mindspore.mint.eq

mindspore.mint.eq(input, other)[source]

Computes the equivalence between two tensors element-wise.

The second argument can be a number or a tensor whose shape is broadcastable with the first argument and vise versa.

\[\begin{split}out_{i} =\begin{cases} & \text{True, if } input_{i} = other_{i} \\ & \text{False, if } input_{i} \ne other_{i} \end{cases}\end{split}\]

Note

  • input and other comply with the implicit type conversion rules to make the data types consistent.

  • The input must be two Tensors, or a Tensor and a Scalar.

  • The shapes of the inputs can be broadcasted to each other.

Parameters

  • input (Union[Tensor, Number]) – The first input is a number or a tensor whose data type is number.

  • other (Union[Tensor, Number]) – The second input is a number when the first input is a tensor. The data type is the same as the first input. If the first input is a number, the second input should be a tensor.

Returns

Tensor, the shape is the same as the one after broadcasting, and the data type is bool.

Raises

TypeError – If neither input nor other is a Tensor.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor, mint
>>> # case 1: The shape of two inputs are different
>>> x = Tensor([1, 2, 3], mindspore.float32)
>>> output = mint.eq(x, 2.0)
>>> print(output)
[False True False]
>>> # case 2: The shape of two inputs are the same
>>> x = Tensor([1, 2, 3], mindspore.int32)
>>> y = Tensor([1, 2, 4], mindspore.int32)
>>> output = mint.eq(x, y)
>>> print(output)
[ True  True False]