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Update tf32 documentation to mention complex64.

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Currently, tf32 is only used with complex64 for batch matrix multiplications, but more cases will likely be added in the future

PiperOrigin-RevId: 338385413
Change-Id: I70e7b123c05f00c83fc19d86dd29a171e3a0b865
This commit is contained in:
Reed Wanderman-Milne 2020-10-21 19:04:14 -07:00 committed by TensorFlower Gardener
parent 9d266e05ac
commit 40a7f30b39
2 changed files with 5 additions and 1 deletions
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3
RELEASE.md
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@ -11,7 +11,8 @@
[TensorFloat-32](https://blogs.nvidia.com/blog/2020/05/14/tensorfloat-32-precision-format/).
Specifically, inputs to such ops are rounded from 23 bits of precision to 10
bits of precision. This is unlikely to cause issues in practice for deep
learning models. TensorFloat-32 can be disabled by running
learning models. In some cases, TensorFloat-32 is also used for complex64 ops.
TensorFloat-32 can be disabled by running
`config.experimental.enable_tensor_float_32_execution(False)`. The "Major
Features and Improvements" section has more details.
* The byte layout for string tensors across the C-API has been updated to match

3
tensorflow/python/framework/config.py
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@ -81,6 +81,9 @@ def enable_tensor_float_32_execution(enabled):
be added in the future. As a result, precision of float32 ops may decrease in
minor versions of TensorFlow.
TensorFloat-32 is also used for some complex64 ops. Currently, TensorFloat-32
is used in fewer cases for complex64 as it is for float32.
Args:
enabled: Bool indicating whether to enable TensorFloat-32 execution.
"""