29 #include <tensorflow/core/framework/op.h>
30 #include <tensorflow/core/framework/op_kernel.h>
31 #include <tensorflow/core/lib/core/errors.h>
35 template <
class TIndex>
39 tensorflow::OpKernelConstruction* construction)
40 : OpKernel(construction) {
41 using namespace tensorflow;
42 OP_REQUIRES_OK(construction,
43 construction->GetAttr(
"normalize", &
normalize));
45 OP_REQUIRES_OK(construction, construction->GetAttr(
"max_temp_mem_MB",
50 using namespace tensorflow;
52 static_assert(
sizeof(int64) ==
sizeof(int64_t),
53 "int64 type is not compatible");
54 const Tensor& filters =
context->input(0);
55 const Tensor& inp_features =
context->input(1);
56 const Tensor& inp_importance =
context->input(2);
57 const Tensor& neighbors_index =
context->input(3);
58 const Tensor& neighbors_kernel_index =
context->input(4);
59 const Tensor& neighbors_importance =
context->input(5);
60 const Tensor& neighbors_row_splits =
context->input(6);
61 const Tensor& out_features_gradient =
context->input(7);
63 Dim num_out(
"num_out");
64 Dim num_inp(
"num_inp");
65 Dim num_kernel_elements(
"num_kernel_elements");
66 Dim in_channels(
"in_channels");
67 Dim out_channels(
"out_channels");
68 Dim num_neighbors(
"num_neighbors");
71 in_channels, out_channels);
80 TensorShape filter_backprop_shape(filters.shape());
81 Tensor* filter_backprop =
nullptr;
83 context->allocate_output(0, filter_backprop_shape,
86 std::vector<int> filter_dims;
87 for (
int i = 0; i < filters.dims(); ++i) {
88 filter_dims.push_back(filters.dim_size(i));
90 bool point_importances = inp_importance.shape().dim_size(0) != 0;
92 bool has_neighbors_importances =
93 neighbors_importance.shape().dim_size(0) != 0;
95 Kernel(
context, filters, inp_features, inp_importance, neighbors_index,
96 neighbors_kernel_index, neighbors_importance,
97 neighbors_row_splits, out_features_gradient, filter_dims,
98 point_importances, has_neighbors_importances, *filter_backprop);
102 const tensorflow::Tensor& filters,
103 const tensorflow::Tensor& inp_features,
104 const tensorflow::Tensor& inp_importance,
105 const tensorflow::Tensor& neighbors_index,
106 const tensorflow::Tensor& neighbors_kernel_index,
107 const tensorflow::Tensor& neighbors_importance,
108 const tensorflow::Tensor& neighbors_row_splits,
109 const tensorflow::Tensor& out_features_gradient,
110 const std::vector<int>& filter_dims,
111 const bool point_importances,
112 const bool has_neighbors_importances,
113 tensorflow::Tensor& filter_backprop) = 0;
#define CHECK_SHAPE_COMBINE_FIRST_DIMS(tensor,...)
Definition: TorchHelper.h:214
#define CHECK_SHAPE(tensor,...)
Definition: TorchHelper.h:205
ImGuiContext * context
Definition: Window.cpp:95
Definition: SparseConvBackpropFilterOpKernel.h:36
SparseConvBackpropFilterOpKernel(tensorflow::OpKernelConstruction *construction)
Definition: SparseConvBackpropFilterOpKernel.h:38
virtual void Kernel(tensorflow::OpKernelContext *context, const tensorflow::Tensor &filters, const tensorflow::Tensor &inp_features, const tensorflow::Tensor &inp_importance, const tensorflow::Tensor &neighbors_index, const tensorflow::Tensor &neighbors_kernel_index, const tensorflow::Tensor &neighbors_importance, const tensorflow::Tensor &neighbors_row_splits, const tensorflow::Tensor &out_features_gradient, const std::vector< int > &filter_dims, const bool point_importances, const bool has_neighbors_importances, tensorflow::Tensor &filter_backprop)=0
int max_temp_mem_MB
Definition: SparseConvBackpropFilterOpKernel.h:117
bool normalize
Definition: SparseConvBackpropFilterOpKernel.h:116
void Compute(tensorflow::OpKernelContext *context) override
Definition: SparseConvBackpropFilterOpKernel.h:49
Class for dimensions for which the value should be inferred.
Definition: ShapeChecking.h:69
Definition: ShapeChecking.h:35