├── .gitignore ├── CONTRIBUTING.md ├── LICENSE ├── README.md ├── build_label_map.py ├── build_tfrecords.py ├── convert_imagenet.py ├── evaluate_checkpoints.py ├── evaluate_model.py ├── lib ├── __init__.py ├── data_provider.py ├── dataset_utils.py ├── hparams.py ├── networks.py ├── our_framework.py ├── paths.py ├── ssl_framework.py ├── ssl_utils.py └── tf_utils.py ├── requirements.txt ├── run-uasd └── cifar10-4000.yml ├── runs ├── figure-2-cifar10-4000-fullysup-olna.yml ├── figure-2-cifar10-4000-mean-teacher-ol0.yml ├── figure-2-cifar10-4000-mean-teacher-ol1.yml ├── figure-2-cifar10-4000-mean-teacher-ol2.yml ├── figure-2-cifar10-4000-mean-teacher-ol3.yml ├── figure-2-cifar10-4000-mean-teacher-ol4.yml ├── figure-2-cifar10-4000-pi-model-ol0.yml ├── figure-2-cifar10-4000-pi-model-ol1.yml ├── figure-2-cifar10-4000-pi-model-ol2.yml ├── figure-2-cifar10-4000-pi-model-ol3.yml ├── figure-2-cifar10-4000-pi-model-ol4.yml ├── figure-2-cifar10-4000-pseudo-label-ol0.yml ├── figure-2-cifar10-4000-pseudo-label-ol1.yml ├── figure-2-cifar10-4000-pseudo-label-ol2.yml ├── figure-2-cifar10-4000-pseudo-label-ol3.yml ├── figure-2-cifar10-4000-pseudo-label-ol4.yml ├── figure-2-cifar10-4000-vat-ol0.yml ├── figure-2-cifar10-4000-vat-ol1.yml ├── figure-2-cifar10-4000-vat-ol2.yml ├── figure-2-cifar10-4000-vat-ol3.yml ├── figure-2-cifar10-4000-vat-ol4.yml ├── figure-3-cifar10-1000-mean-teacher.yml ├── figure-3-cifar10-1000-pi-model.yml ├── figure-3-cifar10-1000-pseudo-label.yml ├── figure-3-cifar10-1000-vat.yml ├── figure-3-cifar10-2000-mean-teacher.yml ├── figure-3-cifar10-2000-pi-model.yml ├── figure-3-cifar10-2000-pseudo-label.yml ├── figure-3-cifar10-2000-vat.yml ├── figure-3-cifar10-250-mean-teacher.yml ├── figure-3-cifar10-250-pi-model.yml ├── figure-3-cifar10-250-pseudo-label.yml ├── figure-3-cifar10-250-vat.yml ├── figure-3-cifar10-4000-mean-teacher.yml ├── figure-3-cifar10-4000-pi-model.yml ├── figure-3-cifar10-4000-pseudo-label.yml ├── figure-3-cifar10-4000-vat.yml ├── figure-3-cifar10-500-mean-teacher.yml ├── figure-3-cifar10-500-pi-model.yml ├── figure-3-cifar10-500-pseudo-label.yml ├── figure-3-cifar10-500-vat.yml ├── figure-3-cifar10-8000-mean-teacher.yml ├── figure-3-cifar10-8000-pi-model.yml ├── figure-3-cifar10-8000-pseudo-label.yml ├── figure-3-cifar10-8000-vat.yml ├── figure-3-svhn-1000-mean-teacher.yml ├── figure-3-svhn-1000-pi-model.yml ├── figure-3-svhn-1000-pseudo-label.yml ├── figure-3-svhn-1000-vat.yml ├── figure-3-svhn-2000-mean-teacher.yml ├── figure-3-svhn-2000-pi-model.yml ├── figure-3-svhn-2000-pseudo-label.yml ├── figure-3-svhn-2000-vat.yml ├── figure-3-svhn-250-mean-teacher.yml ├── figure-3-svhn-250-pi-model.yml ├── figure-3-svhn-250-pseudo-label.yml ├── figure-3-svhn-250-vat.yml ├── figure-3-svhn-4000-mean-teacher.yml ├── figure-3-svhn-4000-pi-model.yml ├── figure-3-svhn-4000-pseudo-label.yml ├── figure-3-svhn-4000-vat.yml ├── figure-3-svhn-500-mean-teacher.yml ├── figure-3-svhn-500-pi-model.yml ├── figure-3-svhn-500-pseudo-label.yml ├── figure-3-svhn-500-vat.yml ├── figure-3-svhn-8000-mean-teacher.yml ├── figure-3-svhn-8000-pi-model.yml ├── figure-3-svhn-8000-pseudo-label.yml ├── figure-3-svhn-8000-vat.yml ├── figure-4-svhn-1000-mean-teacher-unl10000.yml ├── figure-4-svhn-1000-mean-teacher-unl160000.yml ├── figure-4-svhn-1000-mean-teacher-unl20000.yml ├── figure-4-svhn-1000-mean-teacher-unl320000.yml ├── figure-4-svhn-1000-mean-teacher-unl40000.yml ├── figure-4-svhn-1000-mean-teacher-unl531131.yml ├── figure-4-svhn-1000-mean-teacher-unl80000.yml ├── figure-4-svhn-1000-pi-model-unl10000.yml ├── figure-4-svhn-1000-pi-model-unl160000.yml ├── figure-4-svhn-1000-pi-model-unl20000.yml ├── figure-4-svhn-1000-pi-model-unl320000.yml ├── figure-4-svhn-1000-pi-model-unl40000.yml ├── figure-4-svhn-1000-pi-model-unl531131.yml ├── figure-4-svhn-1000-pi-model-unl80000.yml ├── figure-4-svhn-1000-pseudo-label-unl10000.yml ├── figure-4-svhn-1000-pseudo-label-unl160000.yml ├── figure-4-svhn-1000-pseudo-label-unl20000.yml ├── figure-4-svhn-1000-pseudo-label-unl320000.yml ├── figure-4-svhn-1000-pseudo-label-unl40000.yml ├── figure-4-svhn-1000-pseudo-label-unl531131.yml ├── figure-4-svhn-1000-pseudo-label-unl80000.yml ├── figure-4-svhn-1000-vat-unl10000.yml ├── figure-4-svhn-1000-vat-unl160000.yml ├── figure-4-svhn-1000-vat-unl20000.yml ├── figure-4-svhn-1000-vat-unl320000.yml ├── figure-4-svhn-1000-vat-unl40000.yml ├── figure-4-svhn-1000-vat-unl531131.yml ├── figure-4-svhn-1000-vat-unl80000.yml ├── section-4-3-cifar-filtered-file-tuning.yml ├── section-4-3-cifar-fine-tuning.yml ├── section-4-3-filtered-imagenet-pre-training.yml ├── section-4-3-imagenet-pre-training.yml ├── table-1-cifar10-4000-fullysup.yml ├── table-1-cifar10-4000-mean-teacher.yml ├── table-1-cifar10-4000-pi-model.yml ├── table-1-cifar10-4000-pseudo-label.yml ├── table-1-cifar10-4000-vat-em.yml ├── table-1-cifar10-4000-vat.yml ├── table-1-svhn-1000-fullysup.yml ├── table-1-svhn-1000-mean-teacher.yml ├── table-1-svhn-1000-pi-model.yml ├── table-1-svhn-1000-pseudo-label.yml ├── table-1-svhn-1000-vat-em.yml └── table-1-svhn-1000-vat.yml ├── third_party └── vat │ ├── LICENSE │ ├── __init__.py │ └── vat_utils.py ├── train_model.py └── train_model_uasd.py /.gitignore: -------------------------------------------------------------------------------- 1 | ### Initial file generated from http://gitignore.io, with additional modifications. 2 | 3 | ### Emacs ### 4 | # -*- mode: gitignore; -*- 5 | *~ 6 | \#*\# 7 | /.emacs.desktop 8 | /.emacs.desktop.lock 9 | *.elc 10 | auto-save-list 11 | tramp 12 | .\#* 13 | 14 | # Org-mode 15 | .org-id-locations 16 | *_archive 17 | 18 | # flymake-mode 19 | *_flymake.* 20 | 21 | # eshell files 22 | /eshell/history 23 | /eshell/lastdir 24 | 25 | # elpa packages 26 | /elpa/ 27 | 28 | # reftex files 29 | *.rel 30 | 31 | # AUCTeX auto folder 32 | /auto/ 33 | 34 | # cask packages 35 | .cask/ 36 | 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144 | instance/ 145 | .webassets-cache 146 | 147 | # Scrapy stuff: 148 | .scrapy 149 | 150 | # Sphinx documentation 151 | docs/_build/ 152 | 153 | # PyBuilder 154 | target/ 155 | 156 | # Jupyter Notebook 157 | 158 | # pyenv 159 | .python-version 160 | 161 | # celery beat schedule file 162 | celerybeat-schedule 163 | 164 | # SageMath parsed files 165 | *.sage.py 166 | 167 | # Environments 168 | .env 169 | .venv 170 | env/ 171 | venv/ 172 | ENV/ 173 | env.bak/ 174 | venv.bak/ 175 | 176 | # Spyder project settings 177 | .spyderproject 178 | .spyproject 179 | 180 | # Rope project settings 181 | .ropeproject 182 | 183 | # mkdocs documentation 184 | /site 185 | 186 | # mypy 187 | .mypy_cache/ 188 | 189 | ### Python Patch ### 190 | .venv/ 191 | 192 | ### Vim ### 193 | # Swap 194 | [._]*.s[a-v][a-z] 195 | [._]*.sw[a-p] 196 | [._]s[a-rt-v][a-z] 197 | [._]ss[a-gi-z] 198 | [._]sw[a-p] 199 | 200 | # Session 201 | Session.vim 202 | 203 | # Temporary 204 | .netrwhist 205 | # Auto-generated tag files 206 | tags 207 | # Persistent undo 208 | [._]*.un~ 209 | 210 | # The actual data 211 | data/imagenet_32* 212 | data/cifar10/*.tfrecords 213 | data/svhn/*.tfrecords 214 | 215 | # The experiment outputs 216 | experiments/* 217 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # How to Contribute 2 | 3 | We'd love to accept your patches and contributions to this project. There are 4 | just a few small guidelines you need to follow. 5 | 6 | ## Contributor License Agreement 7 | 8 | Contributions to this project must be accompanied by a Contributor License 9 | Agreement. You (or your employer) retain the copyright to your contribution; 10 | this simply gives us permission to use and redistribute your contributions as 11 | part of the project. Head over to to see 12 | your current agreements on file or to sign a new one. 13 | 14 | You generally only need to submit a CLA once, so if you've already submitted one 15 | (even if it was for a different project), you probably don't need to do it 16 | again. 17 | 18 | ## Code reviews 19 | 20 | All submissions, including submissions by project members, require review. We 21 | use GitHub pull requests for this purpose. Consult 22 | [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more 23 | information on using pull requests. 24 | 25 | ## Community Guidelines 26 | 27 | This project follows [Google's Open Source Community 28 | Guidelines](https://opensource.google.com/conduct/). -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ssl-class-mismatch 2 | 3 | This repository contains the code for 4 | [Semi-Supervised Learning under Class Distribution Mismatch](https://yanbeic.github.io/Doc/AAAI20-ChenY.pdf), which is built upon the implementation from [Realistic Evaluation of Deep Semi-Supervised Learning Algorithms](https://arxiv.org/abs/1804.09170). 5 | 6 | The code is designed to run on Python 3 using the dependencies listed in `requirements.txt`. 7 | You can install the dependencies by running `pip3 install -r requirements.txt`. 8 | 9 | # Prepare datasets 10 | 11 | For SVHN and CIFAR-10, we provide scripts to automatically download and preprocess the data. 12 | We also provide a script to create "label maps", which specify which entries of the dataset should be treated as labeled and unlabeled. Both of these scripts use an explicitly chosen random seed, so the same dataset order and label maps will be created each time. The random seeds can be overridden, for example to test robustness to different labeled splits. 13 | Run those scripts as follows: 14 | 15 | ```sh 16 | python3 build_tfrecords.py --dataset_name=cifar10 17 | python3 build_label_map.py --dataset_name=cifar10 18 | python3 build_tfrecords.py --dataset_name=svhn 19 | python3 build_label_map.py --dataset_name=svhn 20 | ``` 21 | 22 | For ImageNet 32x32 (only used in the fine-tuning experiment), you'll first need to download the 32x32 version of the ImageNet dataset by following the instructions [here](https://patrykchrabaszcz.github.io/Imagenet32/). 23 | Unzip the resulting files and put them in a directory called 'data/imagenet_32'. 24 | You'll then need to convert those files (which are pickle files) into .npy files. 25 | You can do this by executing: 26 | 27 | ```sh 28 | mkdir data/imagenet_32 29 | unzip Imagenet32_train.zip -d data/imagenet_32 30 | unzip Imagenet32_val.zip -d data/imagenet_32 31 | python3 convert_imagenet.py 32 | ``` 33 | 34 | Then you can build the TFRecord files like so: 35 | 36 | ```sh 37 | python3 build_tfrecords.py --dataset_name=imagenet_32 38 | ``` 39 | 40 | ImageNet32x32 is the only dataset which must be downloaded manually, due to licensing issues. 41 | 42 | # Running experiments 43 | 44 | All of the experiments in our paper are accompanied by a .yml file in `runs/`.These .yml files are intended to be used with [tmuxp](https://github.com/tmux-python/tmuxp), which is a session manager for tmux. 45 | They essentially provide a simple way to create a tmux session with all of the relevant tasks running (model training and evaluation). 46 | 47 | For example, for the UASD model in [Semi-Supervised Learning under Class Distribution Mismatch](https://yanbeic.github.io/Doc/AAAI20-ChenY.pdf), you could run 48 | 49 | ```sh 50 | tmuxp load run-uasd/cifar10-4000.yml 51 | ``` 52 | 53 | If you want to run an experiment evaluating VAT with 500 labels as shown in Figure 3, you could run 54 | 55 | ```sh 56 | tmuxp load runs/figure-3-svhn-500-vat.yml 57 | ``` 58 | 59 | Of course, you can also run the code without using tmuxp. 60 | Each .yml file specifies the commands needed for running each experiment. 61 | For example, the file listed above `runs/figure-3-svhn-500-vat.yml` runs 62 | 63 | ```sh 64 | CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --n_labeled=500 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_train.log 65 | CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_test.log 66 | CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_valid.log 67 | CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_train.log 68 | ``` 69 | 70 | Note that these commands are formulated to write out results to `/mnt/experiment-logs`. 71 | -------------------------------------------------------------------------------- /convert_imagenet.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """Converts pickled imagenet_32x32 files to .npy files. 18 | 19 | The default imagenet_32x32 data files are stored in Python 3 20 | pickly encoding. 21 | 22 | The rest of our code is in Python 2, so we have a separate script that 23 | just deals with this issue separately. 24 | 25 | You can execute it as: 26 | 27 | python3 convert_imagenet.py 28 | 29 | after which you should no longer have to manually deal with imagenet. 30 | """ 31 | import os 32 | import numpy as np 33 | import pickle 34 | 35 | 36 | _DATA_DIR = "data/imagenet_32/" 37 | 38 | 39 | def unpickle(filename): 40 | with open(filename, "rb") as fo: 41 | dict = pickle.load(fo) 42 | return dict 43 | 44 | 45 | train_file_names = ["train_data_batch_" + str(idx) for idx in range(1, 11)] 46 | val_file_names = ["val_data"] 47 | for file_name in train_file_names + val_file_names: 48 | data = unpickle(os.path.join(_DATA_DIR, file_name)) 49 | image_file_name = file_name + "_image" 50 | label_file_name = file_name + "_label" 51 | np.save(os.path.join(_DATA_DIR, image_file_name), data["data"]) 52 | np.save(os.path.join(_DATA_DIR, label_file_name), np.array(data["labels"])) 53 | -------------------------------------------------------------------------------- /evaluate_checkpoints.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """Evaluate the model. 18 | 19 | This script will loop until it has seen the final checkpoint, 20 | waiting for new checkpoints and evaluating the model 21 | on the test set or the validation set using those new checkpoints. 22 | """ 23 | 24 | from __future__ import division 25 | import random 26 | import sys 27 | from absl import app 28 | from absl import flags 29 | import numpy as np 30 | import tensorflow as tf 31 | from absl import logging 32 | from lib import dataset_utils 33 | from lib import hparams 34 | from lib.ssl_framework import SSLFramework 35 | from lib import networks 36 | 37 | 38 | # Flags for model training 39 | # Evalutation binary never needs to know secondary dataset name or 40 | # the mixing factor. 41 | flags.DEFINE_string( 42 | "hparam_string", None, "String from which we parse hparams." 43 | ) 44 | flags.DEFINE_string( 45 | "primary_dataset_name", "svhn", "Name of dataset containing primary data." 46 | ) 47 | flags.DEFINE_string("split", "test", "train or test or valid.") 48 | flags.DEFINE_integer("examples_to_take", 100, "Number of examples to use.") 49 | flags.DEFINE_integer("num_evals", 10, "Total number of evals to run") 50 | flags.DEFINE_integer( 51 | "shuffle_buffer_size", 1000, "Size of the shuffle buffer." 52 | ) 53 | flags.DEFINE_integer( 54 | "training_length", 500000, "number of steps to train for." 55 | ) 56 | flags.DEFINE_string( 57 | "consistency_model", "mean_teacher", "Which consistency model to use." 58 | ) 59 | flags.DEFINE_string( 60 | "zca_input_file_path", 61 | "", 62 | "Path to ZCA input statistics. '' means don't ZCA.", 63 | ) 64 | 65 | flags.DEFINE_string( 66 | "checkpoints", 67 | None, 68 | "A comma delimited list of checkpoint file prefixes to " 69 | "evaluate and then exit, e.g. " 70 | '"/dir1/model.ckpt-97231,/dir2/model.ckpt-1232".', 71 | ) 72 | flags.mark_flag_as_required("checkpoints") 73 | 74 | FLAGS = flags.FLAGS 75 | 76 | # Dummy value that is more likely to alert us to bugs that might arise 77 | # from looking at the value of n_labeled during eval. 78 | _EVAL_N_LABELED = -4000000000 79 | 80 | 81 | def evaluate(hparams): 82 | """Evalute a set of checkpoints multiple times.""" 83 | accuracies = {} 84 | for explicit_checkpoint_path in FLAGS.checkpoints.split(","): 85 | logging.info(explicit_checkpoint_path) 86 | accuracies[explicit_checkpoint_path] = [] 87 | 88 | tf.reset_default_graph() 89 | coord = tf.train.Coordinator() 90 | with tf.device("/cpu:0"): 91 | images, labels = make_images_and_labels_tensors() 92 | 93 | # Construct model to register global variables. 94 | ssl_framework = SSLFramework( 95 | networks.wide_resnet, 96 | hparams, 97 | images, 98 | labels, 99 | make_train_tensors=False, 100 | consistency_model=FLAGS.consistency_model, 101 | zca_input_file_path=FLAGS.zca_input_file_path, 102 | ) 103 | new_saver = tf.train.Saver(tf.global_variables()) 104 | 105 | with tf.Session() as sess: 106 | new_saver.restore(sess, explicit_checkpoint_path) 107 | 108 | # For some reason, we need to initialize the tables again 109 | sess.run(tf.tables_initializer()) 110 | 111 | for _ in range(FLAGS.num_evals): 112 | # Start the input enqueue threads 113 | tf.train.start_queue_runners(sess=sess, coord=coord) 114 | 115 | # Evaluate the model 116 | all_images, all_labels = sess.run([images, labels]) 117 | 118 | feed_dict = { 119 | ssl_framework.inputs: all_images, 120 | ssl_framework.is_training: False, 121 | } 122 | output = sess.run(ssl_framework.logits, feed_dict=feed_dict) 123 | 124 | correct = np.sum(np.argmax(output, 1) == all_labels) 125 | accuracy = float(correct) / float(FLAGS.examples_to_take) 126 | 127 | logging.info("Accuracy: %f", accuracy) 128 | accuracies[explicit_checkpoint_path].append(accuracy) 129 | 130 | logging.info(accuracies) 131 | 132 | 133 | def make_images_and_labels_tensors(): 134 | """Make tensors for loading images and labels from dataset.""" 135 | 136 | with tf.name_scope("input"): 137 | dataset = dataset_utils.get_dataset( 138 | FLAGS.primary_dataset_name, FLAGS.split 139 | ) 140 | # Shuffle with the same seed to allow comparisons between models on the same subsampled validation sets. 141 | dataset = dataset.shuffle(FLAGS.shuffle_buffer_size, seed=0) 142 | dataset = dataset.batch(FLAGS.examples_to_take) 143 | 144 | # Get the actual results from the iterator 145 | iterator = dataset.make_initializable_iterator() 146 | tf.add_to_collection( 147 | tf.GraphKeys.TABLE_INITIALIZERS, iterator.initializer 148 | ) 149 | images, labels, _ = iterator.get_next() 150 | images = tf.cast(images, tf.float32) 151 | 152 | return images, labels 153 | 154 | 155 | def main(_): 156 | hps = hparams.get_hparams( 157 | FLAGS.primary_dataset_name, FLAGS.consistency_model 158 | ) 159 | if FLAGS.hparam_string: 160 | hps.parse(FLAGS.hparam_string) 161 | evaluate(hps) 162 | 163 | 164 | if __name__ == "__main__": 165 | app.run(main) 166 | -------------------------------------------------------------------------------- /lib/__init__.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | -------------------------------------------------------------------------------- /lib/hparams.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """Hyperparameter class for Pi-model and Mean Teacher models. 18 | 19 | This file contains functions to create default hyperparameters 20 | for various datasets and configuration for training semisupervised 21 | learning models with the pi-model or mean teacher techniques. 22 | """ 23 | 24 | from __future__ import absolute_import 25 | from __future__ import division 26 | 27 | import tensorflow as tf 28 | 29 | # training iterations: 500000 30 | base = dict( 31 | warmup_steps=200000, 32 | initial_lr=3e-3, 33 | horizontal_flip=False, 34 | random_translation=True, 35 | gaussian_noise=True, 36 | consistency_func="forward_kl", 37 | max_cons_multiplier=1.0, 38 | entropy_penalty_multiplier=0., 39 | ema_factor=0.95, 40 | vat_epsilon=6.0, # Norm length of perturbation 41 | vat_xi=1e-6, # Small constant for computing the finite difference in VAT 42 | lr_decay_steps=400000, 43 | lr_decay_rate=0.2, 44 | num_classes=10, 45 | width=2, 46 | num_residual_units=4, 47 | lrelu_leakiness=0.1, 48 | pseudo_label_threshold=0.95, 49 | ) 50 | 51 | 52 | def merge_dicts(x, y): 53 | z = x.copy() 54 | z.update(y) 55 | return z 56 | 57 | 58 | # HParam overrides for different consistency functions 59 | consistency_model_overrides = dict( 60 | ours=dict(initial_lr=1e-3, max_cons_multiplier=8.0), 61 | temporal=dict( 62 | consistency_func="mean_squared_error", 63 | max_cons_multiplier=8.0, 64 | initial_lr=4e-4, 65 | ), 66 | mean_teacher=dict( 67 | consistency_func="mean_squared_error", 68 | max_cons_multiplier=8.0, 69 | initial_lr=4e-4, 70 | ), 71 | swa=dict( 72 | consistency_func="mean_squared_error", 73 | max_cons_multiplier=8.0, 74 | initial_lr=1e-3, 75 | ), 76 | vat=dict(consistency_func="forward_kl", max_cons_multiplier=0.3), 77 | pi_model=dict( 78 | consistency_func="mean_squared_error", 79 | max_cons_multiplier=20.0, 80 | initial_lr=3e-4, 81 | ), 82 | pseudo_label=dict( 83 | consistency_func="reverse_kl", max_cons_multiplier=1.0, initial_lr=3e-4 84 | ), 85 | none=dict(max_cons_multiplier=0.), 86 | ) 87 | 88 | # HParam overrides for different datasets 89 | cifar10_overrides = dict(horizontal_flip=True) 90 | 91 | cifar100_overrides = dict(horizontal_flip=True, gaussian_noise=False) 92 | 93 | cifar_unnormalized_overrides = cifar10_overrides 94 | 95 | imagenet_overrides = dict( 96 | horizontal_flip=True, #num_classes=1000, 97 | random_translation=False, 98 | gaussian_noise=False, 99 | ) 100 | tinyimagenet_overrides = dict( 101 | horizontal_flip=True, #num_classes=1000, random_translation=False, 102 | gaussian_noise=False, 103 | ) 104 | cifar100_tinyimagenet_overrides = dict(horizontal_flip=True, gaussian_noise=False) 105 | 106 | svhn_overrides = dict(gaussian_noise=False, vat_epsilon=1.0) 107 | dataset_overrides = dict( 108 | cifar10=cifar10_overrides, 109 | cifar_unnormalized=cifar_unnormalized_overrides, 110 | imagenet=imagenet_overrides, 111 | imagenet_32=imagenet_overrides, 112 | imagenet_64=imagenet_overrides, 113 | tinyimagenet_32=tinyimagenet_overrides, 114 | svhn=svhn_overrides, 115 | cifar100=cifar100_overrides, 116 | cifar100_tinyimagenet=cifar100_tinyimagenet_overrides, 117 | ) 118 | 119 | 120 | def get_hparams(dataset, consistency_model): 121 | 122 | return tf.contrib.training.HParams( 123 | **merge_dicts( 124 | merge_dicts(base, dataset_overrides[dataset]), 125 | consistency_model_overrides[consistency_model], 126 | ) 127 | ) 128 | -------------------------------------------------------------------------------- /lib/paths.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """Dataset paths used in open-source version of this codebase.""" 18 | 19 | TRAIN_DIR = "./data" 20 | IMAGENET_DATA_DIR = "./data/imagenet-2012-tfrecord" 21 | IMAGENET_32_DATA_DIR = "./data/imagenet_32" 22 | 23 | BUILD_TFRECORDS_DOWNLOAD_PATH = "./data/" 24 | BUILD_TFRECORDS_DATA_PREFIX = "./data/" 25 | RAW_IMAGENET_PATH = "./data/raw/imagenet/" 26 | LABEL_MAP_PATH = "./data/" 27 | -------------------------------------------------------------------------------- /lib/ssl_utils.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """Utilities for doing semisupervised learning.""" 18 | import tensorflow as tf 19 | 20 | 21 | def entropy_from_logits(logits): 22 | """Computes entropy from classifier logits. 23 | 24 | Args: 25 | logits: a tensor of shape (batch_size, class_count) representing the 26 | logits of a classifier. 27 | 28 | Returns: 29 | A tensor of shape (batch_size,) of floats giving the entropies 30 | batchwise. 31 | """ 32 | distribution = tf.contrib.distributions.Categorical(logits=logits) 33 | return distribution.entropy() 34 | 35 | 36 | def entropy_penalty(logits, entropy_penalty_multiplier, mask): 37 | """Computes an entropy penalty using the classifier logits. 38 | 39 | Args: 40 | logits: a tensor of shape (batch_size, class_count) representing the 41 | logits of a classifier. 42 | entropy_penalty_multiplier: A float by which the entropy is multiplied. 43 | mask: A tensor that optionally masks out some of the costs. 44 | 45 | Returns: 46 | The mean entropy penalty 47 | """ 48 | entropy = entropy_from_logits(logits) 49 | losses = entropy * entropy_penalty_multiplier 50 | losses *= tf.cast(mask, tf.float32) 51 | return tf.reduce_mean(losses) 52 | 53 | 54 | def kl_divergence_from_logits(logits_a, logits_b): 55 | """Gets KL divergence from logits parameterizing categorical distributions. 56 | 57 | Args: 58 | logits_a: A tensor of logits parameterizing the first distribution. 59 | logits_b: A tensor of logits parameterizing the second distribution. 60 | 61 | Returns: 62 | The (batch_size,) shaped tensor of KL divergences. 63 | """ 64 | distribution1 = tf.contrib.distributions.Categorical(logits=logits_a) 65 | distribution2 = tf.contrib.distributions.Categorical(logits=logits_b) 66 | return tf.contrib.distributions.kl_divergence(distribution1, distribution2) 67 | 68 | 69 | def mse_from_logits(output_logits, target_logits): 70 | """Computes MSE between predictions associated with logits. 71 | 72 | Args: 73 | output_logits: A tensor of logits from the primary model. 74 | target_logits: A tensor of logits from the secondary model. 75 | 76 | Returns: 77 | The mean MSE 78 | """ 79 | diffs = tf.nn.softmax(output_logits) - tf.nn.softmax(target_logits) 80 | squared_diffs = tf.square(diffs) 81 | return tf.reduce_mean(squared_diffs, -1) 82 | 83 | 84 | def diff_costs(mode, diff_mask, output_logits, target_logits, diff_multiplier): 85 | """Computes diff costs given logits. 86 | 87 | Args: 88 | output_logits: A tensor of logits from the primary model. 89 | target_logits: A tensor of logits from the secondary model. 90 | diff_multiplier : A scalar multiplier for the cost. 91 | diff_mask: A tensor that optionally masks out some of the costs. 92 | mode: A string controlling the specific cost that is used. 93 | 94 | Returns: 95 | The mean cost 96 | 97 | Raises: 98 | ValueError: if the mode is not supported. 99 | """ 100 | if mode == "forward_kl": 101 | losses = kl_divergence_from_logits(output_logits, target_logits) 102 | elif mode == "reverse_kl": 103 | losses = kl_divergence_from_logits(target_logits, output_logits) 104 | elif mode == "mean_squared_error": 105 | losses = mse_from_logits(output_logits, target_logits) 106 | else: 107 | raise ValueError("Unsupported mode: {}".format(mode)) 108 | 109 | losses *= diff_multiplier 110 | losses *= tf.cast(diff_mask, tf.float32) 111 | return tf.reduce_mean(losses) 112 | -------------------------------------------------------------------------------- /lib/tf_utils.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python3 2 | # 3 | # Copyright 2018 Google LLC 4 | # 5 | # Licensed under the Apache License, Version 2.0 (the "License"); 6 | # you may not use this file except in compliance with the License. 7 | # You may obtain a copy of the License at 8 | # 9 | # http://www.apache.org/licenses/LICENSE-2.0 10 | # 11 | # Unless required by applicable law or agreed to in writing, software 12 | # distributed under the License is distributed on an "AS IS" BASIS, 13 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 | # See the License for the specific language governing permissions and 15 | # limitations under the License. 16 | 17 | """A set of small TF utility functions shared between train and evaluate.""" 18 | 19 | from __future__ import absolute_import 20 | from __future__ import division 21 | from __future__ import print_function 22 | 23 | import tensorflow as tf 24 | 25 | 26 | def hash_float(x, big_num=1000 * 1000): 27 | """Hash a tensor 'x' into a floating point number in the range [0, 1).""" 28 | return tf.cast( 29 | tf.string_to_hash_bucket_fast(x, big_num), tf.float32 30 | ) / tf.constant(float(big_num)) 31 | 32 | 33 | def make_set_filter_fn(elements): 34 | """Constructs a TensorFlow "set" data structure. 35 | 36 | Note that sets returned by this function are uninitialized. Initialize them 37 | by calling `sess.run(tf.tables_initializer())` 38 | 39 | Args: 40 | elements: A list of non-Tensor elements. 41 | 42 | Returns: 43 | A function that when called with a single tensor argument, returns 44 | a boolean tensor if the argument is in the set. 45 | """ 46 | table = tf.contrib.lookup.HashTable( 47 | tf.contrib.lookup.KeyValueTensorInitializer( 48 | elements, tf.tile([1], [len(elements)]) 49 | ), 50 | default_value=0, 51 | ) 52 | 53 | return lambda x: tf.equal(table.lookup(x), 1) 54 | 55 | 56 | def filter_fn_from_comma_delimited(string): 57 | """Parses a string of comma delimited numbers, returning a filter function. 58 | 59 | This utility function is useful for parsing flags that represent a set of 60 | options, where the default is "all options". 61 | 62 | Args: 63 | string: e.g. "1,2,3", or empty string for "set of all elements" 64 | 65 | Returns: 66 | A function that when called with a single tensor argument, returns 67 | a boolean tensor that evaluates to True if the argument is in the set. 68 | If 'string' argument is None, the set is understood to contain all 69 | elements and the function always returns a True tensor. 70 | """ 71 | if string: 72 | return make_set_filter_fn(list(map(int, string.split(",")))) 73 | else: 74 | return lambda x: tf.constant(True) 75 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | numpy 2 | absl-py 3 | tensorflow-gpu 4 | scipy 5 | tmuxp 6 | -------------------------------------------------------------------------------- /run-uasd/cifar10-4000.yml: -------------------------------------------------------------------------------- 1 | session_name: cifar10-4000-uasd 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | panes: 6 | - > 7 | CUDA_VISIBLE_DEVICES=0 python3 train_model_uasd.py --label_map_index=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --consistency_model=ours --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1 --n_labeled=4000 --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1_train.log; 8 | CUDA_VISIBLE_DEVICES=0 python3 train_model_uasd.py --label_map_index=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --consistency_model=ours --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1 --n_labeled=4000 --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1_train.log; 9 | CUDA_VISIBLE_DEVICES=0 python3 train_model_uasd.py --label_map_index=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --consistency_model=ours --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1 --n_labeled=4000 --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1_train.log; 10 | CUDA_VISIBLE_DEVICES=0 python3 train_model_uasd.py --label_map_index=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --consistency_model=ours --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1 --n_labeled=4000 --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1_train.log; 11 | CUDA_VISIBLE_DEVICES=0 python3 train_model_uasd.py --label_map_index=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --consistency_model=ours --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1 --n_labeled=4000 --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1_train.log 12 | 13 | - > 14 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=test --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1_eval_test.log; 15 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=test --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1_eval_test.log; 16 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=test --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1_eval_test.log; 17 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=test --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1_eval_test.log; 18 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=test --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1_eval_test.log 19 | 20 | - > 21 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=valid --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol0-c6-v1_eval_valid.log; 22 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=valid --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol1-c6-v1_eval_valid.log; 23 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=valid --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol2-c6-v1_eval_valid.log; 24 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=valid --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol3-c6-v1_eval_valid.log; 25 | CUDA_VISIBLE_DEVICES=0 python3 evaluate_model.py --split=valid --primary_dataset_name='cifar10' --root_dir=./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1 --consistency_model=none --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee ./mnt/cifar10-uasd-rampup/cifar10-4000-uasd-ol4-c6-v1_eval_valid.log 26 | 27 | -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-fullysup-olna.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-fullysup-olna 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna --n_labeled=4000 --dataset_model=labeled --consistency_model=none --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna --consistency_model=none --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna --consistency_model=none --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna --consistency_model=none --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-fullysup-olna_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-mean-teacher-ol0.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-mean-teacher-ol0 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0 --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol0_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-mean-teacher-ol1.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-mean-teacher-ol1 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1 --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol1_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-mean-teacher-ol2.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-mean-teacher-ol2 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2 --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol2_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-mean-teacher-ol3.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-mean-teacher-ol3 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3 --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol3_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-mean-teacher-ol4.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-mean-teacher-ol4 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4 --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4 --consistency_model=mean_teacher --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-mean-teacher-ol4_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pi-model-ol0.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pi-model-ol0 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0 --n_labeled=4000 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol0_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pi-model-ol1.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pi-model-ol1 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1 --n_labeled=4000 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol1_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pi-model-ol2.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pi-model-ol2 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2 --n_labeled=4000 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol2_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pi-model-ol3.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pi-model-ol3 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3 --n_labeled=4000 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol3_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pi-model-ol4.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pi-model-ol4 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4 --n_labeled=4000 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4 --consistency_model=pi_model --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pi-model-ol4_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pseudo-label-ol0.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pseudo-label-ol0 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0 --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol0_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pseudo-label-ol1.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pseudo-label-ol1 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1 --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol1_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pseudo-label-ol2.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pseudo-label-ol2 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2 --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol2_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pseudo-label-ol3.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pseudo-label-ol3 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3 --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol3_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-pseudo-label-ol4.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-pseudo-label-ol4 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4 --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4 --consistency_model=pseudo_label --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-pseudo-label-ol4_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-vat-ol0.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-vat-ol0 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0 --n_labeled=4000 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol0_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-vat-ol1.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-vat-ol1 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1 --n_labeled=4000 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol1_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-vat-ol2.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-vat-ol2 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2 --n_labeled=4000 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol2_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-vat-ol3.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-vat-ol3 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3 --n_labeled=4000 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol3_eval_train.log -------------------------------------------------------------------------------- /runs/figure-2-cifar10-4000-vat-ol4.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-2-cifar10-4000-vat-ol4 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4 --n_labeled=4000 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 --unlabeled_classes_filter=0,1,8,9 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4 --consistency_model=vat --hparam_string="" --labeled_classes_filter=2,3,4,5,6,7 2>&1 | tee /mnt/experiment-logs/figure-2-cifar10-4000-vat-ol4_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-1000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-1000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-1000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-1000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pi-model --n_labeled=1000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-1000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-1000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-1000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-1000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-vat --n_labeled=1000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-1000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-2000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-2000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher --n_labeled=2000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-2000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-2000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pi-model --n_labeled=2000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-2000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-2000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label --n_labeled=2000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-2000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-2000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-vat --n_labeled=2000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-2000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-250-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-250-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-mean-teacher --n_labeled=250 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-250-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-250-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pi-model --n_labeled=250 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-250-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-250-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pseudo-label --n_labeled=250 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-250-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-250-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-vat --n_labeled=250 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-250-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-4000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-4000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-4000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-4000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pi-model --n_labeled=4000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-4000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-4000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-4000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-4000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-vat --n_labeled=4000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-4000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-500-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-500-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-mean-teacher --n_labeled=500 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-500-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-500-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pi-model --n_labeled=500 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-500-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-500-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pseudo-label --n_labeled=500 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-500-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-500-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-vat --n_labeled=500 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-500-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-8000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-8000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher --n_labeled=8000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-8000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-8000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pi-model --n_labeled=8000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-8000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-8000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label --n_labeled=8000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-cifar10-8000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-cifar10-8000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-vat --n_labeled=8000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/figure-3-cifar10-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-cifar10-8000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-1000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-1000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-mean-teacher --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-1000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-1000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pi-model --n_labeled=1000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-1000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-1000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pseudo-label --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-1000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-1000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-vat --n_labeled=1000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-1000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-2000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-2000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-mean-teacher --n_labeled=2000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-2000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-2000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pi-model --n_labeled=2000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-2000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-2000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pseudo-label --n_labeled=2000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-2000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-2000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-vat --n_labeled=2000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-2000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-2000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-250-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-250-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-mean-teacher --n_labeled=250 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-250-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-250-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pi-model --n_labeled=250 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-250-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-250-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pseudo-label --n_labeled=250 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-250-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-250-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-vat --n_labeled=250 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-250-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-250-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-4000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-4000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-mean-teacher --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-4000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-4000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pi-model --n_labeled=4000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-4000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-4000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pseudo-label --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-4000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-4000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-vat --n_labeled=4000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-4000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-500-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-500-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-mean-teacher --n_labeled=500 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-500-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-500-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pi-model --n_labeled=500 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-500-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-500-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pseudo-label --n_labeled=500 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-500-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-500-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --n_labeled=500 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-500-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-500-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-8000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-8000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-mean-teacher --n_labeled=8000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-8000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-8000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pi-model --n_labeled=8000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-8000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-8000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pseudo-label --n_labeled=8000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/figure-3-svhn-8000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-3-svhn-8000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-vat --n_labeled=8000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-3-svhn-8000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-3-svhn-8000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl10000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl10000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.0188277468271 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl10000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl160000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl160000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.301243949233 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl160000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl20000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl20000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.0376554936541 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl20000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl320000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl320000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.602487898466 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl320000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl40000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl40000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.0753109873082 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl40000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl531131.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl531131 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=1.0 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl531131_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-mean-teacher-unl80000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-mean-teacher-unl80000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000 --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" --unlabeled_data_random_fraction=0.150621974616 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-mean-teacher-unl80000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl10000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl10000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.0188277468271 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl10000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl160000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl160000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.301243949233 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl160000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl20000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl20000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.0376554936541 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl20000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl320000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl320000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.602487898466 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl320000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl40000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl40000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.0753109873082 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl40000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl531131.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl531131 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=1.0 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl531131_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pi-model-unl80000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pi-model-unl80000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000 --n_labeled=1000 --consistency_model=pi_model --hparam_string="" --unlabeled_data_random_fraction=0.150621974616 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pi-model-unl80000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl10000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl10000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.0188277468271 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl10000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl160000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl160000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.301243949233 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl160000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl20000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl20000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.0376554936541 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl20000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl320000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl320000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.602487898466 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl320000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl40000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl40000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.0753109873082 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl40000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl531131.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl531131 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=1.0 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl531131_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-pseudo-label-unl80000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-pseudo-label-unl80000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000 --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" --unlabeled_data_random_fraction=0.150621974616 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-pseudo-label-unl80000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl10000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl10000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.0188277468271 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl10000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl160000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl160000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.301243949233 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl160000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl20000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl20000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.0376554936541 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl20000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl320000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl320000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.602487898466 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl320000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl40000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl40000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.0753109873082 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl40000_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl531131.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl531131 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=1.0 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl531131_eval_train.log -------------------------------------------------------------------------------- /runs/figure-4-svhn-1000-vat-unl80000.yml: -------------------------------------------------------------------------------- 1 | session_name: figure-4-svhn-1000-vat-unl80000 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn_extra' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000 --n_labeled=1000 --consistency_model=vat --hparam_string="" --unlabeled_data_random_fraction=0.150621974616 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/figure-4-svhn-1000-vat-unl80000_eval_train.log -------------------------------------------------------------------------------- /runs/section-4-3-cifar-filtered-file-tuning.yml: -------------------------------------------------------------------------------- 1 | session_name: cifar-fine-tuning 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --load_checkpoint=/mnt/experiment-logs/section-4-3-filtered-imagenet-pre-training/default/model.ckpt-500001 --training_length=1000000 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning --n_labeled=4000 --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-filtered-fine-tuning_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/section-4-3-cifar-fine-tuning.yml: -------------------------------------------------------------------------------- 1 | session_name: cifar-fine-tuning 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --load_checkpoint=/mnt/experiment-logs/section-4-3-imagenet-pre-training/default/model.ckpt-500000 --training_length=1000000 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-fine-tuning --n_labeled=4000 --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-fine-tuning_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-fine-tuning_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-fine-tuning_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --training_length=1000000 --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/section-4-3-cifar-fine-tuning --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-cifar-fine-tuning_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/section-4-3-imagenet-pre-training.yml: -------------------------------------------------------------------------------- 1 | session_name: imagenet-pre-training 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --zca_input_file_path='data/' --primary_dataset_name='imagenet_32' --secondary_dataset_name='imagenet_32' --root_dir=/mnt/experiment-logs/section-4-3-imagenet-pre-training --n_labeled=-1 --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-imagenet-pre-training_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --zca_input_file_path='data/' --split=test --verbosity=0 --primary_dataset_name='imagenet_32' --root_dir=/mnt/experiment-logs/section-4-3-imagenet-pre-training --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-imagenet-pre-training_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --zca_input_file_path='data/' --split=valid --verbosity=0 --primary_dataset_name='imagenet_32' --root_dir=/mnt/experiment-logs/section-4-3-imagenet-pre-training --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-imagenet-pre-training_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --zca_input_file_path='data/' --split=train --verbosity=0 --primary_dataset_name='imagenet_32' --root_dir=/mnt/experiment-logs/section-4-3-imagenet-pre-training --consistency_model=none 2>&1 | tee /mnt/experiment-logs/section-4-3-imagenet-pre-training_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-fullysup.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-fullysup 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-fullysup --n_labeled=4000 --dataset_model=labeled --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-fullysup_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-fullysup_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-fullysup_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-fullysup_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-mean-teacher --n_labeled=4000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pi-model --n_labeled=4000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pseudo-label --n_labeled=4000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-vat-em.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-vat-em 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat-em --n_labeled=4000 --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat-em_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat-em_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat-em_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat-em_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-cifar10-4000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-cifar10-4000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='cifar10' --secondary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat --n_labeled=4000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='cifar10' --root_dir=/mnt/experiment-logs/table-1-cifar10-4000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-cifar10-4000-vat_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-fullysup.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-fullysup 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-fullysup --n_labeled=1000 --dataset_model=labeled --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-fullysup_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-fullysup_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-fullysup_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-fullysup --consistency_model=none 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-fullysup_eval_train.log 11 | -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-mean-teacher.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-mean-teacher 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-mean-teacher --n_labeled=1000 --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-mean-teacher_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-mean-teacher_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-mean-teacher_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-mean-teacher --consistency_model=mean_teacher --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-mean-teacher_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-pi-model.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-pi-model 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pi-model --n_labeled=1000 --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pi-model_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pi-model_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pi-model_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pi-model --consistency_model=pi_model --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pi-model_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-pseudo-label.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-pseudo-label 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pseudo-label --n_labeled=1000 --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pseudo-label_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pseudo-label_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pseudo-label_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-pseudo-label --consistency_model=pseudo_label --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-pseudo-label_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-vat-em.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-vat-em 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat-em --n_labeled=1000 --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat-em_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat-em_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat-em_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat-em --consistency_model=vat --hparam_string="entropy_penalty_multiplier=0.1" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat-em_eval_train.log -------------------------------------------------------------------------------- /runs/table-1-svhn-1000-vat.yml: -------------------------------------------------------------------------------- 1 | session_name: table-1-svhn-1000-vat 2 | windows: 3 | - window_name: experiments 4 | layout: even-vertical 5 | shell_command_before: cd /root/realistic-ssl-evaluation 6 | panes: 7 | - CUDA_VISIBLE_DEVICES=0 python3 train_model.py --verbosity=0 --primary_dataset_name='svhn' --secondary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat --n_labeled=1000 --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat_train.log 8 | - CUDA_VISIBLE_DEVICES=1 python3 evaluate_model.py --split=test --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat_eval_test.log 9 | - CUDA_VISIBLE_DEVICES=2 python3 evaluate_model.py --split=valid --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat_eval_valid.log 10 | - CUDA_VISIBLE_DEVICES=3 python3 evaluate_model.py --split=train --verbosity=0 --primary_dataset_name='svhn' --root_dir=/mnt/experiment-logs/table-1-svhn-1000-vat --consistency_model=vat --hparam_string="" 2>&1 | tee /mnt/experiment-logs/table-1-svhn-1000-vat_eval_train.log -------------------------------------------------------------------------------- /third_party/vat/LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright 2015 Google Inc. 4 | This code has been modified from the original version at https://github.com/takerum/vat_tf 5 | Original license reproduced below. 6 | 7 | Copyright (c) 2017 Takeru Miyato 8 | 9 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: 10 | 11 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. 12 | 13 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. -------------------------------------------------------------------------------- /third_party/vat/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/yanbeic/ssl-class-mismatch/e38015a91ceaff62b09a51361f6f7b6a17962da3/third_party/vat/__init__.py -------------------------------------------------------------------------------- /third_party/vat/vat_utils.py: -------------------------------------------------------------------------------- 1 | """Utilities derived from the VAT code.""" 2 | import tensorflow as tf 3 | 4 | 5 | def generate_virtual_adversarial_perturbation(x, logit, forward, hps): 6 | """Generate an adversarial perturbation. 7 | 8 | Args: 9 | x: Model inputs. 10 | logit: Original model output without perturbation. 11 | forward: Callable which computs logits given input. 12 | hps: Model hyperparameters. 13 | 14 | Returns: 15 | Aversarial perturbation to be applied to x. 16 | """ 17 | d = tf.random_normal(shape=tf.shape(x)) 18 | 19 | for _ in range(1): 20 | d = hps.vat_xi * get_normalized_vector(d) 21 | logit_p = logit 22 | logit_m = forward(x + d) 23 | dist = kl_divergence_with_logit(logit_p, logit_m) 24 | grad = tf.gradients(tf.reduce_mean(dist), [d], aggregation_method=2)[0] 25 | d = tf.stop_gradient(grad) 26 | 27 | return hps.vat_epsilon * get_normalized_vector(d) 28 | 29 | 30 | def kl_divergence_with_logit(q_logit, p_logit): 31 | """Compute the per-element KL-divergence of a batch.""" 32 | q = tf.nn.softmax(q_logit) 33 | qlogq = tf.reduce_sum(q * logsoftmax(q_logit), 1) 34 | qlogp = tf.reduce_sum(q * logsoftmax(p_logit), 1) 35 | return qlogq - qlogp 36 | 37 | 38 | def get_normalized_vector(d): 39 | """Normalize d by infinity and L2 norms.""" 40 | d /= 1e-12 + tf.reduce_max( 41 | tf.abs(d), list(range(1, len(d.get_shape()))), keepdims=True 42 | ) 43 | d /= tf.sqrt( 44 | 1e-6 45 | + tf.reduce_sum( 46 | tf.pow(d, 2.0), list(range(1, len(d.get_shape()))), keepdims=True 47 | ) 48 | ) 49 | return d 50 | 51 | 52 | def logsoftmax(x): 53 | """Compute log-domain softmax of logits.""" 54 | xdev = x - tf.reduce_max(x, 1, keepdims=True) 55 | lsm = xdev - tf.log(tf.reduce_sum(tf.exp(xdev), 1, keepdims=True)) 56 | return lsm 57 | --------------------------------------------------------------------------------