mindspore.ops.bias_add

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mindspore.ops.bias_add(input_x, bias)[source]

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

Parameters

  • 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.

Returns

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

Raises

  • TypeError – If input_x or bias is not a Tensor.

  • TypeError – If dtype of input_x and 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)
>>> output = ops.bias_add(input_x, bias)
>>> print(output.shape)
(2, 3)