1 | // This file is MACHINE GENERATED! Do not edit. |
2 | |
3 | |
4 | #include "tensorflow/cc/ops/const_op.h" |
5 | #include "tensorflow/cc/ops/image_ops_internal.h" |
6 | |
7 | namespace tensorflow { |
8 | namespace ops { |
9 | namespace internal { |
10 | // NOTE: This namespace has internal TensorFlow details that |
11 | // are not part of TensorFlow's public API. |
12 | |
13 | ExtractGlimpseV2::(const ::tensorflow::Scope& scope, |
14 | ::tensorflow::Input input, |
15 | ::tensorflow::Input size, |
16 | ::tensorflow::Input offsets, const |
17 | ExtractGlimpseV2::Attrs& attrs) { |
18 | if (!scope.ok()) return; |
19 | auto _input = ::tensorflow::ops::AsNodeOut(scope, input); |
20 | if (!scope.ok()) return; |
21 | auto _size = ::tensorflow::ops::AsNodeOut(scope, size); |
22 | if (!scope.ok()) return; |
23 | auto _offsets = ::tensorflow::ops::AsNodeOut(scope, offsets); |
24 | if (!scope.ok()) return; |
25 | ::tensorflow::Node* ret; |
26 | const auto unique_name = scope.GetUniqueNameForOp("ExtractGlimpseV2" ); |
27 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ExtractGlimpseV2" ) |
28 | .Input(_input) |
29 | .Input(_size) |
30 | .Input(_offsets) |
31 | .Attr("centered" , attrs.centered_) |
32 | .Attr("normalized" , attrs.normalized_) |
33 | .Attr("uniform_noise" , attrs.uniform_noise_) |
34 | .Attr("noise" , attrs.noise_) |
35 | ; |
36 | scope.UpdateBuilder(&builder); |
37 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
38 | if (!scope.ok()) return; |
39 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
40 | this->operation = Operation(ret); |
41 | this->glimpse = Output(ret, 0); |
42 | } |
43 | |
44 | ExtractGlimpseV2::(const ::tensorflow::Scope& scope, |
45 | ::tensorflow::Input input, |
46 | ::tensorflow::Input size, |
47 | ::tensorflow::Input offsets) |
48 | : ExtractGlimpseV2(scope, input, size, offsets, ExtractGlimpseV2::Attrs()) {} |
49 | |
50 | GenerateBoundingBoxProposals::GenerateBoundingBoxProposals(const |
51 | ::tensorflow::Scope& |
52 | scope, |
53 | ::tensorflow::Input |
54 | scores, |
55 | ::tensorflow::Input |
56 | bbox_deltas, |
57 | ::tensorflow::Input |
58 | image_info, |
59 | ::tensorflow::Input |
60 | anchors, |
61 | ::tensorflow::Input |
62 | nms_threshold, |
63 | ::tensorflow::Input |
64 | pre_nms_topn, |
65 | ::tensorflow::Input |
66 | min_size, const |
67 | GenerateBoundingBoxProposals::Attrs& |
68 | attrs) { |
69 | if (!scope.ok()) return; |
70 | auto _scores = ::tensorflow::ops::AsNodeOut(scope, scores); |
71 | if (!scope.ok()) return; |
72 | auto _bbox_deltas = ::tensorflow::ops::AsNodeOut(scope, bbox_deltas); |
73 | if (!scope.ok()) return; |
74 | auto _image_info = ::tensorflow::ops::AsNodeOut(scope, image_info); |
75 | if (!scope.ok()) return; |
76 | auto _anchors = ::tensorflow::ops::AsNodeOut(scope, anchors); |
77 | if (!scope.ok()) return; |
78 | auto _nms_threshold = ::tensorflow::ops::AsNodeOut(scope, nms_threshold); |
79 | if (!scope.ok()) return; |
80 | auto _pre_nms_topn = ::tensorflow::ops::AsNodeOut(scope, pre_nms_topn); |
81 | if (!scope.ok()) return; |
82 | auto _min_size = ::tensorflow::ops::AsNodeOut(scope, min_size); |
83 | if (!scope.ok()) return; |
84 | ::tensorflow::Node* ret; |
85 | const auto unique_name = scope.GetUniqueNameForOp("GenerateBoundingBoxProposals" ); |
86 | auto builder = ::tensorflow::NodeBuilder(unique_name, "GenerateBoundingBoxProposals" ) |
87 | .Input(_scores) |
88 | .Input(_bbox_deltas) |
89 | .Input(_image_info) |
90 | .Input(_anchors) |
91 | .Input(_nms_threshold) |
92 | .Input(_pre_nms_topn) |
93 | .Input(_min_size) |
94 | .Attr("post_nms_topn" , attrs.post_nms_topn_) |
95 | ; |
96 | scope.UpdateBuilder(&builder); |
97 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
98 | if (!scope.ok()) return; |
99 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
100 | this->operation = Operation(ret); |
101 | ::tensorflow::NameRangeMap _outputs_range; |
102 | ::tensorflow::Status _status_ = ::tensorflow::NameRangesForNode(*ret, ret->op_def(), nullptr, &_outputs_range); |
103 | if (!_status_.ok()) { |
104 | scope.UpdateStatus(_status_); |
105 | return; |
106 | } |
107 | |
108 | this->rois = Output(ret, _outputs_range["rois" ].first); |
109 | this->roi_probabilities = Output(ret, _outputs_range["roi_probabilities" ].first); |
110 | } |
111 | |
112 | GenerateBoundingBoxProposals::GenerateBoundingBoxProposals(const |
113 | ::tensorflow::Scope& |
114 | scope, |
115 | ::tensorflow::Input |
116 | scores, |
117 | ::tensorflow::Input |
118 | bbox_deltas, |
119 | ::tensorflow::Input |
120 | image_info, |
121 | ::tensorflow::Input |
122 | anchors, |
123 | ::tensorflow::Input |
124 | nms_threshold, |
125 | ::tensorflow::Input |
126 | pre_nms_topn, |
127 | ::tensorflow::Input |
128 | min_size) |
129 | : GenerateBoundingBoxProposals(scope, scores, bbox_deltas, image_info, anchors, nms_threshold, pre_nms_topn, min_size, GenerateBoundingBoxProposals::Attrs()) {} |
130 | |
131 | ImageProjectiveTransformV2::ImageProjectiveTransformV2(const |
132 | ::tensorflow::Scope& |
133 | scope, |
134 | ::tensorflow::Input |
135 | images, |
136 | ::tensorflow::Input |
137 | transforms, |
138 | ::tensorflow::Input |
139 | output_shape, |
140 | StringPiece |
141 | interpolation, const |
142 | ImageProjectiveTransformV2::Attrs& |
143 | attrs) { |
144 | if (!scope.ok()) return; |
145 | auto _images = ::tensorflow::ops::AsNodeOut(scope, images); |
146 | if (!scope.ok()) return; |
147 | auto _transforms = ::tensorflow::ops::AsNodeOut(scope, transforms); |
148 | if (!scope.ok()) return; |
149 | auto _output_shape = ::tensorflow::ops::AsNodeOut(scope, output_shape); |
150 | if (!scope.ok()) return; |
151 | ::tensorflow::Node* ret; |
152 | const auto unique_name = scope.GetUniqueNameForOp("ImageProjectiveTransformV2" ); |
153 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ImageProjectiveTransformV2" ) |
154 | .Input(_images) |
155 | .Input(_transforms) |
156 | .Input(_output_shape) |
157 | .Attr("interpolation" , interpolation) |
158 | .Attr("fill_mode" , attrs.fill_mode_) |
159 | ; |
160 | scope.UpdateBuilder(&builder); |
161 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
162 | if (!scope.ok()) return; |
163 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
164 | this->operation = Operation(ret); |
165 | this->transformed_images = Output(ret, 0); |
166 | } |
167 | |
168 | ImageProjectiveTransformV2::ImageProjectiveTransformV2(const |
169 | ::tensorflow::Scope& |
170 | scope, |
171 | ::tensorflow::Input |
172 | images, |
173 | ::tensorflow::Input |
174 | transforms, |
175 | ::tensorflow::Input |
176 | output_shape, |
177 | StringPiece |
178 | interpolation) |
179 | : ImageProjectiveTransformV2(scope, images, transforms, output_shape, interpolation, ImageProjectiveTransformV2::Attrs()) {} |
180 | |
181 | ImageProjectiveTransformV3::ImageProjectiveTransformV3(const |
182 | ::tensorflow::Scope& |
183 | scope, |
184 | ::tensorflow::Input |
185 | images, |
186 | ::tensorflow::Input |
187 | transforms, |
188 | ::tensorflow::Input |
189 | output_shape, |
190 | ::tensorflow::Input |
191 | fill_value, StringPiece |
192 | interpolation, const |
193 | ImageProjectiveTransformV3::Attrs& |
194 | attrs) { |
195 | if (!scope.ok()) return; |
196 | auto _images = ::tensorflow::ops::AsNodeOut(scope, images); |
197 | if (!scope.ok()) return; |
198 | auto _transforms = ::tensorflow::ops::AsNodeOut(scope, transforms); |
199 | if (!scope.ok()) return; |
200 | auto _output_shape = ::tensorflow::ops::AsNodeOut(scope, output_shape); |
201 | if (!scope.ok()) return; |
202 | auto _fill_value = ::tensorflow::ops::AsNodeOut(scope, fill_value); |
203 | if (!scope.ok()) return; |
204 | ::tensorflow::Node* ret; |
205 | const auto unique_name = scope.GetUniqueNameForOp("ImageProjectiveTransformV3" ); |
206 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ImageProjectiveTransformV3" ) |
207 | .Input(_images) |
208 | .Input(_transforms) |
209 | .Input(_output_shape) |
210 | .Input(_fill_value) |
211 | .Attr("interpolation" , interpolation) |
212 | .Attr("fill_mode" , attrs.fill_mode_) |
213 | ; |
214 | scope.UpdateBuilder(&builder); |
215 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
216 | if (!scope.ok()) return; |
217 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
218 | this->operation = Operation(ret); |
219 | this->transformed_images = Output(ret, 0); |
220 | } |
221 | |
222 | ImageProjectiveTransformV3::ImageProjectiveTransformV3(const |
223 | ::tensorflow::Scope& |
224 | scope, |
225 | ::tensorflow::Input |
226 | images, |
227 | ::tensorflow::Input |
228 | transforms, |
229 | ::tensorflow::Input |
230 | output_shape, |
231 | ::tensorflow::Input |
232 | fill_value, StringPiece |
233 | interpolation) |
234 | : ImageProjectiveTransformV3(scope, images, transforms, output_shape, fill_value, interpolation, ImageProjectiveTransformV3::Attrs()) {} |
235 | |
236 | ResizeBicubicGrad::ResizeBicubicGrad(const ::tensorflow::Scope& scope, |
237 | ::tensorflow::Input grads, |
238 | ::tensorflow::Input original_image, const |
239 | ResizeBicubicGrad::Attrs& attrs) { |
240 | if (!scope.ok()) return; |
241 | auto _grads = ::tensorflow::ops::AsNodeOut(scope, grads); |
242 | if (!scope.ok()) return; |
243 | auto _original_image = ::tensorflow::ops::AsNodeOut(scope, original_image); |
244 | if (!scope.ok()) return; |
245 | ::tensorflow::Node* ret; |
246 | const auto unique_name = scope.GetUniqueNameForOp("ResizeBicubicGrad" ); |
247 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ResizeBicubicGrad" ) |
248 | .Input(_grads) |
249 | .Input(_original_image) |
250 | .Attr("align_corners" , attrs.align_corners_) |
251 | .Attr("half_pixel_centers" , attrs.half_pixel_centers_) |
252 | ; |
253 | scope.UpdateBuilder(&builder); |
254 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
255 | if (!scope.ok()) return; |
256 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
257 | this->operation = Operation(ret); |
258 | this->output = Output(ret, 0); |
259 | } |
260 | |
261 | ResizeBicubicGrad::ResizeBicubicGrad(const ::tensorflow::Scope& scope, |
262 | ::tensorflow::Input grads, |
263 | ::tensorflow::Input original_image) |
264 | : ResizeBicubicGrad(scope, grads, original_image, ResizeBicubicGrad::Attrs()) {} |
265 | |
266 | ResizeBilinearGrad::ResizeBilinearGrad(const ::tensorflow::Scope& scope, |
267 | ::tensorflow::Input grads, |
268 | ::tensorflow::Input original_image, |
269 | const ResizeBilinearGrad::Attrs& attrs) { |
270 | if (!scope.ok()) return; |
271 | auto _grads = ::tensorflow::ops::AsNodeOut(scope, grads); |
272 | if (!scope.ok()) return; |
273 | auto _original_image = ::tensorflow::ops::AsNodeOut(scope, original_image); |
274 | if (!scope.ok()) return; |
275 | ::tensorflow::Node* ret; |
276 | const auto unique_name = scope.GetUniqueNameForOp("ResizeBilinearGrad" ); |
277 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ResizeBilinearGrad" ) |
278 | .Input(_grads) |
279 | .Input(_original_image) |
280 | .Attr("align_corners" , attrs.align_corners_) |
281 | .Attr("half_pixel_centers" , attrs.half_pixel_centers_) |
282 | ; |
283 | scope.UpdateBuilder(&builder); |
284 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
285 | if (!scope.ok()) return; |
286 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
287 | this->operation = Operation(ret); |
288 | this->output = Output(ret, 0); |
289 | } |
290 | |
291 | ResizeBilinearGrad::ResizeBilinearGrad(const ::tensorflow::Scope& scope, |
292 | ::tensorflow::Input grads, |
293 | ::tensorflow::Input original_image) |
294 | : ResizeBilinearGrad(scope, grads, original_image, ResizeBilinearGrad::Attrs()) {} |
295 | |
296 | ResizeNearestNeighborGrad::ResizeNearestNeighborGrad(const ::tensorflow::Scope& |
297 | scope, ::tensorflow::Input |
298 | grads, ::tensorflow::Input |
299 | size, const |
300 | ResizeNearestNeighborGrad::Attrs& |
301 | attrs) { |
302 | if (!scope.ok()) return; |
303 | auto _grads = ::tensorflow::ops::AsNodeOut(scope, grads); |
304 | if (!scope.ok()) return; |
305 | auto _size = ::tensorflow::ops::AsNodeOut(scope, size); |
306 | if (!scope.ok()) return; |
307 | ::tensorflow::Node* ret; |
308 | const auto unique_name = scope.GetUniqueNameForOp("ResizeNearestNeighborGrad" ); |
309 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ResizeNearestNeighborGrad" ) |
310 | .Input(_grads) |
311 | .Input(_size) |
312 | .Attr("align_corners" , attrs.align_corners_) |
313 | .Attr("half_pixel_centers" , attrs.half_pixel_centers_) |
314 | ; |
315 | scope.UpdateBuilder(&builder); |
316 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
317 | if (!scope.ok()) return; |
318 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
319 | this->operation = Operation(ret); |
320 | this->output = Output(ret, 0); |
321 | } |
322 | |
323 | ResizeNearestNeighborGrad::ResizeNearestNeighborGrad(const ::tensorflow::Scope& |
324 | scope, ::tensorflow::Input |
325 | grads, ::tensorflow::Input |
326 | size) |
327 | : ResizeNearestNeighborGrad(scope, grads, size, ResizeNearestNeighborGrad::Attrs()) {} |
328 | |
329 | ScaleAndTranslateGrad::ScaleAndTranslateGrad(const ::tensorflow::Scope& scope, |
330 | ::tensorflow::Input grads, |
331 | ::tensorflow::Input |
332 | original_image, |
333 | ::tensorflow::Input scale, |
334 | ::tensorflow::Input translation, |
335 | const |
336 | ScaleAndTranslateGrad::Attrs& |
337 | attrs) { |
338 | if (!scope.ok()) return; |
339 | auto _grads = ::tensorflow::ops::AsNodeOut(scope, grads); |
340 | if (!scope.ok()) return; |
341 | auto _original_image = ::tensorflow::ops::AsNodeOut(scope, original_image); |
342 | if (!scope.ok()) return; |
343 | auto _scale = ::tensorflow::ops::AsNodeOut(scope, scale); |
344 | if (!scope.ok()) return; |
345 | auto _translation = ::tensorflow::ops::AsNodeOut(scope, translation); |
346 | if (!scope.ok()) return; |
347 | ::tensorflow::Node* ret; |
348 | const auto unique_name = scope.GetUniqueNameForOp("ScaleAndTranslateGrad" ); |
349 | auto builder = ::tensorflow::NodeBuilder(unique_name, "ScaleAndTranslateGrad" ) |
350 | .Input(_grads) |
351 | .Input(_original_image) |
352 | .Input(_scale) |
353 | .Input(_translation) |
354 | .Attr("kernel_type" , attrs.kernel_type_) |
355 | .Attr("antialias" , attrs.antialias_) |
356 | ; |
357 | scope.UpdateBuilder(&builder); |
358 | scope.UpdateStatus(builder.Finalize(scope.graph(), &ret)); |
359 | if (!scope.ok()) return; |
360 | scope.UpdateStatus(scope.DoShapeInference(ret)); |
361 | this->operation = Operation(ret); |
362 | this->output = Output(ret, 0); |
363 | } |
364 | |
365 | ScaleAndTranslateGrad::ScaleAndTranslateGrad(const ::tensorflow::Scope& scope, |
366 | ::tensorflow::Input grads, |
367 | ::tensorflow::Input |
368 | original_image, |
369 | ::tensorflow::Input scale, |
370 | ::tensorflow::Input translation) |
371 | : ScaleAndTranslateGrad(scope, grads, original_image, scale, translation, ScaleAndTranslateGrad::Attrs()) {} |
372 | |
373 | } // namespace internal |
374 | } // namespace ops |
375 | } // namespace tensorflow |
376 | |