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Feat/unfreeze layers fpn backbone #2160
Feat/unfreeze layers fpn backbone #2160
Commits on Apr 29, 2020
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freeze layers only if pretrained backbone is used
If pretrained backbone is not used and one intends to train the entire network from scratch, no layers should be frozen.
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function argument to control the trainable features
Depending on the size of dataset one might want to control the number of tunable parameters in the backbone, and this parameter in hyper parameter optimization for the dataset. It would be nice to have this function support this.
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backbone freezing in fasterrcnn_resnet50_fpn
Handle backbone freezing in fasterrcnn_resnet50_fpn function rather than the resnet_fpn_backbone function that it uses to get the backbone.
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layer freezing code has been moved to fasterrcnn_resnet50_fpn function that consumes resnet_fpn_backbone function.
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Commits on Apr 30, 2020
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move freezing logic to resnet_fpn_backbone
Moved layer freezing logic to resnet_fpn_backbone with an additional parameter.
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remove layer freezing from fasterrcnn_resnet50_fpn
Layer freezing logic has been moved to resnet_fpn_backbone. This function only ensures that the all layers are made trainable if pretrained models are not used.
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Commits on May 6, 2020
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adding test case for layer freezing in faster rcnn
This PR adds functionality to specify the number of trainable layers while initializing the faster rcnn using fasterrcnn_resnet50_fpn function. This commits adds a test case to test this functionality.
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updating layer freezing condition for clarity
More information in PR
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