torch_cosine_similarity: Cosine_similarity

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Cosine_similarity

Description

Cosine_similarity

Usage

torch_cosine_similarity(x1, x2, dim = 2L, eps = 1e-08)

Arguments

x1	(Tensor) First input.
x2	(Tensor) Second input (of size matching x1).
dim	(int, optional) Dimension of vectors. Default: 1
eps	(float, optional) Small value to avoid division by zero. Default: 1e-8

cosine_similarity(x1, x2, dim=1, eps=1e-8) -> Tensor

Returns cosine similarity between x1 and x2, computed along dim.

\mbox{similarity} = \frac{x_1 \cdot x_2}{\max(\Vert x_1 \Vert _2 \cdot \Vert x_2 \Vert _2, \epsilon)}

Examples

if (torch_is_installed()) {

input1 = torch_randn(c(100, 128))
input2 = torch_randn(c(100, 128))
output = torch_cosine_similarity(input1, input2)
output
}

torch documentation built on May 29, 2024, 9:54 a.m.