Add MobileNetV3 architecture with Classification & Detection models #3243
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* Adding implementation of network architecture * Adding rmsprop support on the train.py * Adding auto-augment and random-erase in the training scripts. * Adding support for reduced tail on MobileNetV3. * Tagging blocks with comments.
* Initial implementation of MobileNet + RetinaNet. * Adding expeted file for mobilenetv3_large. * Adding temp candidate pretrained model for mobilenetv3 large. * Adding temp candidate pretrained model for mobilenetv3 large. * making `_validate_resnet_trainable_layers` generic and using it in mobilenet * Update tests. * Rename output_channels to out_channels * Fixing comments. * Update model. * Better mobilenetv3 large backbone. * Better mobilenetv3 + retinanet model. * Update mobilenetv3 + retinanet model.
zhiqwang
reviewed
Jan 13, 2021
| @@ -557,7 +557,10 @@ def forward(self, images, targets=None): | |||
| return self.eager_outputs(losses, detections) | |||
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| # TODO: replace with pytorch links | |||
There was a problem hiding this comment.
Ha, it seems that this link have already replaced with PyTorch?
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Closing in favour of splitting the PR into two parts: Classification (#3252) and Detection (baking). |
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Fixes #1676
This PR adds MobileNetV3 in TorchVision:
See linked sub-PRs for details.