyright 2015 The TensorFlow Authors. All rights reserved. 2 | 3 | Licensed under the Apache License, Version 2.0 (the "License"); 4 | you may not use this file except in compliance with the License. 5 | You may obtain a copy of the License at 6 | 7 | http://www.apache.org/licenses/LICENSE-2.0 8 | 9 | Unless required by applicable law or agreed to in writing, software 10 | distributed under the License is distributed on an "AS IS" BASIS, 11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | See the License for the specific language governing permissions and 13 | limitations under the License. 14 | -------------------------------------------------------------------------------- /tensorflow/tools/docker/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zplizzi/tensorflow-fast-rcnn/c8ed43793b09f1d89b27ce9b4f0f8b6c5655426e/tensorflow/tools/docker/__init__.py -------------------------------------------------------------------------------- /tensorflow/tools/docker/notebooks/BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//visibility:private"]) 2 | 3 | licenses(["notice"]) # Apache 2.0 4 | 5 | exports_files(["LICENSE"]) 6 | 7 | filegroup( 8 | name = "all_files", 9 | srcs = glob( 10 | ["**/*"], 11 | exclude = [ 12 | "**/METADATA", 13 | "**/OWNERS", 14 | ], 15 | ), 16 | visibility = ["//tensorflow:__subpackages__"], 17 | ) 18 | -------------------------------------------------------------------------------- /tensorflow/tools/docker/notebooks/LICENSE: -------------------------------------------------------------------------------- 1 | Copyright 2015 The TensorFlow Authors. All rights reserved. 2 | 3 | Licensed under the Apache License, Version 2.0 (the "License"); 4 | you may not use this file except in compliance with the License. 5 | You may obtain a copy of the License at 6 | 7 | http://www.apache.org/licenses/LICENSE-2.0 8 | 9 | Unless required by applicable law or agreed to in writing, software 10 | distributed under the License is distributed on an "AS IS" BASIS, 11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | See the License for the specific language governing permissions and 13 | limitations under the License. 14 | -------------------------------------------------------------------------------- /tensorflow/tools/pip_package/MANIFEST.in: -------------------------------------------------------------------------------- 1 | include README 2 | recursive-include * *.py 3 | recursive-include * *.so 4 | recursive-include * *.csv 5 | -------------------------------------------------------------------------------- /tensorflow/tools/pip_package/README: -------------------------------------------------------------------------------- 1 | TensorFlow 2 | -------------------------------------------------------------------------------- /tensorflow/tools/proto_text/placeholder.txt: -------------------------------------------------------------------------------- 1 | Contents are unused. See gen_proto_functions.cc for details. 2 | -------------------------------------------------------------------------------- /tensorflow/tools/swig/.gitignore: -------------------------------------------------------------------------------- 1 | swig_path 2 | -------------------------------------------------------------------------------- /third_party/avro/BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//visibility:public"]) 2 | 3 | licenses(["notice"]) # Apache 2.0 4 | 5 | -------------------------------------------------------------------------------- /third_party/boringssl/BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//visibility:public"]) 2 | 3 | licenses(["restricted"]) # OpenSSL license, partly BSD-like 4 | 5 | # See https://boringssl.googlesource.com/boringssl/+/master/INCORPORATING.md 6 | # on how to re-generate err_data.c. 7 | 8 | filegroup( 9 | name = "err_data_c", 10 | srcs = [ 11 | "err_data.c", 12 | ], 13 | ) 14 | -------------------------------------------------------------------------------- /third_party/eigen3/BUILD: -------------------------------------------------------------------------------- 1 | licenses(["restricted"]) # MPL2, portions GPL v3, LGPL v3, BSD-like 2 | 3 | cc_library( 4 | name = "eigen3", 5 | hdrs = glob([ 6 | "Eigen/Core", 7 | "Eigen/LU", 8 | "Eigen/Cholesky", 9 | "Eigen/Eigenvalues", 10 | "Eigen/QR", 11 | "unsupported/Eigen/CXX11/Tensor", 12 | "unsupported/Eigen/CXX11/FixedPoint", 13 | "unsupported/Eigen/CXX11/src/FixedPoint/*.h", 14 | ]), 15 | includes = ["."], 16 | visibility = ["//visibility:public"], 17 | deps = [ 18 | "@eigen_archive//:eigen", 19 | ], 20 | ) 21 | -------------------------------------------------------------------------------- /third_party/eigen3/Eigen/Cholesky: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/Eigen/Cholesky" 2 | -------------------------------------------------------------------------------- /third_party/eigen3/Eigen/Core: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/Eigen/Core" 2 | -------------------------------------------------------------------------------- /third_party/eigen3/Eigen/Eigenvalues: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/Eigen/Eigenvalues" 2 | -------------------------------------------------------------------------------- /third_party/eigen3/Eigen/LU: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/Eigen/LU" 2 | -------------------------------------------------------------------------------- /third_party/eigen3/Eigen/QR: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/Eigen/QR" 2 | -------------------------------------------------------------------------------- /third_party/eigen3/unsupported/Eigen/CXX11/Tensor: -------------------------------------------------------------------------------- 1 | #include "eigen-eigen-f3a13643ac1f/unsupported/Eigen/CXX11/Tensor" 2 | -------------------------------------------------------------------------------- /third_party/gpus/cuda/build_defs.bzl: -------------------------------------------------------------------------------- 1 | # Macros for building CUDA code. 2 | 3 | def if_cuda(if_true, if_false = []): 4 | """Shorthand for select()'ing on whether we're building with CUDA. 5 | 6 | Returns a select statement which evaluates to if_true if we're building 7 | with CUDA enabled. Otherwise, the select statement evaluates to if_false. 8 | 9 | """ 10 | return select({ 11 | "//third_party/gpus/cuda:using_nvcc": if_true, 12 | "//third_party/gpus/cuda:using_gcudacc": if_true, 13 | "//conditions:default": if_false 14 | }) 15 | -------------------------------------------------------------------------------- /third_party/py/numpy/BUILD: -------------------------------------------------------------------------------- 1 | licenses(["restricted"]) 2 | 3 | package(default_visibility = ["//visibility:public"]) 4 | 5 | cc_library( 6 | name = "headers", 7 | hdrs = glob([ 8 | "numpy_include/**/*.h", 9 | ]), 10 | data = ["//util/python:python_checked"], 11 | includes = [ 12 | "numpy_include", 13 | ], 14 | ) 15 | -------------------------------------------------------------------------------- /tools/bazel.rc.template: -------------------------------------------------------------------------------- 1 | build:cuda --crosstool_top=//third_party/gpus/crosstool 2 | build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true 3 | 4 | build --force_python=py$PYTHON_MAJOR_VERSION 5 | build --python$PYTHON_MAJOR_VERSION_path=$PYTHON_BINARY 6 | build --define=use_fast_cpp_protos=true 7 | build --define=allow_oversize_protos=true 8 | 9 | build --spawn_strategy=standalone 10 | test --spawn_strategy=standalone 11 | run --spawn_strategy=standalone 12 | 13 | build --genrule_strategy=standalone 14 | test --genrule_strategy=standalone 15 | run --genrule_strategy=standalone 16 | -------------------------------------------------------------------------------- /util/python/BUILD: -------------------------------------------------------------------------------- 1 | licenses(["restricted"]) 2 | 3 | package(default_visibility = ["//visibility:public"]) 4 | 5 | cc_library( 6 | name = "python_headers", 7 | hdrs = glob([ 8 | "python_include/**/*.h", 9 | ]), 10 | data = [":python_checked"], 11 | includes = ["python_include"], 12 | ) 13 | 14 | genrule( 15 | name = "python_check", 16 | srcs = [ 17 | "python_config.sh", 18 | ], 19 | outs = [ 20 | "python_checked", 21 | ], 22 | cmd = "OUTPUTDIR=\"$(@D)/\"; $(location :python_config.sh) --check && touch $$OUTPUTDIR/python_checked", 23 | local = 1, 24 | ) 25 | -------------------------------------------------------------------------------- /zlib.BUILD: -------------------------------------------------------------------------------- 1 | package(default_visibility = ["//visibility:public"]) 2 | 3 | licenses(["notice"]) # BSD/MIT-like license (for zlib) 4 | 5 | prefix_dir = "zlib-1.2.8" 6 | 7 | cc_library( 8 | name = "zlib", 9 | srcs = glob([prefix_dir + "/*.c"]), 10 | hdrs = glob([prefix_dir + "/*.h"]), 11 | includes = [prefix_dir], 12 | ) 13 | --------------------------------------------------------------------------------