# tf.autograph.experimental.set_loop_options

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/autograph/lang/directives.py#L45-L94) |

Specifies additional arguments to be passed to the enclosing while_loop.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.autograph.experimental.set_loop_options`](https://www.tensorflow.org/api_docs/python/tf/autograph/experimental/set_loop_options)

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    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.

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| ## Usage ||
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| <br /> >>> @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 <br /> ||

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Also see tf.while_loop.

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| ## Args ||
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| `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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