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【complex op No.45】pow_coo/pow_csr(sparse) #68263

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【complex op No.45】pow_coo/pow_csr(sparse) #68263

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2 changes: 1 addition & 1 deletion paddle/phi/kernels/sparse/cpu/unary_grad_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -69,11 +69,11 @@ PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(sqrt, Sqrt)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(square, Square)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(log1p, Log1p)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(relu, Relu)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(pow, Pow)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(expm1, Expm1)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(relu6, Relu6)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL(leaky_relu, LeakyRelu)

PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL_WITH_COMPLEX(pow, Pow)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL_WITH_COMPLEX(sinh, Sinh)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL_WITH_COMPLEX(tan, Tan)
PD_REGISTER_SPARSE_UNARY_CPU_GRAD_KERNEL_WITH_COMPLEX(sin, Sin)
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2 changes: 1 addition & 1 deletion paddle/phi/kernels/sparse/cpu/unary_kernel.cc
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Expand Up @@ -110,12 +110,12 @@ PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(sqrt, Sqrt)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(square, Square)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(log1p, Log1p)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(relu, Relu)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(pow, Pow)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(scale, Scale)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(expm1, Expm1)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(relu6, Relu6)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL(leaky_relu, LeakyRelu)

PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(pow, Pow)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(sinh, Sinh)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(tan, Tan)
PD_REGISTER_SPARSE_UNARY_CPU_KERNEL_WITH_COMPLEX(sin, Sin)
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2 changes: 1 addition & 1 deletion paddle/phi/kernels/sparse/gpu/unary_grad_kernel.cu
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Expand Up @@ -73,11 +73,11 @@ PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(sqrt, Sqrt)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(square, Square)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(log1p, Log1p)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(relu, Relu)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(pow, Pow)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(expm1, Expm1)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(relu6, Relu6)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL(leaky_relu, LeakyRelu)

PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL_WITH_COMPLEX(pow, Pow)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL_WITH_COMPLEX(sinh, Sinh)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL_WITH_COMPLEX(sin, Sin)
PD_REGISTER_SPARSE_UNARY_GPU_GRAD_KERNEL_WITH_COMPLEX(abs, Abs)
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2 changes: 1 addition & 1 deletion paddle/phi/kernels/sparse/gpu/unary_kernel.cu
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Expand Up @@ -103,12 +103,12 @@ PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(sqrt, Sqrt)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(square, Square)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(log1p, Log1p)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(relu, Relu)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(pow, Pow)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(scale, Scale)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(expm1, Expm1)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(relu6, Relu6)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL(leaky_relu, LeakyRelu)

PD_REGISTER_SPARSE_UNARY_GPU_KERNEL_WITH_COMPLEX(pow, Pow)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL_WITH_COMPLEX(sinh, Sinh)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL_WITH_COMPLEX(tan, Tan)
PD_REGISTER_SPARSE_UNARY_GPU_KERNEL_WITH_COMPLEX(sin, Sin)
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37 changes: 36 additions & 1 deletion paddle/phi/kernels/sparse/impl/unary_kernel_impl.h
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Expand Up @@ -103,6 +103,41 @@ namespace sparse {
dev_ctx, x.non_zero_elements(), out->mutable_non_zero_elements()); \
}

#define DEFINE_SPARSE_UNARY_KERNEL_WITH_ONE_ATTR_COMPLEX(prefix, attr) \
template <typename T, typename Context> \
void prefix##CooKernel(const Context& dev_ctx, \
const SparseCooTensor& x, \
float attr, \
SparseCooTensor* out) { \
*(out->mutable_indices()) = x.indices(); \
DenseTensor* out_values = out->mutable_values(); \
const DenseTensor& x_values = x.values(); \
out_values->Resize(x_values.dims()); \
dev_ctx.template Alloc<T>(out_values); \
phi::prefix##Kernel<T, Context>(dev_ctx, \
x.non_zero_elements(), \
attr, \
out->mutable_non_zero_elements()); \
out->SetIndicesDict(x.GetIndicesDict()); \
} \
\
template <typename T, typename Context> \
void prefix##CsrKernel(const Context& dev_ctx, \
const SparseCsrTensor& x, \
float attr, \
SparseCsrTensor* out) { \
*(out->mutable_crows()) = x.crows(); \
*(out->mutable_cols()) = x.cols(); \
DenseTensor* out_values = out->mutable_values(); \
const DenseTensor& x_values = x.values(); \
out_values->Resize(x_values.dims()); \
dev_ctx.template Alloc<T>(out_values); \
phi::prefix##Kernel<T, Context>(dev_ctx, \
x.non_zero_elements(), \
attr, \
out->mutable_non_zero_elements()); \
}

DEFINE_SPARSE_UNARY_KERNEL(Asin)
DEFINE_SPARSE_UNARY_KERNEL(Atan)
DEFINE_SPARSE_UNARY_KERNEL(Tanh)
Expand All @@ -114,7 +149,7 @@ DEFINE_SPARSE_UNARY_KERNEL(Log1p)
DEFINE_SPARSE_UNARY_KERNEL(Relu)
DEFINE_SPARSE_UNARY_KERNEL(Expm1)
DEFINE_SPARSE_UNARY_KERNEL(Relu6)
DEFINE_SPARSE_UNARY_KERNEL_WITH_ONE_ATTR(Pow, factor)
DEFINE_SPARSE_UNARY_KERNEL_WITH_ONE_ATTR_COMPLEX(Pow, factor)
DEFINE_SPARSE_UNARY_KERNEL_WITH_ONE_ATTR(LeakyRelu, alpha)
DEFINE_SPARSE_UNARY_KERNEL_WITH_COMPLEX(Abs)
DEFINE_SPARSE_UNARY_KERNEL_WITH_COMPLEX(Sin)
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2 changes: 1 addition & 1 deletion python/paddle/sparse/unary.py
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Expand Up @@ -636,7 +636,7 @@ def pow(x: Tensor, factor: float, name: str | None = None) -> Tensor:
out = x^{factor}

Parameters:
x (Tensor): The input Sparse Tensor with data type float32, float64.
x (Tensor): The input Sparse Tensor with data type float32, float64, complex64, complex128.
factor (float|int): factor of pow.
name (str|None, optional): Name for the operation (optional, default is None).
For more information, please refer to :ref:`api_guide_Name`.
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34 changes: 27 additions & 7 deletions test/legacy_test/test_sparse_unary_op.py
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Expand Up @@ -113,16 +113,18 @@ def compare_with_dense(self, dense_func, sparse_func, dtype='float32'):
self.check_result(dense_func, sparse_func, 'coo', device, dtype)
self.check_result(dense_func, sparse_func, 'csr', device, dtype)

def compare_with_dense_one_attr(self, dense_func, sparse_func, attr1):
def compare_with_dense_one_attr(
self, dense_func, sparse_func, attr1, dtype='float32'
):
for device in devices:
if device == 'cpu' or (
device == 'gpu' and paddle.is_compiled_with_cuda()
):
self.check_result(
dense_func, sparse_func, 'coo', device, 'float32', attr1
dense_func, sparse_func, 'coo', device, dtype, attr1
)
self.check_result(
dense_func, sparse_func, 'csr', device, 'float32', attr1
dense_func, sparse_func, 'csr', device, dtype, attr1
)

def compare_with_dense_two_attr(
Expand Down Expand Up @@ -227,7 +229,15 @@ def test_sparse_neg(self):
self.compare_with_dense(paddle.neg, paddle.sparse.neg)

def test_sparse_pow(self):
self.compare_with_dense_one_attr(paddle.pow, paddle.sparse.pow, 3)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'float32'
)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'complex64'
)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'complex128'
)

def test_sparse_mul_scalar(self):
self.compare_with_dense_one_attr(
Expand Down Expand Up @@ -366,14 +376,16 @@ def compare_with_dense(self, dense_func, sparse_func, dtype='float32'):
dense_func, sparse_func, device, dtype
)

def compare_with_dense_one_attr(self, dense_func, sparse_func, attr1):
def compare_with_dense_one_attr(
self, dense_func, sparse_func, attr1, dtype='float32'
):
if in_pir_mode():
for device in devices:
if device == 'cpu' or (
device == 'gpu' and paddle.is_compiled_with_cuda()
):
self.check_result_coo(
dense_func, sparse_func, device, 'float32', attr1
dense_func, sparse_func, device, dtype, attr1
)

def compare_with_dense_two_attr(
Expand Down Expand Up @@ -469,7 +481,15 @@ def test_sparse_neg(self):
self.compare_with_dense(paddle.neg, paddle.sparse.neg)

def test_sparse_pow(self):
self.compare_with_dense_one_attr(paddle.pow, paddle.sparse.pow, 3)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'float32'
)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'complex64'
)
self.compare_with_dense_one_attr(
paddle.pow, paddle.sparse.pow, 3, 'complex128'
)

def test_sparse_mul_scalar(self):
self.compare_with_dense_one_attr(
Expand Down