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【complex op】No.19 add complex support for triangular_solve #59529

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Merged
merged 14 commits into from
Jan 3, 2024
Merged

【complex op】No.19 add complex support for triangular_solve #59529

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1be84c7
triangular_solve complex support
zbt78 Nov 29, 2023
22e495b
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zbt78 Nov 29, 2023
ea76c11
triangular_solve complex support
zbt78 Nov 29, 2023
d6d3b55
fix bug
zbt78 Nov 30, 2023
dab4109
add complex dtype case
zbt78 Dec 4, 2023
7ad9317
add complex128 case & fix max_relative_error
zbt78 Dec 6, 2023
bda2de6
fix cinn bugs
zbt78 Dec 6, 2023
c94bf35
fix cinn bug
zbt78 Dec 7, 2023
fc4012d
Merge branch 'develop' into triangle
zbt78 Dec 7, 2023
499a1f4
Merge branch 'develop' of https://github.com/zbt78/Paddle into triangle
zbt78 Dec 7, 2023
dcc9c1b
fix bug
zbt78 Dec 7, 2023
e28882c
fix cinn
zbt78 Dec 21, 2023
bc14276
remove check_cinn=True for complex dtype
zbt78 Dec 22, 2023
bf83456
fix
zbt78 Dec 23, 2023
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4 changes: 3 additions & 1 deletion paddle/phi/kernels/cpu/triangular_solve_grad_kernel.cc
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Expand Up @@ -20,4 +20,6 @@ PD_REGISTER_KERNEL(triangular_solve_grad,
ALL_LAYOUT,
phi::TriangularSolveGradKernel,
float,
double) {}
double,
phi::dtype::complex<float>,
phi::dtype::complex<double>) {}
4 changes: 3 additions & 1 deletion paddle/phi/kernels/cpu/triangular_solve_kernel.cc
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Expand Up @@ -82,4 +82,6 @@ PD_REGISTER_KERNEL(triangular_solve,
ALL_LAYOUT,
phi::TriangularSolveKernel,
float,
double) {}
double,
phi::dtype::complex<float>,
phi::dtype::complex<double>) {}
2 changes: 1 addition & 1 deletion paddle/phi/kernels/funcs/blas/blas_impl.h
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Expand Up @@ -877,7 +877,7 @@ struct CBlas<phi::dtype::complex<float>> {
const phi::dtype::complex<float> alpha,
const phi::dtype::complex<float> *A,
const int lda,
phi::dtype::complex<double> *B,
phi::dtype::complex<float> *B,
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@GGBond8488 GGBond8488 Dec 26, 2023

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这里为什么改动了，有看过添加这个pr吗，为什么之前要用phi::dtype::complex

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@zbt78 zbt78 Dec 26, 2023

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这个函数调用的是cblas中用于解方程组的单精度复数版本的 cblas_ctrsm,
同时下面也有调用cblas中用于解方程组的双精度复数版本的cblas_ztrsm,
所以说A，B的类型应该是一样的。个人感觉这里应该是笔误。

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@zbt78 zbt78 Jan 3, 2024

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您好，可以再帮忙review一下吗~

const int ldb) {
cblas_ctrsm(layout, side, uplo, transA, diag, M, N, &alpha, A, lda, B, ldb);
}
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2 changes: 2 additions & 0 deletions paddle/phi/kernels/funcs/matrix_reduce.cc
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Expand Up @@ -55,6 +55,8 @@ class MatrixReduceSumFunctor<T, CPUContext> {

template class MatrixReduceSumFunctor<float, CPUContext>;
template class MatrixReduceSumFunctor<double, CPUContext>;
template class MatrixReduceSumFunctor<phi::dtype::complex<float>, CPUContext>;
template class MatrixReduceSumFunctor<phi::dtype::complex<double>, CPUContext>;

} // namespace funcs
} // namespace phi
2 changes: 2 additions & 0 deletions paddle/phi/kernels/funcs/matrix_reduce.cu
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Expand Up @@ -52,6 +52,8 @@ class MatrixReduceSumFunctor<T, GPUContext> {

template class MatrixReduceSumFunctor<float, GPUContext>;
template class MatrixReduceSumFunctor<double, GPUContext>;
template class MatrixReduceSumFunctor<phi::dtype::complex<float>, GPUContext>;
template class MatrixReduceSumFunctor<phi::dtype::complex<double>, GPUContext>;

} // namespace funcs
} // namespace phi
4 changes: 3 additions & 1 deletion paddle/phi/kernels/gpu/triangular_solve_grad_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -20,4 +20,6 @@ PD_REGISTER_KERNEL(triangular_solve_grad,
ALL_LAYOUT,
phi::TriangularSolveGradKernel,
float,
double) {}
double,
phi::dtype::complex<float>,
phi::dtype::complex<double>) {}
4 changes: 3 additions & 1 deletion paddle/phi/kernels/gpu/triangular_solve_kernel.cu
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Expand Up @@ -128,4 +128,6 @@ PD_REGISTER_KERNEL(triangular_solve,
ALL_LAYOUT,
phi::TriangularSolveKernel,
float,
double) {}
double,
phi::dtype::complex<float>,
phi::dtype::complex<double>) {}
14 changes: 10 additions & 4 deletions python/paddle/tensor/linalg.py
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Expand Up @@ -3186,9 +3186,9 @@ def triangular_solve(

Args:
x (Tensor): The input triangular coefficient matrix. Its shape should be `[*, M, M]`, where `*` is zero or
more batch dimensions. Its data type should be float32 or float64.
more batch dimensions. Its data type should be float32, float64, complex64, complex128.
y (Tensor): Multiple right-hand sides of system of equations. Its shape should be `[*, M, K]`, where `*` is
zero or more batch dimensions. Its data type should be float32 or float64.
zero or more batch dimensions. Its data type should be float32, float64, complex64, complex128.
upper (bool, optional): Whether to solve the upper-triangular system of equations (default) or the lower-triangular
system of equations. Default: True.
transpose (bool, optional): whether `x` should be transposed before calculation. Default: False.
Expand Down Expand Up @@ -3227,10 +3227,16 @@ def triangular_solve(
inputs = {"X": [x], "Y": [y]}
helper = LayerHelper("triangular_solve", **locals())
check_variable_and_dtype(
x, 'x', ['float32', 'float64'], 'triangular_solve'
x,
'x',
['float32', 'float64', 'complex64', 'complex128'],
'triangular_solve',
)
check_variable_and_dtype(
y, 'y', ['float32', 'float64'], 'triangular_solve'
y,
'y',
['float32', 'float64', 'complex64', 'complex128'],
'triangular_solve',
)
out = helper.create_variable_for_type_inference(dtype=x.dtype)

Expand Down
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