Maps a function on the list of tensors unpacked from arguments on dimension 0.
tf.raw_ops.MapDefun(
arguments,
captured_inputs,
output_types,
output_shapes,
f,
max_intra_op_parallelism=1,
name=None
)
The function given by f
is assumed to be stateless, and is executed
concurrently on all the slices; up to batch_size (i.e. the size of the 0th
dimension of each argument) functions will be scheduled at once.
The max_intra_op_parallelism
attr, which defaults to 1, can be used to
limit the intra op parallelism. To limit inter-op parallelism, a user can
set a private threadpool on the dataset using tf.data.Options
's
ThreadingOptions
.
Note that this op is not exposed to users directly, but is invoked in tf.data rewrites.
Args | |
---|---|
arguments
|
A list of Tensor objects.
A list of tensors whose types are Targuments , corresponding to the inputs
the function should be mapped over.
|
captured_inputs
|
A list of Tensor objects.
A list of tensors whose types are Tcaptured , corresponding to the captured
inputs of the defun.
|
output_types
|
A list of tf.DTypes that has length >= 1 .
A list of types.
|
output_shapes
|
A list of shapes (each a tf.TensorShape or list of ints ) that has length >= 1 .
A list of shapes.
|
f
|
A function decorated with @Defun. |
max_intra_op_parallelism
|
An optional int . Defaults to 1 .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A list of Tensor objects of type output_types .
|