jax.numpy.squeeze¶

jax.numpy.squeeze(a, axis=None)[source]¶

Remove single-dimensional entries from the shape of an array.

LAX-backend implementation of squeeze(). Original docstring below.

Parameters

a (array_like) – Input data.
axis (None or int or tuple of ints, optional) –

New in version 1.7.0.

Returns

squeezed – The input array, but with all or a subset of the dimensions of length 1 removed. This is always a itself or a view into a. Note that if all axes are squeezed, the result is a 0d array and not a scalar.

Return type

ndarray

Raises

ValueError – If axis is not None, and an axis being squeezed is not of length 1

See also

expand_dims(): The inverse operation, adding singleton dimensions
reshape(): Insert, remove, and combine dimensions, and resize existing ones

Examples

>>> x = np.array([[[0], [1], [2]]])
>>> x.shape
(1, 3, 1)
>>> np.squeeze(x).shape
(3,)
>>> np.squeeze(x, axis=0).shape
(3, 1)
>>> np.squeeze(x, axis=1).shape
Traceback (most recent call last):
...
ValueError: cannot select an axis to squeeze out which has size not equal to one
>>> np.squeeze(x, axis=2).shape
(1, 3)
>>> x = np.array([[1234]])
>>> x.shape
(1, 1)
>>> np.squeeze(x)
array(1234)  # 0d array
>>> np.squeeze(x).shape
()
>>> np.squeeze(x)[()]
1234