Update ops-related pbtxt files.

PiperOrigin-RevId: 157573723
This commit is contained in:
A. Unique TensorFlower 2017-05-31 04:48:12 -07:00 committed by TensorFlower Gardener
parent 473a590c9c
commit 7f96742174
2 changed files with 69 additions and 1 deletions

View File

@ -4019,6 +4019,29 @@ op {
}
}
}
op {
name: "Cholesky"
input_arg {
name: "input"
type_attr: "T"
}
output_arg {
name: "output"
type_attr: "T"
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_DOUBLE
type: DT_FLOAT
type: DT_COMPLEX64
type: DT_COMPLEX128
}
}
}
}
op {
name: "CholeskyGrad"
input_arg {
@ -11506,6 +11529,47 @@ op {
}
}
}
op {
name: "MatrixTriangularSolve"
input_arg {
name: "matrix"
type_attr: "T"
}
input_arg {
name: "rhs"
type_attr: "T"
}
output_arg {
name: "output"
type_attr: "T"
}
attr {
name: "lower"
type: "bool"
default_value {
b: true
}
}
attr {
name: "adjoint"
type: "bool"
default_value {
b: false
}
}
attr {
name: "T"
type: "type"
allowed_values {
list {
type: DT_DOUBLE
type: DT_FLOAT
type: DT_COMPLEX64
type: DT_COMPLEX128
}
}
}
}
op {
name: "Max"
input_arg {

View File

@ -3985,11 +3985,13 @@ op {
list {
type: DT_DOUBLE
type: DT_FLOAT
type: DT_COMPLEX64
type: DT_COMPLEX128
}
}
}
summary: "Computes the Cholesky decomposition of one or more square matrices."
description: "The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices, with the same constraints as the single matrix Cholesky\ndecomposition above. The output is a tensor of the same shape as the input\ncontaining the Cholesky decompositions for all input submatrices `[..., :, :]`."
description: "The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices.\n\nThe input has to be symmetric and positive definite. Only the lower-triangular\npart of the input will be used for this operation. The upper-triangular part\nwill not be read.\n\nThe output is a tensor of the same shape as the input\ncontaining the Cholesky decompositions for all input submatrices `[..., :, :]`.\n\n**Note**: The gradient computation on GPU is faster for large matrices but\nnot for large batch dimensions when the submatrices are small. In this\ncase it might be faster to use the CPU."
}
op {
name: "CholeskyGrad"
@ -11222,6 +11224,8 @@ op {
list {
type: DT_DOUBLE
type: DT_FLOAT
type: DT_COMPLEX64
type: DT_COMPLEX128
}
}
}