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tf.xla.experimental.compile

Builds an operator that compiles and runs computation with XLA.

View aliases

Compat aliases for migration

tf.compat.v1.xla.experimental.compile, `tf.compat.v2.xla.experimental.compile`

tf.xla.experimental.compile(
    computation, inputs=None
)

Note: In eager mode, computation will have @tf.function semantics.

Args

Args
`computation`	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. `computation` may return a list of operations and tensors. Tensors must come before operations in the returned list. The return value of `compile` is a list of tensors corresponding to the tensors from the output of `computation`. All `Operation`s returned from `computation` will be executed when evaluating any of the returned output tensors.
`inputs`	A list of inputs or `None` (equivalent to an empty list). Each input can be a nested structure containing values that are convertible to tensors. Note that passing an N-dimension list of compatible values will result in a N-dimension list of scalar tensors rather than a single Rank-N tensors. If you need different behavior, convert part of inputs to tensors with `tf.convert_to_tensor`.

computation

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.

computation may return a list of operations and tensors. Tensors must come before operations in the returned list. The return value of compile is a list of tensors corresponding to the tensors from the output of computation.

All Operations returned from computation will be executed when evaluating any of the returned output tensors.

inputs A list of inputs or None (equivalent to an empty list). Each input can be a nested structure containing values that are convertible to tensors. Note that passing an N-dimension list of compatible values will result in a N-dimension list of scalar tensors rather than a single Rank-N tensors. If you need different behavior, convert part of inputs to tensors with tf.convert_to_tensor.

Returns
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.

Raises
`RuntimeError`	if called when eager execution is enabled.

© 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.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/xla/experimental/compile