tf.autograph.experimental.set_loop_options
Specifies additional arguments to be passed to the enclosing while_loop.
tf.autograph.experimental.set_loop_options(
parallel_iterations=UNSPECIFIED,
swap_memory=UNSPECIFIED,
maximum_iterations=UNSPECIFIED,
shape_invariants=UNSPECIFIED
)
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.
|
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Last updated 2023-03-17 UTC.
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