mindspore.ops.bmm
- mindspore.ops.bmm(input_x, mat2)[source]
Computes matrix multiplication between two tensors by batch.
\[\text{output}[..., :, :] = \text{matrix}(input_x[..., :, :]) * \text{matrix}(mat2[..., :, :])\]The dim of input_x can not be less than 3 and the dim of mat2 can not be less than 2.
- Parameters
input_x (Tensor) – The first tensor to be multiplied. The shape of the tensor is \((*B, N, C)\), where \(*B\) represents the batch size which can be multidimensional, \(N\) and \(C\) are the size of the last two dimensions.
mat2 (Tensor) – The second tensor to be multiplied. The shape of the tensor is \((*B, C, M)\).
- Returns
Tensor, the shape of the output tensor is \((*B, N, M)\).
- Raises
ValueError – If dim of input_x is less than 3 or dim of mat2 is less than 2.
ValueError – If the length of the third dim of input_x is not equal to the length of the second dim of mat2.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore as ms >>> from mindspore import Tensor, ops >>> import numpy as np >>> input_x = Tensor(np.arange(24).reshape((2, 4, 1, 3)), ms.float32) >>> mat2 = Tensor(np.arange(72).reshape((2, 4, 3, 3)), ms.float32) >>> output = ops.bmm(input_x, mat2) >>> print(output) [[[[ 15. 18. 21.]] [[ 150. 162. 174.]] [[ 447. 468. 489.]] [[ 906. 936. 966.]]] [[[1527. 1566. 1605.]] [[2310. 2358. 2406.]] [[3255. 3312. 3369.]] [[4362. 4428. 4494.]]]]