├── .gitattributes ├── .gitignore ├── Makefile ├── README.md ├── analyze_model.py ├── analyze_training.py ├── clr_callback.py ├── cm.indices.pickle ├── compare_weights.py ├── create_cm.py ├── create_jobs.py ├── create_random_cm.py ├── datasets ├── README.md ├── caltech_101.py ├── caltech_256.py ├── cats_dogs.py ├── cifar-10-mean.npy ├── cifar-100-mean.npy ├── cifar10.py ├── cifar100-hierarchy.json ├── cifar100.py ├── cifar100_keras.py ├── cifar10_keras.py ├── gtsrb-hierarchy.json ├── gtsrb-mean.npy ├── gtsrb.py ├── hasy-hierarchy.json ├── hasy-mean.npy ├── hasy.py ├── labels │ ├── cifar-10.json │ ├── cifar-100-labels.json │ ├── gtsrb.json │ ├── hasy.json │ └── mnist.json ├── mnist.py ├── permutations │ ├── cifar-10.json │ ├── cifar-100.json │ └── gtsrb.json ├── stl10.py ├── svhn-mean.npy ├── svhn.py ├── tiny_imagenet.py └── utils.py ├── ensemble ├── README.md ├── catdog-old.yaml ├── catdog.json ├── catdog.yaml ├── catdog_opt.json ├── catdog_opt.yaml ├── catdog_opt_long.json ├── catdog_opt_long.yaml ├── catdog_opt_train_es.json ├── catdog_opt_train_es.yaml ├── cifar10.yaml ├── cifar100-bs128.json ├── cifar100-bs128.yaml ├── cifar100-bs16.json ├── cifar100-bs16.yaml ├── cifar100-bs32.json ├── cifar100-bs32.yaml ├── cifar100-bs8.json ├── cifar100-bs8.yaml ├── cifar100-eos.json ├── cifar100-eos.yaml ├── cifar100-linear.json ├── cifar100-linear.yaml ├── cifar100-relu.json ├── cifar100-relu.yaml ├── cifar100-softsign.json ├── cifar100-softsign.yaml ├── cifar100.yaml ├── cifar100_colortransformation.json ├── cifar100_colortransformation.yaml ├── cifar100_colortransformation_new.yaml ├── cifar100_large11.json ├── cifar100_large11.yaml ├── cifar100_large11s.json ├── cifar100_large11s.yaml ├── cifar100_large13.json ├── cifar100_large13.yaml ├── cifar100_large9.json ├── cifar100_large9.yaml ├── cifar100_large9s.json ├── cifar100_large9s.yaml ├── cifar100_less16more32.json ├── cifar100_less16more32.yaml ├── cifar100_lessfiltersmorelayers.json ├── cifar100_lessfiltersmorelayers.yaml ├── cifar100_lessintermediate.json ├── cifar100_lessintermediate.yaml ├── cifar100_lesslayermorefilter.json ├── cifar100_lesslayermorefilter.yaml ├── cifar100_maxmeanpool.yaml ├── cifar100_more_middle-nonchk.json ├── cifar100_more_middle-nonchk.yaml ├── cifar100_more_middle.json ├── cifar100_more_middle.yaml ├── cifar100_new-train.json ├── cifar100_new.json ├── cifar100_new.yaml ├── cifar100_nin.yaml ├── cifar100_no_bias.json ├── cifar100_no_bias.yaml ├── cifar100_no_bn.yaml ├── cifar100_no_bn_new.json ├── cifar100_no_bn_new.yaml ├── cifar100_no_bn_p.json ├── cifar100_no_bn_p.yaml ├── cifar100_opt.json ├── cifar100_opt.yaml ├── cifar100_opt_es_test_set.yaml ├── cifar100_opt_long.yaml ├── cifar100_opt_reg001.yaml ├── cifar100_opt_reg01.yaml ├── cifar100_opt_train_es.yaml ├── cifar100_pool_kernel.yaml ├── cifar100_pool_kernel_new.json ├── cifar100_pool_kernel_new.yaml ├── cifar100_prelu.json ├── cifar100_prelu.yaml ├── cifar100_relu_neg.yaml ├── cifar100_s_shape.yaml ├── cifar100_sigmoid.json ├── cifar100_sigmoid.yaml ├── cifar100_sigmoid_neg.yaml ├── cifar100_smooth.json ├── cifar100_smooth.yaml ├── cifar100_softmax.json ├── cifar100_softmax.yaml ├── cifar100_softplus.json ├── cifar100_softplus.yaml ├── cifar100_tanh.json ├── cifar100_tanh.yaml ├── cifar100_vrelu.json ├── cifar100_vrelu.yaml ├── cifar100_wide_resnet.json ├── cifar100_wide_resnet.yaml ├── cifar10_new.yaml ├── cifar10_opt.json ├── cifar10_opt.yaml ├── cifar10_opt_long.yaml ├── cifar10_opt_train_es.yaml ├── gtsrb.yaml ├── gtsrb_linear.yaml ├── gtsrb_new.json ├── gtsrb_new.yaml ├── gtsrb_opt.json ├── gtsrb_opt.yaml ├── gtsrb_opt_long.yaml ├── gtsrb_opt_train_es.yaml ├── gtsrb_prelu.yaml ├── gtsrb_relu.yaml ├── gtsrb_sigmoid.yaml ├── gtsrb_softmax.yaml ├── gtsrb_softplus.yaml ├── gtsrb_softsign.yaml ├── gtsrb_tanh.yaml ├── gtsrb_vlrelu.yaml ├── hasy.json ├── hasy.yaml ├── hasy_linear.json ├── hasy_linear.yaml ├── hasy_new.json ├── hasy_new.yaml ├── hasy_opt.json ├── hasy_opt.yaml ├── hasy_opt_long.yaml ├── hasy_prelu.json ├── hasy_prelu.yaml ├── hasy_relu.json ├── hasy_relu.yaml ├── hasy_sigmoid.json ├── hasy_sigmoid.yaml ├── hasy_softmax.json ├── hasy_softmax.yaml ├── hasy_softplus.yaml ├── hasy_softsign.json ├── hasy_softsign.yaml ├── hasy_tanh.json ├── hasy_tanh.yaml ├── hasy_vlrelu.json ├── hasy_vlrelu.yaml ├── mnist.yaml ├── mnist_linear.json ├── mnist_linear.yaml ├── mnist_new.yaml ├── mnist_no_aug.yaml ├── mnist_opt.json ├── mnist_opt.yaml ├── mnist_opt_long.yaml ├── mnist_opt_train_es.yaml ├── mnist_prelu.json ├── mnist_prelu.yaml ├── mnist_relu.json ├── mnist_relu.yaml ├── mnist_sigmoid.json ├── mnist_sigmoid.yaml ├── mnist_softmax.json ├── mnist_softmax.yaml ├── mnist_softplus.json ├── mnist_softplus.yaml ├── mnist_softsign.json ├── mnist_softsign.yaml ├── mnist_tanh.json ├── mnist_tanh.yaml ├── stl10.yaml ├── stl10_linear.json ├── stl10_linear.yaml ├── stl10_new.yaml ├── stl10_opt.json ├── stl10_opt.yaml ├── stl10_opt_long.yaml ├── stl10_opt_train_es.yaml ├── stl10_prelu.json ├── stl10_prelu.yaml ├── stl10_relu.yaml ├── stl10_sigmoid.yaml ├── stl10_softmax.yaml ├── stl10_softplus.yaml ├── stl10_softsign.yaml ├── stl10_tanh.yaml ├── stl10_vlrelu.json ├── stl10_vlrelu.yaml ├── svhn.yaml ├── svhn_opt.json └── svhn_opt.yaml ├── eval_ensemble.py ├── experiments ├── caltech101_baseline-folder.yaml ├── caltech101_baseline.yaml ├── caltech101_baselineb.yaml ├── caltech101_clr.yaml ├── caltech101_opt.yaml ├── caltech256_baseline.yaml ├── caltech256_opt.yaml ├── cat_dog_baseline.yaml ├── cat_dog_opt.yaml ├── cat_dog_opt_long.yaml ├── cat_dog_opt_train_es.yaml ├── cifar100_b.yaml ├── cifar100_baseline-c1b.yaml ├── cifar100_baseline.yaml ├── cifar100_baseline_chk.yaml ├── cifar100_baseline_chk_low_lr.yaml ├── cifar100_baseline_pool_kernel.yaml ├── cifar100_big.yaml ├── cifar100_bigfilter.yaml ├── cifar100_bs128.yaml ├── cifar100_bs16.yaml ├── cifar100_bs32.yaml ├── cifar100_bs8.yaml ├── cifar100_clr.yaml ├── cifar100_colortransform.yaml ├── cifar100_colortransform_vlrelu.yaml ├── cifar100_composedfilters.yaml ├── cifar100_dense.yaml ├── cifar100_erratic_chk.yaml ├── cifar100_filtermix.yaml ├── cifar100_init_low_lr.yaml ├── cifar100_input_residual.yaml ├── cifar100_large_11.yaml ├── cifar100_large_11s.yaml ├── cifar100_large_13.yaml ├── cifar100_large_9.yaml ├── cifar100_large_9s.yaml ├── cifar100_less16more32.yaml ├── cifar100_less_intermediate.yaml ├── cifar100_lessfiltermorelayer.yaml ├── cifar100_lesslayermorefilter.yaml ├── cifar100_linear.yaml ├── cifar100_long_residual.yaml ├── cifar100_maxmeanpool.yaml ├── cifar100_model4.yaml ├── cifar100_more_middle.yaml ├── cifar100_multi.yaml ├── cifar100_nin.yaml ├── cifar100_no_bias.yaml ├── cifar100_no_bn.yaml ├── cifar100_no_bn_p.yaml ├── cifar100_opt.yaml ├── cifar100_opt_es_test_set.yaml ├── cifar100_opt_long.yaml ├── cifar100_opt_reg001.yaml ├── cifar100_opt_reg01.yaml ├── cifar100_opt_train_es.yaml ├── cifar100_prelu.yaml ├── cifar100_pure.yaml ├── cifar100_relu.yaml ├── cifar100_relu_neg.yaml ├── cifar100_resnetpa.yaml ├── cifar100_root-g1.yaml ├── cifar100_root-g10.yaml ├── cifar100_root-g11.yaml ├── cifar100_root-g12.yaml ├── cifar100_root-g13.yaml ├── cifar100_root-g14.yaml ├── cifar100_root-g2.yaml ├── cifar100_root-g3.yaml ├── cifar100_root-g4.yaml ├── cifar100_root-g5.yaml ├── cifar100_root-g6.yaml ├── cifar100_root-g7.yaml ├── cifar100_root-g8.yaml ├── cifar100_root-g9.yaml ├── cifar100_root.yaml ├── cifar100_s_shape.yaml ├── cifar100_seq2.yaml ├── cifar100_seq3-feat.yaml ├── cifar100_seq3-less-aug.yaml ├── cifar100_seq3-no-pool.yaml ├── cifar100_seq3-sample.yaml ├── cifar100_seq3.yaml ├── cifar100_seq3norm.yaml ├── cifar100_seq_keras-aug.yaml ├── cifar100_seq_keras.yaml ├── cifar100_sgd_chk.yaml ├── cifar100_sigmoid.yaml ├── cifar100_sigmoid_flat.yaml ├── cifar100_sigmoid_neg.yaml ├── cifar100_small_9.yaml ├── cifar100_smooth.yaml ├── cifar100_softmax.yaml ├── cifar100_softplus.yaml ├── cifar100_softsign.yaml ├── cifar100_squeeze.yaml ├── cifar100_tanh.yaml ├── cifar100_thin_resnet.yaml ├── cifar100_twonon.yaml ├── cifar100_vlrelu.yaml ├── cifar100_wide.yaml ├── cifar10_baseline-init.yaml ├── cifar10_baseline.yaml ├── cifar10_baseline_ebn.yaml ├── cifar10_baseline_jeon.yaml ├── cifar10_dense.yaml ├── cifar10_dense_aug.yaml ├── cifar10_fractal.yaml ├── cifar10_opt.yaml ├── cifar10_opt_es_test_set.yaml ├── cifar10_opt_long.yaml ├── cifar10_opt_train_es.yaml ├── cifar10_rflearn.yaml ├── cifar10_seq2.yaml ├── cifar10_seq3-no-pool.yaml ├── cifar10_seq3.yaml ├── cifar10_seq_keras-aug.yaml ├── cifar10_seq_keras.yaml ├── e1.yaml ├── e1 │ └── validation-curve-accuracy-test.csv ├── e2.yaml ├── e2 │ └── validation-curve-accuracy-test.csv ├── e3.yaml ├── e4.yaml ├── e5-cifar10.yaml ├── e5.yaml ├── fast.yaml ├── gtsrb-speed-less-aug.yaml ├── gtsrb-speed.yaml ├── gtsrb-warnings.yaml ├── gtsrb_baseline-init.yaml ├── gtsrb_baseline.yaml ├── gtsrb_dense_keras.yaml ├── gtsrb_linear.yaml ├── gtsrb_opt.yaml ├── gtsrb_opt_linear.yaml ├── gtsrb_opt_long.yaml ├── gtsrb_opt_prelu.yaml ├── gtsrb_opt_reg001.yaml ├── gtsrb_opt_reg01.yaml ├── gtsrb_opt_relu.yaml ├── gtsrb_opt_sigmoid.yaml ├── gtsrb_opt_softmax.yaml ├── gtsrb_opt_softplus.yaml ├── gtsrb_opt_tanh.yaml ├── gtsrb_opt_train_es.yaml ├── gtsrb_opt_vlrelu.yaml ├── gtsrb_prelu.yaml ├── gtsrb_relu.yaml ├── gtsrb_seq2_keras.yaml ├── gtsrb_seq3-no-pool.yaml ├── gtsrb_seq3.yaml ├── gtsrb_seq_keras-aug.yaml ├── gtsrb_seq_keras.yaml ├── gtsrb_seq_keras_root.yaml ├── gtsrb_sigmoid.yaml ├── gtsrb_softmax.yaml ├── gtsrb_softplus.yaml ├── gtsrb_softsign.yaml ├── gtsrb_tanh.yaml ├── gtsrb_vlrelu.yaml ├── hasy_baseline.yaml ├── hasy_dense.yaml ├── hasy_linear.yaml ├── hasy_opt.yaml ├── hasy_opt_linear.yaml ├── hasy_opt_long.yaml ├── hasy_opt_prelu.yaml ├── hasy_opt_relu.yaml ├── hasy_opt_sigmoid.yaml ├── hasy_opt_softmax.yaml ├── hasy_opt_softsign.yaml ├── hasy_opt_tanh.yaml ├── hasy_opt_vlrelu.yaml ├── hasy_prelu.yaml ├── hasy_relu.yaml ├── hasy_seq.yaml ├── hasy_seq2.yaml ├── hasy_seq3-no-pool.yaml ├── hasy_seq3.yaml ├── hasy_seq_fast.yaml ├── hasy_sigmoid.yaml ├── hasy_softmax.yaml ├── hasy_softplus.yaml ├── hasy_softsign.yaml ├── hasy_tanh.yaml ├── hasy_vlrelu.yaml ├── mnist_baseline.yaml ├── mnist_linear.yaml ├── mnist_opt.yaml ├── mnist_opt_es_test_set.yaml ├── mnist_opt_long.yaml ├── mnist_opt_train_es.yaml ├── mnist_prelu.yaml ├── mnist_relu.yaml ├── mnist_sigmoid.yaml ├── mnist_softmax.yaml ├── mnist_softplus.yaml ├── mnist_softsign.yaml ├── mnist_tanh.yaml ├── stl10_baseline.yaml ├── stl10_linear.yaml ├── stl10_opt.yaml ├── stl10_opt_linear.yaml ├── stl10_opt_long.yaml ├── stl10_opt_prelu.yaml ├── stl10_opt_relu.yaml ├── stl10_opt_sigmoid.yaml ├── stl10_opt_softmax.yaml ├── stl10_opt_softplus.yaml ├── stl10_opt_softsign.yaml ├── stl10_opt_tanh.yaml ├── stl10_opt_train_es.yaml ├── stl10_prelu.yaml ├── stl10_relu.yaml ├── stl10_sigmoid.yaml ├── stl10_softmax.yaml ├── stl10_softplus.yaml ├── stl10_softsign.yaml ├── stl10_tanh.yaml ├── stl10_vlrelu.yaml ├── svhn_baseline.yaml ├── svhn_opt.yaml ├── svhn_opt_long.yaml ├── svhn_seq2.yaml ├── svhn_seq3-no-pool.yaml ├── svhn_seq3.yaml ├── svhn_seq_keras-aug.yaml ├── svhn_seq_keras.yaml ├── tf-cifar10.yaml └── tinynet_baseline.yaml ├── inference_timing.py ├── jobs.json ├── misc ├── adverserial_examples.py ├── clustering │ ├── cifar100_seq3 │ │ ├── cifar100-my-clust.txt │ │ └── cifar100-spectral.txt │ └── hasy_seq3 │ │ ├── hasy-my-clust.txt │ │ ├── hasy-spectral-clust.txt │ │ └── hasy_seq3_history.csv ├── fix_keras_optimizer.py ├── get_convs_by_parameters.py └── image.py ├── models ├── baseline.py ├── baseline_b.py ├── baseline_bigger_filter.py ├── baseline_colortransformation.py ├── baseline_colortransformation_vlrelu.py ├── baseline_ebn.py ├── baseline_erratic.py ├── baseline_filtermix.py ├── baseline_jeon.py ├── baseline_less16more32.py ├── baseline_less_intermediate.py ├── baseline_lessfiltersmorelayers.py ├── baseline_long_residual.py ├── baseline_maxmeanpool.py ├── baseline_more_middle.py ├── baseline_multi.py ├── baseline_no_bias.py ├── baseline_no_bn.py ├── baseline_no_bn_p.py ├── baseline_pool_kernel.py ├── baseline_prelu.py ├── baseline_relu.py ├── baseline_relu_neg.py ├── baseline_residuals.py ├── baseline_s_shape.py ├── baseline_sigmoid.py ├── baseline_sigmoid_flat.py ├── baseline_sigmoid_neg.py ├── baseline_softmax.py ├── baseline_softplus.py ├── baseline_tanh.py ├── baseline_twonon.py ├── baseline_vlrelu.py ├── composed_filters.py ├── densenet.py ├── fractalnet.py ├── i-c3-f.py ├── inception-v4.py ├── large11.py ├── large11s.py ├── large13.py ├── large9.py ├── large9s.py ├── lesslayermorefilter.py ├── linear.py ├── mlp.py ├── model4.py ├── nin.py ├── optimized.py ├── optimized_linear.py ├── optimized_prelu.py ├── optimized_relu.py ├── optimized_sigmoid.py ├── optimized_softmax.py ├── optimized_softplus.py ├── optimized_tanh.py ├── optimized_vlrelu.py ├── pure_cnn.py ├── resnetpa.py ├── rflearn.py ├── schmidhuber.py ├── seq3-no-pooling.py ├── seq3.py ├── seq3norm.py ├── sequential_bn_keras.py ├── sequential_keras.py ├── sequential_keras_tiny.py ├── sequential_updated.py ├── softsign.py ├── squeezenet.py ├── tf-cifar.py ├── thin_resnet.py └── wide_resnet.py ├── msthesis_utils.py ├── optimizers ├── adam_keras.py ├── adamdef.py ├── nesterov.py └── sgd.py ├── other_models ├── imagenet-1.jpg ├── vgg16.py └── vgg16.yaml ├── requirements.txt ├── run_training.py ├── schedule.py ├── sgdr.py ├── spektral_clust.py ├── train ├── train.py ├── train_keras.py ├── train_keras_batch_doubling.py ├── train_keras_decay.py ├── train_keras_exact.py ├── train_keras_folder.py └── train_keras_train_es.py └── visualize.py /.gitattributes: -------------------------------------------------------------------------------- 1 | *.h5 filter=lfs diff=lfs merge=lfs -text 2 | -------------------------------------------------------------------------------- /Makefile: -------------------------------------------------------------------------------- 1 | bundle: 2 | git bundle create msthesis-experiments.bundle --all -------------------------------------------------------------------------------- /cm.indices.pickle: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/cm.indices.pickle -------------------------------------------------------------------------------- /create_jobs.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | """Create a jobs.json file for schedule.py.""" 4 | 5 | import glob 6 | import natsort 7 | import json 8 | # Make it work for Python 2+3 and with Unicode 9 | import io 10 | try: 11 | to_unicode = unicode 12 | except NameError: 13 | to_unicode = str 14 | 15 | 16 | def write_json(fname, data): 17 | # Write JSON file 18 | with io.open(fname, 'w', encoding='utf8') as outfile: 19 | for i in range(len(data)): 20 | if 'output' in data[i]: 21 | data[i]['output'] = data[i]['output'].decode('utf8') 22 | str_ = json.dumps(data, 23 | indent=4, sort_keys=True, 24 | separators=(',', ': '), 25 | ensure_ascii=False) 26 | outfile.write(to_unicode(str_)) 27 | 28 | experiment_files = glob.glob("experiments/*.yaml") 29 | experiment_files = natsort.natsorted(experiment_files) 30 | 31 | data = [] 32 | for f in experiment_files: 33 | data.append({'cmd': './run_training.py -f {}'.format(f)}) 34 | 35 | write_json("jobs-auto.json", data) 36 | -------------------------------------------------------------------------------- /datasets/README.md: -------------------------------------------------------------------------------- 1 | Every dataset contains 2 | 3 | * meta: A dict which contains... 4 | * n_classes: the number of classes, 5 | * image_width, image_height, image_depth: the dimensions of the images 6 | * distorted_inputs(data_dir, batch_size): A function which reads the data 7 | and returns a generator. The generator returns data+labels for training. 8 | * -------------------------------------------------------------------------------- /datasets/cifar-10-mean.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/datasets/cifar-10-mean.npy -------------------------------------------------------------------------------- /datasets/cifar-100-mean.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/datasets/cifar-100-mean.npy -------------------------------------------------------------------------------- /datasets/cifar100-hierarchy.json: -------------------------------------------------------------------------------- 1 | [ 53, 0, 2 | 57, 3 | 83, 4 | 82, 5 | [62, 92, 70], 6 | 1, 7 | 54, 8 | [ 2, 11, 35, 98, 46], 9 | 21, 10 | 75, 11 | 36, 12 | 51, 13 | 43, 14 | 88, 15 | 34, 16 | [ 19, 15 ], 17 | [ 31, 3], 18 | 97, 19 | 66, 20 | 38, 21 | 64, 22 | 42, 23 | 80, 24 | 65, 25 | 63, 26 | [ 50, 74, 4], 27 | [ 55, 72 ], 28 | 32, 29 | 77, 30 | 29, 31 | 14, 32 | 6, 33 | 26, 34 | 93, 35 | 45, 36 | [ 44, 27 ], 37 | 18, 38 | 78, 39 | 7, 40 | 79, 41 | 24, 42 | 67, 43 | 91, 44 | 73, 45 | 99, 46 | [ 30, 95 ], 47 | 10, 48 | [ 22, 61 ], 49 | 40, 50 | 28, 51 | 16, 52 | 86, 53 | 84, 54 | 9, 55 | 87, 56 | 69, 57 | 94, 58 | [ 25, 5 ], 59 | 41, 60 | 39, 61 | 20, 62 | 8, 63 | 48, 64 | 89, 65 | 85, 66 | 58, 67 | 90, 68 | [ 13, 81], 69 | 12, 70 | [ 37, 17], 71 | 33, 72 | 76, 73 | 49, 74 | 56, 75 | 96, 76 | 59, 77 | [ 47, 52], 78 | [ 23, 71, 60], 79 | 68 80 | ] -------------------------------------------------------------------------------- /datasets/gtsrb-hierarchy.json: -------------------------------------------------------------------------------- 1 | [[0, 1, 2, 3, 4, 5, 7, 8], 2 | [19, 21], 3 | [11, 25, 26, 27, 18], 4 | 6, 9, 10, 12, 13, 14, 15, 16, 17, 20, 22, 23, 24, 28, 29, 30, 31, 5 | 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42] -------------------------------------------------------------------------------- /datasets/gtsrb-mean.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/datasets/gtsrb-mean.npy -------------------------------------------------------------------------------- /datasets/hasy-mean.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/datasets/hasy-mean.npy -------------------------------------------------------------------------------- /datasets/labels/cifar-10.json: -------------------------------------------------------------------------------- 1 | ["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"] -------------------------------------------------------------------------------- /datasets/labels/gtsrb.json: -------------------------------------------------------------------------------- 1 | [ "20", "30", 2 | "50", 3 | "60", 4 | "70", 5 | "80", 6 | "restriction ends 80", 7 | "100", 8 | "120", 9 | "no overtaking", 10 | "no overtaking (tr)", 11 | "priority at next int", 12 | "priority road", 13 | "give way", 14 | "stop", 15 | "no traffic both ways", 16 | "no trucks", 17 | "no entry", 18 | "danger", 19 | "bend left", 20 | "bend right", 21 | "bend", 22 | "uneven road", 23 | "slippery road", 24 | "road narrows", 25 | "construction", 26 | "traffic signal", 27 | "pedestrian crossing", 28 | "school crossing", 29 | "cycles crossing", 30 | "snow", 31 | "animals", 32 | "restriction ends", 33 | "go right", 34 | "go left", 35 | "go straight", 36 | "go right or straight", 37 | "go left or straight", 38 | "keep right", 39 | "keep left", 40 | "roundabout", 41 | "no overt. ends", 42 | "no overt trucks ends" 43 | ] -------------------------------------------------------------------------------- /datasets/labels/mnist.json: -------------------------------------------------------------------------------- 1 | ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"] -------------------------------------------------------------------------------- /datasets/permutations/cifar-10.json: -------------------------------------------------------------------------------- 1 | [1, 9, 8, 0, 7, 5, 3, 2, 4, 6] -------------------------------------------------------------------------------- /datasets/permutations/cifar-100.json: -------------------------------------------------------------------------------- 1 | [60, 71, 23, 49, 68, 58, 13, 81, 90, 17, 37, 12, 85, 76, 69, 48, 94, 8, 89, 41, 9, 20, 25, 5, 84, 87, 86, 39, 16, 40, 28, 22, 61, 10, 0, 53, 83, 57, 82, 62, 92, 70, 54, 2, 11, 35, 98, 46, 45, 26, 24, 7, 6, 99, 78, 14, 79, 18, 44, 1, 91, 32, 93, 67, 73, 30, 95, 77, 27, 72, 55, 66, 65, 36, 64, 50, 74, 97, 80, 38, 4, 63, 3, 21, 29, 31, 15, 19, 51, 42, 43, 34, 75, 33, 88, 56, 59, 96, 52, 47] -------------------------------------------------------------------------------- /datasets/permutations/gtsrb.json: -------------------------------------------------------------------------------- 1 | [32, 33, 28, 37, 29, 19, 41, 17, 39, 12, 15, 34, 14, 0, 22, 20, 21, 26, 18, 31, 24, 25, 27, 11, 30, 23, 10, 1, 38, 2, 4, 5, 3, 6, 42, 13, 7, 40, 36, 8, 9, 35, 16] -------------------------------------------------------------------------------- /datasets/svhn-mean.npy: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/datasets/svhn-mean.npy -------------------------------------------------------------------------------- /ensemble/catdog_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cats_dogs.py 3 | img_rows: 128 4 | img_cols: 128 5 | models: 6 | - "../artifacts/catdog_opt/catdog_opt_20170503-0731-26.h5" 7 | - "../artifacts/catdog_opt/catdog_opt_20170503-0915-15.h5" 8 | - "../artifacts/catdog_opt/catdog_opt_20170503-1110-03.h5" 9 | - "../artifacts/catdog_opt/catdog_opt_20170503-1301-07.h5" 10 | - "../artifacts/catdog_opt/catdog_opt_20170503-1459-51.h5" 11 | - "../artifacts/catdog_opt/catdog_opt_20170503-1712-02.h5" 12 | - "../artifacts/catdog_opt/catdog_opt_20170503-1934-52.h5" 13 | - "../artifacts/catdog_opt/catdog_opt_20170504-1154-23.h5" 14 | - "../artifacts/catdog_opt/catdog_opt_20170504-1502-50.h5" 15 | - "../artifacts/catdog_opt/catdog_opt_20170504-1705-44.h5" 16 | evaluate: 17 | batch_size: 250 18 | batch_size_train: 4522 19 | augmentation_factor: 32 20 | data_augmentation: 21 | samplewise_center: False 22 | samplewise_std_normalization: False 23 | rotation_range: 0 24 | width_shift_range: 0.15 25 | height_shift_range: 0.15 26 | horizontal_flip: True 27 | vertical_flip: False 28 | zoom_range: 0 29 | shear_range: 0 30 | channel_shift_range: 0 31 | featurewise_center: False 32 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/catdog_opt_train_es.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cats_dogs.py 3 | img_rows: 128 4 | img_cols: 128 5 | models: 6 | - "../artifacts/catdog_opt_train_es/catdog_opt_train_es_20170530-0913-59.h5" 7 | - "../artifacts/catdog_opt_train_es/catdog_opt_train_es_20170530-1828-38.h5" 8 | - "../artifacts/catdog_opt_train_es/catdog_opt_train_es_20170531-0812-52.h5" 9 | evaluate: 10 | batch_size: 250 11 | batch_size_train: 4522 12 | augmentation_factor: 32 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar10.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | models: 4 | - "../artifacts/cifar10_baseline/cifar10_baseline.h5" 5 | - "../artifacts/cifar10_baseline/cifar10_baseline-1.h5" 6 | - "../artifacts/cifar10_baseline/cifar10_baseline-2.h5" 7 | - "../artifacts/cifar10_baseline/cifar10_baseline-3.h5" 8 | - "../artifacts/cifar10_baseline/cifar10_baseline-4.h5" 9 | - "../artifacts/cifar10_baseline/cifar10_baseline-5.h5" 10 | - "../artifacts/cifar10_baseline/cifar10_baseline-6.h5" 11 | - "../artifacts/cifar10_baseline/cifar10_baseline-7.h5" 12 | - "../artifacts/cifar10_baseline/cifar10_baseline-8.h5" 13 | - "../artifacts/cifar10_baseline/cifar10_baseline-9.h5" 14 | evaluate: 15 | batch_size: 5000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100-bs16.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170421-2230-30.h5" 5 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-0115-31.h5" 6 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-0354-29.h5" 7 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-0714-19.h5" 8 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-0917-46.h5" 9 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-1202-18.h5" 10 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-1414-08.h5" 11 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-1617-17.h5" 12 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-1932-29.h5" 13 | - "../artifacts/cifar100_bs16/cifar100_bs16_20170422-2213-10.h5" 14 | evaluate: 15 | batch_size: 5000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100-bs32.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1004-11.h5" 5 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1136-09.h5" 6 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1316-16.h5" 7 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1510-49.h5" 8 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1632-06.h5" 9 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1752-05.h5" 10 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-1924-19.h5" 11 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-2116-50.h5" 12 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170422-2235-53.h5" 13 | - "../artifacts/cifar100_bs32/cifar100_bs32_20170423-0020-14.h5" 14 | evaluate: 15 | batch_size: 5000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100-bs8.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170421-1721-27.h5" 5 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170421-2238-10.h5" 6 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170422-0415-25.h5" 7 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170422-0724-26.h5" 8 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170422-1204-39.h5" 9 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170422-1547-31.h5" 10 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170422-2050-52.h5" 11 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170423-0119-41.h5" 12 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170423-0457-36.h5" 13 | - "../artifacts/cifar100_bs8/cifar100_bs8_20170423-1002-45.h5" 14 | evaluate: 15 | batch_size: 5000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100_less16more32.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1251-11.h5" 5 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1403-21.h5" 6 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1501-16.h5" 7 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1619-43.h5" 8 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1738-23.h5" 9 | - "../artifacts/cifar100_less16more32/cifar100_less16more32_20170430-1850-15.h5" 10 | evaluate: 11 | batch_size: 5000 12 | augmentation_factor: 32 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100_nin.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_nin/cifar100_nin_20170424-2003-19.h5" 5 | - "../artifacts/cifar100_nin/cifar100_nin_20170424-2059-11.h5" 6 | - "../artifacts/cifar100_nin/cifar100_nin_20170424-2152-32.h5" 7 | - "../artifacts/cifar100_nin/cifar100_nin_20170424-2248-05.h5" 8 | - "../artifacts/cifar100_nin/cifar100_nin_20170424-2353-28.h5" 9 | - "../artifacts/cifar100_nin/cifar100_nin_20170425-0110-15.h5" 10 | - "../artifacts/cifar100_nin/cifar100_nin_20170425-0205-24.h5" 11 | - "../artifacts/cifar100_nin/cifar100_nin_20170425-0255-40.h5" 12 | - "../artifacts/cifar100_nin/cifar100_nin_20170425-0413-10.h5" 13 | - "../artifacts/cifar100_nin/cifar100_nin_20170425-0505-18.h5" 14 | evaluate: 15 | batch_size: 5000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-2148-59.h5" 5 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-2022-51.h5" 6 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1916-51.h5" 7 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1810-33.h5" 8 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1644-53.h5" 9 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1538-28.h5" 10 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1400-32.h5" 11 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1219-51.h5" 12 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-1115-07.h5" 13 | - "../artifacts/cifar100_opt/cifar100_opt_20170501-0939-30.h5" 14 | evaluate: 15 | batch_size: 5000 16 | batch_size_train: 4500 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar100_wide_resnet.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | models: 4 | - "../artifacts/cifar100_wide_resnet/cifar100_wide_resnet_20170423-1914-38.h5" 5 | - "../artifacts/cifar100_wide_resnet/cifar100_wide_resnet_20170424-0151-02.h5" 6 | - "../artifacts/cifar100_wide_resnet/cifar100_wide_resnet_20170424-0948-56.h5" 7 | evaluate: 8 | batch_size: 5000 9 | augmentation_factor: 32 10 | data_augmentation: 11 | samplewise_center: False 12 | samplewise_std_normalization: False 13 | rotation_range: 0 14 | width_shift_range: 0.15 15 | height_shift_range: 0.15 16 | horizontal_flip: True 17 | vertical_flip: False 18 | zoom_range: 0 19 | shear_range: 0 20 | channel_shift_range: 0 21 | featurewise_center: False 22 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/cifar10_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | models: 4 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1334-55.h5" 5 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1419-42.h5" 6 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1523-58.h5" 7 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1608-53.h5" 8 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1707-45.h5" 9 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1810-24.h5" 10 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-1942-27.h5" 11 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-2046-51.h5" 12 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-2147-16.h5" 13 | - "../artifacts/cifar10_opt/cifar10_opt_20170502-2244-16.h5" 14 | evaluate: 15 | batch_size: 5000 16 | batch_size_train: 4500 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170522-2032-41.h5" 5 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170522-2118-39.h5" 6 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170522-2217-59.h5" 7 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170522-2303-10.h5" 8 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170522-2347-54.h5" 9 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170523-0036-43.h5" 10 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170523-0123-49.h5" 11 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170523-0201-14.h5" 12 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170523-0252-41.h5" 13 | - "../artifacts/gtsrb_linear/gtsrb_linear_20170523-0336-16.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_new.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170415-0004-34.h5" 5 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2316-32.h5" 6 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2305-57.h5" 7 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2235-44.h5" 8 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2228-25.h5" 9 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2150-43.h5" 10 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2149-39.h5" 11 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-2048-55.h5" 12 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-1904-49.h5" 13 | - "../artifacts/gtsrb_baseline/gtsrb_baseline_20170414-1809-38.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0135-45.h5" 5 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0213-05.h5" 6 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0250-11.h5" 7 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0327-24.h5" 8 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0404-42.h5" 9 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0441-52.h5" 10 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0519-05.h5" 11 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0556-28.h5" 12 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0633-35.h5" 13 | - "../artifacts/gtsrb_opt_long/gtsrb_opt_long_20170525-0710-55.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-0855-13.h5" 5 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-0919-30.h5" 6 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-0945-12.h5" 7 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1014-04.h5" 8 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1040-27.h5" 9 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1108-09.h5" 10 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1133-36.h5" 11 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1200-49.h5" 12 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1233-57.h5" 13 | - "../artifacts/gtsrb_prelu/gtsrb_prelu_20170524-1257-10.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-0858-18.h5" 5 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-0925-34.h5" 6 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-0947-43.h5" 7 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1014-03.h5" 8 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1034-04.h5" 9 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1057-57.h5" 10 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1122-23.h5" 11 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1141-36.h5" 12 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1207-29.h5" 13 | - "../artifacts/gtsrb_sigmoid/gtsrb_sigmoid_20170524-1234-59.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170523-2359-08.h5" 5 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0043-20.h5" 6 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0125-09.h5" 7 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0213-16.h5" 8 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0304-41.h5" 9 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0347-08.h5" 10 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0438-46.h5" 11 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0523-45.h5" 12 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0603-47.h5" 13 | - "../artifacts/gtsrb_softmax/gtsrb_softmax_20170524-0644-18.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_softplus.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1622-44.h5" 5 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1639-56.h5" 6 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1656-32.h5" 7 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1713-10.h5" 8 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1729-46.h5" 9 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1746-19.h5" 10 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1802-53.h5" 11 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1819-29.h5" 12 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1839-55.h5" 13 | - "../artifacts/gtsrb_softplus/gtsrb_softplus_20170524-1858-43.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0040-26.h5" 5 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0113-16.h5" 6 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0137-31.h5" 7 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0207-01.h5" 8 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0232-46.h5" 9 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0256-54.h5" 10 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0316-24.h5" 11 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0342-45.h5" 12 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0412-30.h5" 13 | - "../artifacts/gtsrb_softsign/gtsrb_softsign_20170524-0440-21.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170523-2356-27.h5" 5 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0032-11.h5" 6 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0103-28.h5" 7 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0138-41.h5" 8 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0209-18.h5" 9 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0243-13.h5" 10 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0318-24.h5" 11 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0355-20.h5" 12 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0435-30.h5" 13 | - "../artifacts/gtsrb_tanh/gtsrb_tanh_20170524-0510-39.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/gtsrb_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | models: 4 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-0856-33.h5" 5 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-0928-47.h5" 6 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-0957-28.h5" 7 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1032-54.h5" 8 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1100-24.h5" 9 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1131-58.h5" 10 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1211-27.h5" 11 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1242-00.h5" 12 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1307-20.h5" 13 | - "../artifacts/gtsrb_vlrelu/gtsrb_vlrelu_20170524-1339-18.h5" 14 | evaluate: 15 | batch_size: 842 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_baseline/hasy_baseline.h5" 5 | - "../artifacts/hasy_baseline/hasy_baseline-1.h5" 6 | - "../artifacts/hasy_baseline/hasy_baseline-2.h5" 7 | - "../artifacts/hasy_baseline/hasy_baseline-3.h5" 8 | - "../artifacts/hasy_baseline/hasy_baseline-4.h5" 9 | - "../artifacts/hasy_baseline/hasy_baseline-5.h5" 10 | - "../artifacts/hasy_baseline/hasy_baseline-6.h5" 11 | - "../artifacts/hasy_baseline/hasy_baseline-7.h5" 12 | - "../artifacts/hasy_baseline/hasy_baseline-8.h5" 13 | - "../artifacts/hasy_baseline/hasy_baseline-9.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_linear/hasy_linear_20170504-0056-05.h5" 5 | - "../artifacts/hasy_linear/hasy_linear_20170504-0436-08.h5" 6 | - "../artifacts/hasy_linear/hasy_linear_20170504-0711-09.h5" 7 | - "../artifacts/hasy_linear/hasy_linear_20170504-1010-40.h5" 8 | - "../artifacts/hasy_linear/hasy_linear_20170504-1256-28.h5" 9 | - "../artifacts/hasy_linear/hasy_linear_20170504-1524-45.h5" 10 | - "../artifacts/hasy_linear/hasy_linear_20170504-1832-22.h5" 11 | - "../artifacts/hasy_linear/hasy_linear_20170504-2120-29.h5" 12 | - "../artifacts/hasy_linear/hasy_linear_20170505-0045-56.h5" 13 | - "../artifacts/hasy_linear/hasy_linear_20170505-0406-27.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_new.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_baseline/hasy_baseline_20170420-2232-04.h5" 5 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-0055-51.h5" 6 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-0259-03.h5" 7 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-0516-57.h5" 8 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-0736-05.h5" 9 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-0945-04.h5" 10 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-1151-46.h5" 11 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-1418-05.h5" 12 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-1641-15.h5" 13 | - "../artifacts/hasy_baseline/hasy_baseline_20170421-1924-18.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_opt/hasy_opt_20170503-1503-12.h5" 5 | - "../artifacts/hasy_opt/hasy_opt_20170503-1209-03.h5" 6 | - "../artifacts/hasy_opt/hasy_opt_20170503-0912-50.h5" 7 | - "../artifacts/hasy_opt/hasy_opt_20170503-0715-31.h5" 8 | - "../artifacts/hasy_opt/hasy_opt_20170503-0319-14.h5" 9 | - "../artifacts/hasy_opt/hasy_opt_20170503-0013-48.h5" 10 | - "../artifacts/hasy_opt/hasy_opt_20170502-2050-19.h5" 11 | - "../artifacts/hasy_opt/hasy_opt_20170502-1747-05.h5" 12 | - "../artifacts/hasy_opt/hasy_opt_20170502-1444-57.h5" 13 | - "../artifacts/hasy_opt/hasy_opt_20170502-1242-05.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170525-0935-39.h5" 5 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170525-1226-37.h5" 6 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170525-1809-21.h5" 7 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170525-2100-46.h5" 8 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170525-2351-47.h5" 9 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170526-0242-31.h5" 10 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170526-0533-51.h5" 11 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170526-0824-28.h5" 12 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170526-1114-48.h5" 13 | - "../artifacts/hasy_opt_long/hasy_opt_long_20170527-0038-05.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_prelu/hasy_prelu_20170505-1622-43.h5" 5 | - "../artifacts/hasy_prelu/hasy_prelu_20170505-1848-50.h5" 6 | - "../artifacts/hasy_prelu/hasy_prelu_20170505-2054-18.h5" 7 | - "../artifacts/hasy_prelu/hasy_prelu_20170505-2308-02.h5" 8 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-0135-33.h5" 9 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-0357-03.h5" 10 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-0625-12.h5" 11 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-0841-31.h5" 12 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-1052-56.h5" 13 | - "../artifacts/hasy_prelu/hasy_prelu_20170506-1246-44.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_relu/hasy_relu_20170504-1824-53.h5" 5 | - "../artifacts/hasy_relu/hasy_relu_20170504-2023-00.h5" 6 | - "../artifacts/hasy_relu/hasy_relu_20170504-2151-51.h5" 7 | - "../artifacts/hasy_relu/hasy_relu_20170504-2317-53.h5" 8 | - "../artifacts/hasy_relu/hasy_relu_20170505-0043-56.h5" 9 | - "../artifacts/hasy_relu/hasy_relu_20170505-0217-05.h5" 10 | - "../artifacts/hasy_relu/hasy_relu_20170505-0346-03.h5" 11 | - "../artifacts/hasy_relu/hasy_relu_20170505-0512-55.h5" 12 | - "../artifacts/hasy_relu/hasy_relu_20170505-0638-46.h5" 13 | - "../artifacts/hasy_relu/hasy_relu_20170505-0812-00.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170504-1826-25.h5" 5 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170504-2010-35.h5" 6 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170504-2120-28.h5" 7 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170504-2248-10.h5" 8 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0016-17.h5" 9 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0155-47.h5" 10 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0301-51.h5" 11 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0439-44.h5" 12 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0617-12.h5" 13 | - "../artifacts/hasy_sigmoid/hasy_sigmoid_20170505-0740-42.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_softmax/hasy_softmax_20170506-1751-11.h5" 5 | - "../artifacts/hasy_softmax/hasy_softmax_20170506-2111-45.h5" 6 | - "../artifacts/hasy_softmax/hasy_softmax_20170507-0042-14.h5" 7 | - "../artifacts/hasy_softmax/hasy_softmax_20170507-0439-07.h5" 8 | - "../artifacts/hasy_softmax/hasy_softmax_20170508-1006-47.h5" 9 | - "../artifacts/hasy_softmax/hasy_softmax_20170508-1326-07.h5" 10 | - "../artifacts/hasy_softmax/hasy_softmax_20170508-1641-04.h5" 11 | - "../artifacts/hasy_softmax/hasy_softmax_20170508-2022-55.h5" 12 | - "../artifacts/hasy_softmax/hasy_softmax_20170508-2323-21.h5" 13 | - "../artifacts/hasy_softmax/hasy_softmax_20170509-0239-52.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-1623-27.h5" 5 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-1732-44.h5" 6 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-1906-12.h5" 7 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-2044-12.h5" 8 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-2208-36.h5" 9 | - "../artifacts/hasy_softsign/hasy_softsign_20170505-2345-42.h5" 10 | - "../artifacts/hasy_softsign/hasy_softsign_20170506-0132-36.h5" 11 | - "../artifacts/hasy_softsign/hasy_softsign_20170506-0257-55.h5" 12 | - "../artifacts/hasy_softsign/hasy_softsign_20170506-0437-39.h5" 13 | - "../artifacts/hasy_softsign/hasy_softsign_20170506-0618-14.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-0813-46.h5" 5 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-0953-19.h5" 6 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1141-49.h5" 7 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1314-08.h5" 8 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1440-25.h5" 9 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1612-04.h5" 10 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1732-01.h5" 11 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-1922-07.h5" 12 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-2109-50.h5" 13 | - "../artifacts/hasy_tanh/hasy_tanh_20170507-2253-55.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/hasy_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | models: 4 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-0817-37.h5" 5 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-1033-15.h5" 6 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-1249-35.h5" 7 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-1442-47.h5" 8 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-1716-14.h5" 9 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-1942-45.h5" 10 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170507-2211-02.h5" 11 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170508-0033-44.h5" 12 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170508-0234-47.h5" 13 | - "../artifacts/hasy_vlrelu/hasy_vlrelu_20170508-0458-59.h5" 14 | evaluate: 15 | batch_size: 2124 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_baseline/mnist_baseline.h5" 5 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1323-06.h5" 6 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1326-05.h5" 7 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1441-29.h5" 8 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1443-10.h5" 9 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1447-59.h5" 10 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-1701-00.h5" 11 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-2219-47.h5" 12 | - "../artifacts/mnist_baseline/mnist_baseline_20170410-2220-33.h5" 13 | - "../artifacts/mnist_baseline/mnist_baseline-1.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_linear/mnist_linear_20170503-0932-36.h5" 5 | - "../artifacts/mnist_linear/mnist_linear_20170503-1009-51.h5" 6 | - "../artifacts/mnist_linear/mnist_linear_20170503-1047-05.h5" 7 | - "../artifacts/mnist_linear/mnist_linear_20170503-1125-19.h5" 8 | - "../artifacts/mnist_linear/mnist_linear_20170503-1206-18.h5" 9 | - "../artifacts/mnist_linear/mnist_linear_20170503-1244-11.h5" 10 | - "../artifacts/mnist_linear/mnist_linear_20170503-1336-16.h5" 11 | - "../artifacts/mnist_linear/mnist_linear_20170503-1413-49.h5" 12 | - "../artifacts/mnist_linear/mnist_linear_20170503-1501-24.h5" 13 | - "../artifacts/mnist_linear/mnist_linear_20170503-1552-37.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_new.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1618-47.h5" 5 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1645-38.h5" 6 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1709-52.h5" 7 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1733-22.h5" 8 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1757-11.h5" 9 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1821-42.h5" 10 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1852-00.h5" 11 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1923-54.h5" 12 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-1947-08.h5" 13 | - "../artifacts/mnist_baseline/mnist_baseline_20170420-2009-59.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_no_aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1611-01.h5" 5 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1613-32.h5" 6 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1650-13.h5" 7 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1701-59.h5" 8 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1723-17.h5" 9 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1749-22.h5" 10 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1909-52.h5" 11 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1945-42.h5" 12 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-1946-11.h5" 13 | - "../artifacts/mnist_baseline/mnist_baseline_20170414-2009-29.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_opt/mnist_opt_20170501-0942-40.h5" 5 | - "../artifacts/mnist_opt/mnist_opt_20170501-1008-44.h5" 6 | - "../artifacts/mnist_opt/mnist_opt_20170501-1059-05.h5" 7 | - "../artifacts/mnist_opt/mnist_opt_20170501-1136-47.h5" 8 | - "../artifacts/mnist_opt/mnist_opt_20170501-1225-38.h5" 9 | - "../artifacts/mnist_opt/mnist_opt_20170501-1308-22.h5" 10 | - "../artifacts/mnist_opt/mnist_opt_20170501-1341-36.h5" 11 | - "../artifacts/mnist_opt/mnist_opt_20170501-1423-34.h5" 12 | - "../artifacts/mnist_opt/mnist_opt_20170501-1458-52.h5" 13 | - "../artifacts/mnist_opt/mnist_opt_20170501-1534-43.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-0932-31.h5" 5 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1002-44.h5" 6 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1033-03.h5" 7 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1103-18.h5" 8 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1133-32.h5" 9 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1203-49.h5" 10 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1234-08.h5" 11 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1304-30.h5" 12 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1334-45.h5" 13 | - "../artifacts/mnist_opt_long/mnist_opt_long_20170525-1405-01.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_prelu/mnist_prelu_20170430-2240-32.h5" 5 | - "../artifacts/mnist_prelu/mnist_prelu_20170430-2314-27.h5" 6 | - "../artifacts/mnist_prelu/mnist_prelu_20170430-2339-41.h5" 7 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0018-11.h5" 8 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0054-58.h5" 9 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0130-30.h5" 10 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0200-55.h5" 11 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0220-14.h5" 12 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0254-08.h5" 13 | - "../artifacts/mnist_prelu/mnist_prelu_20170501-0319-24.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_relu/mnist_relu_20170430-1521-16.h5" 5 | - "../artifacts/mnist_relu/mnist_relu_20170430-1540-47.h5" 6 | - "../artifacts/mnist_relu/mnist_relu_20170430-1614-38.h5" 7 | - "../artifacts/mnist_relu/mnist_relu_20170430-1633-13.h5" 8 | - "../artifacts/mnist_relu/mnist_relu_20170430-1702-18.h5" 9 | - "../artifacts/mnist_relu/mnist_relu_20170430-1724-50.h5" 10 | - "../artifacts/mnist_relu/mnist_relu_20170430-1745-15.h5" 11 | - "../artifacts/mnist_relu/mnist_relu_20170430-1813-12.h5" 12 | - "../artifacts/mnist_relu/mnist_relu_20170430-1847-16.h5" 13 | - "../artifacts/mnist_relu/mnist_relu_20170430-1915-58.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1638-03.h5" 5 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1702-58.h5" 6 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1736-02.h5" 7 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1752-18.h5" 8 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1816-05.h5" 9 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1839-53.h5" 10 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1858-21.h5" 11 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1923-26.h5" 12 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-1952-51.h5" 13 | - "../artifacts/mnist_sigmoid/mnist_sigmoid_20170503-2021-16.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-0934-04.h5" 5 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1019-54.h5" 6 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1048-30.h5" 7 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1117-36.h5" 8 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1201-56.h5" 9 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1230-52.h5" 10 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1259-52.h5" 11 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1346-48.h5" 12 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1433-30.h5" 13 | - "../artifacts/mnist_softmax/mnist_softmax_20170503-1502-04.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_softplus.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1338-18.h5" 5 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1409-01.h5" 6 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1439-44.h5" 7 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1507-00.h5" 8 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1537-53.h5" 9 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1608-30.h5" 10 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1639-04.h5" 11 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1709-19.h5" 12 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1740-05.h5" 13 | - "../artifacts/mnist_softplus/mnist_softplus_20170502-1811-22.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0426-19.h5" 5 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0355-01.h5" 6 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0322-23.h5" 7 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0249-30.h5" 8 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0207-44.h5" 9 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0128-10.h5" 10 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0054-47.h5" 11 | - "../artifacts/mnist_softsign/mnist_softsign_20170503-0016-15.h5" 12 | - "../artifacts/mnist_softsign/mnist_softsign_20170502-2344-00.h5" 13 | - "../artifacts/mnist_softsign/mnist_softsign_20170502-2259-34.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/mnist_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | models: 4 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0014-15.h5" 5 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0045-47.h5" 6 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0114-11.h5" 7 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0140-59.h5" 8 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0205-44.h5" 9 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0240-54.h5" 10 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0314-01.h5" 11 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0344-17.h5" 12 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0412-50.h5" 13 | - "../artifacts/mnist_tanh/mnist_tanh_20170504-0445-33.h5" 14 | evaluate: 15 | batch_size: 10000 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_linear/stl10_linear_20170508-0949-40.h5" 5 | - "../artifacts/stl10_linear/stl10_linear_20170508-1025-47.h5" 6 | - "../artifacts/stl10_linear/stl10_linear_20170508-1043-32.h5" 7 | - "../artifacts/stl10_linear/stl10_linear_20170508-1058-35.h5" 8 | - "../artifacts/stl10_linear/stl10_linear_20170508-1113-11.h5" 9 | - "../artifacts/stl10_linear/stl10_linear_20170508-1127-42.h5" 10 | - "../artifacts/stl10_linear/stl10_linear_20170508-1142-14.h5" 11 | - "../artifacts/stl10_linear/stl10_linear_20170508-1156-33.h5" 12 | - "../artifacts/stl10_linear/stl10_linear_20170508-1211-27.h5" 13 | - "../artifacts/stl10_linear/stl10_linear_20170508-1226-24.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 675 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_new.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1238-41.h5" 5 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1259-54.h5" 6 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1322-01.h5" 7 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1344-09.h5" 8 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1407-07.h5" 9 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1429-28.h5" 10 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1451-03.h5" 11 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1517-06.h5" 12 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1538-43.h5" 13 | - "../artifacts/stl10_baseline/stl10_baseline_20170420-1601-13.h5" 14 | evaluate: 15 | batch_size: 810 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_opt/stl10_opt_20170501-1224-03.h5" 5 | - "../artifacts/stl10_opt/stl10_opt_20170501-1212-56.h5" 6 | - "../artifacts/stl10_opt/stl10_opt_20170501-1212-56.h5" 7 | - "../artifacts/stl10_opt/stl10_opt_20170501-1148-06.h5" 8 | - "../artifacts/stl10_opt/stl10_opt_20170501-1129-31.h5" 9 | - "../artifacts/stl10_opt/stl10_opt_20170501-1109-57.h5" 10 | - "../artifacts/stl10_opt/stl10_opt_20170501-1058-50.h5" 11 | - "../artifacts/stl10_opt/stl10_opt_20170501-1041-16.h5" 12 | - "../artifacts/stl10_opt/stl10_opt_20170501-1020-57.h5" 13 | - "../artifacts/stl10_opt/stl10_opt_20170501-0943-20.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 4050 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1005-37.h5" 5 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1031-46.h5" 6 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1049-11.h5" 7 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1112-59.h5" 8 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1135-02.h5" 9 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1157-41.h5" 10 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1217-58.h5" 11 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1241-47.h5" 12 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1311-25.h5" 13 | - "../artifacts/stl10_prelu/stl10_prelu_20170508-1329-42.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 675 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_relu/stl10_relu_20170514-2322-45.h5" 5 | - "../artifacts/stl10_relu/stl10_relu_20170514-2343-28.h5" 6 | - "../artifacts/stl10_relu/stl10_relu_20170515-0001-12.h5" 7 | - "../artifacts/stl10_relu/stl10_relu_20170515-1938-40.h5" 8 | - "../artifacts/stl10_relu/stl10_relu_20170515-1952-56.h5" 9 | - "../artifacts/stl10_relu/stl10_relu_20170515-2015-22.h5" 10 | - "../artifacts/stl10_relu/stl10_relu_20170515-2030-33.h5" 11 | - "../artifacts/stl10_relu/stl10_relu_20170515-2049-11.h5" 12 | - "../artifacts/stl10_relu/stl10_relu_20170515-2104-07.h5" 13 | - "../artifacts/stl10_relu/stl10_relu_20170515-2125-38.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 675 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1148-56.h5" 5 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1203-59.h5" 6 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1219-15.h5" 7 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1225-45.h5" 8 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1242-59.h5" 9 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1257-56.h5" 10 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170508-1326-34.h5" 11 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170512-2123-48.h5" 12 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170512-2141-49.h5" 13 | - "../artifacts/stl10_sigmoid/stl10_sigmoid_20170512-2159-39.h5" 14 | evaluate: 15 | batch_size: 500 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: True 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1146-41.h5" 5 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1205-21.h5" 6 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1220-03.h5" 7 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1234-47.h5" 8 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1246-20.h5" 9 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1301-34.h5" 10 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1323-24.h5" 11 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1338-24.h5" 12 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1356-02.h5" 13 | - "../artifacts/stl10_tanh/stl10_tanh_20170517-1413-57.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 675 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/stl10_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | models: 4 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1008-20.h5" 5 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1021-51.h5" 6 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1036-28.h5" 7 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1057-50.h5" 8 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1128-19.h5" 9 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1156-10.h5" 10 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1210-41.h5" 11 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1234-20.h5" 12 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1258-57.h5" 13 | - "../artifacts/stl10_vlrelu/stl10_vlrelu_20170508-1318-16.h5" 14 | evaluate: 15 | batch_size: 500 16 | batch_size_train: 675 17 | augmentation_factor: 32 18 | data_augmentation: 19 | samplewise_center: False 20 | samplewise_std_normalization: False 21 | rotation_range: 0 22 | width_shift_range: 0.15 23 | height_shift_range: 0.15 24 | horizontal_flip: True 25 | vertical_flip: False 26 | zoom_range: 0 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/svhn.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | models: 4 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-1711-59.h5" 5 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-1728-50.h5" 6 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-1846-26.h5" 7 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-2127-42.h5" 8 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-2128-55.h5" 9 | - "../artifacts/svhn_baseline/svhn_baseline_20170412-2357-53.h5" 10 | - "../artifacts/svhn_baseline/svhn_baseline_20170413-0000-22.h5" 11 | - "../artifacts/svhn_baseline/svhn_baseline_20170413-0023-51.h5" 12 | - "../artifacts/svhn_baseline/svhn_baseline_20170413-0138-39.h5" 13 | - "../artifacts/svhn_baseline/svhn_baseline_20170413-0341-49.h5" 14 | evaluate: 15 | batch_size: 1627 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0.1 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /ensemble/svhn_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | models: 4 | - "../artifacts/svhn_opt/svhn_opt_20170502-2244-53.h5" 5 | - "../artifacts/svhn_opt/svhn_opt_20170503-0150-50.h5" 6 | - "../artifacts/svhn_opt/svhn_opt_20170503-0626-43.h5" 7 | - "../artifacts/svhn_opt/svhn_opt_20170503-1134-12.h5" 8 | - "../artifacts/svhn_opt/svhn_opt_20170503-1540-52.h5" 9 | - "../artifacts/svhn_opt/svhn_opt_20170503-1926-11.h5" 10 | - "../artifacts/svhn_opt/svhn_opt_20170503-2250-22.h5" 11 | - "../artifacts/svhn_opt/svhn_opt_20170504-0224-18.h5" 12 | - "../artifacts/svhn_opt/svhn_opt_20170504-0525-17.h5" 13 | - "../artifacts/svhn_opt/svhn_opt_20170504-1028-41.h5" 14 | evaluate: 15 | batch_size: 1627 16 | augmentation_factor: 1 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 0 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0 26 | shear_range: 0.1 27 | channel_shift_range: 0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_b.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_b.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_baselineb/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_baseline/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_big.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_big.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_big/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_bs128.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_bs128/ 11 | batch_size: 128 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_bs16.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_bs16/ 11 | batch_size: 16 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_bs32.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_bs32/ 11 | batch_size: 32 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_bs8.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_bs8/ 11 | batch_size: 8 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_dense.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/densenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_dense/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_large_11.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/large11.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_large11/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_large_13.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/large13.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_large13/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_large_9.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/large9.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_large9/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_large_9s.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/large9s.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_large9s/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_linear/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_maxmeanpool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_maxmeanpool.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_maxmeanpool/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_model4.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/model4.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_model4/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_multi.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_multi.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_multi/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_nin.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/nin.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_nin/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_no_bias.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_no_bias.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_baseline_no_bias/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_no_bn.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_no_bn.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_no_bn/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_opt/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_prelu/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_pure.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/pure_cnn.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_baseline/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_relu/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_seq2.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/sequential_updated.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq2/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.05 18 | height_shift_range: 0.05 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.1 22 | saturation_scale: 0.1 23 | saturation_shift: 0.1 24 | value_scale: 0.1 25 | value_shift: 0.1 26 | zoom_range: 0.1 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_seq3-feat.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/seq3.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3-feat/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: True 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_seq3-less-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/seq3.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3-less-aug/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | shear_range: 0.1 22 | channel_shift_range: 0.05 23 | featurewise_center: False 24 | zca_whitening: False 25 | zoom_range: 0.1 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | shear_range: 0.1 38 | channel_shift_range: 0.05 39 | featurewise_center: False 40 | zca_whitening: False 41 | zoom_range: 0.1 -------------------------------------------------------------------------------- /experiments/cifar100_seq3-no-pool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/seq3-no-pooling.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3-no-pooling/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_seq3-sample.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/seq3.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3-feat/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: True 15 | samplewise_std_normalization: True 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_seq3.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/seq3.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_seq_keras-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq_keras-aug/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_seq_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | batch_size: 64 11 | epochs: 50 12 | data_augmentation: False 13 | artifacts_path: ../artifacts/cifar100_seq_keras/ 14 | -------------------------------------------------------------------------------- /experiments/cifar100_sgd_chk.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/sgd.py 7 | initial_lr: 0.1 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_sgd_chk/ 11 | saveall: True 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_softsign/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar100_squeeze.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/squeezenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_seq3/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar100_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/baseline_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar100_tanh/ 11 | saveall: False 12 | batch_size: 64 13 | epochs: 1000 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 0 18 | width_shift_range: 0.1 19 | height_shift_range: 0.1 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0 23 | shear_range: 0 24 | channel_shift_range: 0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 0 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0 39 | shear_range: 0 40 | channel_shift_range: 0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_baseline/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_baseline_ebn.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/baseline_ebn.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_baseline_ebn/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_baseline_jeon.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/baseline_jeon.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | nesterov: True 9 | momentum: 0.9 10 | train: 11 | script_path: ../train/train_keras.py 12 | artifacts_path: ../artifacts/cifar10_baseline_jeon/ 13 | batch_size: 64 14 | epochs: 300 15 | data_augmentation: 16 | samplewise_center: False 17 | samplewise_std_normalization: False 18 | rotation_range: 0 19 | width_shift_range: 0.15 20 | height_shift_range: 0.15 21 | horizontal_flip: True 22 | vertical_flip: False 23 | hue_shift: 0 24 | saturation_scale: 0 25 | saturation_shift: 0 26 | value_scale: 0 27 | value_shift: 0 28 | zoom_range: 0.2 29 | shear_range: 0 30 | channel_shift_range: 0 31 | featurewise_center: False 32 | zca_whitening: True 33 | -------------------------------------------------------------------------------- /experiments/cifar10_dense.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/densenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_dense/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_dense_aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/densenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_dense_aug/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_fractal.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/fractalnet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_fractal/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0 22 | saturation_scale: 0 23 | saturation_shift: 0 24 | value_scale: 0 25 | value_shift: 0 26 | zoom_range: 0.2 27 | shear_range: 0 28 | channel_shift_range: 0 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_opt/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_exact.py 10 | artifacts_path: ../artifacts/cifar10_opt_long/ 11 | batch_size: 64 12 | epochs: 84 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_opt_train_es.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_train_es.py 10 | artifacts_path: ../artifacts/cifar10_opt_train_es/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/cifar10_rflearn.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/rflearn.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_rflearn/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_seq2.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/sequential_updated.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_seq2/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_seq3-no-pool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/seq3-no-pooling.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_seq3-no-pooling/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: True 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/cifar10_seq_keras-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | batch_size: 64 11 | epochs: 300 12 | data_augmentation: 13 | samplewise_center: False 14 | samplewise_std_normalization: False 15 | rotation_range: 15 16 | width_shift_range: 0.15 17 | height_shift_range: 0.15 18 | horizontal_flip: True 19 | vertical_flip: False 20 | hue_shift: 0.2 21 | saturation_scale: 0.5 22 | saturation_shift: 0.2 23 | value_scale: 0.5 24 | value_shift: 0.2 25 | zoom_range: 0.5 26 | shear_range: 0.1 27 | channel_shift_range: 0.1 28 | featurewise_center: False 29 | zca_whitening: False 30 | artifacts_path: ../artifacts/cifar10_seq-aug/ 31 | -------------------------------------------------------------------------------- /experiments/cifar10_seq_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/cifar10_seq/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: False 14 | -------------------------------------------------------------------------------- /experiments/e1.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10.py 3 | model: 4 | script_path: ../models/mlp.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.01 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e1/ 11 | batch_size: 32 12 | epochs: 100 -------------------------------------------------------------------------------- /experiments/e1/validation-curve-accuracy-test.csv: -------------------------------------------------------------------------------- 1 | 0;0.095556;0.093800 2 | 1562;0.153356;0.150700 3 | 3124;0.166889;0.165600 4 | 4686;0.166911;0.166300 5 | 6248;0.166711;0.165600 6 | 7810;0.156378;0.152600 7 | 9372;0.160533;0.162600 8 | 10934;0.161178;0.162700 9 | 12496;0.165756;0.165200 10 | 14058;0.155822;0.153100 11 | 15620;0.157667;0.154600 12 | 17182;0.162156;0.163000 13 | 18744;0.166822;0.166200 14 | 20306;0.163978;0.163500 15 | 21868;0.166667;0.165300 16 | 23430;0.181711;0.181200 17 | 24992;0.185489;0.183100 18 | 26554;0.194444;0.192100 19 | 28116;0.205200;0.204400 20 | 29678;0.199556;0.197300 21 | 31240;0.207511;0.206900 22 | 32802;0.202867;0.203100 23 | 34364;0.203578;0.202900 24 | 35926;0.198089;0.195500 25 | 37488;0.197511;0.195900 26 | 39050;0.210422;0.209800 27 | 40612;0.210622;0.208200 28 | 42174;0.210356;0.208200 29 | 43736;0.189178;0.189200 30 | 45298;0.199244;0.199900 31 | 46860;0.211533;0.209700 32 | 48422;0.206267;0.206800 33 | 49984;0.201467;0.203600 34 | 51546;0.207822;0.208800 35 | 53108;0.197422;0.200200 36 | 54670;0.213067;0.209200 37 | 56232;0.206222;0.202800 38 | -------------------------------------------------------------------------------- /experiments/e2.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10.py 3 | model: 4 | script_path: ../models/i-c3-f.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.01 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e2/ 11 | batch_size: 32 12 | epochs: 100 -------------------------------------------------------------------------------- /experiments/e2/validation-curve-accuracy-test.csv: -------------------------------------------------------------------------------- 1 | 0;0.109444;0.107200 2 | 1562;0.373911;0.347200 3 | 3124;0.397400;0.353500 4 | 4686;0.415467;0.347800 5 | 6248;0.414067;0.335500 6 | 7810;0.444222;0.348600 7 | 9372;0.435867;0.355200 8 | 10934;0.446111;0.347900 9 | 12496;0.430933;0.331300 10 | 14058;0.468822;0.359600 11 | 15620;0.424711;0.313200 12 | 17182;0.466800;0.348000 13 | 18744;0.476911;0.351900 14 | 20306;0.460489;0.350500 15 | 21868;0.483067;0.355700 16 | 23430;0.460867;0.339700 17 | 24992;0.469044;0.344800 18 | 26554;0.482889;0.349600 19 | 28116;0.454067;0.338500 20 | 29678;0.467244;0.347000 21 | 31240;0.491911;0.358200 22 | 32802;0.461422;0.330400 23 | 34364;0.489356;0.363900 24 | 35926;0.489222;0.351700 25 | 37488;0.428622;0.308900 26 | 39050;0.478644;0.359200 27 | 40612;0.460000;0.341700 28 | 42174;0.444178;0.343500 29 | 43736;0.458556;0.329600 30 | 45298;0.474000;0.340500 31 | -------------------------------------------------------------------------------- /experiments/e3.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100.py 3 | model: 4 | script_path: ../models/i-c3-f.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.01 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e3/ 11 | batch_size: 32 12 | epochs: 100 13 | -------------------------------------------------------------------------------- /experiments/e4.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100.py 3 | model: 4 | script_path: ../models/i-c8-m-c8-f.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.01 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e4-cifar100/ 11 | batch_size: 32 12 | epochs: 100 13 | -------------------------------------------------------------------------------- /experiments/e5-cifar10.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10.py 3 | model: 4 | script_path: ../models/i-c8-m-c8-f-f.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.001 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e5-cifar10/ 11 | batch_size: 32 12 | epochs: 100 13 | -------------------------------------------------------------------------------- /experiments/e5.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100.py 3 | model: 4 | script_path: ../models/i-c8-m-c8-f-f.py 5 | optimizer: 6 | script_path: ../optimizers/adamdef.py 7 | initial_lr: 0.001 8 | train: 9 | script_path: ../train/train.py 10 | artifacts_path: ../artifacts/e5/ 11 | batch_size: 32 12 | epochs: 100 13 | -------------------------------------------------------------------------------- /experiments/fast.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar10_keras.py 3 | model: 4 | script_path: ../models/sequential_keras_tiny.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/fast/ 11 | saveall: True 12 | batch_size: 32 13 | epochs: 10 14 | data_augmentation: 15 | samplewise_center: False 16 | samplewise_std_normalization: False 17 | rotation_range: 5 18 | width_shift_range: 0.15 19 | height_shift_range: 0.15 20 | horizontal_flip: True 21 | vertical_flip: False 22 | zoom_range: 0.2 23 | shear_range: 0.1 24 | channel_shift_range: 0.0 25 | featurewise_center: False 26 | zca_whitening: False 27 | evaluate: 28 | batch_size: 1000 29 | augmentation_factor: 32 30 | data_augmentation: 31 | samplewise_center: False 32 | samplewise_std_normalization: False 33 | rotation_range: 5 34 | width_shift_range: 0.15 35 | height_shift_range: 0.15 36 | horizontal_flip: True 37 | vertical_flip: False 38 | zoom_range: 0.2 39 | shear_range: 0.1 40 | channel_shift_range: 0.0 41 | featurewise_center: False 42 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/gtsrb-speed-less-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [0] 5 | coarse: False 6 | model: 7 | script_path: ../models/sequential_keras.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq_keras_speed-less-aug/ 14 | batch_size: 64 15 | epochs: 50 16 | data_augmentation: 17 | samplewise_center: False 18 | samplewise_std_normalization: False 19 | rotation_range: 10 20 | width_shift_range: 0.15 21 | height_shift_range: 0.15 22 | horizontal_flip: False 23 | vertical_flip: False 24 | hue_shift: 0.2 25 | saturation_scale: 0.2 26 | saturation_shift: 0.1 27 | value_scale: 0.2 28 | value_shift: 0.1 29 | zoom_range: 0.2 30 | shear_range: 0.1 31 | channel_shift_range: 0.1 32 | featurewise_center: False 33 | zca_whitening: False 34 | -------------------------------------------------------------------------------- /experiments/gtsrb-speed.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [0] 5 | coarse: False 6 | model: 7 | script_path: ../models/sequential_keras.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq_keras_speed/ 14 | batch_size: 64 15 | epochs: 50 16 | data_augmentation: 17 | samplewise_center: False 18 | samplewise_std_normalization: False 19 | rotation_range: 15 20 | width_shift_range: 0.15 21 | height_shift_range: 0.15 22 | horizontal_flip: False 23 | vertical_flip: False 24 | hue_shift: 0.2 25 | saturation_scale: 0.5 26 | saturation_shift: 0.2 27 | value_scale: 0.5 28 | value_shift: 0.2 29 | zoom_range: 0.5 30 | shear_range: 0.1 31 | channel_shift_range: 0.1 32 | featurewise_center: False 33 | zca_whitening: False 34 | -------------------------------------------------------------------------------- /experiments/gtsrb-warnings.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [2] 5 | coarse: False 6 | model: 7 | script_path: ../models/sequential_keras.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq_keras_warnings/ 14 | batch_size: 64 15 | epochs: 50 16 | data_augmentation: 17 | samplewise_center: False 18 | samplewise_std_normalization: False 19 | rotation_range: 15 20 | width_shift_range: 0.15 21 | height_shift_range: 0.15 22 | horizontal_flip: False 23 | vertical_flip: False 24 | hue_shift: 0.2 25 | saturation_scale: 0.5 26 | saturation_shift: 0.2 27 | value_scale: 0.5 28 | value_shift: 0.2 29 | zoom_range: 0.5 30 | shear_range: 0.1 31 | channel_shift_range: 0.1 32 | featurewise_center: False 33 | zca_whitening: False 34 | -------------------------------------------------------------------------------- /experiments/gtsrb_dense_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | model: 4 | script_path: ../models/densenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | batch_size: 64 11 | epochs: 50 12 | data_augmentation: False 13 | artifacts_path: ../artifacts/gtsrb_dense_keras/ 14 | -------------------------------------------------------------------------------- /experiments/gtsrb_seq2_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [] 5 | coarse: False 6 | model: 7 | script_path: ../models/sequential_updated.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq2_keras/ 14 | batch_size: 64 15 | epochs: 200 16 | data_augmentation: 17 | samplewise_center: False 18 | samplewise_std_normalization: False 19 | rotation_range: 15 20 | width_shift_range: 0.15 21 | height_shift_range: 0.15 22 | horizontal_flip: False 23 | vertical_flip: False 24 | hue_shift: 0.2 25 | saturation_scale: 0.5 26 | saturation_shift: 0.2 27 | value_scale: 0.5 28 | value_shift: 0.2 29 | zoom_range: 0.5 30 | shear_range: 0.1 31 | channel_shift_range: 0.1 32 | featurewise_center: False 33 | zca_whitening: False 34 | -------------------------------------------------------------------------------- /experiments/gtsrb_seq3-no-pool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [] 5 | coarse: False 6 | model: 7 | script_path: ../models/seq3-no-pooling.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq3-no-pooling/ 14 | batch_size: 64 15 | epochs: 200 16 | data_augmentation: 17 | samplewise_center: False 18 | samplewise_std_normalization: False 19 | rotation_range: 15 20 | width_shift_range: 0.15 21 | height_shift_range: 0.15 22 | horizontal_flip: False 23 | vertical_flip: False 24 | hue_shift: 0.2 25 | saturation_scale: 0.5 26 | saturation_shift: 0.2 27 | value_scale: 0.5 28 | value_shift: 0.2 29 | zoom_range: 0.5 30 | shear_range: 0.1 31 | channel_shift_range: 0.1 32 | featurewise_center: False 33 | zca_whitening: False 34 | -------------------------------------------------------------------------------- /experiments/gtsrb_seq_keras-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/gtsrb_seq_keras-aug/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/gtsrb_seq_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | subset: [] 5 | coarse: False 6 | model: 7 | script_path: ../models/sequential_keras.py 8 | optimizer: 9 | script_path: ../optimizers/adam_keras.py 10 | initial_lr: 0.0001 11 | train: 12 | script_path: ../train/train_keras.py 13 | artifacts_path: ../artifacts/gtsrb_seq_keras/ 14 | batch_size: 64 15 | epochs: 50 16 | data_augmentation: False 17 | -------------------------------------------------------------------------------- /experiments/gtsrb_seq_keras_root.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/gtsrb.py 3 | hierarchy_path: ../datasets/gtsrb-hierarchy.json 4 | model: 5 | script_path: ../models/sequential_keras.py 6 | optimizer: 7 | script_path: ../optimizers/adam_keras.py 8 | initial_lr: 0.0001 9 | train: 10 | script_path: ../train/train_keras.py 11 | artifacts_path: ../artifacts/gtsrb_seq_keras_root/ 12 | batch_size: 64 13 | epochs: 50 14 | data_augmentation: False 15 | -------------------------------------------------------------------------------- /experiments/hasy_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_baseline/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_dense.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/densenet.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_dense/ 11 | batch_size: 64 12 | epochs: 50 13 | data_augmentation: False 14 | -------------------------------------------------------------------------------- /experiments/hasy_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_linear/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_linear/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_exact.py 10 | artifacts_path: ../artifacts/hasy_opt_long/ 11 | batch_size: 64 12 | epochs: 92 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_prelu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_relu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_sigmoid.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_sigmoid/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_softmax.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_softmax/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_softsign/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_tanh/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_opt_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/optimized_vlrelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_opt_vlrelu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_prelu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_relu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_seq.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_seq/ 11 | batch_size: 64 12 | epochs: 50 13 | data_augmentation: False 14 | -------------------------------------------------------------------------------- /experiments/hasy_seq2.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/sequential_updated.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_seq2/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_seq3-no-pool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/seq3-no-pooling.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_seq3-no-pooling/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_seq3.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/seq3.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_seq3/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_seq_fast.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/sequential_keras_tiny.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_seq_keras_fast/ 11 | batch_size: 128 12 | epochs: 1 13 | data_augmentation: False 14 | -------------------------------------------------------------------------------- /experiments/hasy_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_sigmoid.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_sigmoid/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_softmax.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_softmax/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_softplus.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_softplus.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_softplus/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_softsign/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_tanh/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/hasy_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/hasy.py 3 | model: 4 | script_path: ../models/baseline_vlrelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/hasy_vlrelu/ 11 | batch_size: 64 12 | epochs: 200 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 5 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | -------------------------------------------------------------------------------- /experiments/mnist_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_baseline/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_linear/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_opt/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/baseline_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_prelu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/baseline_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_relu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_softsign/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/mnist_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/mnist.py 3 | model: 4 | script_path: ../models/baseline_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/mnist_tanh/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | zoom_range: 0.5 22 | shear_range: 0.1 23 | channel_shift_range: 0.1 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 5 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: False 36 | vertical_flip: False 37 | zoom_range: 0.2 38 | shear_range: 0.1 39 | channel_shift_range: 0.0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_baseline/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_linear/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_linear.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_linear.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_linear/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_exact.py 10 | artifacts_path: ../artifacts/stl10_opt_long/ 11 | batch_size: 64 12 | epochs: 116 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_prelu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_relu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_sigmoid.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_sigmoid/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_softmax.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_softmax/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_softplus.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_softplus.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_softplus/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_softsign/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_opt_tanh/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_opt_train_es.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_train_es.py 10 | artifacts_path: ../artifacts/stl10_opt_train_es/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_prelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_prelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_prelu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_relu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_relu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_relu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_sigmoid.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_sigmoid.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_sigmoid/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_softmax.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_softmax.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_softmax/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_softplus.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_softplus.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_softplus/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_softsign.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/softsign.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_softsign/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_tanh.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_tanh.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_tanh/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/stl10_vlrelu.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/stl10.py 3 | model: 4 | script_path: ../models/baseline_vlrelu.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/stl10_vlrelu/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/svhn_baseline.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/baseline.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_baseline/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: False 14 | evaluate: 15 | batch_size: 1000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 5 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0.2 26 | shear_range: 0.1 27 | channel_shift_range: 0.0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/svhn_opt.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_opt/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: False 14 | evaluate: 15 | batch_size: 1000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 5 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0.2 26 | shear_range: 0.1 27 | channel_shift_range: 0.0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/svhn_opt_long.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/optimized.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras_exact.py 10 | artifacts_path: ../artifacts/svhn_opt_long/ 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: False 14 | evaluate: 15 | batch_size: 1000 16 | augmentation_factor: 32 17 | data_augmentation: 18 | samplewise_center: False 19 | samplewise_std_normalization: False 20 | rotation_range: 5 21 | width_shift_range: 0.15 22 | height_shift_range: 0.15 23 | horizontal_flip: False 24 | vertical_flip: False 25 | zoom_range: 0.2 26 | shear_range: 0.1 27 | channel_shift_range: 0.0 28 | featurewise_center: False 29 | zca_whitening: False -------------------------------------------------------------------------------- /experiments/svhn_seq2.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/sequential_updated.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_seq2/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/svhn_seq3-no-pool.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/seq3-no-pooling.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_seq3-no-pooling/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/svhn_seq_keras-aug.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_seq_keras-aug/ 11 | batch_size: 64 12 | epochs: 300 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 15 17 | width_shift_range: 0.15 18 | height_shift_range: 0.15 19 | horizontal_flip: False 20 | vertical_flip: False 21 | hue_shift: 0.2 22 | saturation_scale: 0.5 23 | saturation_shift: 0.2 24 | value_scale: 0.5 25 | value_shift: 0.2 26 | zoom_range: 0.5 27 | shear_range: 0.1 28 | channel_shift_range: 0.1 29 | featurewise_center: False 30 | zca_whitening: False 31 | -------------------------------------------------------------------------------- /experiments/svhn_seq_keras.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/svhn.py 3 | model: 4 | script_path: ../models/sequential_keras.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: ../artifacts/svhn_seq_keras/ 11 | batch_size: 64 12 | epochs: 50 13 | data_augmentation: False 14 | -------------------------------------------------------------------------------- /experiments/tf-cifar10.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: datasets/cifar10.py 3 | model: 4 | script_path: models/tf-cifar.py 5 | optimizer: 6 | script_path: optimizers/adamdef.py 7 | initial_lr: 0.001 8 | train: 9 | script_path: train/train.py 10 | batch_size: 128 11 | epochs: 100 12 | -------------------------------------------------------------------------------- /jobs.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "cmd": "./run_training.py -f experiments/cifar10_seq2.yaml" 4 | }, 5 | { 6 | "cmd": "./run_training.py -f experiments/cifar100_seq2.yaml" 7 | }, 8 | { 9 | "cmd": "./run_training.py -f experiments/svhn_seq2.yaml" 10 | } 11 | ] -------------------------------------------------------------------------------- /misc/fix_keras_optimizer.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | """ 4 | Make keras 1.x models usable in keras 2.x. 5 | 6 | Run this when you get the following error: 7 | 8 | ValueError: Optimizer weight shape (512,) not compatible with provided weight shape (32,) 9 | """ 10 | 11 | import glob 12 | import h5py 13 | 14 | model_files = sorted(glob.glob('*.h5')) 15 | for model_file in model_files: 16 | print("Update '{}'".format(model_file)) 17 | with h5py.File(model_file, 'a') as f: 18 | if 'optimizer_weights' in f.keys(): 19 | del f['optimizer_weights'] 20 | -------------------------------------------------------------------------------- /models/mlp.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | """MLP model.""" 4 | 5 | import tensorflow as tf 6 | import tflearn 7 | from tflearn.layers.core import fully_connected 8 | 9 | 10 | def inference(images, dataset_meta): 11 | """ 12 | Build the CIFAR-10 model. 13 | 14 | Parameters 15 | ---------- 16 | images : tensor 17 | Images returned from distorted_inputs() or inputs(). 18 | dataset_meta : dict 19 | Has key 'n_classes' 20 | 21 | Returns 22 | ------- 23 | logits 24 | """ 25 | net = tf.reshape(images, [-1, 26 | dataset_meta['image_width'], 27 | dataset_meta['image_height'], 28 | dataset_meta['image_depth']]) 29 | net = tflearn.layers.core.flatten(net, name='Flatten') 30 | y_conv = fully_connected(net, dataset_meta['n_classes'], 31 | activation='softmax', 32 | weights_init='truncated_normal', 33 | bias_init='zeros', 34 | regularizer=None, 35 | weight_decay=0) 36 | return y_conv 37 | -------------------------------------------------------------------------------- /models/sequential_keras_tiny.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | """Create a sequential model.""" 4 | 5 | from keras import backend as K 6 | from keras.models import Sequential 7 | from keras.layers import Dropout, Flatten, Activation, Dense 8 | from keras.layers import Convolution2D, MaxPooling2D 9 | 10 | 11 | def create_model(nb_classes, input_shape, config=None): 12 | """Create a VGG-16 like model.""" 13 | model = Sequential() 14 | model.add(Convolution2D(4, (3, 3), padding='same', activation='relu', 15 | input_shape=input_shape)) 16 | model.add(MaxPooling2D(pool_size=(2, 2))) 17 | model.add(Convolution2D(4, (3, 3), padding='same', activation='relu')) 18 | model.add(MaxPooling2D(pool_size=(2, 2))) 19 | model.add(Flatten()) 20 | model.add(Dense(512, activation='relu')) 21 | model.add(Dropout(0.5)) 22 | model.add(Dense(nb_classes)) 23 | model.add(Activation('softmax')) 24 | return model 25 | 26 | if __name__ == '__main__': 27 | model = create_model(100, (32, 32, 3)) 28 | model.summary() 29 | -------------------------------------------------------------------------------- /msthesis_utils.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import numpy as np 4 | 5 | 6 | def make_mosaic(imgs, nrows, ncols, border=1, mode='tf'): 7 | """ 8 | Make mosaik. 9 | 10 | Given a set of images with all the same shape, makes a 11 | mosaic with nrows and ncols 12 | """ 13 | if mode == 'tf': 14 | imgs = imgs.transpose(2, 0, 1) 15 | imshape = imgs.shape[1:] 16 | 17 | if len(imgs.shape) == 4: 18 | if imgs.shape[-1] >= 3: 19 | channels = 3 20 | else: 21 | channels = imgs.shape[-1] 22 | else: 23 | channels = 1 24 | 25 | mosaic = np.zeros((nrows * imshape[0] + (nrows - 1) * border, 26 | ncols * imshape[1] + (ncols - 1) * border, 27 | channels), 28 | dtype=np.float32) 29 | 30 | paddedh = imshape[0] + border 31 | paddedw = imshape[1] + border 32 | for i in range(nrows * ncols): 33 | row = int(np.floor(i / ncols)) 34 | col = i % ncols 35 | 36 | mosaic[row * paddedh:row * paddedh + imshape[0], 37 | col * paddedw:col * paddedw + imshape[1], 0] = imgs[i] 38 | return mosaic.squeeze() 39 | -------------------------------------------------------------------------------- /optimizers/adam_keras.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | from keras.optimizers import Adam 4 | 5 | 6 | def get_optimizer(config): 7 | lr = config['optimizer']['initial_lr'] 8 | optimizer = Adam(lr=lr) # Using Adam instead of SGD to speed up training 9 | return optimizer 10 | -------------------------------------------------------------------------------- /optimizers/nesterov.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | from keras.optimizers import SGD 4 | 5 | 6 | def get_optimizer(config): 7 | optimizer = SGD(lr=config['optimizer']['initial_lr'], 8 | momentum=config['optimizer']['momentum'], 9 | nesterov=True) 10 | return optimizer 11 | -------------------------------------------------------------------------------- /optimizers/sgd.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | from keras.optimizers import SGD 4 | 5 | 6 | def get_optimizer(config): 7 | lr = config['optimizer']['initial_lr'] 8 | optimizer = SGD(lr=lr) # Using Adam instead of SGD to speed up training 9 | return optimizer 10 | -------------------------------------------------------------------------------- /other_models/imagenet-1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MartinThoma/msthesis-experiments/f86e344c972f2b61c3fa16eae523fd20303e8842/other_models/imagenet-1.jpg -------------------------------------------------------------------------------- /other_models/vgg16.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """VGG16 model for Keras.""" 3 | import keras 4 | 5 | model = keras.applications.VGG16() 6 | model.save("vgg16.h5") 7 | -------------------------------------------------------------------------------- /other_models/vgg16.yaml: -------------------------------------------------------------------------------- 1 | dataset: 2 | script_path: ../datasets/cifar100_keras.py 3 | model: 4 | script_path: ../models/vgg16.py 5 | optimizer: 6 | script_path: ../optimizers/adam_keras.py 7 | initial_lr: 0.0001 8 | train: 9 | script_path: ../train/train_keras.py 10 | artifacts_path: . 11 | batch_size: 64 12 | epochs: 1000 13 | data_augmentation: 14 | samplewise_center: False 15 | samplewise_std_normalization: False 16 | rotation_range: 0 17 | width_shift_range: 0.1 18 | height_shift_range: 0.1 19 | horizontal_flip: True 20 | vertical_flip: False 21 | zoom_range: 0 22 | shear_range: 0 23 | channel_shift_range: 0 24 | featurewise_center: False 25 | zca_whitening: False 26 | evaluate: 27 | batch_size: 1000 28 | augmentation_factor: 32 29 | data_augmentation: 30 | samplewise_center: False 31 | samplewise_std_normalization: False 32 | rotation_range: 0 33 | width_shift_range: 0.15 34 | height_shift_range: 0.15 35 | horizontal_flip: True 36 | vertical_flip: False 37 | zoom_range: 0 38 | shear_range: 0 39 | channel_shift_range: 0 40 | featurewise_center: False 41 | zca_whitening: False -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | appdirs==1.4.3 2 | cycler==0.10.0 3 | funcsigs==1.0.2 4 | functools32==3.2.3.post2 5 | graphviz==0.6 6 | h5py==2.7.0 7 | Keras==2.0.2 8 | matplotlib==2.0.0 9 | mock==2.0.0 10 | natsort==5.0.1 11 | numpy==1.12.1 12 | olefile==0.44 13 | packaging==16.8 14 | pandas==0.19.2 15 | pbr==2.0.0 16 | Pillow==4.0.0 17 | protobuf==3.2.0 18 | pydot==1.2.3 19 | pyparsing==2.2.0 20 | python-dateutil==2.6.0 21 | python-nmap==0.6.1 22 | pytz==2017.2 23 | PyYAML==3.12 24 | requests==2.13.0 25 | scapy==2.3.3 26 | scikit-learn==0.18.1 27 | scipy==0.19.0 28 | seaborn==0.7.1 29 | six==1.10.0 30 | sklearn==0.0 31 | subprocess32==3.2.7 32 | tensorflow-gpu==1.0.1 33 | Theano==0.9.0 34 | tqdm==4.11.2 35 | -------------------------------------------------------------------------------- /sgdr.py: -------------------------------------------------------------------------------- 1 | import math 2 | import keras 3 | 4 | def lr(epoch,maxlr,minlr,t0=5,tm=2): 5 | tz=t0 6 | tcur=0 7 | for i in range(epoch): 8 | if tcur>=tz: 9 | tcur=0 10 | tz=int(tz*tm) 11 | else: 12 | tcur+=1 13 | nowlr = minlr+0.5*(maxlr-minlr)*(1+math.cos(float(tcur)/tz*math.pi)) 14 | print('lr:{:.6f}, @ep {}, phase:{}/{}'.format(nowlr,epoch,tcur,tz)) 15 | return nowlr 16 | 17 | def gen_scheduler(minlr=1e-4,maxlr=0.05,t0=5,tm=2): # https://arxiv.org/pdf/1608.03983.pdf 18 | print('generating SGDR: {}