mindspore.numpy.reshape
- mindspore.numpy.reshape(x, new_shape)[source]
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]