mindspore.ops.BiasAdd

class mindspore.ops.BiasAdd(data_format='NCHW')[source]

Returns the sum of the input Tensor and the bias Tensor. Before adding, the bias Tensor will be broadcasted to be consistent with the shape of the input Tensor.

Parameters:: data_format (str, optional) – The format of input and output data. It should be "NHWC" , "NCHW" or "NCDHW" . Default is "NCHW" .

Inputs:

input_x (Tensor) - The input tensor. The shape can be 2-5 dimensions. Supported dtypes:
- Ascend/CPU: all Number type.
- GPU: float16, float32, int8.
bias (Tensor) - The bias tensor, with shape \((C)\). C must be the same as channel dimension C of input_x. It has the same type as input_x.

Outputs:

Tensor, with the same shape and data type as input_x.

Raises:

TypeError – If data_format is not a str.
ValueError – If value of data_format is not in the range of ['NHWC','NCHW','NCDHW'].
TypeError – If input_x or bias is not a Tensor.
TypeError – If dtype of input_x or bias is inconsistent.
TypeError – If dimension of input_x is not in the range [2, 5].

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input_x = Tensor(np.arange(6).reshape((2, 3)), mindspore.float32)
>>> bias = Tensor(np.random.random(3).reshape((3,)), mindspore.float32)
>>> bias_add = ops.BiasAdd()
>>> output = bias_add(input_x, bias)
>>> print(output.shape)
(2, 3)