GitLab

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

As titled.

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* support random seed used to shuffle the sampler

* fix bug for RA samper
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Adding repaeted data-augument sampler

* rebase on top of latest main

* fix formatting

* rename file

* adding coode source

* support amp training for video classification models

* Removed extra empty line and used scaler instead of args.amp as function argument

* apply formating to pass lint tests
Co-authored-by: Konstantinos Bozas <kbz@kbz-mbp.broadband>

* Change the `default` weights mechanism to sue Enum aliases.

* Change `get_weights` to work with full Enum names and make it public.

* Applying improvements from code review.

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* support amp training for segmention models

* fix lint
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add multi-type support on get_weight.

* Fix bug on method call.

* Adding logging suffix for QAT.

* support amp training

* support amp training

* support amp training

* Update references/detection/train.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update references/detection/engine.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* fix lint issues
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* fix bug in amp

* fix bug in training by amp

* support use gradient clipping when amp is enabled
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* Clean up unnecessary quant builders and add quant weights for 0.5

* Fixing mypy.

* Reordering the builders to use proper typing.

* Adding additional meta-data on existing quantized models.

* Fixing meta on unquantized model.

* Adding quantized googlenet builder.

* undo inception move.

* Adding recipe information.

* Aligning exception with all other models.

* Adding prototype preprocessing on video references.

* Adding the rest of model builders on faster_rcnn.

* Adding prototype preprocessing on segmentation references.

* Adding prototype preprocessing on video references.

* [references] Adding gradient clipping

* ufmt formatting

* remove apex code

* resolve naming issue

* Adding multi-weight support to Quantized ResNet.

* Update references script to support testing quantized models with the new API.

* Handle quantized models correctly in ref script.

* Fixing references for quantization.

* Update training references from legacy models.

* Refactoring to share common parts.

* Moving original builder at the bottom of the page to use proper typing.

* Adding multiweight support to inception.

* Update doc.

Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* Update model checkpoint for resnet50.

* Add get_weight method to retrieve weights from name.

* Update the references to support prototype weights.

* Fixing mypy typing.

* Switching to a python 3.6 supported equivalent.

* Add unit-test.

* Add optional num_classes.

* Add type to default argument

To resolve issue #4694

* Resolve issue #4694

Add missing types on argument parser

* Update with ufmt

formatted with ufmt

* Updated with review

Updated with review

* Update type of arguments

Add train.py from video_classification, similarity and train_quantization.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update EMA every X iters.

* Adding AdamW optimizer.

* Adjusting EMA decay scheme.

* Support custom weight decay for Normalization layers.

* Fix identation bug.

* Change EMA adjustment.

* Quality of life changes to faciliate testing

* ufmt format

* Fixing imports.

* Adding FixRes improvement.

* Support EMA in store_model_weights.

* Adding interpolation values.

* Change train_crop_size.

* Add interpolation option.

* Removing hardcoded interpolation and sizes from the scripts.

* Fixing linter.

* Incorporating feedback from code review.

* Updated classification reference script to use torch.cuda.amp

* Assigned scaler to None if amp is False

* Fixed linter errors