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* decouple DeepSpeedConfigHF from Trainer * add LoggingLevel ctx manager; add new test * cleanup * add docs * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * implemented suggested renames * formatter workaround Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
57 lines
2.4 KiB
ReStructuredText
57 lines
2.4 KiB
ReStructuredText
..
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Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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HfDeepSpeedConfig
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-----------------------------------------------------------------------------------------------------------------------
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The :class:`~transformers.integrations.HfDeepSpeedConfig` is used to integrate Deepspeed into the 🤗 Transformer core
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functionality, when :class:`~transformers.Trainer` is not used.
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When using :class:`~transformers.Trainer` everything is automatically taken care of.
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When not using :class:`~transformers.Trainer`, to efficiently deploy DeepSpeed stage 3, you must instantiate the
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:class:`~transformers.integrations.HfDeepSpeedConfig` object before instantiating the model.
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For example for a pretrained model:
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.. code-block:: python
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from transformers.integrations import HfDeepSpeedConfig
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from transformers import AugoModel
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ds_config = { ... } # deepspeed config object or path to the file
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# must run before instantiating the model
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dschf = HfDeepSpeedConfig(ds_config) # keep this object alive
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model = AutoModel.from_pretrained("gpt2")
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engine = deepspeed.initialize(model=model, config_params=ds_config, ...)
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or for non-pretrained model:
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.. code-block:: python
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from transformers.integrations import HfDeepSpeedConfig
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from transformers import AugoModel, AutoConfig
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ds_config = { ... } # deepspeed config object or path to the file
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# must run before instantiating the model
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dschf = HfDeepSpeedConfig(ds_config) # keep this object alive
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config = AutoConfig.from_pretrained("gpt2")
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model = AutoModel.from_config(config)
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engine = deepspeed.initialize(model=model, config_params=ds_config, ...)
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HfDeepSpeedConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.integrations.HfDeepSpeedConfig
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:members:
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