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stop_gradient#

ivy.stop_gradient(x, /, *, preserve_type=True, out=None)[source]#

Stop gradient computation.

Parameters:

  • x (Union[Array, NativeArray]) – Array for which to stop the gradient.

  • preserve_type (bool, default: True) – Whether to preserve gradient computation on ivy.Array instances. Default is True.

  • out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

  • ret – The same array x, but with no gradient information.

  • Both the description and the type hints above assumes an array input for simplicity,

  • but this function is nestable, and therefore also accepts ivy.Container

  • instances in place of any of the arguments.

Examples

With ivy.Array inputs:

>>> x = ivy.array([1., 2., 3.])
>>> y = ivy.stop_gradient(x, preserve_type=True)
>>> print(y)
ivy.array([1., 2., 3.])

>>> x = ivy.zeros((2, 3))
>>> ivy.stop_gradient(x, preserve_type=False, out=x)
>>> print(x)
ivy.array([[0., 0., 0.],
           [0., 0., 0.]])

With one ivy.Container inputs:

>>> x = ivy.Container(a=ivy.array([0., 1., 2.]),
...                   b=ivy.array([3., 4., 5.]))
>>> y = ivy.stop_gradient(x, preserve_type=False)
>>> print(y)
{
    a: ivy.array([0., 1., 2.]),
    b: ivy.array([3., 4., 5.])
}

With multiple ivy.Container inputs:

>>> x = ivy.Container(a=ivy.array([0., 1., 2.]),
...                   b=ivy.array([3., 4., 5.]))
>>> ivy.stop_gradient(x, preserve_type=True, out=x)
>>> print(x)
{
    a: ivy.array([0., 1., 2.]),
    b: ivy.array([3., 4., 5.])
}
Array.stop_gradient(self, /, *, preserve_type=True, out=None)[source]#

ivy.Array instance method variant of ivy.stop_gradient. This method simply wraps the function, and so the docstring for ivy.stop_gradient also applies to this method with minimal changes.

Parameters:

  • self (Array) – Array for which to stop the gradient.

  • preserve_type (bool, default: True) – Whether to preserve gradient computation on ivy.Array instances. Default is True.

  • out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

ret – The same array x, but with no gradient information.

Examples

>>> x = ivy.array([1., 2., 3.])
>>> y = x.stop_gradient(preserve_type=True)
>>> print(y)
ivy.array([1., 2., 3.])
Container.stop_gradient(self, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, preserve_type=True, out=None)[source]#

ivy.Container instance method variant of ivy.stop_gradient. This method simply wraps the function, and so the docstring for ivy.stop_gradient also applies to this method with minimal changes.

Parameters:

  • self (Container) – Container for which to stop the gradient.

  • key_chains (Optional[Union[List[str], Dict[str, str], Container]], default: None) – The key-chains to apply or not apply the method to. Default is None.

  • to_apply (Union[bool, Container], default: True) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is True.

  • prune_unapplied (Union[bool, Container], default: False) – Whether to prune key_chains for which the function was not applied. Default is False.

  • map_sequences (Union[bool, Container], default: False) – Whether to also map method to sequences (lists, tuples). Default is False.

  • preserve_type (Union[bool, Container], default: True) – Whether to preserve gradient computation on ivy.Array instances. Default is True.

  • out (Optional[Container], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Container

Returns:

ret – The same array x, but with no gradient information.

Examples

With one ivy.Container inputs:

>>> x = ivy.Container(a=ivy.array([0., 1., 2.]),
...                      b=ivy.array([3., 4., 5.]))
>>> y = x.stop_gradient(preserve_type=False)
>>> print(y)
{
    a: ivy.array([0., 1., 2.]),
    b: ivy.array([3., 4., 5.])
}

With multiple ivy.Container inputs:

>>> x = ivy.Container(a=ivy.array([0., 1., 2.]),
...                      b=ivy.array([3., 4., 5.]))
>>> x.stop_gradient(preserve_type=True, out=x)
>>> print(x)
{
    a: ivy.array([0., 1., 2.]),
    b: ivy.array([3., 4., 5.])
}
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