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Pytorch Updates

11/16/21, by artyom ; Posted in: Internals; 0 comments

In order to improve the progress I started validating all pretrained torchvision models one by one. I found several features I needed to implement but what is more important I found several critical bugs I could fix.

https://pytorch.org/vision/stable/models.html#classification

At this point following networks are validated against CPU version in both forward and backward propagation:

  • alexnet
  • resnet18
  • resnet50
  • vgg16
  • densenet161
  • googlenet
  • squeezenet1_0
  • inception_v3 (fwd only - backward fails on cuda/cpu)
  • shufflenet_v2_x1_0
  • mobilenet_v2
  • mobilenet_v3_large
  • mobilenet_v3_small (fwd only - same failure on bwd on cuda)
  • resnext50_32x4d
  • wide_resnet50_2
  • mnasnet1_0
  • efficientnet_b0
  • efficientnet_b4
  • regnet_y_400mf

To be continued...

Update Nov 17, 2021: I implemneted ceil rounding pooling mode, thus googlenet and squeezenet1_0 now pass validation

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