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|
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.
All |
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. |