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
#> -0.0696
#>  0.1017
#>  0.0997
#>  0.0271
#> -0.0702
#>  0.1115
#>  0.0374
#>  0.0652
#>  0.0067
#>  0.2535
#>  0.1018
#>  0.0276
#> -0.0774
#>  0.0946
#> -0.0288
#> -0.1134
#>  0.0072
#>  0.1359
#>  0.0328
#>  0.0058
#>  0.0152
#>  0.0777
#>  0.0776
#>  0.0509
#>  0.0454
#> -0.0583
#>  0.1607
#> -0.0631
#>  0.0201
#>  0.0493
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{100} ]