├── .gitignore ├── .gitmodules ├── README.md ├── how_to_guides ├── autoschedule │ ├── conv_gpu.py │ ├── nn_nvgpu.py │ └── nn_x86.py ├── autotvm │ ├── cnn_gpu.py │ ├── cnn_x86.py │ ├── conv_gpu.py │ ├── graph_tuner.log │ ├── resnet-18.log │ └── resnet-18_graph_opt.log ├── compile_dl_models │ ├── compile_onnx.py │ └── pytorch.py ├── extend_tvm │ └── add_pass │ │ ├── README.md │ │ └── add_pass.py └── work_with_tensor_expression_and_schedules │ └── schedule_intrinsic │ ├── README.md │ └── src │ ├── bind.py │ ├── cache_read.py │ ├── cache_write.py │ ├── compute_at.py │ ├── compute_inline.py │ ├── compute_root.py │ ├── create_group.py │ ├── fuse.py │ ├── normalize.py │ ├── parallel.py │ ├── pragma.py │ ├── prefetch.py │ ├── reorder.py │ ├── rfactor.py │ ├── set_scope.py │ ├── set_store_predicate.py │ ├── split.py │ ├── storage_align.py │ ├── tensorize.py │ ├── tile.py │ ├── unroll.py │ └── vectorize.py ├── hpc ├── README.md ├── cuda │ └── README.md └── gemm │ ├── MMult0.h │ ├── MMult1.h │ ├── MMult2.h │ ├── MMult_1x4_3.h │ ├── MMult_1x4_4.h │ ├── MMult_1x4_5.h │ ├── MMult_1x4_6.h │ ├── MMult_1x4_7.h │ ├── MMult_1x4_8.h │ ├── MMult_1x4_9.h │ ├── MMult_1x4x6.h │ ├── MMult_4x4_10.h │ ├── MMult_4x4_11.h │ ├── MMult_4x4_12.h │ ├── MMult_4x4_13.h │ ├── MMult_4x4_14.h │ ├── MMult_4x4_3.h │ ├── MMult_4x4_4.h │ ├── MMult_4x4_5.h │ ├── MMult_4x4_6.h │ ├── MMult_4x4_7.h │ ├── MMult_4x4_8.h │ ├── Makefile │ ├── README.md │ ├── dclock.h │ ├── matrix_multiply_origin.h │ ├── now.txt │ ├── plot_gflops.py │ └── test_matrix_multiply.cpp ├── image ├── frontend │ ├── after_pass_ast.jpg │ ├── ast.jpg │ ├── class_derive.jpg │ ├── convert_map.jpg │ ├── nn_relay.jpg │ ├── node.jpg │ ├── node_derive.jpg │ ├── node_inputs.jpg │ └── node_name.jpg ├── log │ ├── task.jpg │ ├── task_table.jpg │ └── tasks.jpg ├── op_fusion │ ├── 1.jpg │ └── 2.jpg └── read_code │ ├── architecture_diagram.jpg │ ├── build.jpg │ └── pipeline.jpg ├── inference_framework └── note │ ├── 01.md │ ├── 02.md │ ├── 03.md │ ├── 04.md │ ├── 05.md │ ├── 06.md │ ├── 07.md │ ├── 08.md │ ├── 09.md │ ├── 10.md │ ├── 11.md │ ├── README.md │ └── image │ ├── 01_image1.png │ ├── 01_image2.jpg │ ├── 01_image3.jpg │ ├── 02_image1.jpg │ ├── 02_image2.jpg │ ├── 02_image3.jpg │ ├── 02_image4.jpg │ ├── 11_image1.jpg │ ├── 11_image2.jpg │ └── 11_image3.jpg ├── note ├── IRModule.md ├── build.md ├── frontend │ ├── converted_node.md │ ├── import_onnx.md │ ├── import_pytorch.md │ ├── op_fusion.md │ ├── register_op.md │ └── relay.md ├── ir.md ├── log.md ├── matmul.log ├── object.md ├── pass.md ├── python2c++.md ├── pytorchjit.md ├── relax.md ├── transfer_learning.md ├── tuning.md ├── visitexpr.md └── visitor.md ├── onnx ├── inference │ ├── README.md │ ├── fasterRCNN_inference.ipynb │ ├── resnet50_inference.ipynb │ ├── simple_inference.ipynb │ ├── super_resolution_inference.py │ └── yoloV3_inference.ipynb └── quant │ └── image_classification │ ├── cpu │ ├── README.md │ ├── mobilenetv2-7.onnx │ ├── resnet50_data_reader.py │ ├── run.py │ ├── run_qdq_debug.py │ └── test_images │ │ ├── daisy.jpg │ │ ├── rose.jpg │ │ └── tulip.jpg │ └── trt │ └── resnet50 │ └── e2e_tensorrt_resnet_example.py ├── paper ├── README.md ├── distributed_computing.md ├── gnn.md ├── graph.md ├── infra.md ├── ir.md ├── other.md ├── polyhedral.md ├── resource.md ├── todo.md └── tuning.md └── user_tutorial ├── Blitz_Course_to_TensorIR └── TensorIR.py ├── Compiling_Deep_Learning_Models └── nn.py ├── Compiling_and_Optimizing_a_Model_with_TVMC ├── postprocess.py ├── preprocess.py └── script.sh ├── Compiling_and_Optimizing_a_Model_with_the_Python_Interface_autotvm └── autotvm.py ├── Getting_Starting_using_TVMC_Python ├── records.log └── tvmcPythonIntro.py ├── Introduction_to_TOPI └── topi.py ├── Optimizing_Operators_with_Auto-scheduling └── autoSchedule.py ├── Optimizing_Operators_with_Schedule_Templates_and_AutoTVM └── autotvm.py └── Working_with_Operators_Using_Tensor_Expression ├── MatrixMultiplication.py └── schedule.py /.gitignore: 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