mindspore.numpy.empty_like
- mindspore.numpy.empty_like(prototype, dtype=None, shape=None)[source]
Returns a new array with the same shape and type as a given array.
Note
Input array must have the same size across a dimension. If prototype is not a Tensor, dtype is float32 by default if not provided.
- Parameters
prototype (Union[Tensor, list, tuple]) – The shape and data-type of prototype define these same attributes of the returned array.
dtype (
mindspore.dtype
, optional) – Overrides the data type of the result.shape (int or sequence of ints, optional) – Overrides the shape of the result.
- Returns
Tensor, array of uninitialized (arbitrary) data with the same shape and type as prototype.
- Raises
ValueError – if prototype is not a Tensor, list or tuple.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore.numpy as np >>> a = np.ones((4,1,2)) >>> output = np.empty_like(a) >>> print(output) # result may vary Tensor(shape=[4, 1, 2], dtype=Float32, value= <uninitialized>)