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Release v0.17.5

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@AnirudhDagar AnirudhDagar released this 31 Mar 05:54
· 1714 commits to master since this release

This release fixes issues when installing d2l package and running d2l notebooks on Google Colab with Python 3.7 and updates PyTorch & TensorFlow to their respective latest versions.

More concretely, this release includes the following upgrades/fixes:

  • Update TensorFlow==2.8.0 (#2055)
  • Update PyTorch: torch==1.11.0 & torchvision==0.12.0 (#2063)
  • Rollback NumPy==1.21.5 & Support Python>=3.7 (#2066)
  • Fix MXNet plots; NumPy auto coercion & Unpin matplotlib==3.4 dependency (#2078)
  • Fix the broken download link for MovieLens dataset (#2074)
  • Fix iPython deprecation warning of set_matplotlib_formats (#2065)
  • Fix Densenet PyTorch implementation using nn.AdaptiveAvgPool2d (f6b1dd0)
  • Fix the hotdog class in section Fine Tuning for imagenet, which is number 934 instead of 713 (#2009)
  • Use reduction=none in PyTorch loss for train_epoch_ch3 (#2007)
  • Fix argument test_feature->test_features of train_and_pred in kaggle house price section (#1982)
  • Fix TypeError: can’t convert CUDA tensor to numpy, explicitly moving torch tensor to cpu before plotting (#1966)