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Fork/join parallelism for ensemble export modules #310
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Summary: Pull Request resolved: pytorch#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Differential Revision: D13827861 fbshipit-source-id: 3adfce3f8ba90ef0ee29a9a6ec81af183a1eebf8
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Summary: Pull Request resolved: pytorch#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Differential Revision: D13827861 fbshipit-source-id: 785444186426fe07f3f555d2ec13895e3095a87b
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Summary: Pull Request resolved: pytorch#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Reviewed By: jmp84 Differential Revision: D13827861 fbshipit-source-id: 6f5f7993eef557f8715fca1a684f0561fec6c1ef
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Summary: Pull Request resolved: pytorch#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Reviewed By: jmp84 Differential Revision: D13827861 fbshipit-source-id: 0b88412198ba9d43ab4990e9812a306f292fbf67
Summary: Pull Request resolved: pytorch#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Reviewed By: jmp84 Differential Revision: D13827861 fbshipit-source-id: 2d6d9e32836fef7f30f0c3f430a6d3a1a7d262f5
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Summary: Pull Request resolved: pytorch/translate#310 This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel. Benchmark validation is pending me slogging through FBLearner Flow issues, as usual Reviewed By: jmp84 Differential Revision: D13827861 fbshipit-source-id: 0cb9df6e10c0ba64a6b81fa374e077bce90f1d5b
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Summary:
This adds fork/join parallelism to the EncoderEnsemble and DecoderBatchedStepEnsemble models. Note that when run in Python, these calls are no-op, and similarly we remove these calls before exporting to ONNX. But when we run in the PyTorch native runtime, we will now have the opportunity to run these sections in parallel.
Benchmark validation is pending me slogging through FBLearner Flow issues, as usual
Differential Revision: D13827861