v0.4.0

This release includes the following enhancements and bug-fixes:

• Support PyTorch 1.8.1
• Fix several bugs in TabularDataset
• Fix several bugs with snapshot autoload feature
• LogReport now allows appending results using json-lines or yaml file formats
• Add Batch-Normalization aware gradient checkpointing
• Add LRScheduler extension

In this release there are also the following backward breaking changes:

• Drop PyTorch 1.6 & Python 3.5 support
• Remove bundled DataLoader as the minimum supported version is PyTorch 1.7 whose DataLoader supports the same features

We have upstreamed ppe.nn.LazyLinear and ppe.nn.LazyConv[123]d (lazy modules), and they are now available in PyTorch 1.8! Use of torch.nn.LazyLinear and torch.nn.LazyConv[123]d instead of PPE implementations is now recommended. See torch.nn.LazyModuleMixin for the details of the PyTorch lazy implementations.

See the list of merged pull-requests for the details.

v0.3.2

This release includes the following enhancements and bug-fixes:

• Support PyTorch 1.7.0
• Add custom DistributedDataParallel implementation to handle torch.util.checkpoint and dynamic computational graph
• Add metrics option to Evaluator extension to run metrics functions for every batch
• Expose ExtensionManager.models and ExtensionManager.optimizers to be used from extensions
• Add custom types for Optuna in the config system

See the list of merged pull-requests for the details.

v0.3.1

This release includes the following enhancements and bug-fixes:

• Add pytorch_pfn_extras.cuda APIs which adds interoperability with CuPy
• Add extensions for Jupyter Notebook (PrintReportNotebook and ProgressBarNotebook)
• Fix error when resuming training using IgniteExtensionsManager
• Fix backward breaking changes (updater attribute removal in ExtensionManager) in v0.3.0 release

See the list of merged pull-requests for the details.

Compatibility Notes

Starting in v0.3.0, the updater attribute of the ExtensionManager, which is a pseudo interface for compatibility with Chainer's extensions, has been deprecated. Extensions using the attribute to access training statistics (e.g., epoch/iteration number) must be changed to directly use attributes of ExtensionManager (e.g., ExtensionManager().epoch). Also, if you are using the updater in a snapshot filename template, you need to update it too (e.g., from snapshot_iter_{.updater.iteration} to snapshot_iter_{.iteration}). In this release, accessing the updater attribute raises a DeprecationWarning.

v0.3.0

This release includes the following enhancements and bug-fixes:

• Add pytorch_pfn_extras.onnx APIs which is an extension to torch.onnx.
• Add pytorch_pfn_extras.nn.LazyBatchNorm(1,2,3)d
• Add pytorch_pfn_extras.dataloaders.DataLoader which reuses the worker process
• Add pytorch_pfn_extras.dataset.SharedDataset
• Add pytorch_pfn_extras.dataset.TabularDataset
• Add pytorch_pfn_extras.writing.TensorBoardWriter
• Add step_optimizers parameter to ExtensionsManager.run_iteration()
• Fix memory leak in Reporter

See the list of merged pull-requests for the details.

Compatibility Notes

This release removes the updater attribute from the ExtensionManager which was a pseudo interface for compatibility with Chainer's extensions. Extensions using the attribute to access training statistics (e.g., epoch/iteration number) must be changed to directly use attributes of ExtensionManager (e.g., ExtensionManager().epoch).

v0.2.1

This release includes the next enhancements and bug-fixes:

• Add pytorch_pfn_extras.nn.ExtendedSequential which extends torch.nn.Sequential to support repeat
• Support transformation when taking / loading snapshot
• Improved example code (thanks @regonn!)
• Fix IgniteEvaluator reporting wrong metrics
• Fix circular reference in between Manager and ProgressBar
• Fix issues specific to Windows (thanks @take0212 for reporting!)

See the list of merged pull-requests for the details.

v0.2.0

The initial release of pytorch-pfn-extras.