2020-11-19 10:21:34 +00:00
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# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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2020-11-25 20:16:20 +00:00
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try:
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from fairscale.nn.data_parallel.sharded_ddp import ShardedDataParallel
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except (ModuleNotFoundError, ImportError):
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FAIRSCALE_SHARDED_AVAILABLE = False
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else:
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FAIRSCALE_SHARDED_AVAILABLE = True
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2020-11-19 10:21:34 +00:00
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2020-11-25 20:16:20 +00:00
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class LightningShardedDataParallel(ShardedDataParallel):
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2020-11-19 10:21:34 +00:00
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2020-11-25 20:16:20 +00:00
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def forward(self, *inputs, **kwargs):
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if self.enable_broadcast_buffers:
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self.sync_buffers()
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2020-11-19 10:21:34 +00:00
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2020-11-25 20:16:20 +00:00
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if self.module.training:
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outputs = self.module.training_step(*inputs, **kwargs)
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elif self.module.testing:
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outputs = self.module.test_step(*inputs, **kwargs)
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else:
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outputs = self.module.validation_step(*inputs, **kwargs)
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return outputs
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