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resnet-50.keys
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resnet-50.keys
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loading weights from pretrained resnet: microsoft/resnet-50
odict_keys(['resnet.embedder.embedder.convolution.weight', 'resnet.embedder.embedder.normalization.weight', 'resnet.embedder.embedder.normalization.bias', 'resnet.embedder.embedder.normalization.running_mean', 'resnet.embedder.embedder.normalization.running_var', 'resnet.embedder.embedder.normalization.num_batches_tracked', 'resnet.encoder.stages.0.layers.0.shortcut.convolution.weight', 'resnet.encoder.stages.0.layers.0.shortcut.normalization.weight', 'resnet.encoder.stages.0.layers.0.shortcut.normalization.bias', 'resnet.encoder.stages.0.layers.0.shortcut.normalization.running_mean', 'resnet.encoder.stages.0.layers.0.shortcut.normalization.running_var', 'resnet.encoder.stages.0.layers.0.shortcut.normalization.num_batches_tracked', 'resnet.encoder.stages.0.layers.0.layer.0.convolution.weight', 'resnet.encoder.stages.0.layers.0.layer.0.normalization.weight', 'resnet.encoder.stages.0.layers.0.layer.0.normalization.bias', 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'resnet.encoder.stages.3.layers.2.layer.1.normalization.running_mean', 'resnet.encoder.stages.3.layers.2.layer.1.normalization.running_var', 'resnet.encoder.stages.3.layers.2.layer.1.normalization.num_batches_tracked', 'resnet.encoder.stages.3.layers.2.layer.2.convolution.weight', 'resnet.encoder.stages.3.layers.2.layer.2.normalization.weight', 'resnet.encoder.stages.3.layers.2.layer.2.normalization.bias', 'resnet.encoder.stages.3.layers.2.layer.2.normalization.running_mean', 'resnet.encoder.stages.3.layers.2.layer.2.normalization.running_var', 'resnet.encoder.stages.3.layers.2.layer.2.normalization.num_batches_tracked', 'classifier.1.weight', 'classifier.1.bias'])
write model to microsoft-resnet-50, the keys of model is 320