Update torch requirement from <1.11.0,>=1.6.0 to >=1.6.0,<1.12.0

[dependabot]

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

PyTorch 1.11, TorchData, and functorch are now available

PyTorch 1.11 Release Notes

• Highlights
• Backwards Incompatible Change
• New Features
• Improvements
• Performance
• Documentation

Highlights

We are excited to announce the release of PyTorch 1.11. This release is composed of over 3,300 commits since 1.10, made by 434 contributors. Along with 1.11, we are releasing beta versions of TorchData and functorch. We want to sincerely thank our community for continuously improving PyTorch.

• TorchData is a new library for common modular data loading primitives for easily constructing flexible and performant data pipelines. View it on GitHub.
• functorch, a library that adds composable function transforms to PyTorch, is now available in beta. View it on GitHub.
• Distributed Data Parallel (DDP) static graph optimizations available in stable.

You can check the blogpost that shows the new features here.

Backwards Incompatible changes

Python API

Fixed python deepcopy to correctly copy all attributes on Tensor objects (#65584)

This change ensures that the deepcopy operation on Tensor properly copies all the attributes (and not just the plain Tensor properties).

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

• General Overview
• Cutting release branches
  • Making release branch specific changes
  • Getting CI signal on release branches:
• Drafting RCs (https://github.com/pytorch/pytorch/blob/master/Release Candidates)
  • Release Candidate Storage
  • Cherry Picking Fixes
• Promoting RCs to Stable
• Special Topics
  • Updating submodules for a release

General Overview

Releasing a new version of PyTorch generally entails 3 major steps:

1. Cutting a release branch and making release branch specific changes
2. Drafting RCs (Release Candidates), and merging cherry picks
3. Promoting RCs to stable

Cutting release branches

Release branches are typically cut from the branch viable/strict as to ensure that tests are passing on the release branch.

Release branches should be prefixed like so:

release/{MAJOR}.{MINOR}

An example of this would look like:

release/1.8

Please make sure to create branch that pins divergent point of release branch from the main branch, i.e. orig/release/{MAJOR}.{MINOR}

Making release branch specific changes

These are examples of changes that should be made to release branches so that CI / tooling can function normally on them:

• Update target determinator to use release branch:
  • Example: pytorch/pytorch#40712
• Update backwards compatibility tests to use RC binaries instead of nightlies
  • Example: pytorch/pytorch#40706
• A release branches should also be created in pytorch/xla and pytorch/builder repos and pinned in pytorch/pytorch

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Commits

• bc2c6ed Re-enable Windows debug libtorch (#73900)
• 46f8586 Also install c10d headers with .h extension (#73422) (#73497)
• a556333 scatter_reduce documentation (#73125) (#73365)
• 3c14fe2 Introduce an environment variable to change c10 log level (#71746) (#73357)
• 055052b Improvements to C10d log (#73358)
• 68ef2a2 Documenting cuda 11.5 windows issue (#73013) (#73312)
• 9647fb7 Use "large" macos for binary builds
• e494487 stop sccache server after building (#72794) (#73122)
• bbf2c0e Disable test history as it's fragile
• e6e8877 avoiding adding some functions to the public python API before 1.11 release (...
• Additional commits viewable in compare view

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[epwalsh]

Waiting on https://github.com/allenai/docker-images/pull/35

[epwalsh]

Needs allenai/allennlp-models#325 before model tests will pass.