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
#> -0.0518
#> -0.1353
#>  0.0055
#>  0.1350
#>  0.0106
#>  0.0236
#>  0.0152
#> -0.0359
#> -0.0339
#>  0.0344
#>  0.0024
#>  0.0932
#>  0.0735
#>  0.0522
#>  0.0258
#>  0.0779
#> -0.1295
#> -0.0928
#>  0.0746
#>  0.0432
#>  0.0355
#>  0.0251
#>  0.0303
#> -0.0159
#>  0.1192
#>  0.0507
#>  0.1229
#> -0.0884
#> -0.0054
#> -0.0657
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{100} ]