to_numpy#
- ivy.to_numpy(x, /, *, copy=True)[source]#
Convert an array into a numpy array.
- Parameters:
x (
Union
[Array
,NativeArray
]) – input arraycopy (
bool
, default:True
) – whether to copy the array to a new address or not. Default isTrue
.
- Return type:
ndarray
- Returns:
ret – a numpy array copying all the element of the array
x
.
Examples
With
ivy.Array
inputs:>>> x = ivy.array([-1, 0, 1]) >>> y = ivy.to_numpy(x, copy=True) >>> print(y) [-1 0 1]
>>> x = ivy.array([[-1, 0, 1],[-1, 0, 1], [1,0,-1]]) >>> y = ivy.to_numpy(x, copy=True) >>> print(y) [[-1 0 1] [-1 0 1] [ 1 0 -1]]
With
ivy.Container
input:>>> x = ivy.Container(a=ivy.array([-1, 0, 1])) >>> y = ivy.to_numpy(x) >>> print(y) { a: array([-1, 0, 1], dtype=int32) }
>>> x = ivy.Container(a=ivy.array([[-1.0, 0., 1.], [-1, 0, 1], [1, 0, -1]]), ... b=ivy.array([[-1, 0, 0], [1, 0, 1], [1, 1, 1]])) >>> y = ivy.to_numpy(x) >>> print(y) { a: array([[-1., 0., 1.], [-1., 0., 1.], [1., 0., -1.]], dtype=float32), b: array([[-1, 0, 0], [1, 0, 1], [1, 1, 1]], dtype=int32) }
- Array.to_numpy(self, /, *, copy=True)[source]#
ivy.Array instance method variant of ivy.to_numpy. This method simply wraps the function, and so the docstring for ivy.to_numpy also applies to this method with minimal changes.
- Parameters:
self (
Array
) – input array.copy (
bool
, default:True
) – whether to copy the array to a new address or not. Default isTrue
.
- Return type:
ndarray
- Returns:
ret – a numpy array copying all the element of the array
self
.
Examples
With
ivy.Array
inputs:>>> x = ivy.array([-1, 0, 1]) >>> y = x.to_numpy() >>> print(y) [-1 0 1]
>>> x = ivy.array([[-1, 0, 1],[-1, 0, 1], [1,0,-1]]) >>> y = x.to_numpy() >>> print(y) [[-1 0 1] [-1 0 1] [ 1 0 -1]]
- Container.to_numpy(self, /, *, copy=True, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False)[source]#
ivy.Container instance method variant of ivy.to_numpy. This method simply wraps the function, and so the docstring for ivy.to_numpy also applies to this method with minimal changes.
- Parameters:
self (
Container
) – input container.copy (
Union
[bool
,Container
], default:True
) – Whether to copy the input. Default isTrue
.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
.
- Return type:
Container
- Returns:
ret – a container of numpy arrays copying all the element of the container
self
.
Examples
With one
ivy.Container
instances:>>> x = ivy.Container(a=ivy.array([-1, 0, 1]), b=ivy.array([1, 0, 1, 1])) >>> y = x.to_numpy() >>> print(y) { a: array([-1, 0, 1], dtype=int32), b: array([1, 0, 1, 1], dtype=int32) }
>>> x = ivy.Container(a=ivy.native_array([[-1, 0, 1], [-1, 0, 1], [1, 0, -1]]), ... b=ivy.native_array([[-1, 0, 0], [1, 0, 1], [1, 1, 1]])) >>> y = x.to_numpy() >>> print(y) { a: array([[-1, 0, 1], [-1, 0, 1], [1, 0, -1]], dtype=int32), b: array([[-1, 0, 0], [1, 0, 1], [1, 1, 1]], dtype=int32) }