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mindspore.ops.cosine_similarity

mindspore.ops.cosine_similarity(x1, x2, dim=1, eps=1e-08)

Calculate cosine similarity between x1 and x2 along the axis, dim.

$$\text{similarity}={\displaystyle \frac{x_1\cdot x_2}{max(\Vert x_1{\Vert }_2\cdot \Vert x_2{\Vert }_2,ϵ)}}$$

Note

Currently, broadcast of input is not supported.

Parameters

• x1 (Tensor) – The first input Tensor.

• x2 (Tensor) – The second input Tensor.

• dim (int, optional) – Axis for calculating cosine similarity. Default: 1 .

• eps (float, optional) – Minimal value to avoid division by zero. Default: 1e-08 .

Returns

Tensor, cosine similarity between x1 and x2.

Raises

TypeError – If the dtype of x1 or x2 is neither float16 nor float32.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore as ms
>>> from mindspore import ops
>>> x1 = ms.Tensor([[-0.0256, 0.0127, -0.2475, 0.2316, 0.8037],
...                 [0.5809, -1.2712, -0.7038, -0.2558, 0.7494]], dtype=ms.float32)
>>> x2 = ms.Tensor([[-0.6115, -0.1965, -0.8484, 0.2389, 0.2409],
...                 [1.8940, -2.1997, 0.1915, 0.0856, 0.7542]], dtype=ms.float32)
>>> output = ops.cosine_similarity(x1, x2)
>>> print(output)
[0.4843164  0.81647635]