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未验证 提交 9e307229 编写于 作者: Z zhangkaihuo 提交者： GitHub
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Standard name of sparse pool (#44344)

上级 f382eb06
隐藏空白更改
内联 并排
Showing with 152 addition and 152 deletion
paddle/phi/api/yaml/sparse_api.yaml
浏览文件 @ 9e307229
...@@ -316,10 +316,10 @@ ...@@ -316,10 +316,10 @@
args : (Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) args : (Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides)
output : Tensor(out), Tensor(rulebook) output : Tensor(out), Tensor(rulebook)
kernel : kernel :
func : sparse_maxpool{sparse_coo -> sparse_coo, dense} func : maxpool_coo{sparse_coo -> sparse_coo, dense}
layout : x layout : x
intermediate : rulebook intermediate : rulebook
backward : sparse_maxpool_grad backward : maxpool_grad
- api: mv - api: mv
args : (Tensor x, Tensor vec) args : (Tensor x, Tensor vec)
......
paddle/phi/api/yaml/sparse_bw_api.yaml
浏览文件 @ 9e307229
...@@ -137,6 +137,13 @@ ...@@ -137,6 +137,13 @@
matmul_coo_dense_grad {sparse_coo, dense, dense -> sparse_coo, dense}, matmul_coo_dense_grad {sparse_coo, dense, dense -> sparse_coo, dense},
matmul_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo} matmul_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}
- backward_api : maxpool_grad
forward : maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook)
args : (Tensor x, Tensor rulebook, Tensor out, Tensor out_grad, int[] kernel_sizes)
output : Tensor(x_grad)
kernel :
func : maxpool_coo_grad {sparse_coo, dense, sparse_coo, sparse_coo -> sparse_coo}
- backward_api : multiply_grad - backward_api : multiply_grad
forward : multiply(Tensor x, Tensor y) -> Tensor(out) forward : multiply(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
...@@ -198,13 +205,6 @@ ...@@ -198,13 +205,6 @@
kernel : kernel :
func : softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr} func : softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr}
- backward_api : sparse_maxpool_grad
forward : sparse_maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook)
args : (Tensor x, Tensor rulebook, Tensor out, Tensor out_grad, int[] kernel_sizes)
output : Tensor(x_grad)
kernel :
func : sparse_maxpool_grad {sparse_coo, dense, sparse_coo, sparse_coo -> sparse_coo}
- backward_api : sqrt_grad - backward_api : sqrt_grad
forward : sqrt(Tensor x) -> Tensor(out) forward : sqrt(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
...@@ -255,7 +255,7 @@ ...@@ -255,7 +255,7 @@
- backward_api: fused_attention_grad - backward_api: fused_attention_grad
forward : fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax) forward : fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax)
args: (Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad) args: (Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad)
output : Tensor(query_grad), Tensor(key_grad), Tensor(value_grad) output : Tensor(query_grad), Tensor(key_grad), Tensor(value_grad)
kernel : kernel :
func : fused_attention_csr_grad{dense, dense, dense, sparse_csr, dense -> dense, dense, dense} func : fused_attention_csr_grad{dense, dense, dense, sparse_csr, dense -> dense, dense, dense}
layout : softmax layout : softmax
......
paddle/phi/kernels/sparse/cpu/sparse_pool_grad_kernel.cc → paddle/phi/kernels/sparse/cpu/pool_grad_kernel.cc
浏览文件 @ 9e307229
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/phi/kernels/sparse/sparse_pool_grad_kernel.h" #include "paddle/phi/kernels/sparse/pool_grad_kernel.h"
#include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h" #include "paddle/phi/core/tensor_utils.h"
...@@ -25,13 +25,13 @@ namespace phi { ...@@ -25,13 +25,13 @@ namespace phi {
namespace sparse { namespace sparse {
template <typename T, typename IntT = int> template <typename T, typename IntT = int>
void MaxPoolGradCPUKernel(const CPUContext& dev_ctx, void MaxPoolCooGradCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
SparseCooTensor* x_grad) { SparseCooTensor* x_grad) {
int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2]; int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2];
const int channels = x.dims()[4]; const int channels = x.dims()[4];
int rulebook_len = rulebook.dims()[1]; int rulebook_len = rulebook.dims()[1];
...@@ -75,16 +75,16 @@ void MaxPoolGradCPUKernel(const CPUContext& dev_ctx, ...@@ -75,16 +75,16 @@ void MaxPoolGradCPUKernel(const CPUContext& dev_ctx,
} }
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolGradKernel(const Context& dev_ctx, void MaxPoolCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
SparseCooTensor* x_grad) { SparseCooTensor* x_grad) {
PD_VISIT_INTEGRAL_TYPES( PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "MaxPoolGradCPUKernel", ([&] { x.non_zero_indices().dtype(), "MaxPoolCooGradCPUKernel", ([&] {
MaxPoolGradCPUKernel<T, data_t>( MaxPoolCooGradCPUKernel<T, data_t>(
dev_ctx, x, rulebook, out, out_grad, kernel_sizes, x_grad); dev_ctx, x, rulebook, out, out_grad, kernel_sizes, x_grad);
})); }));
} }
...@@ -92,10 +92,10 @@ void MaxPoolGradKernel(const Context& dev_ctx, ...@@ -92,10 +92,10 @@ void MaxPoolGradKernel(const Context& dev_ctx,
} // namespace sparse } // namespace sparse
} // namespace phi } // namespace phi
PD_REGISTER_KERNEL(sparse_maxpool_grad, PD_REGISTER_KERNEL(maxpool_coo_grad,
CPU, CPU,
ALL_LAYOUT, ALL_LAYOUT,
phi::sparse::MaxPoolGradKernel, phi::sparse::MaxPoolCooGradKernel,
float, float,
double) { double) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
......
paddle/phi/kernels/sparse/cpu/sparse_pool_kernel.cc → paddle/phi/kernels/sparse/cpu/pool_kernel.cc
浏览文件 @ 9e307229
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/phi/kernels/sparse/sparse_pool_kernel.h" #include "paddle/phi/kernels/sparse/pool_kernel.h"
#include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_meta.h" #include "paddle/phi/core/tensor_meta.h"
...@@ -30,14 +30,14 @@ namespace sparse { ...@@ -30,14 +30,14 @@ namespace sparse {
* out: (N, D, H, W, OC) * out: (N, D, H, W, OC)
**/ **/
template <typename T, typename IntT = int> template <typename T, typename IntT = int>
void MaxPoolCPUKernel(const CPUContext& dev_ctx, void MaxPoolCooCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
SparseCooTensor* out, SparseCooTensor* out,
DenseTensor* rulebook) { DenseTensor* rulebook) {
const auto& x_dims = x.dims(); const auto& x_dims = x.dims();
int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2]; int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2];
const std::vector<int>& real_kernel_sizes = const std::vector<int>& real_kernel_sizes =
...@@ -98,34 +98,34 @@ void MaxPoolCPUKernel(const CPUContext& dev_ctx, ...@@ -98,34 +98,34 @@ void MaxPoolCPUKernel(const CPUContext& dev_ctx,
} }
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolKernel(const Context& dev_ctx, void MaxPoolCooKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
SparseCooTensor* out, SparseCooTensor* out,
DenseTensor* rulebook) { DenseTensor* rulebook) {
PD_VISIT_INTEGRAL_TYPES( PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "MaxPoolCPUKernel", ([&] { x.non_zero_indices().dtype(), "MaxPoolCooCPUKernel", ([&] {
MaxPoolCPUKernel<T, data_t>(dev_ctx, MaxPoolCooCPUKernel<T, data_t>(dev_ctx,
x, x,
kernel_sizes, kernel_sizes,
paddings, paddings,
dilations, dilations,
strides, strides,
out, out,
rulebook); rulebook);
})); }));
} }
} // namespace sparse } // namespace sparse
} // namespace phi } // namespace phi
PD_REGISTER_KERNEL(sparse_maxpool, PD_REGISTER_KERNEL(maxpool_coo,
CPU, CPU,
ALL_LAYOUT, ALL_LAYOUT,
phi::sparse::MaxPoolKernel, phi::sparse::MaxPoolCooKernel,
float, float,
double) { double) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
......
paddle/phi/kernels/sparse/gpu/sparse_pool_grad_kernel.cu → paddle/phi/kernels/sparse/gpu/pool_grad_kernel.cu
浏览文件 @ 9e307229
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/phi/kernels/sparse/sparse_pool_grad_kernel.h" #include "paddle/phi/kernels/sparse/pool_grad_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h" #include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/backends/gpu/gpu_info.h" #include "paddle/phi/backends/gpu/gpu_info.h"
...@@ -52,13 +52,13 @@ __global__ void MaxPoolGradCudaKernel(const T* in_features_ptr, ...@@ -52,13 +52,13 @@ __global__ void MaxPoolGradCudaKernel(const T* in_features_ptr,
} }
template <typename T, typename IntT = int> template <typename T, typename IntT = int>
void MaxPoolGradGPUKernel(const GPUContext& dev_ctx, void MaxPoolCooGradGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
SparseCooTensor* x_grad) { SparseCooTensor* x_grad) {
int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2]; int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2];
const int in_channels = x.dims()[4]; const int in_channels = x.dims()[4];
int rulebook_len = rulebook.dims()[1]; int rulebook_len = rulebook.dims()[1];
...@@ -121,16 +121,16 @@ void MaxPoolGradGPUKernel(const GPUContext& dev_ctx, ...@@ -121,16 +121,16 @@ void MaxPoolGradGPUKernel(const GPUContext& dev_ctx,
} }
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolGradKernel(const Context& dev_ctx, void MaxPoolCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
SparseCooTensor* x_grad) { SparseCooTensor* x_grad) {
PD_VISIT_INTEGRAL_TYPES( PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "MaxPoolGradGPUKernel", ([&] { x.non_zero_indices().dtype(), "MaxPoolCooGradGPUKernel", ([&] {
MaxPoolGradGPUKernel<T, data_t>( MaxPoolCooGradGPUKernel<T, data_t>(
dev_ctx, x, rulebook, out, out_grad, kernel_sizes, x_grad); dev_ctx, x, rulebook, out, out_grad, kernel_sizes, x_grad);
})); }));
} }
...@@ -138,10 +138,10 @@ void MaxPoolGradKernel(const Context& dev_ctx, ...@@ -138,10 +138,10 @@ void MaxPoolGradKernel(const Context& dev_ctx,
} // namespace sparse } // namespace sparse
} // namespace phi } // namespace phi
PD_REGISTER_KERNEL(sparse_maxpool_grad, PD_REGISTER_KERNEL(maxpool_coo_grad,
GPU, GPU,
ALL_LAYOUT, ALL_LAYOUT,
phi::sparse::MaxPoolGradKernel, phi::sparse::MaxPoolCooGradKernel,
float, float,
double) { double) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO); kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
......
paddle/phi/kernels/sparse/gpu/sparse_pool_kernel.cu → paddle/phi/kernels/sparse/gpu/pool_kernel.cu
浏览文件 @ 9e307229
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/phi/kernels/sparse/sparse_pool_kernel.h" #include "paddle/phi/kernels/sparse/pool_kernel.h"
#include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_meta.h" #include "paddle/phi/core/tensor_meta.h"
...@@ -48,14 +48,14 @@ __global__ void MaxPoolCudaKernel(const T* in_features_ptr, ...@@ -48,14 +48,14 @@ __global__ void MaxPoolCudaKernel(const T* in_features_ptr,
* out: (N, D, H, W, OC) * out: (N, D, H, W, OC)
**/ **/
template <typename T, typename IntT = int> template <typename T, typename IntT = int>
void MaxPoolGPUKernel(const GPUContext& dev_ctx, void MaxPoolCooGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
SparseCooTensor* out, SparseCooTensor* out,
DenseTensor* rulebook) { DenseTensor* rulebook) {
const auto& x_dims = x.dims(); const auto& x_dims = x.dims();
int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2]; int kernel_size = kernel_sizes[0] * kernel_sizes[1] * kernel_sizes[2];
const std::vector<int>& real_kernel_sizes = const std::vector<int>& real_kernel_sizes =
...@@ -127,34 +127,34 @@ void MaxPoolGPUKernel(const GPUContext& dev_ctx, ...@@ -127,34 +127,34 @@ void MaxPoolGPUKernel(const GPUContext& dev_ctx,
} }
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolKernel(const Context& dev_ctx, void MaxPoolCooKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
SparseCooTensor* out, SparseCooTensor* out,
DenseTensor* rulebook) { DenseTensor* rulebook) {
PD_VISIT_INTEGRAL_TYPES( PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "MaxPoolGPUKernel", ([&] { x.non_zero_indices().dtype(), "MaxPoolCooGPUKernel", ([&] {
MaxPoolGPUKernel<T, data_t>(dev_ctx, MaxPoolCooGPUKernel<T, data_t>(dev_ctx,
x, x,
kernel_sizes, kernel_sizes,
paddings, paddings,
dilations, dilations,
strides, strides,
out, out,
rulebook); rulebook);
})); }));
} }
} // namespace sparse } // namespace sparse
} // namespace phi } // namespace phi
PD_REGISTER_KERNEL(sparse_maxpool, PD_REGISTER_KERNEL(maxpool_coo,
GPU, GPU,
ALL_LAYOUT, ALL_LAYOUT,
phi::sparse::MaxPoolKernel, phi::sparse::MaxPoolCooKernel,
float, float,
double, double,
phi::dtype::float16) { phi::dtype::float16) {
......
paddle/phi/kernels/sparse/sparse_pool_grad_kernel.h → paddle/phi/kernels/sparse/pool_grad_kernel.h
浏览文件 @ 9e307229
...@@ -22,23 +22,23 @@ namespace phi { ...@@ -22,23 +22,23 @@ namespace phi {
namespace sparse { namespace sparse {
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolGradKernel(const Context& dev_ctx, void MaxPoolCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
SparseCooTensor* x_grad); SparseCooTensor* x_grad);
template <typename T, typename Context> template <typename T, typename Context>
SparseCooTensor MaxPoolGrad(const Context& dev_ctx, SparseCooTensor MaxPoolCooGrad(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const DenseTensor& rulebook, const DenseTensor& rulebook,
const SparseCooTensor& out, const SparseCooTensor& out,
const SparseCooTensor& out_grad, const SparseCooTensor& out_grad,
const std::vector<int>& kernel_sizes) { const std::vector<int>& kernel_sizes) {
SparseCooTensor x_grad; SparseCooTensor x_grad;
MaxPoolGradKernel<T, Context>( MaxPoolCooGradKernel<T, Context>(
dev_ctx, x, rulebook, out, out_grad, kernel_sizes, &x_grad); dev_ctx, x, rulebook, out, out_grad, kernel_sizes, &x_grad);
return x_grad; return x_grad;
} }
......
paddle/phi/kernels/sparse/sparse_pool_kernel.h → paddle/phi/kernels/sparse/pool_kernel.h
浏览文件 @ 9e307229
...@@ -22,25 +22,25 @@ namespace phi { ...@@ -22,25 +22,25 @@ namespace phi {
namespace sparse { namespace sparse {
template <typename T, typename Context> template <typename T, typename Context>
void MaxPoolKernel(const Context& dev_ctx, void MaxPoolCooKernel(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
SparseCooTensor* out, SparseCooTensor* out,
DenseTensor* rulebook); DenseTensor* rulebook);
template <typename T, typename Context> template <typename T, typename Context>
SparseCooTensor MaxPool(const Context& dev_ctx, SparseCooTensor MaxPoolCoo(const Context& dev_ctx,
const SparseCooTensor& x, const SparseCooTensor& x,
const std::vector<int>& kernel_sizes, const std::vector<int>& kernel_sizes,
const std::vector<int>& paddings, const std::vector<int>& paddings,
const std::vector<int>& dilations, const std::vector<int>& dilations,
const std::vector<int>& strides, const std::vector<int>& strides,
DenseTensor* rulebook) { DenseTensor* rulebook) {
SparseCooTensor coo; SparseCooTensor coo;
MaxPoolKernel<T, Context>( MaxPoolCooKernel<T, Context>(
dev_ctx, x, kernel_sizes, paddings, dilations, strides, &coo, rulebook); dev_ctx, x, kernel_sizes, paddings, dilations, strides, &coo, rulebook);
return coo; return coo;
} }
......
paddle/phi/tests/kernels/test_sparse_pool_dev_api.cc
浏览文件 @ 9e307229
...@@ -23,8 +23,8 @@ limitations under the License. */ ...@@ -23,8 +23,8 @@ limitations under the License. */
#include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h" #include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/sparse/coalesce_kernel.h" #include "paddle/phi/kernels/sparse/coalesce_kernel.h"
#include "paddle/phi/kernels/sparse/sparse_pool_grad_kernel.h" #include "paddle/phi/kernels/sparse/pool_grad_kernel.h"
#include "paddle/phi/kernels/sparse/sparse_pool_kernel.h" #include "paddle/phi/kernels/sparse/pool_kernel.h"
namespace phi { namespace phi {
namespace tests { namespace tests {
...@@ -91,13 +91,13 @@ void TestMaxPoolBase(const std::vector<IntT>& indices, ...@@ -91,13 +91,13 @@ void TestMaxPoolBase(const std::vector<IntT>& indices,
if (!std::is_same<T, phi::dtype::float16>::value) { if (!std::is_same<T, phi::dtype::float16>::value) {
DenseTensor rulebook; DenseTensor rulebook;
SparseCooTensor out = sparse::MaxPool<T>(dev_ctx_cpu, SparseCooTensor out = sparse::MaxPoolCoo<T>(dev_ctx_cpu,
x_tensor, x_tensor,
kernel_sizes, kernel_sizes,
paddings, paddings,
dilations, dilations,
strides, strides,
&rulebook); &rulebook);
ASSERT_EQ(correct_out_dims.size(), out.dims().size()); ASSERT_EQ(correct_out_dims.size(), out.dims().size());
for (int i = 0; i < correct_out_dims.size(); i++) { for (int i = 0; i < correct_out_dims.size(); i++) {
...@@ -113,7 +113,7 @@ void TestMaxPoolBase(const std::vector<IntT>& indices, ...@@ -113,7 +113,7 @@ void TestMaxPoolBase(const std::vector<IntT>& indices,
f_verify(out.non_zero_elements().data<T>(), correct_out_features); f_verify(out.non_zero_elements().data<T>(), correct_out_features);
if (backward) { if (backward) {
SparseCooTensor x_grad = sparse::MaxPoolGrad<T>( SparseCooTensor x_grad = sparse::MaxPoolCooGrad<T>(
dev_ctx_cpu, x_tensor, rulebook, out, out, kernel_sizes); dev_ctx_cpu, x_tensor, rulebook, out, out, kernel_sizes);
f_verify(x_grad.non_zero_elements().data<T>(), features_grad); f_verify(x_grad.non_zero_elements().data<T>(), features_grad);
} }
...@@ -151,13 +151,13 @@ void TestMaxPoolBase(const std::vector<IntT>& indices, ...@@ -151,13 +151,13 @@ void TestMaxPoolBase(const std::vector<IntT>& indices,
SparseCooTensor d_x_tensor(d_indices_tensor, d_features_tensor, x_dims); SparseCooTensor d_x_tensor(d_indices_tensor, d_features_tensor, x_dims);
DenseTensor d_rulebook; DenseTensor d_rulebook;
SparseCooTensor d_out = sparse::MaxPool<T>(dev_ctx_gpu, SparseCooTensor d_out = sparse::MaxPoolCoo<T>(dev_ctx_gpu,
d_x_tensor, d_x_tensor,
kernel_sizes, kernel_sizes,
paddings, paddings,
dilations, dilations,
strides, strides,
&d_rulebook); &d_rulebook);
SparseCooTensor tmp_d_out = sparse::Coalesce<T>(dev_ctx_gpu, d_out); SparseCooTensor tmp_d_out = sparse::Coalesce<T>(dev_ctx_gpu, d_out);
ASSERT_EQ(correct_out_dims.size(), d_out.dims().size()); ASSERT_EQ(correct_out_dims.size(), d_out.dims().size());
...@@ -191,7 +191,7 @@ void TestMaxPoolBase(const std::vector<IntT>& indices, ...@@ -191,7 +191,7 @@ void TestMaxPoolBase(const std::vector<IntT>& indices,
f_verify(h_features_tensor.data<T>(), correct_out_features); f_verify(h_features_tensor.data<T>(), correct_out_features);
if (backward) { if (backward) {
SparseCooTensor x_grad = sparse::MaxPoolGrad<T>( SparseCooTensor x_grad = sparse::MaxPoolCooGrad<T>(
dev_ctx_gpu, d_x_tensor, d_rulebook, d_out, d_out, kernel_sizes); dev_ctx_gpu, d_x_tensor, d_rulebook, d_out, d_out, kernel_sizes);
DenseTensor h_features_grad = DenseTensor h_features_grad =
phi::EmptyLike<T>(dev_ctx_cpu, x_grad.non_zero_elements()); phi::EmptyLike<T>(dev_ctx_cpu, x_grad.non_zero_elements());
......
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