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Merge branch 'master' into loadams/update-transformers-deepspeed-modules
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mrwyattii authored Dec 15, 2023
2 parents 3a1def0 + d1f1d45 commit 0efae32
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Original file line number Diff line number Diff line change
Expand Up @@ -163,7 +163,7 @@ def forward(

if (self.config.dtype in [torch.float16, torch.bfloat16, torch.int8]) \
and input.dtype == torch.float:
target_dtype = torch.half if self.dtype == torch.int8 else self.dtype
target_dtype = torch.half if self.config.dtype == torch.int8 else self.config.dtype
input = input.to(target_dtype)

with torch.no_grad():
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2 changes: 1 addition & 1 deletion docs/_tutorials/getting-started.md
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Expand Up @@ -8,7 +8,7 @@ tags: getting-started
## Installation

* Installing is as simple as `pip install deepspeed`, [see more details](/tutorials/advanced-install/).
* To get started with DeepSpeed on AzureML, please see the [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/python-sdk/workflows/train/deepspeed)
* To get started with DeepSpeed on AzureML, please see the [AzureML Examples GitHub](https://github.com/Azure/azureml-examples/tree/main/cli/jobs/deepspeed)
* DeepSpeed has direct integrations with [HuggingFace Transformers](https://github.com/huggingface/transformers) and [PyTorch Lightning](https://github.com/PyTorchLightning/pytorch-lightning). HuggingFace Transformers users can now easily accelerate their models with DeepSpeed through a simple ``--deepspeed`` flag + config file [See more details](https://huggingface.co/docs/transformers/main_classes/deepspeed). PyTorch Lightning provides easy access to DeepSpeed through the Lightning Trainer [See more details](https://pytorch-lightning.readthedocs.io/en/stable/advanced/multi_gpu.html?highlight=deepspeed#deepspeed).
* DeepSpeed on AMD can be used via our [ROCm images](https://hub.docker.com/r/deepspeed/rocm501/tags), e.g., `docker pull deepspeed/rocm501:ds060_pytorch110`.

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