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
#>  0.0694
#>  0.1258
#>  0.0879
#>  0.1043
#>  0.0454
#> -0.1570
#> -0.0335
#> -0.0908
#>  0.0051
#>  0.0326
#>  0.1504
#> -0.1074
#>  0.1100
#>  0.0074
#>  0.1805
#> -0.1196
#>  0.0321
#>  0.1185
#>  0.1106
#>  0.1133
#> -0.1167
#> -0.0193
#> -0.0248
#> -0.0850
#> -0.1618
#>  0.0066
#>  0.0806
#> -0.0096
#>  0.1869
#>  0.1189
#> ... [the output was truncated (use n=-1 to disable)]
#> [ CPUFloatType{100} ]