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- 22 Mar, 2022 1 commit
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Vasilis Vryniotis authored
* Moving basefiles outside of prototype and porting Alexnet, ConvNext, Densenet and EfficientNet. * Porting googlenet * Porting inception * Porting mnasnet * Porting mobilenetv2 * Porting mobilenetv3 * Porting regnet * Porting resnet * Porting shufflenetv2 * Porting squeezenet * Porting vgg * Porting vit * Fix docstrings * Fixing imports * Adding missing import * Fix mobilenet imports * Fix tests * Fix prototype tests * Exclude get_weight from models on test * Fix init files * Porting googlenet * Porting inception * porting mobilenetv2 * porting mobilenetv3 * porting resnet * porting shufflenetv2 * Fix test and linter * Fixing docs. * Porting Detection models (#5617) * fix inits * fix docs * Port faster_rcnn * Port fcos * Port keypoint_rcnn * Port mask_rcnn * Port retinanet * Port ssd * Port ssdlite * Fix linter * Fixing tests * Fixing tests * Fixing vgg test * Porting Optical Flow, Segmentation, Video models (#5619) * Porting raft * Porting video resnet * Porting deeplabv3 * Porting fcn and lraspp * Fixing the tests and linter * Porting docs, examples, tutorials and galleries (#5620) * Fix examples, tutorials and gallery * Update gallery/plot_optical_flow.py Co-authored-by:
Nicolas Hug <contact@nicolas-hug.com> * Fix import * Revert hardcoded normalization * fix uncommitted changes * Fix bug * Fix more bugs * Making resize optional for segmentation * Fixing preset * Fix mypy * Fixing documentation strings * Fix flake8 * minor refactoring Co-authored-by:
Nicolas Hug <contact@nicolas-hug.com> * Resolve conflict * Porting model tests (#5622) * Porting tests * Remove unnecessary variable * Fix linter * Move prototype to extended tests * Fix download models job * Update CI on Multiweight branch to use the new weight download approach (#5628) * port Pad to prototype transforms (#5621) * port Pad to prototype transforms * use literal * Bump up LibTorchvision version number for Podspec to release Cocoapods (#5624) Co-authored-by:
Anton Thomma <anton@pri.co.nz> Co-authored-by:
Vasilis Vryniotis <datumbox@users.noreply.github.com> * pre-download model weights in CI docs build (#5625) * pre-download model weights in CI docs build * move changes into template * change docs image * Regenerated config.yml Co-authored-by:
Philip Meier <github.pmeier@posteo.de> Co-authored-by:
Anton Thomma <11010310+thommaa@users.noreply.github.com> Co-authored-by:
Anton Thomma <anton@pri.co.nz> * Porting reference scripts and updating presets (#5629) * Making _preset.py classes * Remove support of targets on presets. * Rewriting the video preset * Adding tests to check that the bundled transforms are JIT scriptable * Rename all presets from *Eval to *Inference * Minor refactoring * Remove --prototype and --pretrained from reference scripts * remove pretained_backbone refs * Corrections and simplifications * Fixing bug * Fixing linter * Fix flake8 * restore documentation example * minor fixes * fix optical flow missing param * Fixing commands * Adding weights_backbone support in detection and segmentation * Updating the commands for InceptionV3 * Setting `weights_backbone` to its fully BC value (#5653) * Replace default `weights_backbone=None` with its BC values. * Fixing tests * Fix linter * Update docs. * Update preprocessing on reference scripts. * Change qat/ptq to their full values. * Refactoring preprocessing * Fix video preset * No initialization on VGG if pretrained * Fix warning messages for backbone utils. * Adding star to all preset constructors. * Fix mypy. Co-authored-by:
Nicolas Hug <contact@nicolas-hug.com> Co-authored-by:
Philip Meier <github.pmeier@posteo.de> Co-authored-by:
Anton Thomma <11010310+thommaa@users.noreply.github.com> Co-authored-by:
Anton Thomma <anton@pri.co.nz>
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- 31 Oct, 2019 1 commit
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hx89 authored
* quantizable googlenet * Minor improvements * Rename basic_conv2d with conv_block plus additional fixes * More renamings and fixes * Bugfix * Fix missing import for mypy * Add pretrained weights
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- 26 Oct, 2019 1 commit
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raghuramank100 authored
* add quantized models * Modify mobilenet.py documentation and clean up comments Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Move fuse_model method to QuantizableInvertedResidual and clean up args documentation Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Restore relu settings to default in resnet.py Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix missing return in forward Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix missing return in forwards Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Change pretrained -> pretrained_float_models Replace InvertedResidual with block Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Update tests to follow similar structure to test_models.py, allowing for modular testing Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Replace forward method with simple function assignment Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix error in arguments for resnet18 Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * pretrained_float_model argument missing for mobilenet Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * reference script for quantization aware training and post training quantization * reference script for quantization aware training and post training quantization * set pretrained_float_model as False and explicitly provide float model Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Address review comments: 1. Replace forward with _forward 2. Use pretrained models in reference train/eval script 3. Modify test to skip if fbgemm is not supported Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix lint errors. Use _forward for common code between float and quantized models Clean up linting for reference train scripts Test over all quantizable models Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Update default values for args in quantization/train.py Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Update models to conform to new API with quantize argument Remove apex in training script, add post training quant as an option Add support for separate calibration data set. Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix minor errors in train_quantization.py Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Remove duplicate file * Bugfix * Minor improvements on the models * Expose print_freq to evaluate * Minor improvements on train_quantization.py * Ensure that quantized models are created and run on the specified backends Fix errors in test only mode Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Add model urls * Fix errors in quantized model tests. Speedup creation of random quantized model by removing histogram observers Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Move setting qengine prior to convert. Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix lint error Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Add readme.md Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Readme.md Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: * Fix lint
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