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intermediate_source/rpc_async_execution.rst
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This tutorial demonstrates how to build batch-processing RPC applications with
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the `@rpc.functions.async_execution <https://pytorch.org/docs/master/rpc.html#torch.distributed.rpc.functions.async_execution>`__
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decorator, which helps to speed up training by reducing the number of blocked
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-RPC threads and consolidating CUDA operations on the callee. This shares the
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-same idea as `Batch Inference with TorchServe <https://pytorch.org/serve/batch_inference_with_ts.html>`__.
+RPC threads and consolidating CUDA operations on the callee.
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.. note:: This tutorial requires PyTorch v1.6.0 or above.
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