|View source on GitHub|
Builds an operator that compiles and runs
computation with XLA.
Compat aliases for migration
See Migration guide for more details.
tf.xla.experimental.compile( computation, inputs=None )
Note: In eager mode,
| || A Python function that builds a computation to apply to the input. If the function takes n inputs, 'inputs' should be a list of n tensors. |
| || A list of inputs or |
| Same data structure as if computation(*inputs) is called directly with some exceptions for correctness. Exceptions include: |
1) None output: a NoOp would be returned which control-depends on computation. 2) Single value output: A tuple containing the value would be returned. 3) Operation-only outputs: a NoOp would be returned which control-depends on computation.
| ||if called when eager execution is enabled.|
When a tf.random operation is built with XLA, the implementation doesn't pass the user provided seed to the XLA compiler. As such, the XLA compiler generates a random number and uses it as a seed when compiling the operation. This implementation causes a violation of the Tensorflow defined semantics in two aspects. First, changing the value of the user defined seed doesn't change the numbers generated by the operation. Second, when a seed is not specified, running the program multiple times will generate the same numbers.
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.