3 Commits

Author	SHA1	Message	Date
Xuehai Pan	758a0a88a2	[BE][Easy] enable ruff rule PIE790: unnecessary pass statement (#133200) ... This PR removes unnecessary `pass` statement. This is semanticly safe because the bytecode for the Python code does not change. Note that if there is a docstring in the function, a empty function does not need a `pass` statement as placeholder. Pull Request resolved: https://github.com/pytorch/pytorch/pull/133200 Approved by: https://github.com/malfet, https://github.com/eqy, https://github.com/kit1980	2024-08-15 15:50:19 +00:00
Xuehai Pan	22d258427b	[BE][Easy] enable UFMT for torch/distributed/_shard/ (#128867) ... Part of #123062 - #123062 Pull Request resolved: https://github.com/pytorch/pytorch/pull/128867 Approved by: https://github.com/fegin ghstack dependencies: #128866	2024-06-18 14:39:25 +00:00
Wanchao Liang	a37141addd	[shard] Extensible Sharder and ShardingPlanner (#75844) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/75844 Add extensible Sharder and ShardingPlanner for advanced users to extend and do custom sharding, some details: * ShardingPlanner is merely a interface that could be extended to plan advanced sharding strategies, it will produce a ShardingPlan that outlines the detailed sharding strategies for each submodule, note that it could also include custom sharders. * a custom Sharder is another interface that could be extended to define advanced sharding strategies for specific modules (i.e. a collection of `nn.EmbeddingBag`s.) The custom sharder defined by the user can be picked up by `share_module` API. `shard_module` will call `Sharder.shard` to the module, the output of the `Sharder.shard` will replace the original submodule. ghstack-source-id: 154978919 Test Plan: test_sharder test_sharding_plan Reviewed By: pritamdamania87 Differential Revision: D35658657 fbshipit-source-id: ad9deb39a6a0ab91ceb1de3a78c4709aa50ad699 (cherry picked from commit f9796471bd7f8ad94a9d3462cac30eacacf68b31)	2022-04-28 04:11:10 +00:00