[PJRT] Only alias inputs and outputs when force_ltc_sync == True
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JackCaoG
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Feb 6, 2023
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I ran our imagenet benchmark on TPU v4 with the PJRT C API. Performance is actually a little better than the last time I checked, but that could be related to another change. |
alanwaketan
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Feb 6, 2023
JackCaoG
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Feb 7, 2023
| @@ -1102,7 +1102,8 @@ XLAGraphExecutor::CompilationResult XLAGraphExecutor::Compile( | |||
| // TODO(yeounoh) aliasing is disabled for partitioned computation, | |||
| // since the current aliasing compares the unpartitioned input and output | |||
| // shapes which can lead to an incorrect aliasing pairs if sharded. | |||
| if (enable_aliasing && coll.config.sync_ltc_data && !is_sharded) { | |||
| if (enable_aliasing && coll.config.sync_ltc_data && | |||
| coll.config.force_ltc_data && !is_sharded) { | |||
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as a follow up, we should add a test to https://github.com/pytorch/xla/blob/master/test/test_input_output_aliases.py and make sure only mark_step trigger the aliasing.
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Updating logic to match comment.
According to the documentation for PJRT, when an input buffer is aliased to an output of an executable, the original input buffer is no longer available. When we reference the
DataPtrthat holds the buffer again, we will inevitably see this error:RuntimeError: ./tensorflow/compiler/xla/xla_client/pjrt_computation_client.h:140 : Check failed: HasValue()Fixes the following failing C++ tests on CPU: