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path: root/models/model.py
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2021-02-18Merge branch 'master' into python3.8Jordan Gong
2021-02-18Implement adjustable input size and change some default configsJordan Gong
2021-02-18Decode mean appearance featureJordan Gong
2021-02-16Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/model.py
2021-02-16Split transform and evaluate methodJordan Gong
2021-02-15Revert "Memory usage improvement"Jordan Gong
This reverts commit be508061
2021-02-15Revert "Memory usage improvement"Jordan Gong
This reverts commit be508061
2021-02-14Merge branch 'master' into python3.8Jordan Gong
2021-02-14Memory usage improvementJordan Gong
This update separates input data to two batches, which reduces ~30% memory usage.
2021-02-14Prepare for DataParallelJordan Gong
2021-02-10Merge branch 'master' into python3.8Jordan Gong
2021-02-10Save scheduler state_dictJordan Gong
2021-02-09Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/rgb_part_net.py
2021-02-09Improve performance when disentanglingJordan Gong
This is a HUGE performance optimization, up to 2x faster than before. Mainly because of the replacement of randomized for-loop with randomized tensor.
2021-02-09Some optimizationsJordan Gong
1. Scheduler will decay the learning rate of auto-encoder only 2. Write learning rate history to tensorboard 3. Reduce image log frequency
2021-02-08Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/hpm.py # models/layers.py # models/model.py # models/rgb_part_net.py # utils/configuration.py
2021-02-08Code refactoring, modifications and new featuresJordan Gong
1. Decode features outside of auto-encoder 2. Turn off HPM 1x1 conv by default 3. Change canonical feature map size from `feature_channels * 8 x 4 x 2` to `feature_channels * 2 x 16 x 8` 4. Use mean of canonical embeddings instead of mean of static features 5. Calculate static and dynamic loss separately 6. Calculate mean of parts in triplet loss instead of sum of parts 7. Add switch to log disentangled images 8. Change default configuration
2021-01-23Remove the third term in canonical consistency lossJordan Gong
2021-01-23Add late start support for non-disentangling partsJordan Gong
2021-01-23Type hint fixesJordan Gong
2021-01-23Merge branch 'master' into python3.8Jordan Gong
2021-01-23Evaluation bug fixes and code reviewJordan Gong
1. Return full cached clip in evaluation 2. Add multi-iter checkpoints support in evaluation 3. Remove duplicated code while transforming
2021-01-22Handle unexpected restore iterJordan Gong
1. Skip finished model before load it 2. Raise error when restore iter is greater than total iter
2021-01-21A type hint fixJordan Gong
2021-01-21Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # utils/configuration.py
2021-01-21Print average losses after 100 itersJordan Gong
2021-01-14Enable optimizer fine tuningJordan Gong
2021-01-14Remove DataParallelJordan Gong
2021-01-14Remove DataParallelJordan Gong
2021-01-13Merge branch 'master' into python3.8Jordan Gong
2021-01-13Update config file and convert int to str when joiningJordan Gong
2021-01-13Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/model.py
2021-01-13Add multiple checkpoints for different model and set default config valueJordan Gong
2021-01-12Merge branch 'master' into python3.8Jordan Gong
2021-01-12Move the model to GPU before constructing optimizerJordan Gong
2021-01-12Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # utils/configuration.py
2021-01-12Some changes in hyperparameter configJordan Gong
1. Separate hyperparameter configs in model, optimizer and scheduler 2. Add more tunable hyperparameters in optimizer and scheduler
2021-01-12Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/model.py # utils/dataset.py
2021-01-12Some type hint fixesJordan Gong
2021-01-12Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/model.py
2021-01-12Typo correct in evaluate functionJordan Gong
2021-01-11Add evaluation script, code review and fix some bugsJordan Gong
1. Add new `train_all` method for one shot calling 2. Print time used in 1k iterations 3. Correct label dimension in predict function 4. Transpose distance matrix for convenient indexing 5. Sort dictionary before generate signature 6. Extract visible CUDA setting function
2021-01-11Implement evaluatorJordan Gong
2021-01-10Make predict function transform samples different conditions in a single shotJordan Gong
2021-01-09Add prototype predict functionJordan Gong
2021-01-07Merge branch 'master' into python3.8Jordan Gong
# Conflicts: # models/model.py
2021-01-07Train different models in different conditionsJordan Gong
2021-01-07Type hint for python version lower than 3.9Jordan Gong
2021-01-07Type hint for python version lower than 3.9Jordan Gong
2021-01-07Add typical training script and some bug fixesJordan Gong
1. Resolve deprecated scheduler stepping issue 2. Make losses in the same scale(replace mean with sum in separate triplet loss, enlarge pose similarity loss 10x) 3. Add ReLU when compute distance in triplet loss 4. Remove classes except Model from `models` package init
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