tf.raw_ops.MapDefun | TensorFlow v2.16.1 (original) (raw)
tf.raw_ops.MapDefun
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Maps a function on the list of tensors unpacked from arguments on dimension 0.
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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'sThreadingOptions.
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. |