Update torch requirement from <=1.4.0,>1.3.1 to >1.3.1,<1.6.0

[dependabot-preview]

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

Stable C++ Frontend, Distributed RPC framework, and more. New experimental higher-level autograd API, Channels Last memory format, and more.

PyTorch 1.5.0 Release Notes

• Highlights
• Known Issues
• Backwards Incompatible Changes
  • Python
  • C++ API
  • JIT
  • Quantization
  • RPC
• New Features
• Improvements
• Bug Fixes
• Performance
• Documentation
• Deprecations
  • Python
  • C++ API
• Miscellaneous

Highlights

This release includes several major new API additions and improvements. These include new APIs for autograd allowing for easy computation of hessians and jacobians, a significant update to the C++ frontend, ‘channels last’ memory format for more performant computer vision models, a stable release of the distributed RPC framework used for model parallel training, and a new API that allows for the creation of Custom C++ Classes that was inspired by PyBind. Additionally torch_xla 1.5 is now available and tested with the PyTorch 1.5 release providing a mature Cloud TPU experience.

C++ Frontend API [Now Stable]

The C++ frontend API is now at parity with Python and the features overall has been moved to ‘stable’. (previously tagged as experimental). Some of the major highlights include:

• C++ torch::nn module/functional are now at ~100% parity with Python API, with appropriate documentation. Now users can easily translate their model from Python API to C++ API, making the model authoring experience much smoother.
• C++ optimizers now behave identically to the Python API. In the past, optimizers in C++ had deviated from the Python equivalent: C++ optimizers couldn’t take parameter groups as input while the Python ones could. Also step function implementations were not exactly the same. With the 1.5 release, C++ optimizers will always behave the same as the Python equivalent.
• New C++ tensor multi-dim indexing API which looks and behaves the similar to the Python API. The previous workaround was to use a combination of narrow / select / index_select / masked_select, which is clunky and error-prone compared to the Python API’s elegant tensor[:, 0, ..., mask] syntax. With the 1.5 release users can use tensor.index({Slice(), 0, "...", mask}) to achieve the same result.

Channels last memory format for Computer Vision models [Experimental]

Channels Last memory format is an alternative way of ordering NCHW tensors in memory while preserving the NCHW semantic dimensions ordering. Channels Last tensors are ordered in memory in such a way that channels become the densest dimension (aka storing images pixel-per-pixel).

Channels Last memory format unlocks the ability to use performance efficient convolution algorithms and hardware (NVidia’s Tensor Cores, FBGEMM, QNNPACK). Additionally it was designed to automatically propagate through the operators, which allows easy switching between memory layouts.

Learn more here on how to write memory format aware operators.

Custom C++ Classes [Experimental]

This release adds a new API for binding custom C++ classes into TorchScript and Python simultaneously. This API is almost identical in syntax to pybind11. It allows users to expose their C++ class and its methods to the TorchScript type system and runtime system such that they can instantiate and manipulate arbitrary C++ objects from TorchScript and Python. An example C++ binding:

template <class T>
struct MyStackClass : torch::CustomClassHolder {
  std::vector<T> stack_;
  MyStackClass(std::vector<T> init) : stack_(std::move(init)) {}
</tr></table> ... (truncated)

Commits

• 4ff3872 [v.1.5.0] Ensure linearIndex of advanced indexing backwards is contig… (#36962)
• d7bdffa [v1.5 Patch] Disable flaky test_backward_node_failure_python_udf test in dist...
• 9ba0a89 Overwrite bazel if /usr/bin/bazel already exists.
• c164fbc Add TorchServe
• 9a51e47 make simple executor the default for OSS
• 375566f Handle log_sigmoid(out=) properly.
• dfdc788 Fix incorrect merge of #34136.
• 9e6ef81 [v1.5.0] Print keyword-only arg symbol for function signature suggestions.
• 3146180 Migrate release CI jobs to CircleCI for Windows (v1.5 Release) (#36658)
• e741839 Fixing SyncBN dgrad (#36382)
• Additional commits viewable in compare view

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[epwalsh]

Looks like torch wasn't upgraded in the GitHub Actions workflow. That should be fixed by this change though: 98a2953#diff-04eb107ee163a50b61281ca08f4e4c7bR37

There's another pip flag that needs to be set --upgrade-strategy eager. See #4120

[epwalsh]

Seems I'm running into this now actions/cache#208 (comment)

[epwalsh]

Ok this is now failing where it's supposed to, which is somewhere in ELMO.

[dependabot-preview]

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If you change your mind, just re-open this PR and I'll resolve any conflicts on it.