Bump accelerate from 0.33.0 to 1.1.1

[dependabot]

Bumps accelerate from 0.33.0 to 1.1.1.

Release notes

Sourced from accelerate's releases.

v1.0.1: Bugfix

Bugfixes

• Fixes an issue where the auto values were no longer being parsed when using deepspeed
• Fixes a broken test in the deepspeed tests related to the auto values

Full Changelog: huggingface/accelerate@v1.0.0...v1.0.1

Accelerate 1.0.0 is here!

🚀 Accelerate 1.0 🚀

With accelerate 1.0, we are officially stating that the core parts of the API are now "stable" and ready for the future of what the world of distributed training and PyTorch has to handle. With these release notes, we will focus first on the major breaking changes to get your code fixed, followed by what is new specifically between 0.34.0 and 1.0.

To read more, check out our official blog here

Migration assistance

• Passing in dispatch_batches, split_batches, even_batches, and use_seedable_sampler to the Accelerator() should now be handled by creating an accelerate.utils.DataLoaderConfiguration() and passing this to the Accelerator() instead (Accelerator(dataloader_config=DataLoaderConfiguration(...)))
• Accelerator().use_fp16 and AcceleratorState().use_fp16 have been removed; this should be replaced by checking accelerator.mixed_precision == "fp16"
• Accelerator().autocast() no longer accepts a cache_enabled argument. Instead, an AutocastKwargs() instance should be used which handles this flag (among others) passing it to the Accelerator (Accelerator(kwargs_handlers=[AutocastKwargs(cache_enabled=True)]))
• accelerate.utils.is_tpu_available should be replaced with accelerate.utils.is_torch_xla_available
• accelerate.utils.modeling.shard_checkpoint should be replaced with split_torch_state_dict_into_shards from the huggingface_hub library
• accelerate.tqdm.tqdm() no longer accepts True/False as the first argument, and instead, main_process_only should be passed in as a named argument

Multiple Model DeepSpeed Support

After long request, we finally have multiple model DeepSpeed support in Accelerate! (though it is quite early still). Read the full tutorial here, however essentially:

When using multiple models, a DeepSpeed plugin should be created for each model (and as a result, a separate config). a few examples are below:

Knowledge distillation

(Where we train only one model, zero3, and another is used for inference, zero2)

from accelerate import Accelerator
from accelerate.utils import DeepSpeedPlugin
zero2_plugin = DeepSpeedPlugin(hf_ds_config="zero2_config.json")
zero3_plugin = DeepSpeedPlugin(hf_ds_config="zero3_config.json")
deepspeed_plugins = {"student": zero2_plugin, "teacher": zero3_plugin}
accelerator = Accelerator(deepspeed_plugins=deepspeed_plugins)

To then select which plugin to be used at a certain time (aka when calling prepare), we call `accelerator.state.select_deepspeed_plugin("name"), where the first plugin is active by default:

</tr></table> 

... (truncated)

Commits

• cdde654 Fix align_module_device, ensure only cpu tensors for `get_state_dict_offloa...
• d0e80e5 Release: v1.1.0
• bf4572b [Utils] align_module_device (#3204)
• a4a44ac Update big_modeling.py (#3207)
• b0e5fd3 add xpu (#3163)
• 8159c98 Models With Tied Weights Need Re-Tieing After FSDP Param Init (#3154)
• 497eb3c fix bug (#3166)
• 87732a4 take torch.nn.Module model into account when moving to device (#3167)
• ffbca15 eliminate dead code (#3198)
• ba7ab93 Update transformers.deepspeed references from transformers 4.46.0 release (#3...
• Additional commits viewable in compare view

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[github-actions]

Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

OpenSSF Scorecard

Package	Version	Score	Details
pip/accelerate	1.1.1	🟢 6.1	Details Check Score Reason Maintained 🟢 10 30 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10 Code-Review 🟢 9 Found 28/30 approved changesets -- score normalized to 9 CII-Best-Practices ⚠️ 0 no effort to earn an OpenSSF best practices badge detected License 🟢 10 license file detected Signed-Releases ⚠️ -1 no releases found Branch-Protection ⚠️ -1 internal error: error during branchesHandler.setup: internal error: githubv4.Query: Resource not accessible by integration Binary-Artifacts 🟢 10 no binaries found in the repo Dangerous-Workflow 🟢 10 no dangerous workflow patterns detected Security-Policy ⚠️ 0 security policy file not detected Token-Permissions ⚠️ 0 detected GitHub workflow tokens with excessive permissions Fuzzing ⚠️ 0 project is not fuzzed Vulnerabilities 🟢 10 0 existing vulnerabilities detected Pinned-Dependencies ⚠️ 0 dependency not pinned by hash detected -- score normalized to 0 Packaging 🟢 10 packaging workflow detected SAST ⚠️ 1 SAST tool is not run on all commits -- score normalized to 1

Scanned Files

• setup.py