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Update smd_model_parallel_pytorch.rst (#2106)
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doc/api/training/smp_versions/v1.2.0/smd_model_parallel_pytorch.rst

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@@ -140,16 +140,16 @@ This API document assumes you use the following import statements in your traini
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computation. \ ``bucket_cap_mb``\ controls the bucket size in MegaBytes
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(MB).
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- ``trace_memory_usage`` (default: False): When set to True, the library attempts
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- ``trace_memory_usage`` (default: False): When set to True, the library attempts
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to measure memory usage per module during tracing. If this is disabled,
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memory usage will be estimated through the sizes of tensors returned from
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the module.
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- ``broadcast_buffers`` (default: True): Flag to be used with ``ddp=True``.
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- ``broadcast_buffers`` (default: True): Flag to be used with ``ddp=True``.
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This parameter is forwarded to the underlying ``DistributedDataParallel`` wrapper.
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Please see: `broadcast_buffer <https://pytorch.org/docs/stable/generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel>`__.
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- ``gradient_as_bucket_view (PyTorch 1.7 only)`` (default: False): To be
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- ``gradient_as_bucket_view (PyTorch 1.7 only)`` (default: False): To be
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used with ``ddp=True``. This parameter is forwarded to the underlying
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``DistributedDataParallel`` wrapper. Please see `gradient_as_bucket_view <https://pytorch.org/docs/stable/generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel>`__.
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