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_tensor
#>  0.0106
#>  0.0462
#>  0.0225
#> -0.0280
#> -0.0758
#>  0.1148
#>  0.0002
#>  0.0741
#>  0.0000
#> -0.1320
#>  0.0299
#> -0.0354
#> -0.0308
#> -0.0399
#>  0.0015
#> -0.0119
#>  0.0876
#> -0.1525
#>  0.1750
#>  0.1743
#>  0.0715
#>  0.0495
#> -0.0582
#>  0.0520
#> -0.0923
#> -0.0001
#> -0.1454
#>  0.0377
#> -0.0451
#> -0.0971
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{100} ]