tf.compat.v1.tpu.rewrite

Rewrites computation for execution on a TPU system.

tf.compat.v1.tpu.rewrite(
    computation, inputs=None, infeed_queue=None, device_assignment=None, name=None,
    xla_options=None
)

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 `rewrite` is a list of tensors corresponding to the tensors from the output of `computation`. All `Operation`s constructed during `computation` will be executed when evaluating any of the returned output tensors, not just the ones returned.
`inputs`	A list of input tensors 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`.
`infeed_queue`	If not `None`, the `InfeedQueue` from which to append a tuple of arguments as inputs to `computation`.
`device_assignment`	if not `None`, a `DeviceAssignment` describing the mapping between logical cores in the computation with physical cores in the TPU topology. May be omitted for a single-core computation, in which case the core attached to task 0, TPU device 0 is used.
`name`	(Deprecated) Does nothing.
`xla_options`	An instance of `tpu.XLAOptions` which indicates the options passed to XLA compiler. Use `None` for default options.

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.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/tpu/rewrite