Open3D (C++ API)  0.15.1
FixedRadiusSearchOpKernel.h
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26
27#pragma once
28
29#include "../TensorFlowHelper.h"
32#include "tensorflow/core/framework/op.h"
33#include "tensorflow/core/framework/op_kernel.h"
34#include "tensorflow/core/lib/core/errors.h"
35
37// namespace for code that is common for all kernels
38namespace fixed_radius_search_opkernel {
39
40// class for the allocator object
41template <class T>
42class OutputAllocator {
43public:
44 OutputAllocator(tensorflow::OpKernelContext* context) : context(context) {}
45
46 void AllocIndices(int32_t** ptr, size_t num) {
47 using namespace tensorflow;
48 *ptr = nullptr;
49 Tensor* tensor = 0;
50 TensorShape shape({int64_t(num)});
51 OP_REQUIRES_OK(context, context->allocate_output(0, shape, &tensor));
52 auto flat_tensor = tensor->flat<int32>();
53 static_assert(sizeof(int32) == sizeof(int32_t),
54 "int32 and int32_t not compatible");
55 *ptr = (int32_t*)flat_tensor.data();
56 }
57
58 void AllocDistances(T** ptr, size_t num) {
59 using namespace tensorflow;
60 *ptr = nullptr;
61 Tensor* tensor = 0;
62 TensorShape shape({int64_t(num)});
63 OP_REQUIRES_OK(context, context->allocate_output(2, shape, &tensor));
64 auto flat_tensor = tensor->flat<T>();
65 *ptr = flat_tensor.data();
66 }
67
68private:
69 tensorflow::OpKernelContext* context;
70};
71
72class FixedRadiusSearchOpKernel : public tensorflow::OpKernel {
73public:
74 explicit FixedRadiusSearchOpKernel(
75 tensorflow::OpKernelConstruction* construction)
76 : OpKernel(construction) {
77 using namespace tensorflow;
78 using namespace open3d::core::nns;
79
80 std::string metric_str;
81 OP_REQUIRES_OK(construction,
82 construction->GetAttr("metric", &metric_str));
83 if (metric_str == "L1")
84 metric = L1;
85 else if (metric_str == "L2")
86 metric = L2;
87 else
88 metric = Linf;
89
90 OP_REQUIRES_OK(construction,
91 construction->GetAttr("ignore_query_point",
92 &ignore_query_point));
93
94 OP_REQUIRES_OK(construction, construction->GetAttr("return_distances",
95 &return_distances));
96 }
97
98 void Compute(tensorflow::OpKernelContext* context) override {
99 using namespace tensorflow;
100 static_assert(sizeof(int64) == sizeof(int64_t),
101 "int64 type is not compatible");
102
103 const Tensor& points = context->input(0);
104 const Tensor& queries = context->input(1);
105
106 const Tensor& radius = context->input(2);
107 OP_REQUIRES(context, TensorShapeUtils::IsScalar(radius.shape()),
108 errors::InvalidArgument("radius must be scalar, got shape ",
109 radius.shape().DebugString()));
110
111 const Tensor& points_row_splits = context->input(3);
112 const Tensor& queries_row_splits = context->input(4);
113
114 const Tensor& hash_table_splits = context->input(5);
115 const Tensor& hash_table_index = context->input(6);
116 const Tensor& hash_table_cell_splits = context->input(7);
117
118 {
119 using namespace open3d::ml::op_util;
120
121 Dim num_points("num_points");
122 Dim num_queries("num_queries");
123 Dim batch_size("batch_size");
124 Dim num_cells("num_cells");
125 CHECK_SHAPE(context, points, num_points, 3);
126 CHECK_SHAPE(context, hash_table_index, num_points);
127 CHECK_SHAPE(context, queries, num_queries, 3);
128 CHECK_SHAPE(context, points_row_splits, batch_size + 1);
129 CHECK_SHAPE(context, queries_row_splits, batch_size + 1);
130 CHECK_SHAPE(context, hash_table_splits, batch_size + 1);
131 CHECK_SHAPE(context, hash_table_cell_splits, num_cells + 1);
132 }
133 Tensor* query_neighbors_row_splits = 0;
134 TensorShape query_neighbors_row_splits_shape(
135 {queries.shape().dim_size(0) + 1});
136 OP_REQUIRES_OK(context, context->allocate_output(
137 1, query_neighbors_row_splits_shape,
138 &query_neighbors_row_splits));
139
140 Kernel(context, points, queries, radius, points_row_splits,
141 queries_row_splits, hash_table_splits, hash_table_index,
142 hash_table_cell_splits, *query_neighbors_row_splits);
143 }
144
145 virtual void Kernel(tensorflow::OpKernelContext* context,
146 const tensorflow::Tensor& points,
147 const tensorflow::Tensor& queries,
148 const tensorflow::Tensor& radius,
149 const tensorflow::Tensor& points_row_splits,
150 const tensorflow::Tensor& queries_row_splits,
151 const tensorflow::Tensor& hash_table_splits,
152 const tensorflow::Tensor& hash_table_index,
153 const tensorflow::Tensor& hash_table_cell_splits,
154 tensorflow::Tensor& query_neighbors_row_splits) = 0;
155
156protected:
158 bool ignore_query_point;
159 bool return_distances;
160};
161} // namespace fixed_radius_search_opkernel
#define CHECK_SHAPE(tensor,...)
Definition: TorchHelper.h:205
ImGuiContext * context
Definition: Window.cpp:95
Definition: Tensor.h:51
Class for dimensions for which the value should be inferred.
Definition: ShapeChecking.h:69
int points
Definition: FilePCD.cpp:73
Definition: FixedRadiusIndex.cpp:35
Metric
Supported metrics.
Definition: NeighborSearchCommon.h:38
@ Linf
Definition: NeighborSearchCommon.h:38
@ L1
Definition: NeighborSearchCommon.h:38
@ L2
Definition: NeighborSearchCommon.h:38
const char const char value recording_handle imu_sample recording_handle uint8_t size_t data_size k4a_record_configuration_t config target_format k4a_capture_t capture_handle k4a_imu_sample_t imu_sample playback_handle k4a_logging_message_cb_t void min_level device_handle k4a_imu_sample_t int32_t
Definition: K4aPlugin.cpp:414
Definition: ShapeChecking.h:35