Open3D (C++ API)  0.17.0
ContinuousConvTransposeBackpropFilterOpKernel.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>
17 : public tensorflow::OpKernel {
18public:
20 tensorflow::OpKernelConstruction* construction)
21 : OpKernel(construction) {
22 using namespace tensorflow;
23 using namespace open3d::ml::impl;
24 OP_REQUIRES_OK(construction,
25 construction->GetAttr("align_corners", &align_corners));
26 OP_REQUIRES_OK(construction,
27 construction->GetAttr("normalize", &normalize));
28
29 std::string interpolation_str;
30 OP_REQUIRES_OK(construction, construction->GetAttr("interpolation",
31 &interpolation_str));
32
33 if (interpolation_str == "linear")
34 interpolation = InterpolationMode::LINEAR;
35 else if (interpolation_str == "linear_border")
36 interpolation = InterpolationMode::LINEAR_BORDER;
37 else
39
40 std::string mapping_str;
41 OP_REQUIRES_OK(construction, construction->GetAttr("coordinate_mapping",
42 &mapping_str));
43
44 if (mapping_str == "ball_to_cube_radial")
45 coordinate_mapping = CoordinateMapping::BALL_TO_CUBE_RADIAL;
46 else if (mapping_str == "ball_to_cube_volume_preserving")
48 CoordinateMapping::BALL_TO_CUBE_VOLUME_PRESERVING;
49 else
50 coordinate_mapping = CoordinateMapping::IDENTITY;
51
52 OP_REQUIRES_OK(construction, construction->GetAttr("max_temp_mem_MB",
54 }
55
56 void Compute(tensorflow::OpKernelContext* context) override {
57 using namespace tensorflow;
58 static_assert(sizeof(int64) == sizeof(int64_t),
59 "int64 type is not compatible");
60 const Tensor& filter = context->input(0);
61
62 const Tensor& out_positions = context->input(1);
63 OP_REQUIRES(context,
64 out_positions.shape().dim_size(0) <=
65 std::numeric_limits<TIndex>::max(),
66 errors::InvalidArgument("Too many output points"));
67
68 const Tensor& out_importance = context->input(2);
69 OP_REQUIRES(context,
70 out_importance.shape().dim_size(0) == 0 ||
71 out_importance.shape().dim_size(0) ==
72 out_positions.shape().dim_size(0),
73 errors::InvalidArgument("length of out_importance must "
74 "match the number of output points "
75 "or must be 0"));
76
77 const Tensor& extents = context->input(3);
78
79 const Tensor& offset = context->input(4);
80 OP_REQUIRES(context, offset.shape().dims() == 1,
81 errors::InvalidArgument("offset must be a rank 1 tensor"));
82 OP_REQUIRES(context, offset.shape().dim_size(0) == 3,
83 errors::InvalidArgument("offset length must be 3"));
84
85 const Tensor& inp_positions = context->input(5);
86 OP_REQUIRES(context,
87 inp_positions.shape().dim_size(0) <=
88 std::numeric_limits<TIndex>::max(),
89 errors::InvalidArgument("Too many input points"));
90
91 const Tensor& inp_features = context->input(6);
92
93 const Tensor& inp_neighbors_importance_sum = context->input(7);
94
95 const Tensor& inp_neighbors_row_splits = context->input(8);
96
97 const Tensor& neighbors_index = context->input(9);
98
99 const Tensor& neighbors_importance = context->input(10);
100
101 const Tensor& neighbors_row_splits = context->input(11);
102
103 const Tensor& out_features_gradient = context->input(12);
104
105 OP_REQUIRES(context, extents.shape().dims() == 2,
106 errors::InvalidArgument("extents must be a rank 2 tensor"));
107 OP_REQUIRES(context,
108 extents.shape().dim_size(0) ==
109 inp_positions.shape().dim_size(0) ||
110 extents.shape().dim_size(0) == 1,
111 errors::InvalidArgument("number of extents must match the "
112 "number of inp_positions or must "
113 "be 1"));
114 OP_REQUIRES(context,
115 extents.shape().dim_size(1) == 3 ||
116 extents.shape().dim_size(1) == 1,
117 errors::InvalidArgument(
118 "number of components for extents must be 3 or 1"));
119
120 OP_REQUIRES(
121 context,
122 inp_positions.shape().dim_size(0) ==
123 inp_features.shape().dim_size(0),
124 errors::InvalidArgument("first dim of inp_positions does not "
125 "match the first dim of inp_features"));
126
127 OP_REQUIRES(
128 context,
129 inp_neighbors_importance_sum.shape().dim_size(0) ==
130 inp_positions.shape().dim_size(0) ||
131 inp_neighbors_importance_sum.shape().dim_size(0) == 0,
132 errors::InvalidArgument(
133 "first dim of inp_neighbors_importance_sum does not "
134 "match the first dim of inp_positions",
135 inp_neighbors_importance_sum.shape().dim_size(0), " ",
136 inp_positions.shape().dim_size(0)));
137
138 OP_REQUIRES(context,
139 out_positions.shape().dim_size(0) ==
140 out_importance.shape().dim_size(0) ||
141 out_importance.shape().dim_size(0) == 0,
142 errors::InvalidArgument("first dim of out_positions does "
143 "not match the first dim of "
144 "out_importance"));
145
146 OP_REQUIRES(context,
147 neighbors_importance.shape().dim_size(0) ==
148 neighbors_index.shape().dim_size(0) ||
149 neighbors_importance.shape().dim_size(0) == 0,
150 errors::InvalidArgument("first dim of neighbors_importance "
151 "does not match the first dim of "
152 "neighbors_index"));
153
154 OP_REQUIRES(
155 context,
156 filter.shape().dim_size(3) == inp_features.shape().dim_size(1),
157 errors::InvalidArgument("number of input channels in filter "
158 "and inp_features does not match"));
159
160 OP_REQUIRES(context,
161 out_features_gradient.shape().dim_size(0) ==
162 out_positions.shape().dim_size(0),
163 errors::InvalidArgument("first dim of out_positions, does "
164 "not match the first dim of "
165 "out_features_gradient"));
166
167 TensorShape filter_backprop_shape(filter.shape());
168 Tensor* filter_backprop = nullptr;
169 OP_REQUIRES_OK(context,
170 context->allocate_output(0, filter_backprop_shape,
171 &filter_backprop));
172
173 std::vector<int> filter_dims({
174 int(filter.shape().dim_size(0)),
175 int(filter.shape().dim_size(1)),
176 int(filter.shape().dim_size(2)),
177 int(filter.shape().dim_size(3)),
178 int(filter.shape().dim_size(4)),
179 });
180
181 bool individual_extents = extents.shape().dim_size(0) ==
182 out_positions.shape().dim_size(0) &&
183 extents.shape().dim_size(0) > 1;
184
185 bool isotropic_extents = extents.shape().dim_size(1) == 1;
186
187 bool point_importances = out_importance.shape().dim_size(0) != 0;
188
189 bool has_neighbors_importances =
190 neighbors_importance.shape().dim_size(0) != 0;
191
192 Kernel(context, filter, out_positions, out_importance, extents, offset,
193 inp_positions, inp_features, inp_neighbors_importance_sum,
194 inp_neighbors_row_splits, neighbors_index, neighbors_importance,
195 neighbors_row_splits, out_features_gradient, filter_dims,
196 individual_extents, isotropic_extents, point_importances,
197 has_neighbors_importances, *filter_backprop);
198 }
199
200 virtual void Kernel(tensorflow::OpKernelContext* context,
201 const tensorflow::Tensor& filter,
202 const tensorflow::Tensor& out_positions,
203 const tensorflow::Tensor& out_importance,
204 const tensorflow::Tensor& extents,
205 const tensorflow::Tensor& offset,
206 const tensorflow::Tensor& inp_positions,
207 const tensorflow::Tensor& inp_features,
208 const tensorflow::Tensor& inp_neighbors_importance_sum,
209 const tensorflow::Tensor& inp_neighbors_row_splits,
210 const tensorflow::Tensor& neighbors_index,
211 const tensorflow::Tensor& neighbors_importance,
212 const tensorflow::Tensor& neighbors_row_splits,
213 const tensorflow::Tensor& out_features_gradient,
214 const std::vector<int>& filter_dims,
215 const bool individual_extents,
216 const bool isotropic_extents,
217 const bool point_importances,
218 const bool has_neighbors_importances,
219 tensorflow::Tensor& filter_backprop) = 0;
220
221public:
227};
ImGuiContext * context
Definition: Window.cpp:76
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:17
ContinuousConvTransposeBackpropFilterOpKernel(tensorflow::OpKernelConstruction *construction)
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:19
virtual void Kernel(tensorflow::OpKernelContext *context, const tensorflow::Tensor &filter, const tensorflow::Tensor &out_positions, const tensorflow::Tensor &out_importance, const tensorflow::Tensor &extents, const tensorflow::Tensor &offset, const tensorflow::Tensor &inp_positions, const tensorflow::Tensor &inp_features, const tensorflow::Tensor &inp_neighbors_importance_sum, const tensorflow::Tensor &inp_neighbors_row_splits, const tensorflow::Tensor &neighbors_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 individual_extents, const bool isotropic_extents, const bool point_importances, const bool has_neighbors_importances, tensorflow::Tensor &filter_backprop)=0
bool align_corners
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:222
void Compute(tensorflow::OpKernelContext *context) override
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:56
open3d::ml::impl::InterpolationMode interpolation
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:224
open3d::ml::impl::CoordinateMapping coordinate_mapping
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:225
bool normalize
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:223
int max_temp_mem_MB
Definition: ContinuousConvTransposeBackpropFilterOpKernel.h:226
int offset
Definition: FilePCD.cpp:45
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 timeout_in_ms capture_handle capture_handle capture_handle image_handle temperature_c int
Definition: K4aPlugin.cpp:474
Definition: ContinuousConv.h:16
InterpolationMode
Definition: ContinuousConvTypes.h:18
@ NEAREST_NEIGHBOR
Definition: VoxelPooling.h:21
CoordinateMapping
Definition: ContinuousConvTypes.h:26