torch.tril

torch.tril(input, diagonal=0, *, out=None) → Tensor

Returns the lower triangular part of the matrix (2-D tensor) or batch of matrices input, the other elements of the result tensor out are set to 0.

The lower triangular part of the matrix is defined as the elements on and below the diagonal.

The argument diagonal controls which diagonal to consider. If diagonal = 0, all elements on and below the main diagonal are retained. A positive value includes just as many diagonals above the main diagonal, and similarly a negative value excludes just as many diagonals below the main diagonal. The main diagonal are the set of indices $\lbrace (i, i) \rbrace$ for $i \in [0, \min\{d_{1}, d_{2}\} - 1]$ where $d_{1}, d_{2}$ are the dimensions of the matrix.

Parameters

• input (Tensor) – the input tensor.

• diagonal (int, optional) – the diagonal to consider

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> a = torch.randn(3, 3)
>>> a
tensor([[-1.0813, -0.8619,  0.7105],
        [ 0.0935,  0.1380,  2.2112],
        [-0.3409, -0.9828,  0.0289]])
>>> torch.tril(a)
tensor([[-1.0813,  0.0000,  0.0000],
        [ 0.0935,  0.1380,  0.0000],
        [-0.3409, -0.9828,  0.0289]])

>>> b = torch.randn(4, 6)
>>> b
tensor([[ 1.2219,  0.5653, -0.2521, -0.2345,  1.2544,  0.3461],
        [ 0.4785, -0.4477,  0.6049,  0.6368,  0.8775,  0.7145],
        [ 1.1502,  3.2716, -1.1243, -0.5413,  0.3615,  0.6864],
        [-0.0614, -0.7344, -1.3164, -0.7648, -1.4024,  0.0978]])
>>> torch.tril(b, diagonal=1)
tensor([[ 1.2219,  0.5653,  0.0000,  0.0000,  0.0000,  0.0000],
        [ 0.4785, -0.4477,  0.6049,  0.0000,  0.0000,  0.0000],
        [ 1.1502,  3.2716, -1.1243, -0.5413,  0.0000,  0.0000],
        [-0.0614, -0.7344, -1.3164, -0.7648, -1.4024,  0.0000]])
>>> torch.tril(b, diagonal=-1)
tensor([[ 0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000],
        [ 0.4785,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000],
        [ 1.1502,  3.2716,  0.0000,  0.0000,  0.0000,  0.0000],
        [-0.0614, -0.7344, -1.3164,  0.0000,  0.0000,  0.0000]])