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pytorch_models

Self-supervised Models

In models/self_supervised.py, we provide a stand-alone file that provides model definitions for self-supervised models converted from Caffe to PyTorch.

model = models.self_supervised.alexnet(task_name='weakly_solvingpuzzle', pretrained=True)

The following models have been converted and fully verified to be equivalent:

  • weakly_deepcontext
  • weakly_learningbymoving
  • weakly_objectcentric
  • weakly_solvingpuzzle
  • weakly_videoorder
  • weakly_videotracking

These models have been verified to be equivalent in the forward pass but have discrepancies in the backwards pass (i.e., gradients):

  • weakly_audio
  • weakly_egomotion

TODO-models:

  • weakly_colorization
  • weakly_splitbrain

TODO-misc:

  • define get_transform to provide the right data transformations for each task.

Model definition and weights were taken from http://netdissect.csail.mit.edu.

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