W3cubDocs

/TensorFlow 2.4

tf.autograph.experimental.set_loop_options

Specifies additional arguments to be passed to the enclosing while_loop.

The parameters apply to and only to the immediately enclosing loop. It only has effect if the loop is staged as a TF while_loop; otherwise the parameters have no effect.

Usage:

@tf.function(autograph=True)
def f():
  n = 0
  for i in tf.range(10):
    tf.autograph.experimental.set_loop_options(maximum_iterations=3)
    n += 1
  return n
@tf.function(autograph=True)
def f():
  v = tf.constant((0,))
  for i in tf.range(3):
    tf.autograph.experimental.set_loop_options(
        shape_invariants=[(v, tf.TensorShape([None]))]
    )
    v = tf.concat((v, [i]), 0)
  return v

Also see tf.while_loop.

Args
parallel_iterations The maximum number of iterations allowed to run in parallel at any given time. Note that this does not guarantee parallel execution.
swap_memory Whether to store intermediate values needed for gradients on the CPU instead of GPU.
maximum_iterations Allows limiting the total number of iterations executed by the loop.
shape_invariants Allows controlling the argument with the same name passed to tf.while_loop. Unlike tf.while_loop, this is a list of (tensor, shape) pairs.

© 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/r2.4/api_docs/python/tf/autograph/experimental/set_loop_options