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update
Signed-off-by: Tyler Michael Smith <tyler@neuralmagic.com>
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@ -782,7 +782,6 @@ class GroupCoordinator:
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def prepare_communication_buffer_for_model(self, model: torch.nn.Module):
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if self.device_communicator is not None:
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torch.distributed.barrier(self.device_communicator)
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self.device_communicator.prepare_communication_buffer_for_model(
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model)
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@ -1116,6 +1115,7 @@ def prepare_communication_buffer_for_model(model: torch.nn.Module):
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MoE all2all (DeepEP) usually allocate the communication buffer
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based on the model shape for optimal performance.
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"""
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get_world_group().barrier()
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if _TP is not None:
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_TP.prepare_communication_buffer_for_model(model)
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if _PP is not None:
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