Skip to content

P
Paddle

BaiXuePrincess / Paddle
与 Fork 源项目一致

Fork自 PaddlePaddle / Paddle

通知 1
Star 1
Fork 0
P
Paddle
未验证 提交 87443831 编写于 作者: Z zhangkaihuo 提交者： GitHub
浏览文件
操作

Standard sparse conv name (#44353)

上级 0dafbb03
隐藏空白更改
内联 并排
Showing with 278 addition and 217 deletion
paddle/phi/api/yaml/sparse_api.yaml
浏览文件 @ 87443831
......@@ -84,7 +84,7 @@
args : (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm)
output : Tensor(out), Tensor(rulebook)
kernel :
func : sparse_conv3d{sparse_coo, dense -> sparse_coo, dense}
func : conv3d_coo{sparse_coo, dense -> sparse_coo, dense}
layout : x
intermediate : rulebook
backward : conv3d_grad
......
paddle/phi/api/yaml/sparse_bw_api.yaml
浏览文件 @ 87443831
......@@ -76,7 +76,7 @@
args : (Tensor x, Tensor kernel, Tensor rulebook, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm)
output : Tensor(x_grad), Tensor(kernel_grad)
kernel :
func : sparse_conv3d_grad{sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
func : conv3d_coo_grad{sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
- backward_api : coo_to_dense_grad
forward : coo_to_dense(Tensor x) -> Tensor(out)
......
paddle/phi/kernels/sparse/convolution_grad_kernel.h → paddle/phi/kernels/sparse/conv_grad_kernel.h
浏览文件 @ 87443831
......@@ -17,27 +17,26 @@ limitations under the License. */
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/kernels/empty_kernel.h"
#include "paddle/phi/kernels/sparse/convolution_kernel.h"
namespace phi {
namespace sparse {
template <typename T, typename Context>
void Conv3dGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad);
void Conv3dCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad);
template <typename T, typename Context>
std::tuple<SparseCooTensor, DenseTensor> Conv3dGrad(
std::tuple<SparseCooTensor, DenseTensor> Conv3dCooGrad(
const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
......@@ -52,18 +51,18 @@ std::tuple<SparseCooTensor, DenseTensor> Conv3dGrad(
DenseTensor kernel_grad;
// TODO(zhangkaihuo): call InferMeta func here
Conv3dGradKernel<T, Context>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
&x_grad,
&kernel_grad);
Conv3dCooGradKernel<T, Context>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
&x_grad,
&kernel_grad);
return std::make_tuple(x_grad, kernel_grad);
}
......
paddle/phi/kernels/sparse/convolution_kernel.h → paddle/phi/kernels/sparse/conv_kernel.h
浏览文件 @ 87443831
......@@ -23,38 +23,38 @@ namespace phi {
namespace sparse {
template <typename T, typename Context>
void Conv3dKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook);
void Conv3dCooKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook);
template <typename T, typename Context>
SparseCooTensor Conv3d(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
DenseTensor* rulebook) {
SparseCooTensor Conv3dCoo(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
DenseTensor* rulebook) {
SparseCooTensor coo;
Conv3dKernel<T, Context>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
&coo,
rulebook);
Conv3dCooKernel<T, Context>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
&coo,
rulebook);
return coo;
}
......
paddle/phi/kernels/sparse/cpu/convolution_grad_kernel.cc → paddle/phi/kernels/sparse/cpu/conv_grad_kernel.cc
浏览文件 @ 87443831
......@@ -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
limitations under the License. */
#include "paddle/phi/kernels/sparse/convolution_grad_kernel.h"
#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
#include "paddle/phi/core/visit_type.h"
#include "paddle/phi/kernels/funcs/blas/blas.h"
......@@ -31,18 +31,18 @@ namespace sparse {
// x_grad = out_grad * transpose(kenrel)
// kernel_grad = transpose(x) * out_grad
template <typename T, typename IntT = int>
void Conv3dGradCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
void Conv3dCooGradCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
const auto& kernel_dims = kernel.dims();
const int kernel_size = kernel_dims[0] * kernel_dims[1] * kernel_dims[2];
const int in_channels = kernel_dims[3];
......@@ -178,42 +178,42 @@ void Conv3dGradCPUKernel(const CPUContext& dev_ctx,
}
template <typename T, typename Context>
void Conv3dGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
void Conv3dCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "Conv3dGradCPUKernel", ([&] {
Conv3dGradCPUKernel<T, data_t>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
x_grad,
kernel_grad);
x.non_zero_indices().dtype(), "Conv3dCooGradCPUKernel", ([&] {
Conv3dCooGradCPUKernel<T, data_t>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
x_grad,
kernel_grad);
}));
}
} // namespace sparse
} // namespace phi
PD_REGISTER_KERNEL(sparse_conv3d_grad,
PD_REGISTER_KERNEL(conv3d_coo_grad,
CPU,
ALL_LAYOUT,
phi::sparse::Conv3dGradKernel,
phi::sparse::Conv3dCooGradKernel,
float,
double) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
......
paddle/phi/kernels/sparse/cpu/convolution_kernel.cc → paddle/phi/kernels/sparse/cpu/conv_kernel.cc
浏览文件 @ 87443831
......@@ -27,16 +27,16 @@ namespace sparse {
* out: (N, D, H, W, OC)
**/
template <typename T, typename IntT = int>
void Conv3dCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
void Conv3dCooCPUKernel(const CPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
// update padding and dilation
// Currently, only support x.layout is NDHWC, groups = 1
// if x.layout != NDHWC then transpose(x), transpose(weight)
......@@ -151,28 +151,28 @@ void Conv3dCPUKernel(const CPUContext& dev_ctx,
}
template <typename T, typename Context>
void Conv3dKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
void Conv3dCooKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "Conv3dCPUKernel", ([&] {
Conv3dCPUKernel<T, data_t>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
out,
rulebook);
x.non_zero_indices().dtype(), "Conv3dCooCPUKernel", ([&] {
Conv3dCooCPUKernel<T, data_t>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
out,
rulebook);
}));
}
......@@ -180,6 +180,6 @@ void Conv3dKernel(const Context& dev_ctx,
} // namespace phi
PD_REGISTER_KERNEL(
sparse_conv3d, CPU, ALL_LAYOUT, phi::sparse::Conv3dKernel, float, double) {
conv3d_coo, CPU, ALL_LAYOUT, phi::sparse::Conv3dCooKernel, float, double) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
}
paddle/phi/kernels/sparse/cpu/convolution.h
浏览文件 @ 87443831
......@@ -21,7 +21,7 @@ limitations under the License. */
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/core/tensor_meta.h"
#include "paddle/phi/kernels/funcs/blas/blas.h"
#include "paddle/phi/kernels/sparse/convolution_kernel.h"
#include "paddle/phi/kernels/sparse/conv_kernel.h"
namespace phi {
namespace sparse {
......
paddle/phi/kernels/sparse/gpu/convolution_grad_kernel.cu → paddle/phi/kernels/sparse/gpu/conv_grad_kernel.cu
浏览文件 @ 87443831
......@@ -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
limitations under the License. */
#include "paddle/phi/kernels/sparse/convolution_grad_kernel.h"
#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
#include "glog/logging.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
......@@ -39,18 +39,18 @@ namespace sparse {
// x_grad = out_grad * transpose(kenrel)
// kernel_grad = transpose(x) * out_grad
template <typename T, typename IntT>
void Conv3dGradGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
void Conv3dCooGradGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
const auto& kernel_dims = kernel.dims();
const int kernel_size = kernel_dims[0] * kernel_dims[1] * kernel_dims[2];
const int in_channels = kernel_dims[3];
......@@ -220,42 +220,42 @@ void Conv3dGradGPUKernel(const GPUContext& dev_ctx,
}
template <typename T, typename Context>
void Conv3dGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
void Conv3dCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const DenseTensor& rulebook,
const SparseCooTensor& out_grad,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* x_grad,
DenseTensor* kernel_grad) {
PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "Conv3dGradGPUKernel", ([&] {
Conv3dGradGPUKernel<T, data_t>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
x_grad,
kernel_grad);
x.non_zero_indices().dtype(), "Conv3dCooGradGPUKernel", ([&] {
Conv3dCooGradGPUKernel<T, data_t>(dev_ctx,
x,
kernel,
rulebook,
out_grad,
paddings,
dilations,
strides,
groups,
subm,
x_grad,
kernel_grad);
}));
}
} // namespace sparse
} // namespace phi
PD_REGISTER_KERNEL(sparse_conv3d_grad,
PD_REGISTER_KERNEL(conv3d_coo_grad,
GPU,
ALL_LAYOUT,
phi::sparse::Conv3dGradKernel,
phi::sparse::Conv3dCooGradKernel,
float,
double,
phi::dtype::float16) {
......
paddle/phi/kernels/sparse/gpu/convolution_kernel.cu → paddle/phi/kernels/sparse/gpu/conv_kernel.cu
浏览文件 @ 87443831
......@@ -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
limitations under the License. */
#include "paddle/phi/kernels/sparse/convolution_kernel.h"
#include "paddle/phi/kernels/sparse/conv_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
......@@ -27,16 +27,16 @@ namespace phi {
namespace sparse {
template <typename T, typename IntT>
void Conv3dGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
void Conv3dCooGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
// update padding and dilation
// Currently, only support x.layout is NDHWC, groups = 1
// if x.layout != NDHWC then transpose(x), transpose(weight)
......@@ -190,38 +190,38 @@ void Conv3dGPUKernel(const GPUContext& dev_ctx,
* out: (N, D, H, W, OC)
**/
template <typename T, typename Context>
void Conv3dKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
void Conv3dCooKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const DenseTensor& kernel,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
const std::vector<int>& strides,
const int groups,
const bool subm,
SparseCooTensor* out,
DenseTensor* rulebook) {
PD_VISIT_INTEGRAL_TYPES(
x.non_zero_indices().dtype(), "Conv3dGPUKernel", ([&] {
Conv3dGPUKernel<T, data_t>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
out,
rulebook);
x.non_zero_indices().dtype(), "Conv3dCooGPUKernel", ([&] {
Conv3dCooGPUKernel<T, data_t>(dev_ctx,
x,
kernel,
paddings,
dilations,
strides,
groups,
subm,
out,
rulebook);
}));
}
} // namespace sparse
} // namespace phi
PD_REGISTER_KERNEL(sparse_conv3d,
PD_REGISTER_KERNEL(conv3d_coo,
GPU,
ALL_LAYOUT,
phi::sparse::Conv3dKernel,
phi::sparse::Conv3dCooKernel,
float,
double,
phi::dtype::float16) {
......
paddle/phi/kernels/sparse/gpu/convolution.cu.h
浏览文件 @ 87443831
......@@ -28,7 +28,7 @@ limitations under the License. */
#include "paddle/phi/kernels/funcs/math_function.h"
#include "paddle/phi/kernels/funcs/sparse/utils.cu.h"
#include "paddle/phi/kernels/primitive/compute_primitives.h"
#include "paddle/phi/kernels/sparse/convolution_kernel.h"
#include "paddle/phi/kernels/sparse/conv_kernel.h"
namespace phi {
namespace sparse {
......
paddle/phi/tests/api/test_sparse_conv_api.cc
浏览文件 @ 87443831
......@@ -23,7 +23,7 @@ limitations under the License. */
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
PD_DECLARE_KERNEL(sparse_conv3d, CPU, ALL_LAYOUT);
PD_DECLARE_KERNEL(conv3d_coo, CPU, ALL_LAYOUT);
template <typename T>
void TestConv3dBase(const std::vector<int>& indices,
......
paddle/phi/tests/kernels/test_sparse_conv3d_dev_api.cc
浏览文件 @ 87443831
......@@ -23,8 +23,8 @@ limitations under the License. */
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/sparse/coalesce_kernel.h"
#include "paddle/phi/kernels/sparse/convolution_grad_kernel.h"
#include "paddle/phi/kernels/sparse/convolution_kernel.h"
#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
#include "paddle/phi/kernels/sparse/conv_kernel.h"
namespace phi {
namespace tests {
......@@ -114,15 +114,15 @@ void TestConv3dBase(const std::vector<IntT>& indices,
if (!std::is_same<T, phi::dtype::float16>::value) {
DenseTensor rulebook = phi::Empty(
dev_ctx_cpu, DenseTensorMeta(indices_dtype, {1}, DataLayout::NCHW));
SparseCooTensor out = sparse::Conv3d<T>(dev_ctx_cpu,
x_tensor,
kernel_tensor,
paddings,
dilations,
strides,
1,
subm,
&rulebook);
SparseCooTensor out = sparse::Conv3dCoo<T>(dev_ctx_cpu,
x_tensor,
kernel_tensor,
paddings,
dilations,
strides,
1,
subm,
&rulebook);
ASSERT_EQ(correct_out_dims.size(), out.dims().size());
for (int i = 0; i < correct_out_dims.size(); i++) {
......@@ -139,16 +139,16 @@ void TestConv3dBase(const std::vector<IntT>& indices,
if (backward) {
std::tuple<SparseCooTensor, DenseTensor> grads =
sparse::Conv3dGrad<T>(dev_ctx_cpu,
x_tensor,
kernel_tensor,
rulebook,
out,
paddings,
dilations,
strides,
1,
subm);
sparse::Conv3dCooGrad<T>(dev_ctx_cpu,
x_tensor,
kernel_tensor,
rulebook,
out,
paddings,
dilations,
strides,
1,
subm);
f_verify(std::get<0>(grads).non_zero_elements().data<T>(), features_grad);
f_verify(std::get<1>(grads).data<T>(), kernel_grad);
}
......@@ -198,15 +198,15 @@ void TestConv3dBase(const std::vector<IntT>& indices,
DenseTensor d_rulebook = phi::Empty(
dev_ctx_gpu, DenseTensorMeta(indices_dtype, {1}, DataLayout::NCHW));
SparseCooTensor d_out = sparse::Conv3d<T>(dev_ctx_gpu,
d_x_tensor,
d_kernel_tensor,
paddings,
dilations,
strides,
1,
subm,
&d_rulebook);
SparseCooTensor d_out = sparse::Conv3dCoo<T>(dev_ctx_gpu,
d_x_tensor,
d_kernel_tensor,
paddings,
dilations,
strides,
1,
subm,
&d_rulebook);
SparseCooTensor tmp_d_out = sparse::Coalesce<T>(dev_ctx_gpu, d_out);
......@@ -242,16 +242,16 @@ void TestConv3dBase(const std::vector<IntT>& indices,
if (backward) {
std::tuple<SparseCooTensor, DenseTensor> grads =
sparse::Conv3dGrad<T>(dev_ctx_gpu,
d_x_tensor,
d_kernel_tensor,
d_rulebook,
d_out,
paddings,
dilations,
strides,
1,
subm);
sparse::Conv3dCooGrad<T>(dev_ctx_gpu,
d_x_tensor,
d_kernel_tensor,
d_rulebook,
d_out,
paddings,
dilations,
strides,
1,
subm);
DenseTensor d_features_grad = std::get<0>(grads).non_zero_elements();
DenseTensor d_kernel_grad = std::get<1>(grads);
DenseTensor h_features_grad =
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或