zero_pad#
- ivy.zero_pad(x, /, pad_width, *, out=None)[source]#
Pad an array with zeros.
- Parameters:
x (
Union
[Array
,NativeArray
]) – Input array to pad.pad_width (
Iterable
[Tuple
[int
]]) – Number of values padded to the edges of each axis. Specified as ((before_1, after_1), … (before_N, after_N)), where N is number of axes of x.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:
- Returns:
ret – Padded array of rank equal to x with shape increased according to pad_width.
This function conforms to the `Array API Standard
<https (//data-apis.org/array-api/latest/>`_. This docstring is an extension of the)
`docstring <https (//data-apis.org/array-api/latest/)
API_specification/generated/array_api.concat.html>`_
in the standard.
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
input:>>> x = ivy.array([1., 2., 3.,4, 5, 6]) >>> y = ivy.zero_pad(x, pad_width = [[2, 3]]) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 0., 0., 0.])
>>> x = ivy.array([[1., 2., 3.],[4, 5, 6]]) >>> y = ivy.zero_pad(x, pad_width = [[2, 3], [2, 3]]) >>> print(y) ivy.array([[0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 1., 2., 3., 0., 0., 0.], [0., 0., 4., 5., 6., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.]])
>>> x = ivy.Container(a = ivy.array([1., 2., 3.]), b = ivy.array([3., 4., 5.])) >>> y = ivy.zero_pad(x, pad_width = [[2, 3]]) >>> print(y) { a: ivy.array([0., 0., 1., 2., 3., 0., 0., 0.]), b: ivy.array([0., 0., 3., 4., 5., 0., 0., 0.]) }
- Array.zero_pad(self, /, pad_width, *, out=None)[source]#
ivy.Array instance method variant of ivy.zero_pad. This method simply wraps the function, and so the docstring for ivy.zero_pad also applies to this method with minimal changes.
- Parameters:
self (
Array
) – Input array to pad.pad_width (
Iterable
[Tuple
[int
]]) – Number of values padded to the edges of each axis. Specified as ((before_1, after_1), … (before_N, after_N)), where N is number of axes of x.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 – Padded array of rank equal to x with shape increased according to pad_width.
Examples
With
ivy.Array
input:>>> x = ivy.array([1., 2., 3.,4, 5, 6]) >>> y = x.zero_pad(pad_width = [[2, 3]]) >>> print(y) ivy.array([0., 0., 1., 2., 3., 4., 5., 6., 0., 0., 0.])
- Container.zero_pad(self, /, pad_width, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#
ivy.Container instance method variant of ivy.zero_pad. This method simply wraps the function, and so the docstring for ivy.zero_pad also applies to this method with minimal changes.
- Parameters:
self (
Container
) – Input array to pad.pad_width (
Union
[Iterable
[Tuple
[int
]],Container
]) – Number of values padded to the edges of each axis. Specified as ((before_1, after_1), … (before_N, after_N)), where N is number of axes of x.key_chains (
Optional
[Union
[List
[str
],Dict
[str
,str
],Container
]], default:None
) – The key-chains to apply or not apply the method to. Default isNone
.to_apply (
Union
[bool
,Container
], default:True
) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default isTrue
.prune_unapplied (
Union
[bool
,Container
], default:False
) – Whether to prune key_chains for which the function was not applied. Default isFalse
.map_sequences (
Union
[bool
,Container
], default:False
) – Whether to also map method to sequences (lists, tuples). Default isFalse
.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 – Padded array of rank equal to x with shape increased according to pad_width.
Examples
With
ivy.Container
input:>>> x = ivy.Container(a = ivy.array([1., 2., 3.]), b = ivy.array([3., 4., 5.])) >>> y = x.zero_pad(pad_width = [[2, 3]]) >>> print(y) { a: ivy.array([0., 0., 1., 2., 3., 0., 0., 0.]), b: ivy.array([0., 0., 3., 4., 5., 0., 0., 0.]) }