mindspore.numpy.reshape

mindspore.numpy.reshape(x, new_shape)

Reshapes a tensor without changing its data.

Parameters

• x (Tensor) – A tensor to be reshaped.

• new_shape (Union[int, list(int), tuple(int)]) – The new shape should be compatible with the original shape. If the tuple has only one element, the result will be a 1-D tensor of that length. One shape dimension can be \(-1\). In this case, the value is inferred from the length of the tensor and remaining dimensions.

Returns

Reshaped Tensor. Has the same data type as the original tensor x.

Raises

• TypeError – If new_shape is not integer, list or tuple, or x is not tensor.

• ValueError – If new_shape is not compatible with the original shape.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> x = np.asarray([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]])
>>> output = np.reshape(x, (3, 2))
>>> print(output)
[[-0.1  0.3]
 [ 3.6  0.4]
 [ 0.5 -3.2]]
>>> output = np.reshape(x, (3, -1))
>>> print(output)
[[-0.1  0.3]
 [ 3.6  0.4]
 [ 0.5 -3.2]]
>>> output = np.reshape(x, (6, ))
>>> print(output)
[-0.1  0.3  3.6  0.4  0.5 -3.2]