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Bump pytorch-lightning from 1.1.8 to 1.2.1 #6

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Bump pytorch-lightning from 1.1.8 to 1.2.1 #6

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@dependabot dependabot bot commented on behalf of github Mar 1, 2021

Bumps pytorch-lightning from 1.1.8 to 1.2.1.

Release notes

Sourced from pytorch-lightning's releases.

Standard weekly patch release

[1.2.1] - 2021-02-23

Fixed

  • Fixed incorrect yield logic for the amp autocast context manager (#6080)
  • Fixed priority of plugin/accelerator when setting distributed mode (#6089)
  • Fixed error message for AMP + CPU incompatibility (#6107)

Contributors

@​awaelchli, @​SeanNaren, @​carmocca

If we forgot someone due to not matching commit email with GitHub account, let us know :]

Pruning & Quantization & SWA

[1.2.0] - 2021-02-18

Added

  • Added DataType, AverageMethod and MDMCAverageMethod enum in metrics (#5657)
  • Added support for summarized model total params size in megabytes (#5590)
  • Added support for multiple train loaders (#1959)
  • Added Accuracy metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the top_k parameter (#4838)
  • Added Accuracy metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the subset_accuracy parameter (#4838)
  • Added HammingDistance metric to compute the hamming distance (loss) (#4838)
  • Added max_fpr parameter to auroc metric for computing partial auroc metric (#3790)
  • Added StatScores metric to compute the number of true positives, false positives, true negatives and false negatives (#4839)
  • Added R2Score metric (#5241)
  • Added LambdaCallback (#5347)
  • Added BackboneLambdaFinetuningCallback (#5377)
  • Accelerator all_gather supports collection (#5221)
  • Added image_gradients functional metric to compute the image gradients of a given input image. (#5056)
  • Added MetricCollection (#4318)
  • Added .clone() method to metrics (#4318)
  • Added IoU class interface (#4704)
  • Support to tie weights after moving model to TPU via on_post_move_to_device hook
  • Added missing val/test hooks in LightningModule (#5467)
  • The Recall and Precision metrics (and their functional counterparts recall and precision) can now be generalized to Recall@K and Precision@K with the use of top_k parameter (#4842)
  • Added ModelPruning Callback (#5618, #5825, #6045)
  • Added PyTorchProfiler (#5560)
  • Added compositional metrics (#5464)
  • Added Trainer method predict(...) for high performence predictions (#5579)
  • Added on_before_batch_transfer and on_after_batch_transfer data hooks (#3671)
  • Added AUC/AUROC class interface (#5479)
  • Added PredictLoop object (#5752)
  • Added QuantizationAwareTraining callback (#5706, #6040)
  • Added LightningModule.configure_callbacks to enable the definition of model-specific callbacks (#5621)
  • Added dim to PSNR metric for mean-squared-error reduction (#5957)
  • Added promxial policy optimization template to pl_examples (#5394)
  • Added log_graph to CometLogger (#5295)

... (truncated)

Changelog

Sourced from pytorch-lightning's changelog.

[1.2.1] - 2021-02-23

Fixed

  • Fixed incorrect yield logic for the amp autocast context manager (#6080)
  • Fixed priority of plugin/accelerator when setting distributed mode (#6089)
  • Fixed error message for AMP + CPU incompatibility (#6107)

[1.2.0] - 2021-02-18

Added

  • Added DataType, AverageMethod and MDMCAverageMethod enum in metrics (#5657)
  • Added support for summarized model total params size in megabytes (#5590)
  • Added support for multiple train loaders (#1959)
  • Added Accuracy metric now generalizes to Top-k accuracy for (multi-dimensional) multi-class inputs using the top_k parameter (#4838)
  • Added Accuracy metric now enables the computation of subset accuracy for multi-label or multi-dimensional multi-class inputs with the subset_accuracy parameter (#4838)
  • Added HammingDistance metric to compute the hamming distance (loss) (#4838)
  • Added max_fpr parameter to auroc metric for computing partial auroc metric (#3790)
  • Added StatScores metric to compute the number of true positives, false positives, true negatives and false negatives (#4839)
  • Added R2Score metric (#5241)
  • Added LambdaCallback (#5347)
  • Added BackboneLambdaFinetuningCallback (#5377)
  • Accelerator all_gather supports collection (#5221)
  • Added image_gradients functional metric to compute the image gradients of a given input image. (#5056)
  • Added MetricCollection (#4318)
  • Added .clone() method to metrics (#4318)
  • Added IoU class interface (#4704)
  • Support to tie weights after moving model to TPU via on_post_move_to_device hook
  • Added missing val/test hooks in LightningModule (#5467)
  • The Recall and Precision metrics (and their functional counterparts recall and precision) can now be generalized to Recall@K and Precision@K with the use of top_k parameter (#4842)
  • Added ModelPruning Callback (#5618, #5825, #6045)
  • Added PyTorchProfiler (#5560)
  • Added compositional metrics (#5464)
  • Added Trainer method predict(...) for high performence predictions (#5579)
  • Added on_before_batch_transfer and on_after_batch_transfer data hooks (#3671)
  • Added AUC/AUROC class interface (#5479)
  • Added PredictLoop object (#5752)
  • Added QuantizationAwareTraining callback (#5706, #6040)
  • Added LightningModule.configure_callbacks to enable the definition of model-specific callbacks (#5621)
  • Added dim to PSNR metric for mean-squared-error reduction (#5957)
  • Added promxial policy optimization template to pl_examples (#5394)
  • Added log_graph to CometLogger (#5295)
  • Added possibility for nested loaders (#5404)
  • Added sync_step to Wandb logger (#5351)
  • Added StochasticWeightAveraging callback (#5640)

... (truncated)

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Mar 1, 2021
@dependabot dependabot bot requested a review from amogkam March 1, 2021 07:11
@dependabot dependabot bot mentioned this pull request Mar 1, 2021
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dependabot bot commented on behalf of github Mar 8, 2021

Superseded by #12.

@dependabot dependabot bot closed this Mar 8, 2021
@dependabot dependabot bot deleted the dependabot/pip/pytorch-lightning-1.2.1 branch March 8, 2021 07:02
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