Open3D (C++ API)  0.18.0
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ContinuousConvOpKernel.h
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1// ----------------------------------------------------------------------------
2// - Open3D: www.open3d.org -
3// ----------------------------------------------------------------------------
4// Copyright (c) 2018-2023 www.open3d.org
5// SPDX-License-Identifier: MIT
6// ----------------------------------------------------------------------------
7
8#pragma once
9
11#include "tensorflow/core/framework/op.h"
12#include "tensorflow/core/framework/op_kernel.h"
13#include "tensorflow/core/lib/core/errors.h"
14
15template <class TIndex>
16class ContinuousConvOpKernel : public tensorflow::OpKernel {
17public:
19 tensorflow::OpKernelConstruction* construction)
20 : OpKernel(construction) {
21 using namespace tensorflow;
22 using namespace open3d::ml::impl;
23 OP_REQUIRES_OK(construction,
24 construction->GetAttr("align_corners", &align_corners));
25 OP_REQUIRES_OK(construction,
26 construction->GetAttr("normalize", &normalize));
27
28 std::string interpolation_str;
29 OP_REQUIRES_OK(construction, construction->GetAttr("interpolation",
30 &interpolation_str));
31
32 if (interpolation_str == "linear")
33 interpolation = InterpolationMode::LINEAR;
34 else if (interpolation_str == "linear_border")
35 interpolation = InterpolationMode::LINEAR_BORDER;
36 else
37 interpolation = InterpolationMode::NEAREST_NEIGHBOR;
38
39 std::string mapping_str;
40 OP_REQUIRES_OK(construction, construction->GetAttr("coordinate_mapping",
41 &mapping_str));
42
43 if (mapping_str == "ball_to_cube_radial")
44 coordinate_mapping = CoordinateMapping::BALL_TO_CUBE_RADIAL;
45 else if (mapping_str == "ball_to_cube_volume_preserving")
47 CoordinateMapping::BALL_TO_CUBE_VOLUME_PRESERVING;
48 else
49 coordinate_mapping = CoordinateMapping::IDENTITY;
50
51 OP_REQUIRES_OK(construction, construction->GetAttr("max_temp_mem_MB",
53 }
54
55 void Compute(tensorflow::OpKernelContext* context) override {
56 using namespace tensorflow;
57 static_assert(sizeof(int64) == sizeof(int64_t),
58 "int64 type is not compatible");
59 const Tensor& filter = context->input(0);
60
61 const Tensor& out_positions = context->input(1);
62 OP_REQUIRES(context,
63 out_positions.shape().dim_size(0) <=
64 std::numeric_limits<TIndex>::max(),
65 errors::InvalidArgument("Too many output points"));
66
67 const Tensor& extents = context->input(2);
68 OP_REQUIRES(context, extents.shape().dims() == 2,
69 errors::InvalidArgument("extents must be a rank 2 tensor"));
70 OP_REQUIRES(context,
71 extents.shape().dim_size(0) ==
72 out_positions.shape().dim_size(0) ||
73 extents.shape().dim_size(0) == 1,
74 errors::InvalidArgument("number of extents must match the "
75 "number of out_positions or must "
76 "be 1"));
77 OP_REQUIRES(context,
78 extents.shape().dim_size(1) == 3 ||
79 extents.shape().dim_size(1) == 1,
80 errors::InvalidArgument(
81 "number of components for extents must be 3 or 1"));
82
83 const Tensor& offset = context->input(3);
84 OP_REQUIRES(context, offset.shape().dims() == 1,
85 errors::InvalidArgument("offset must be a rank 1 tensor"));
86 OP_REQUIRES(context, offset.shape().dim_size(0) == 3,
87 errors::InvalidArgument("offset length must be 3"));
88
89 const Tensor& inp_positions = context->input(4);
90 OP_REQUIRES(context,
91 inp_positions.shape().dim_size(0) <=
92 std::numeric_limits<TIndex>::max(),
93 errors::InvalidArgument("Too many input points"));
94
95 const Tensor& inp_features = context->input(5);
96
97 const Tensor& inp_importance = context->input(6);
98
99 const Tensor& neighbors_index = context->input(7);
100
101 const Tensor& neighbors_importance = context->input(8);
102
103 const Tensor& neighbors_row_splits = context->input(9);
104
105 OP_REQUIRES(
106 context,
107 inp_positions.shape().dim_size(0) ==
108 inp_features.shape().dim_size(0),
109 errors::InvalidArgument("first dim of inp_positions does not "
110 "match the first dim of inp_features"));
111
112 OP_REQUIRES(context,
113 inp_positions.shape().dim_size(0) ==
114 inp_importance.shape().dim_size(0) ||
115 inp_importance.shape().dim_size(0) == 0,
116 errors::InvalidArgument("first dim of inp_positions does "
117 "not match the first dim of "
118 "inp_importance"));
119
120 OP_REQUIRES(context,
121 neighbors_importance.shape().dim_size(0) ==
122 neighbors_index.shape().dim_size(0) ||
123 neighbors_importance.shape().dim_size(0) == 0,
124 errors::InvalidArgument("first dim of neighbors_importance "
125 "does not match the first dim of "
126 "neighbors_index"));
127
128 OP_REQUIRES(
129 context,
130 filter.shape().dim_size(3) == inp_features.shape().dim_size(1),
131 errors::InvalidArgument("number of input channels in filter "
132 "and inp_features does not match"));
133
134 TensorShape out_features_shape({out_positions.shape().dim_size(0),
135 filter.shape().dim_size(4)});
136 Tensor* out_features = nullptr;
137 OP_REQUIRES_OK(context, context->allocate_output(0, out_features_shape,
138 &out_features));
139
140 std::vector<int> filter_dims({
141 int(filter.shape().dim_size(0)),
142 int(filter.shape().dim_size(1)),
143 int(filter.shape().dim_size(2)),
144 int(filter.shape().dim_size(3)),
145 int(filter.shape().dim_size(4)),
146 });
147
148 bool individual_extents = extents.shape().dim_size(0) ==
149 out_positions.shape().dim_size(0) &&
150 extents.shape().dim_size(0) > 1;
151
152 bool isotropic_extents = extents.shape().dim_size(1) == 1;
153
154 bool point_importances = inp_importance.shape().dim_size(0) != 0;
155
156 bool has_neighbors_importances =
157 neighbors_importance.shape().dim_size(0) != 0;
158
159 Kernel(context, filter, out_positions, extents, offset, inp_positions,
160 inp_features, inp_importance, neighbors_index,
161 neighbors_importance, neighbors_row_splits, filter_dims,
162 individual_extents, isotropic_extents, point_importances,
163 has_neighbors_importances, *out_features);
164 }
165
166 virtual void Kernel(tensorflow::OpKernelContext* context,
167 const tensorflow::Tensor& filter,
168 const tensorflow::Tensor& out_positions,
169 const tensorflow::Tensor& extents,
170 const tensorflow::Tensor& offset,
171 const tensorflow::Tensor& inp_positions,
172 const tensorflow::Tensor& inp_features,
173 const tensorflow::Tensor& inp_importance,
174 const tensorflow::Tensor& neighbors_index,
175 const tensorflow::Tensor& neighbors_importance,
176 const tensorflow::Tensor& neighbors_row_splits,
177 const std::vector<int>& filter_dims,
178 const bool individual_extents,
179 const bool isotropic_extents,
180 const bool point_importances,
181 const bool has_neighbors_importances,
182 tensorflow::Tensor& out_features) = 0;
183
184public:
190};
ImGuiContext * context
Definition Window.cpp:76
Definition ContinuousConvOpKernel.h:16
bool normalize
Definition ContinuousConvOpKernel.h:186
open3d::ml::impl::InterpolationMode interpolation
Definition ContinuousConvOpKernel.h:187
void Compute(tensorflow::OpKernelContext *context) override
Definition ContinuousConvOpKernel.h:55
bool align_corners
Definition ContinuousConvOpKernel.h:185
virtual void Kernel(tensorflow::OpKernelContext *context, const tensorflow::Tensor &filter, const tensorflow::Tensor &out_positions, const tensorflow::Tensor &extents, const tensorflow::Tensor &offset, const tensorflow::Tensor &inp_positions, const tensorflow::Tensor &inp_features, const tensorflow::Tensor &inp_importance, const tensorflow::Tensor &neighbors_index, const tensorflow::Tensor &neighbors_importance, const tensorflow::Tensor &neighbors_row_splits, const std::vector< int > &filter_dims, const bool individual_extents, const bool isotropic_extents, const bool point_importances, const bool has_neighbors_importances, tensorflow::Tensor &out_features)=0
ContinuousConvOpKernel(tensorflow::OpKernelConstruction *construction)
Definition ContinuousConvOpKernel.h:18
int max_temp_mem_MB
Definition ContinuousConvOpKernel.h:189
open3d::ml::impl::CoordinateMapping coordinate_mapping
Definition ContinuousConvOpKernel.h:188
int offset
Definition FilePCD.cpp:45
Definition ContinuousConv.h:16
InterpolationMode
Definition ContinuousConvTypes.h:18
CoordinateMapping
Definition ContinuousConvTypes.h:26