tril¶
- paddle. tril ( x, diagonal=0, name=None ) [source]
-
Returns the lower triangular part of a matrix (2-D tensor) or batch of matrices
x
, the other elements of the result tensor are set to 0. The lower triangular part of the matrix is defined as the elements on and below the diagonal.- Parameters
-
x (Tensor) – The input x which is a Tensor. Support data types:
bool
,float64
,float32
,int32
,int64
,complex64
,complex128
.diagonal (int, optional) – The diagonal to consider, default value is 0. 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 \(\{(i, i)\}\) for \(i \in [0, \min\{d_{1}, d_{2}\} - 1]\) where \(d_{1}, d_{2}\) are the dimensions of the matrix.name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
- Returns
-
Results of lower triangular operation by the specified diagonal of input tensor x, it’s data type is the same as x’s Tensor.
- Return type
-
Tensor
Examples
>>> import paddle >>> data = paddle.arange(1, 13, dtype="int64").reshape([3,-1]) >>> print(data) Tensor(shape=[3, 4], dtype=int64, place=Place(cpu), stop_gradient=True, [[1 , 2 , 3 , 4 ], [5 , 6 , 7 , 8 ], [9 , 10, 11, 12]]) >>> tril1 = paddle.tril(data) >>> print(tril1) Tensor(shape=[3, 4], dtype=int64, place=Place(cpu), stop_gradient=True, [[1 , 0 , 0 , 0 ], [5 , 6 , 0 , 0 ], [9 , 10, 11, 0 ]]) >>> # example 2, positive diagonal value >>> tril2 = paddle.tril(data, diagonal=2) >>> print(tril2) Tensor(shape=[3, 4], dtype=int64, place=Place(cpu), stop_gradient=True, [[1 , 2 , 3 , 0 ], [5 , 6 , 7 , 8 ], [9 , 10, 11, 12]]) >>> # example 3, negative diagonal value >>> tril3 = paddle.tril(data, diagonal=-1) >>> print(tril3) Tensor(shape=[3, 4], dtype=int64, place=Place(cpu), stop_gradient=True, [[0 , 0 , 0 , 0 ], [5 , 0 , 0 , 0 ], [9 , 10, 0 , 0 ]])