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gerrit-public.fairphone.software / platform / external / ComputeLibrary / 06ea048f062a50404b1b3998a61a45449c2d1f0f / . / examples / graph_inception_v3.cpp
blob: b49bc473ec86368519f9e01d209bd50503f3d803 [file] [log] [blame]
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]1/*
2 * Copyright (c) 2017-2018 ARM Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#include "arm_compute/graph/Graph.h"
25#include "arm_compute/graph/Nodes.h"
26#include "arm_compute/graph/SubGraph.h"
27#include "support/ToolchainSupport.h"
28#include "utils/GraphUtils.h"
29#include "utils/Utils.h"
30
31#include <cstdlib>
32#include <tuple>
33
34using namespace arm_compute::utils;
35using namespace arm_compute::graph;
36using namespace arm_compute::graph_utils;
37
38/** Example demonstrating how to implement InceptionV3's network using the Compute Library's graph API
39 *
40 * @param[in] argc Number of arguments
41 * @param[in] argv Arguments ( [optional] Path to the weights folder, [optional] image, [optional] labels )
42 */
43class InceptionV3Example : public Example
44{
45public:
46 void do_setup(int argc, char **argv) override
47 {
48 std::string data_path; /* Path to the trainable data */
49 std::string image; /* Image data */
50 std::string label; /* Label data */
51
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]52 // Create a preprocessor object
53 std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]54
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]55 // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
56 const int int_target_hint = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
57 TargetHint target_hint = set_target_hint(int_target_hint);
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]58
59 // Parse arguments
60 if(argc < 2)
61 {
62 // Print help
63 std::cout << "Usage: " << argv[0] << " [target] [path_to_data] [image] [labels]\n\n";
64 std::cout << "No data folder provided: using random values\n\n";
65 }
66 else if(argc == 2)
67 {
68 std::cout << "Usage: " << argv[0] << " " << argv[1] << " [path_to_data] [image] [labels]\n\n";
69 std::cout << "No data folder provided: using random values\n\n";
70 }
71 else if(argc == 3)
72 {
73 data_path = argv[2];
74 std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " [image] [labels]\n\n";
75 std::cout << "No image provided: using random values\n\n";
76 }
77 else if(argc == 4)
78 {
79 data_path = argv[2];
80 image = argv[3];
81 std::cout << "Usage: " << argv[0] << " " << argv[1] << " " << argv[2] << " " << argv[3] << " [labels]\n\n";
82 std::cout << "No text file with labels provided: skipping output accessor\n\n";
83 }
84 else
85 {
86 data_path = argv[2];
87 image = argv[3];
88 label = argv[4];
89 }
90
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]91 graph << target_hint << Tensor(TensorInfo(TensorShape(299U, 299U, 3U, 1U), 1, DataType::F32),
92 get_input_accessor(image, std::move(preprocessor), false))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]93
94 << ConvolutionLayer(3U, 3U, 32U,
95 get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_weights.npy"),
96 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(2, 2, 0, 0))
97 << BatchNormalizationLayer(get_weights_accessor(data_path,
98 "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_moving_mean.npy"),
99 get_weights_accessor(data_path,
100 "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_moving_variance.npy"),
101 get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
102 "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]103 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]104
105 << ConvolutionLayer(3U, 3U, 32U,
106 get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_weights.npy"),
107 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0))
108 << BatchNormalizationLayer(get_weights_accessor(data_path,
109 "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_moving_mean.npy"),
110 get_weights_accessor(data_path,
111 "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_moving_variance.npy"),
112 get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
113 "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]114 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]115
116 << ConvolutionLayer(3U, 3U, 64U,
117 get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_weights.npy"),
118 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 1, 1))
119 << BatchNormalizationLayer(get_weights_accessor(data_path,
120 "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_moving_mean.npy"),
121 get_weights_accessor(data_path,
122 "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_moving_variance.npy"),
123 get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
124 "/cnn_data/inceptionv3_model/Conv2d_2b_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]125 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]126
127 << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
128
129 << ConvolutionLayer(1U, 1U, 80U,
130 get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_weights.npy"),
131 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0))
132 << BatchNormalizationLayer(get_weights_accessor(data_path,
133 "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_moving_mean.npy"),
134 get_weights_accessor(data_path,
135 "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_moving_variance.npy"),
136 get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
137 "/cnn_data/inceptionv3_model/Conv2d_3b_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]138 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]139
140 << ConvolutionLayer(3U, 3U, 192U,
141 get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_weights.npy"),
142 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0))
143 << BatchNormalizationLayer(get_weights_accessor(data_path,
144 "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_moving_mean.npy"),
145 get_weights_accessor(data_path,
146 "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_moving_variance.npy"),
147 get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
148 "/cnn_data/inceptionv3_model/Conv2d_4a_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]149 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]150
151 << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
152
153 << get_inception_node_A(data_path, "Mixed_5b", 64U, std::make_tuple(48U, 64U), std::make_tuple(64U, 96U, 96U),
154 32U)
155 << get_inception_node_A(data_path, "Mixed_5c", 64U, std::make_tuple(48U, 64U), std::make_tuple(64U, 96U, 96U),
156 64U, true)
157 << get_inception_node_A(data_path, "Mixed_5d", 64U, std::make_tuple(48U, 64U), std::make_tuple(64U, 96U, 96U),
158 64U)
159
160 << get_inception_node_B(data_path, "Mixed_6a", 384U, std::make_tuple(64U, 96U, 96U))
161
162 << get_inception_node_C(data_path, "Mixed_6b", 192U, std::make_tuple(128U, 128U, 192U),
163 std::make_tuple(128U, 128U, 128U, 128U, 192U), 192U)
164 << get_inception_node_C(data_path, "Mixed_6c", 192U, std::make_tuple(160U, 160U, 192U),
165 std::make_tuple(160U, 160U, 160U, 160U, 192U), 192U)
166 << get_inception_node_C(data_path, "Mixed_6d", 192U, std::make_tuple(160U, 160U, 192U),
167 std::make_tuple(160U, 160U, 160U, 160U, 192U), 192U)
168 << get_inception_node_C(data_path, "Mixed_6e", 192U, std::make_tuple(192U, 192U, 192U),
169 std::make_tuple(192U, 192U, 192U, 192U, 192U), 192U)
170
171 << get_inception_node_D(data_path, "Mixed_7a", std::make_tuple(192U, 320U),
172 std::make_tuple(192U, 192U, 192U, 192U))
173
174 << get_inception_node_E(data_path, "Mixed_7b", 320U, std::make_tuple(384U, 384U, 384U),
175 std::make_tuple(448U, 384U, 384U, 384U), 192U)
176 << get_inception_node_E(data_path, "Mixed_7c", 320U, std::make_tuple(384U, 384U, 384U),
177 std::make_tuple(448U, 384U, 384U, 384U), 192U, true)
178
179 << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, 8, PadStrideInfo(1, 1, 0, 0, DimensionRoundingType::CEIL)))
180 << ConvolutionLayer(1U, 1U, 1001U, get_weights_accessor(data_path,
181 "/cnn_data/inceptionv3_model/Logits_Conv2d_1c_1x1_weights.npy"),
182 get_weights_accessor(data_path,
183 "/cnn_data/inceptionv3_model/Logits_Conv2d_1c_1x1_biases.npy"),
184 PadStrideInfo(1, 1, 0, 0))
185 << ReshapeLayer(TensorShape(1001U)) << SoftmaxLayer()
186 << Tensor(get_output_accessor(label, 5));
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]187
188 // In order to enable the OpenCL tuner, graph_init() has to be called only when all nodes have been instantiated
189 graph.graph_init(int_target_hint == 2);
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]190 }
191
192 void do_run() override
193 {
194 graph.run();
195 }
196
197private:
198 Graph graph{};
199
200private:
201 BranchLayer get_inception_node_A(const std::string &data_path, std::string &&param_path,
202 unsigned int a_filt,
203 std::tuple<unsigned int, unsigned int> b_filters,
204 std::tuple<unsigned int, unsigned int, unsigned int> c_filters,
205 unsigned int d_filt,
206 bool is_name_different = false)
207 {
208 std::string total_path = "/cnn_data/inceptionv3_model/" + param_path + "_";
209 std::cout << total_path << std::endl;
210
211 // This is due to a naming issue in the tf model
212 std::string conv_id0 = "_0a_";
213 std::string conv_id1 = "2d_0b_";
214 if(is_name_different)
215 {
216 conv_id0 = "_0b_";
217 conv_id1 = "_1_0c_";
218 }
219
220 SubGraph i_a;
221 i_a << ConvolutionLayer(
222 1U, 1U, a_filt,
223 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_weights.npy"),
224 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
225 PadStrideInfo(1, 1, 0, 0))
226 << BatchNormalizationLayer(
227 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
228 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
229 get_random_accessor(1.f, 1.f),
230 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]231 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]232
233 SubGraph i_b;
234 i_b << ConvolutionLayer(
235 1U, 1U, std::get<0>(b_filters),
236 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_weights.npy"),
237 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
238 PadStrideInfo(1, 1, 0, 0))
239 << BatchNormalizationLayer(
240 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_moving_mean.npy"),
241 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_moving_variance.npy"),
242 get_random_accessor(1.f, 1.f),
243 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id0 + "1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]244 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]245 << ConvolutionLayer(
246 5U, 5U, std::get<1>(b_filters),
247 get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_weights.npy"),
248 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
249 PadStrideInfo(1, 1, 2, 2))
250 << BatchNormalizationLayer(
251 get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_moving_mean.npy"),
252 get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_moving_variance.npy"),
253 get_random_accessor(1.f, 1.f),
254 get_weights_accessor(data_path, total_path + "Branch_1_Conv" + conv_id1 + "5x5_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]255 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]256
257 SubGraph i_c;
258 i_c << ConvolutionLayer(
259 1U, 1U, std::get<0>(c_filters),
260 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_weights.npy"),
261 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
262 PadStrideInfo(1, 1, 0, 0))
263 << BatchNormalizationLayer(
264 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
265 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
266 get_random_accessor(1.f, 1.f),
267 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]268 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]269 << ConvolutionLayer(
270 3U, 3U, std::get<1>(c_filters),
271 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_weights.npy"),
272 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
273 PadStrideInfo(1, 1, 1, 1))
274 << BatchNormalizationLayer(
275 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"),
276 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"),
277 get_random_accessor(1.f, 1.f),
278 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]279 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]280 << ConvolutionLayer(
281 3U, 3U, std::get<2>(c_filters),
282 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_weights.npy"),
283 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
284 PadStrideInfo(1, 1, 1, 1))
285 << BatchNormalizationLayer(
286 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_moving_mean.npy"),
287 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_moving_variance.npy"),
288 get_random_accessor(1.f, 1.f),
289 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]290 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]291
292 SubGraph i_d;
293 i_d << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), true))
294 << ConvolutionLayer(
295 1U, 1U, d_filt,
296 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_weights.npy"),
297 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
298 PadStrideInfo(1, 1, 0, 0))
299 << BatchNormalizationLayer(
300 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"),
301 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"),
302 get_random_accessor(1.f, 1.f),
303 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]304 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]305
306 return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
307 }
308
309 BranchLayer get_inception_node_B(const std::string &data_path, std::string &&param_path,
310 unsigned int a_filt,
311 std::tuple<unsigned int, unsigned int, unsigned int> b_filters)
312 {
313 std::string total_path = "/cnn_data/inceptionv3_model/" + param_path + "_";
314 SubGraph i_a;
315 i_a << ConvolutionLayer(
316 3U, 3U, a_filt,
317 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_weights.npy"),
318 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
319 PadStrideInfo(2, 2, 0, 0))
320 << BatchNormalizationLayer(
321 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_moving_mean.npy"),
322 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_moving_variance.npy"),
323 get_random_accessor(1.f, 1.f),
324 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]325 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]326
327 SubGraph i_b;
328 i_b << ConvolutionLayer(
329 1U, 1U, std::get<0>(b_filters),
330 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_weights.npy"),
331 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
332 PadStrideInfo(1, 1, 0, 0))
333 << BatchNormalizationLayer(
334 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
335 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
336 get_random_accessor(1.f, 1.f),
337 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]338 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]339 << ConvolutionLayer(
340 3U, 3U, std::get<1>(b_filters),
341 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_weights.npy"),
342 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
343 PadStrideInfo(1, 1, 1, 1))
344 << BatchNormalizationLayer(
345 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"),
346 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"),
347 get_random_accessor(1.f, 1.f),
348 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]349 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]350 << ConvolutionLayer(
351 3U, 3U, std::get<2>(b_filters),
352 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_weights.npy"),
353 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
354 PadStrideInfo(2, 2, 0, 0))
355 << BatchNormalizationLayer(
356 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_moving_mean.npy"),
357 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_moving_variance.npy"),
358 get_random_accessor(1.f, 1.f),
359 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]360 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]361
362 SubGraph i_c;
363 i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]364 << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR, 1.f, 0.f));
365
366 return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c));
367 }
368
369 BranchLayer get_inception_node_C(const std::string &data_path, std::string &&param_path,
370 unsigned int a_filt,
371 std::tuple<unsigned int, unsigned int, unsigned int> b_filters,
372 std::tuple<unsigned int, unsigned int, unsigned int, unsigned int, unsigned int> c_filters,
373 unsigned int d_filt)
374 {
375 std::string total_path = "/cnn_data/inceptionv3_model/" + param_path + "_";
376 SubGraph i_a;
377 i_a << ConvolutionLayer(
378 1U, 1U, a_filt,
379 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_weights.npy"),
380 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
381 PadStrideInfo(1, 1, 0, 0))
382 << BatchNormalizationLayer(
383 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
384 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
385 get_random_accessor(1.f, 1.f),
386 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]387 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]388
389 SubGraph i_b;
390 i_b << ConvolutionLayer(
391 1U, 1U, std::get<0>(b_filters),
392 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_weights.npy"),
393 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
394 PadStrideInfo(1, 1, 0, 0))
395 << BatchNormalizationLayer(
396 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
397 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
398 get_random_accessor(1.f, 1.f),
399 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]400 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]401 << ConvolutionLayer(
402 7U, 1U, std::get<1>(b_filters),
403 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_weights.npy"),
404 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
405 PadStrideInfo(1, 1, 3, 0))
406 << BatchNormalizationLayer(
407 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_mean.npy"),
408 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_variance.npy"),
409 get_random_accessor(1.f, 1.f),
410 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]411 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]412 << ConvolutionLayer(
413 1U, 7U, std::get<2>(b_filters),
414 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_weights.npy"),
415 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
416 PadStrideInfo(1, 1, 0, 3))
417 << BatchNormalizationLayer(
418 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_mean.npy"),
419 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_variance.npy"),
420 get_random_accessor(1.f, 1.f),
421 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]422 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]423
424 SubGraph i_c;
425 i_c << ConvolutionLayer(
426 1U, 1U, std::get<0>(c_filters),
427 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_weights.npy"),
428 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
429 PadStrideInfo(1, 1, 0, 0))
430 << BatchNormalizationLayer(
431 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
432 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
433 get_random_accessor(1.f, 1.f),
434 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]435 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]436 << ConvolutionLayer(
437 1U, 7U, std::get<1>(c_filters),
438 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_weights.npy"),
439 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
440 PadStrideInfo(1, 1, 0, 3))
441 << BatchNormalizationLayer(
442 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_moving_mean.npy"),
443 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_moving_variance.npy"),
444 get_random_accessor(1.f, 1.f),
445 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_7x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]446 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]447 << ConvolutionLayer(
448 7U, 1U, std::get<2>(c_filters),
449 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_weights.npy"),
450 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
451 PadStrideInfo(1, 1, 3, 0))
452 << BatchNormalizationLayer(
453 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_moving_mean.npy"),
454 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_moving_variance.npy"),
455 get_random_accessor(1.f, 1.f),
456 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x7_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]457 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]458 << ConvolutionLayer(
459 1U, 7U, std::get<3>(c_filters),
460 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_weights.npy"),
461 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
462 PadStrideInfo(1, 1, 0, 3))
463 << BatchNormalizationLayer(
464 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_moving_mean.npy"),
465 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_moving_variance.npy"),
466 get_random_accessor(1.f, 1.f),
467 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_7x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]468 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]469 << ConvolutionLayer(
470 7U, 1U, std::get<4>(c_filters),
471 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_weights.npy"),
472 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
473 PadStrideInfo(1, 1, 3, 0))
474 << BatchNormalizationLayer(
475 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_moving_mean.npy"),
476 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_moving_variance.npy"),
477 get_random_accessor(1.f, 1.f),
478 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0e_1x7_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]479 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]480
481 SubGraph i_d;
482 i_d << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), true))
483 << ConvolutionLayer(
484 1U, 1U, d_filt,
485 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_weights.npy"),
486 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
487 PadStrideInfo(1, 1, 0, 0))
488 << BatchNormalizationLayer(
489 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"),
490 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"),
491 get_random_accessor(1.f, 1.f),
492 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]493 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]494
495 return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
496 }
497
498 BranchLayer get_inception_node_D(const std::string &data_path, std::string &&param_path,
499 std::tuple<unsigned int, unsigned int> a_filters,
500 std::tuple<unsigned int, unsigned int, unsigned int, unsigned int> b_filters)
501 {
502 std::string total_path = "/cnn_data/inceptionv3_model/" + param_path + "_";
503 SubGraph i_a;
504 i_a << ConvolutionLayer(
505 1U, 1U, std::get<0>(a_filters),
506 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_weights.npy"),
507 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
508 PadStrideInfo(1, 1, 0, 0))
509 << BatchNormalizationLayer(
510 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
511 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
512 get_random_accessor(1.f, 1.f),
513 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]514 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]515 << ConvolutionLayer(
516 3U, 3U, std::get<1>(a_filters),
517 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_weights.npy"),
518 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
519 PadStrideInfo(2, 2, 0, 0))
520 << BatchNormalizationLayer(
521 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_moving_mean.npy"),
522 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_moving_variance.npy"),
523 get_random_accessor(1.f, 1.f),
524 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_1a_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]525 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]526
527 SubGraph i_b;
528 i_b << ConvolutionLayer(
529 1U, 1U, std::get<0>(b_filters),
530 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_weights.npy"),
531 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
532 PadStrideInfo(1, 1, 0, 0))
533 << BatchNormalizationLayer(
534 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
535 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
536 get_random_accessor(1.f, 1.f),
537 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]538 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]539 << ConvolutionLayer(
540 7U, 1U, std::get<1>(b_filters),
541 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_weights.npy"),
542 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
543 PadStrideInfo(1, 1, 3, 0))
544 << BatchNormalizationLayer(
545 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_mean.npy"),
546 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_moving_variance.npy"),
547 get_random_accessor(1.f, 1.f),
548 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x7_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]549 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]550 << ConvolutionLayer(
551 1U, 7U, std::get<2>(b_filters),
552 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_weights.npy"),
553 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
554 PadStrideInfo(1, 1, 0, 3))
555 << BatchNormalizationLayer(
556 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_mean.npy"),
557 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_moving_variance.npy"),
558 get_random_accessor(1.f, 1.f),
559 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0c_7x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]560 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]561 << ConvolutionLayer(
562 3U, 3U, std::get<3>(b_filters),
563 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_weights.npy"),
564 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
565 PadStrideInfo(2, 2, 0, 0))
566 << BatchNormalizationLayer(
567 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_moving_mean.npy"),
568 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_moving_variance.npy"),
569 get_random_accessor(1.f, 1.f),
570 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_1a_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]571 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]572
573 SubGraph i_c;
574 i_c << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]575 << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR, 1.f, 0.f));
576
577 return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c));
578 }
579
580 BranchLayer get_inception_node_E(const std::string &data_path, std::string &&param_path,
581 unsigned int a_filt,
582 std::tuple<unsigned int, unsigned int, unsigned int> b_filters,
583 std::tuple<unsigned int, unsigned int, unsigned int, unsigned int> c_filters,
584 unsigned int d_filt,
585 bool is_name_different = false)
586 {
587 // This is due to a naming issue in the tf model
588 std::string conv_id = "_0b_";
589 if(is_name_different)
590 {
591 conv_id = "_0c_";
592 }
593
594 std::string total_path = "/cnn_data/inceptionv3_model/" + param_path + "_";
595 SubGraph i_a;
596 i_a << ConvolutionLayer(
597 1U, 1U, a_filt,
598 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_weights.npy"),
599 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
600 PadStrideInfo(1, 1, 0, 0))
601 << BatchNormalizationLayer(
602 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
603 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
604 get_random_accessor(1.f, 1.f),
605 get_weights_accessor(data_path, total_path + "Branch_0_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]606 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]607
608 SubGraph i_b1;
609 i_b1 << ConvolutionLayer(
610 3U, 1U, std::get<1>(b_filters),
611 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_weights.npy"),
612 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
613 PadStrideInfo(1, 1, 1, 0))
614 << BatchNormalizationLayer(
615 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_moving_mean.npy"),
616 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_moving_variance.npy"),
617 get_random_accessor(1.f, 1.f),
618 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0b_1x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]619 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]620
621 SubGraph i_b2;
622 i_b2 << ConvolutionLayer(
623 1U, 3U, std::get<2>(b_filters),
624 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_weights.npy"),
625 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
626 PadStrideInfo(1, 1, 0, 1))
627 << BatchNormalizationLayer(
628 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_moving_mean.npy"),
629 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_moving_variance.npy"),
630 get_random_accessor(1.f, 1.f),
631 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d" + conv_id + "3x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]632 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]633
634 SubGraph i_b;
635 i_b << ConvolutionLayer(
636 1U, 1U, std::get<0>(b_filters),
637 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_weights.npy"),
638 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
639 PadStrideInfo(1, 1, 0, 0))
640 << BatchNormalizationLayer(
641 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
642 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
643 get_random_accessor(1.f, 1.f),
644 get_weights_accessor(data_path, total_path + "Branch_1_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]645 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]646 << BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_b1), std::move(i_b2));
647
648 SubGraph i_c1;
649 i_c1 << ConvolutionLayer(
650 3U, 1U, std::get<2>(c_filters),
651 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_weights.npy"),
652 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
653 PadStrideInfo(1, 1, 1, 0))
654 << BatchNormalizationLayer(
655 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_moving_mean.npy"),
656 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_moving_variance.npy"),
657 get_random_accessor(1.f, 1.f),
658 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0c_1x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]659 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]660
661 SubGraph i_c2;
662 i_c2 << ConvolutionLayer(
663 1U, 3U, std::get<3>(c_filters),
664 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_weights.npy"),
665 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
666 PadStrideInfo(1, 1, 0, 1))
667 << BatchNormalizationLayer(
668 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_moving_mean.npy"),
669 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_moving_variance.npy"),
670 get_random_accessor(1.f, 1.f),
671 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0d_3x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]672 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]673
674 SubGraph i_c;
675 i_c << ConvolutionLayer(
676 1U, 1U, std::get<0>(c_filters),
677 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_weights.npy"),
678 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
679 PadStrideInfo(1, 1, 0, 0))
680 << BatchNormalizationLayer(
681 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_mean.npy"),
682 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_moving_variance.npy"),
683 get_random_accessor(1.f, 1.f),
684 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0a_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]685 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]686 << ConvolutionLayer(
687 3U, 3U, std::get<1>(c_filters),
688 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_weights.npy"),
689 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
690 PadStrideInfo(1, 1, 1, 1))
691 << BatchNormalizationLayer(
692 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_mean.npy"),
693 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_moving_variance.npy"),
694 get_random_accessor(1.f, 1.f),
695 get_weights_accessor(data_path, total_path + "Branch_2_Conv2d_0b_3x3_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]696 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]697 << BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_c1), std::move(i_c2));
698
699 SubGraph i_d;
700 i_d << PoolingLayer(PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), true))
701 << ConvolutionLayer(
702 1U, 1U, d_filt,
703 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_weights.npy"),
704 std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr),
705 PadStrideInfo(1, 1, 0, 0))
706 << BatchNormalizationLayer(
707 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_mean.npy"),
708 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_moving_variance.npy"),
709 get_random_accessor(1.f, 1.f),
710 get_weights_accessor(data_path, total_path + "Branch_3_Conv2d_0b_1x1_BatchNorm_beta.npy"),
Anthony Barbier06ea0482018-02-22 15:45:35 +0000[diff] [blame^]711 0.001f, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU));
Anthony Barbierf45d5a92018-01-24 16:23:15 +0000[diff] [blame]712
713 return BranchLayer(BranchMergeMethod::DEPTH_CONCATENATE, std::move(i_a), std::move(i_b), std::move(i_c), std::move(i_d));
714 }
715};
716
717/** Main program for Inception V3
718 *
719 * @param[in] argc Number of arguments
720 * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL), [optional] Path to the weights folder, [optional] image, [optional] labels )
721 */
722int main(int argc, char **argv)
723{
724 return arm_compute::utils::run_example<InceptionV3Example>(argc, argv);
725}