inference-engine/tests/unit/cnn_network/cnn_net_reader_impl_test.cpp

   1 // Copyright (C) 2018-2019 Intel Corporation
   2 // SPDX-License-Identifier: Apache-2.0
   3 //
   4
   5 #include <gtest/gtest.h>
   6 #include <inference_engine/parsers.h>
   7 #include <inference_engine/ie_cnn_net_reader_impl.h>
   8 #include <test_model_path.hpp>
   9 #include <mock_icnn_network.hpp>
  10 #include <gmock/gmock-more-actions.h>
  11 #include "cnn_network_impl.hpp"
  12 #include "mock_iformat_parser.hpp"
  13 #include <test_assertions.hpp>
  14 #include <single_layer_common.hpp>
  15
  16 using namespace testing;
  17 using namespace InferenceEngine;
  18 using namespace InferenceEngine::details;
  19 using namespace std;
  20
  21 class CNNNetReaderImplTest : public ::testing::Test {
  22 public:
  23     StatusCode sts = OK;
  24     ResponseDesc resp;
  25 };
  26
  27 struct MockFormatParserCreator : public FormatParserCreator {
  28     MockFormatParserCreator() {
  29         _parser = make_shared<MockIFormatParser>();
  30     }
  31
  32     std::shared_ptr<IFormatParser> create(int version) override {
  33         return _parser;
  34     }
  35
  36     MockIFormatParser* getParser() {
  37         return _parser.get();
  38     }
  39
  40 private:
  41     std::shared_ptr<MockIFormatParser> _parser;
  42 };
  43
  44 TEST_F(CNNNetReaderImplTest, validateIsCalled) {
  45     std::string model =
  46             "<net name=\"PVANET\" version=\"2\" batch=\"1\">"
  47             "    <layers>"
  48             "        <layer name=\"data\" type=\"Input\" precision=\"FP32\" id=\"0\">"
  49             "            <output>"
  50             "                <port id=\"0\">"
  51             "                    <dim>1</dim>"
  52             "                    <dim>3</dim>"
  53             "                    <dim>544</dim>"
  54             "                    <dim>992</dim>"
  55             "                </port>"
  56             "            </output>"
  57             "        </layer>"
  58             "        <layer name=\"conv1_1_conv\" type=\"Convolution\" precision=\"FP32\" id=\"2\">"
  59             "            <convolution_data stride-x=\"2\" stride-y=\"2\" pad-x=\"3\" pad-y=\"3\" kernel-x=\"7\" kernel-y=\"7\" output=\"16\" group=\"1\"/>"
  60             "            <input>"
  61             "                <port id=\"2\">"
  62             "                    <dim>1</dim>"
  63             "                    <dim>3</dim>"
  64             "                    <dim>544</dim>"
  65             "                    <dim>992</dim>"
  66             "                </port>"
  67             "            </input>"
  68             "            <output>"
  69             "                <port id=\"3\">"
  70             "                    <dim>1</dim>"
  71             "                    <dim>16</dim>"
  72             "                    <dim>272</dim>"
  73             "                    <dim>496</dim>"
  74             "                </port>"
  75             "            </output>"
  76             "            <weights offset=\"0\" size=\"9408\"/>"
  77             "            <biases offset=\"9408\" size=\"64\"/>"
  78             "        </layer>"
  79             "        <layer name=\"conv1_1_neg\" type=\"Power\" precision=\"FP32\" id=\"3\">"
  80             "            <power_data power=\"1\" scale=\"-1\" shift=\"0\"/>"
  81             "            <input>"
  82             "                <port id=\"4\">"
  83             "                    <dim>1</dim>"
  84             "                    <dim>16</dim>"
  85             "                    <dim>272</dim>"
  86             "                    <dim>496</dim>"
  87             "                </port>"
  88             "            </input>"
  89             "            <output>"
  90             "                <port id=\"5\">"
  91             "                    <dim>1</dim>"
  92             "                    <dim>16</dim>"
  93             "                    <dim>272</dim>"
  94             "                    <dim>496</dim>"
  95             "                </port>"
  96             "            </output>"
  97             "        </layer>"
  98             "        <layer name=\"conv1_1_concat\" type=\"Concat\" precision=\"FP32\" id=\"4\">"
  99             "            <concat_data axis=\"1\"/>"
 100             "            <input>"
 101             "                <port id=\"6\">"
 102             "                    <dim>1</dim>"
 103             "                    <dim>16</dim>"
 104             "                    <dim>272</dim>"
 105             "                    <dim>496</dim>"
 106             "                </port>"
 107             "                <port id=\"7\">"
 108             "                    <dim>1</dim>"
 109             "                    <dim>16</dim>"
 110             "                    <dim>272</dim>"
 111             "                    <dim>496</dim>"
 112             "                </port>"
 113             "            </input>"
 114             "            <output>"
 115             "                <port id=\"8\">"
 116             "                    <dim>1</dim>"
 117             "                    <dim>32</dim>"
 118             "                    <dim>272</dim>"
 119             "                    <dim>496</dim>"
 120             "                </port>"
 121             "            </output>"
 122             "        </layer>"
 123             "        <layer name=\"conv1_1_scale\" type=\"ScaleShift\" precision=\"FP32\" id=\"5\">"
 124             "            <input>"
 125             "                <port id=\"9\">"
 126             "                    <dim>1</dim>"
 127             "                    <dim>32</dim>"
 128             "                    <dim>272</dim>"
 129             "                    <dim>496</dim>"
 130             "                </port>"
 131             "            </input>"
 132             "            <output>"
 133             "                <port id=\"10\">"
 134             "                    <dim>1</dim>"
 135             "                    <dim>32</dim>"
 136             "                    <dim>272</dim>"
 137             "                    <dim>496</dim>"
 138             "                </port>"
 139             "            </output>"
 140             "            <weights offset=\"9472\" size=\"128\"/>"
 141             "            <biases offset=\"9600\" size=\"128\"/>"
 142             "        </layer>"
 143             "        <layer name=\"conv1_1_relu\" type=\"ReLU\" precision=\"FP32\" id=\"6\">"
 144             "            <data negative_slope=\"0\" engine=\"caffe.ReLUParameter.DEFAULT\"/>"
 145             "            <input>"
 146             "                <port id=\"11\">"
 147             "                    <dim>1</dim>"
 148             "                    <dim>32</dim>"
 149             "                    <dim>272</dim>"
 150             "                    <dim>496</dim>"
 151             "                </port>"
 152             "            </input>"
 153             "            <output>"
 154             "                <port id=\"12\">"
 155             "                    <dim>1</dim>"
 156             "                    <dim>32</dim>"
 157             "                    <dim>272</dim>"
 158             "                    <dim>496</dim>"
 159             "                </port>"
 160             "            </output>"
 161             "        </layer>"
 162             "        <layer name=\"pool1\" type=\"Pooling\" precision=\"FP32\" id=\"7\">"
 163             "            <pooling_data kernel-x=\"3\" kernel-y=\"3\" pad-x=\"0\" pad-y=\"0\" stride-x=\"2\" stride-y=\"2\" rounding-type=\"ceil\" pool-method=\"max\"/>"
 164             "            <input>"
 165             "                <port id=\"13\">"
 166             "                    <dim>1</dim>"
 167             "                    <dim>32</dim>"
 168             "                    <dim>272</dim>"
 169             "                    <dim>496</dim>"
 170             "                </port>"
 171             "            </input>"
 172             "            <output>"
 173             "                <port id=\"14\">"
 174             "                    <dim>1</dim>"
 175             "                    <dim>32</dim>"
 176             "                    <dim>136</dim>"
 177             "                    <dim>248</dim>"
 178             "                </port>"
 179             "            </output>"
 180             "        </layer>"
 181             "    </layers>"
 182             "    <edges>"
 183             "        <edge from-layer=\"0\" from-port=\"0\" to-layer=\"2\" to-port=\"2\"/>"
 184             "        <edge from-layer=\"2\" from-port=\"3\" to-layer=\"3\" to-port=\"4\"/>"
 185             "        <edge from-layer=\"2\" from-port=\"3\" to-layer=\"4\" to-port=\"6\"/>"
 186             "        <edge from-layer=\"3\" from-port=\"5\" to-layer=\"4\" to-port=\"7\"/>"
 187             "        <edge from-layer=\"4\" from-port=\"8\" to-layer=\"5\" to-port=\"9\"/>"
 188             "        <edge from-layer=\"5\" from-port=\"10\" to-layer=\"6\" to-port=\"11\"/>"
 189             "        <edge from-layer=\"6\" from-port=\"12\" to-layer=\"7\" to-port=\"13\"/>"
 190             "    </edges>"
 191             "</net>";
 192     auto parserCreator = make_shared<MockFormatParserCreator>();
 193     CNNNetReaderImpl reader(parserCreator);
 194     auto network = make_shared<MockCNNNetworkImpl>();
 195     auto name = std::string{"AlexNet"};
 196
 197     EXPECT_CALL(*parserCreator->getParser(), Parse(_)).Times(1).WillOnce(Return(network));
 198     EXPECT_CALL(*network.get(), validate(_)).Times(1);
 199     EXPECT_CALL(*network.get(), getName()).Times(1).WillOnce(ReturnRef(name));
 200
 201     ASSERT_NO_THROW(sts = reader.ReadNetwork(model.data(), model.length(), &resp));
 202     ASSERT_EQ(OK, sts);
 203 }
 204
 205 TEST_F(CNNNetReaderImplTest, cycleIsDetectedInReader) {
 206     std::string model =
 207             "<net batch=\"1\" name=\"model\" version=\"2\">"
 208             "    <layers>"
 209             "        <layer id=\"0\" name=\"data\" precision=\"FP32\" type=\"Input\">"
 210             "            <output>"
 211             "                <port id=\"0\">"
 212             "                    <dim>1</dim>"
 213             "                    <dim>3</dim>"
 214             "                    <dim>227</dim>"
 215             "                    <dim>227</dim>"
 216             "                </port>"
 217             "            </output>"
 218             "        </layer>"
 219             "        <layer id=\"1\" name=\"conv1\" precision=\"FP32\" type=\"Convolution\">"
 220             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"64\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,2,2\" stride-x=\"2\" stride-y=\"2\"/>"
 221             "            <input>"
 222             "                <port id=\"0\">"
 223             "                    <dim>1</dim>"
 224             "                    <dim>3</dim>"
 225             "                    <dim>227</dim>"
 226             "                    <dim>227</dim>"
 227             "                </port>"
 228             "            </input>"
 229             "            <output>"
 230             "                <port id=\"3\">"
 231             "                    <dim>1</dim>"
 232             "                    <dim>64</dim>"
 233             "                    <dim>113</dim>"
 234             "                    <dim>113</dim>"
 235             "                </port>"
 236             "            </output>"
 237             "            <blobs>"
 238             "                <weights offset=\"0\" size=\"6912\"/>"
 239             "                <biases offset=\"6912\" size=\"256\"/>"
 240             "            </blobs>"
 241             "        </layer>"
 242             "        <layer id=\"2\" name=\"relu_conv1\" precision=\"FP32\" type=\"ReLU\">"
 243             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 244             "            <input>"
 245             "                <port id=\"0\">"
 246             "                    <dim>1</dim>"
 247             "                    <dim>64</dim>"
 248             "                    <dim>113</dim>"
 249             "                    <dim>113</dim>"
 250             "                </port>"
 251             "            </input>"
 252             "            <output>"
 253             "                <port id=\"1\">"
 254             "                    <dim>1</dim>"
 255             "                    <dim>64</dim>"
 256             "                    <dim>113</dim>"
 257             "                    <dim>113</dim>"
 258             "                </port>"
 259             "            </output>"
 260             "        </layer>"
 261             "        <layer id=\"3\" name=\"pool1\" precision=\"FP32\" type=\"Pooling\">"
 262             "            <data exclude-pad=\"false\" kernel-x=\"3\" kernel-y=\"3\" pad-x=\"0\" pad-y=\"0\" pool-method=\"max\" rounding_type=\"ceil\" stride=\"1,1,2,2\" stride-x=\"2\" stride-y=\"2\"/>"
 263             "            <input>"
 264             "                <port id=\"0\">"
 265             "                    <dim>1</dim>"
 266             "                    <dim>64</dim>"
 267             "                    <dim>113</dim>"
 268             "                    <dim>113</dim>"
 269             "                </port>"
 270             "            </input>"
 271             "            <output>"
 272             "                <port id=\"1\">"
 273             "                    <dim>1</dim>"
 274             "                    <dim>64</dim>"
 275             "                    <dim>56</dim>"
 276             "                    <dim>56</dim>"
 277             "                </port>"
 278             "            </output>"
 279             "        </layer>"
 280             "        <layer id=\"4\" name=\"fire2/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
 281             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"16\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 282             "            <input>"
 283             "                <port id=\"0\">"
 284             "                    <dim>1</dim>"
 285             "                    <dim>64</dim>"
 286             "                    <dim>56</dim>"
 287             "                    <dim>56</dim>"
 288             "                </port>"
 289             "            </input>"
 290             "            <output>"
 291             "                <port id=\"3\">"
 292             "                    <dim>1</dim>"
 293             "                    <dim>16</dim>"
 294             "                    <dim>56</dim>"
 295             "                    <dim>56</dim>"
 296             "                </port>"
 297             "            </output>"
 298             "            <blobs>"
 299             "                <weights offset=\"7168\" size=\"4096\"/>"
 300             "                <biases offset=\"11264\" size=\"64\"/>"
 301             "            </blobs>"
 302             "        </layer>"
 303             "        <layer id=\"5\" name=\"fire2/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
 304             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 305             "            <input>"
 306             "                <port id=\"0\">"
 307             "                    <dim>1</dim>"
 308             "                    <dim>16</dim>"
 309             "                    <dim>56</dim>"
 310             "                    <dim>56</dim>"
 311             "                </port>"
 312             "            </input>"
 313             "            <output>"
 314             "                <port id=\"1\">"
 315             "                    <dim>1</dim>"
 316             "                    <dim>16</dim>"
 317             "                    <dim>56</dim>"
 318             "                    <dim>56</dim>"
 319             "                </port>"
 320             "            </output>"
 321             "        </layer>"
 322             "        <layer id=\"6\" name=\"fire2/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
 323             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"64\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 324             "            <input>"
 325             "                <port id=\"0\">"
 326             "                    <dim>1</dim>"
 327             "                    <dim>16</dim>"
 328             "                    <dim>56</dim>"
 329             "                    <dim>56</dim>"
 330             "                </port>"
 331             "            </input>"
 332             "            <output>"
 333             "                <port id=\"3\">"
 334             "                    <dim>1</dim>"
 335             "                    <dim>64</dim>"
 336             "                    <dim>56</dim>"
 337             "                    <dim>56</dim>"
 338             "                </port>"
 339             "            </output>"
 340             "            <blobs>"
 341             "                <weights offset=\"11328\" size=\"4096\"/>"
 342             "                <biases offset=\"15424\" size=\"256\"/>"
 343             "            </blobs>"
 344             "        </layer>"
 345             "        <layer id=\"7\" name=\"fire2/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
 346             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 347             "            <input>"
 348             "                <port id=\"0\">"
 349             "                    <dim>1</dim>"
 350             "                    <dim>64</dim>"
 351             "                    <dim>56</dim>"
 352             "                    <dim>56</dim>"
 353             "                </port>"
 354             "            </input>"
 355             "            <output>"
 356             "                <port id=\"1\">"
 357             "                    <dim>1</dim>"
 358             "                    <dim>64</dim>"
 359             "                    <dim>56</dim>"
 360             "                    <dim>56</dim>"
 361             "                </port>"
 362             "            </output>"
 363             "        </layer>"
 364             "        <layer id=\"8\" name=\"fire2/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
 365             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"64\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 366             "            <input>"
 367             "                <port id=\"0\">"
 368             "                    <dim>1</dim>"
 369             "                    <dim>16</dim>"
 370             "                    <dim>56</dim>"
 371             "                    <dim>56</dim>"
 372             "                </port>"
 373             "                <port id=\"1\">"
 374             "                    <dim>1</dim>"
 375             "                    <dim>16</dim>"
 376             "                    <dim>56</dim>"
 377             "                    <dim>56</dim>"
 378             "                </port>"
 379             "            </input>"
 380             "            <output>"
 381             "                <port id=\"3\">"
 382             "                    <dim>1</dim>"
 383             "                    <dim>64</dim>"
 384             "                    <dim>56</dim>"
 385             "                    <dim>56</dim>"
 386             "                </port>"
 387             "            </output>"
 388             "            <blobs>"
 389             "                <weights offset=\"15680\" size=\"36864\"/>"
 390             "                <biases offset=\"52544\" size=\"256\"/>"
 391             "            </blobs>"
 392             "        </layer>"
 393             "        <layer id=\"9\" name=\"fire2/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
 394             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 395             "            <input>"
 396             "                <port id=\"0\">"
 397             "                    <dim>1</dim>"
 398             "                    <dim>64</dim>"
 399             "                    <dim>56</dim>"
 400             "                    <dim>56</dim>"
 401             "                </port>"
 402             "            </input>"
 403             "            <output>"
 404             "                <port id=\"1\">"
 405             "                    <dim>1</dim>"
 406             "                    <dim>64</dim>"
 407             "                    <dim>56</dim>"
 408             "                    <dim>56</dim>"
 409             "                </port>"
 410             "            </output>"
 411             "        </layer>"
 412             "        <layer id=\"10\" name=\"fire2/concat\" precision=\"FP32\" type=\"Concat\">"
 413             "            <data axis=\"1\"/>"
 414             "            <input>"
 415             "                <port id=\"0\">"
 416             "                    <dim>1</dim>"
 417             "                    <dim>64</dim>"
 418             "                    <dim>56</dim>"
 419             "                    <dim>56</dim>"
 420             "                </port>"
 421             "                <port id=\"1\">"
 422             "                    <dim>1</dim>"
 423             "                    <dim>64</dim>"
 424             "                    <dim>56</dim>"
 425             "                    <dim>56</dim>"
 426             "                </port>"
 427             "            </input>"
 428             "            <output>"
 429             "                <port id=\"2\">"
 430             "                    <dim>1</dim>"
 431             "                    <dim>128</dim>"
 432             "                    <dim>56</dim>"
 433             "                    <dim>56</dim>"
 434             "                </port>"
 435             "            </output>"
 436             "        </layer>"
 437             "        <layer id=\"11\" name=\"fire3/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
 438             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"16\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 439             "            <input>"
 440             "                <port id=\"0\">"
 441             "                    <dim>1</dim>"
 442             "                    <dim>128</dim>"
 443             "                    <dim>56</dim>"
 444             "                    <dim>56</dim>"
 445             "                </port>"
 446             "            </input>"
 447             "            <output>"
 448             "                <port id=\"3\">"
 449             "                    <dim>1</dim>"
 450             "                    <dim>16</dim>"
 451             "                    <dim>56</dim>"
 452             "                    <dim>56</dim>"
 453             "                </port>"
 454             "                <port id=\"4\">"
 455             "                    <dim>1</dim>"
 456             "                    <dim>16</dim>"
 457             "                    <dim>56</dim>"
 458             "                    <dim>56</dim>"
 459             "                </port>"
 460             "            </output>"
 461             "            <blobs>"
 462             "                <weights offset=\"52800\" size=\"8192\"/>"
 463             "                <biases offset=\"60992\" size=\"64\"/>"
 464             "            </blobs>"
 465             "        </layer>"
 466             "        <layer id=\"12\" name=\"fire3/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
 467             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 468             "            <input>"
 469             "                <port id=\"0\">"
 470             "                    <dim>1</dim>"
 471             "                    <dim>16</dim>"
 472             "                    <dim>56</dim>"
 473             "                    <dim>56</dim>"
 474             "                </port>"
 475             "            </input>"
 476             "            <output>"
 477             "                <port id=\"1\">"
 478             "                    <dim>1</dim>"
 479             "                    <dim>16</dim>"
 480             "                    <dim>56</dim>"
 481             "                    <dim>56</dim>"
 482             "                </port>"
 483             "            </output>"
 484             "        </layer>"
 485             "        <layer id=\"13\" name=\"fire3/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
 486             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"64\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 487             "            <input>"
 488             "                <port id=\"0\">"
 489             "                    <dim>1</dim>"
 490             "                    <dim>16</dim>"
 491             "                    <dim>56</dim>"
 492             "                    <dim>56</dim>"
 493             "                </port>"
 494             "            </input>"
 495             "            <output>"
 496             "                <port id=\"3\">"
 497             "                    <dim>1</dim>"
 498             "                    <dim>64</dim>"
 499             "                    <dim>56</dim>"
 500             "                    <dim>56</dim>"
 501             "                </port>"
 502             "            </output>"
 503             "            <blobs>"
 504             "                <weights offset=\"61056\" size=\"4096\"/>"
 505             "                <biases offset=\"65152\" size=\"256\"/>"
 506             "            </blobs>"
 507             "        </layer>"
 508             "        <layer id=\"14\" name=\"fire3/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
 509             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 510             "            <input>"
 511             "                <port id=\"0\">"
 512             "                    <dim>1</dim>"
 513             "                    <dim>64</dim>"
 514             "                    <dim>56</dim>"
 515             "                    <dim>56</dim>"
 516             "                </port>"
 517             "            </input>"
 518             "            <output>"
 519             "                <port id=\"1\">"
 520             "                    <dim>1</dim>"
 521             "                    <dim>64</dim>"
 522             "                    <dim>56</dim>"
 523             "                    <dim>56</dim>"
 524             "                </port>"
 525             "            </output>"
 526             "        </layer>"
 527             "        <layer id=\"15\" name=\"fire3/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
 528             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"64\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 529             "            <input>"
 530             "                <port id=\"0\">"
 531             "                    <dim>1</dim>"
 532             "                    <dim>16</dim>"
 533             "                    <dim>56</dim>"
 534             "                    <dim>56</dim>"
 535             "                </port>"
 536             "            </input>"
 537             "            <output>"
 538             "                <port id=\"3\">"
 539             "                    <dim>1</dim>"
 540             "                    <dim>64</dim>"
 541             "                    <dim>56</dim>"
 542             "                    <dim>56</dim>"
 543             "                </port>"
 544             "            </output>"
 545             "            <blobs>"
 546             "                <weights offset=\"65408\" size=\"36864\"/>"
 547             "                <biases offset=\"102272\" size=\"256\"/>"
 548             "            </blobs>"
 549             "        </layer>"
 550             "        <layer id=\"16\" name=\"fire3/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
 551             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 552             "            <input>"
 553             "                <port id=\"0\">"
 554             "                    <dim>1</dim>"
 555             "                    <dim>64</dim>"
 556             "                    <dim>56</dim>"
 557             "                    <dim>56</dim>"
 558             "                </port>"
 559             "            </input>"
 560             "            <output>"
 561             "                <port id=\"1\">"
 562             "                    <dim>1</dim>"
 563             "                    <dim>64</dim>"
 564             "                    <dim>56</dim>"
 565             "                    <dim>56</dim>"
 566             "                </port>"
 567             "            </output>"
 568             "        </layer>"
 569             "        <layer id=\"17\" name=\"fire3/concat\" precision=\"FP32\" type=\"Concat\">"
 570             "            <data axis=\"1\"/>"
 571             "            <input>"
 572             "                <port id=\"0\">"
 573             "                    <dim>1</dim>"
 574             "                    <dim>64</dim>"
 575             "                    <dim>56</dim>"
 576             "                    <dim>56</dim>"
 577             "                </port>"
 578             "                <port id=\"1\">"
 579             "                    <dim>1</dim>"
 580             "                    <dim>64</dim>"
 581             "                    <dim>56</dim>"
 582             "                    <dim>56</dim>"
 583             "                </port>"
 584             "            </input>"
 585             "            <output>"
 586             "                <port id=\"2\">"
 587             "                    <dim>1</dim>"
 588             "                    <dim>128</dim>"
 589             "                    <dim>56</dim>"
 590             "                    <dim>56</dim>"
 591             "                </port>"
 592             "            </output>"
 593             "        </layer>"
 594             "        <layer id=\"18\" name=\"pool3\" precision=\"FP32\" type=\"Pooling\">"
 595             "            <data exclude-pad=\"false\" kernel-x=\"3\" kernel-y=\"3\" pad-x=\"0\" pad-y=\"0\" pool-method=\"max\" rounding_type=\"ceil\" stride=\"1,1,2,2\" stride-x=\"2\" stride-y=\"2\"/>"
 596             "            <input>"
 597             "                <port id=\"0\">"
 598             "                    <dim>1</dim>"
 599             "                    <dim>128</dim>"
 600             "                    <dim>56</dim>"
 601             "                    <dim>56</dim>"
 602             "                </port>"
 603             "            </input>"
 604             "            <output>"
 605             "                <port id=\"1\">"
 606             "                    <dim>1</dim>"
 607             "                    <dim>128</dim>"
 608             "                    <dim>28</dim>"
 609             "                    <dim>28</dim>"
 610             "                </port>"
 611             "            </output>"
 612             "        </layer>"
 613             "        <layer id=\"19\" name=\"fire4/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
 614             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"32\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 615             "            <input>"
 616             "                <port id=\"0\">"
 617             "                    <dim>1</dim>"
 618             "                    <dim>128</dim>"
 619             "                    <dim>28</dim>"
 620             "                    <dim>28</dim>"
 621             "                </port>"
 622             "            </input>"
 623             "            <output>"
 624             "                <port id=\"3\">"
 625             "                    <dim>1</dim>"
 626             "                    <dim>32</dim>"
 627             "                    <dim>28</dim>"
 628             "                    <dim>28</dim>"
 629             "                </port>"
 630             "            </output>"
 631             "            <blobs>"
 632             "                <weights offset=\"102528\" size=\"16384\"/>"
 633             "                <biases offset=\"118912\" size=\"128\"/>"
 634             "            </blobs>"
 635             "        </layer>"
 636             "        <layer id=\"20\" name=\"fire4/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
 637             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 638             "            <input>"
 639             "                <port id=\"0\">"
 640             "                    <dim>1</dim>"
 641             "                    <dim>32</dim>"
 642             "                    <dim>28</dim>"
 643             "                    <dim>28</dim>"
 644             "                </port>"
 645             "            </input>"
 646             "            <output>"
 647             "                <port id=\"1\">"
 648             "                    <dim>1</dim>"
 649             "                    <dim>32</dim>"
 650             "                    <dim>28</dim>"
 651             "                    <dim>28</dim>"
 652             "                </port>"
 653             "            </output>"
 654             "        </layer>"
 655             "        <layer id=\"21\" name=\"fire4/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
 656             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"128\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 657             "            <input>"
 658             "                <port id=\"0\">"
 659             "                    <dim>1</dim>"
 660             "                    <dim>32</dim>"
 661             "                    <dim>28</dim>"
 662             "                    <dim>28</dim>"
 663             "                </port>"
 664             "            </input>"
 665             "            <output>"
 666             "                <port id=\"3\">"
 667             "                    <dim>1</dim>"
 668             "                    <dim>128</dim>"
 669             "                    <dim>28</dim>"
 670             "                    <dim>28</dim>"
 671             "                </port>"
 672             "            </output>"
 673             "            <blobs>"
 674             "                <weights offset=\"119040\" size=\"16384\"/>"
 675             "                <biases offset=\"135424\" size=\"512\"/>"
 676             "            </blobs>"
 677             "        </layer>"
 678             "        <layer id=\"22\" name=\"fire4/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
 679             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 680             "            <input>"
 681             "                <port id=\"0\">"
 682             "                    <dim>1</dim>"
 683             "                    <dim>128</dim>"
 684             "                    <dim>28</dim>"
 685             "                    <dim>28</dim>"
 686             "                </port>"
 687             "            </input>"
 688             "            <output>"
 689             "                <port id=\"1\">"
 690             "                    <dim>1</dim>"
 691             "                    <dim>128</dim>"
 692             "                    <dim>28</dim>"
 693             "                    <dim>28</dim>"
 694             "                </port>"
 695             "            </output>"
 696             "        </layer>"
 697             "        <layer id=\"23\" name=\"fire4/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
 698             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"128\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 699             "            <input>"
 700             "                <port id=\"0\">"
 701             "                    <dim>1</dim>"
 702             "                    <dim>32</dim>"
 703             "                    <dim>28</dim>"
 704             "                    <dim>28</dim>"
 705             "                </port>"
 706             "            </input>"
 707             "            <output>"
 708             "                <port id=\"3\">"
 709             "                    <dim>1</dim>"
 710             "                    <dim>128</dim>"
 711             "                    <dim>28</dim>"
 712             "                    <dim>28</dim>"
 713             "                </port>"
 714             "            </output>"
 715             "            <blobs>"
 716             "                <weights offset=\"135936\" size=\"147456\"/>"
 717             "                <biases offset=\"283392\" size=\"512\"/>"
 718             "            </blobs>"
 719             "        </layer>"
 720             "        <layer id=\"24\" name=\"fire4/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
 721             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 722             "            <input>"
 723             "                <port id=\"0\">"
 724             "                    <dim>1</dim>"
 725             "                    <dim>128</dim>"
 726             "                    <dim>28</dim>"
 727             "                    <dim>28</dim>"
 728             "                </port>"
 729             "            </input>"
 730             "            <output>"
 731             "                <port id=\"1\">"
 732             "                    <dim>1</dim>"
 733             "                    <dim>128</dim>"
 734             "                    <dim>28</dim>"
 735             "                    <dim>28</dim>"
 736             "                </port>"
 737             "            </output>"
 738             "        </layer>"
 739             "        <layer id=\"25\" name=\"fire4/concat\" precision=\"FP32\" type=\"Concat\">"
 740             "            <data axis=\"1\"/>"
 741             "            <input>"
 742             "                <port id=\"0\">"
 743             "                    <dim>1</dim>"
 744             "                    <dim>128</dim>"
 745             "                    <dim>28</dim>"
 746             "                    <dim>28</dim>"
 747             "                </port>"
 748             "                <port id=\"1\">"
 749             "                    <dim>1</dim>"
 750             "                    <dim>128</dim>"
 751             "                    <dim>28</dim>"
 752             "                    <dim>28</dim>"
 753             "                </port>"
 754             "            </input>"
 755             "            <output>"
 756             "                <port id=\"2\">"
 757             "                    <dim>1</dim>"
 758             "                    <dim>256</dim>"
 759             "                    <dim>28</dim>"
 760             "                    <dim>28</dim>"
 761             "                </port>"
 762             "            </output>"
 763             "        </layer>"
 764             "        <layer id=\"26\" name=\"fire5/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
 765             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"32\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 766             "            <input>"
 767             "                <port id=\"0\">"
 768             "                    <dim>1</dim>"
 769             "                    <dim>256</dim>"
 770             "                    <dim>28</dim>"
 771             "                    <dim>28</dim>"
 772             "                </port>"
 773             "            </input>"
 774             "            <output>"
 775             "                <port id=\"3\">"
 776             "                    <dim>1</dim>"
 777             "                    <dim>32</dim>"
 778             "                    <dim>28</dim>"
 779             "                    <dim>28</dim>"
 780             "                </port>"
 781             "            </output>"
 782             "            <blobs>"
 783             "                <weights offset=\"283904\" size=\"32768\"/>"
 784             "                <biases offset=\"316672\" size=\"128\"/>"
 785             "            </blobs>"
 786             "        </layer>"
 787             "        <layer id=\"27\" name=\"fire5/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
 788             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 789             "            <input>"
 790             "                <port id=\"0\">"
 791             "                    <dim>1</dim>"
 792             "                    <dim>32</dim>"
 793             "                    <dim>28</dim>"
 794             "                    <dim>28</dim>"
 795             "                </port>"
 796             "            </input>"
 797             "            <output>"
 798             "                <port id=\"1\">"
 799             "                    <dim>1</dim>"
 800             "                    <dim>32</dim>"
 801             "                    <dim>28</dim>"
 802             "                    <dim>28</dim>"
 803             "                </port>"
 804             "            </output>"
 805             "        </layer>"
 806             "        <layer id=\"28\" name=\"fire5/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
 807             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"128\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 808             "            <input>"
 809             "                <port id=\"0\">"
 810             "                    <dim>1</dim>"
 811             "                    <dim>32</dim>"
 812             "                    <dim>28</dim>"
 813             "                    <dim>28</dim>"
 814             "                </port>"
 815             "            </input>"
 816             "            <output>"
 817             "                <port id=\"3\">"
 818             "                    <dim>1</dim>"
 819             "                    <dim>128</dim>"
 820             "                    <dim>28</dim>"
 821             "                    <dim>28</dim>"
 822             "                </port>"
 823             "            </output>"
 824             "            <blobs>"
 825             "                <weights offset=\"316800\" size=\"16384\"/>"
 826             "                <biases offset=\"333184\" size=\"512\"/>"
 827             "            </blobs>"
 828             "        </layer>"
 829             "        <layer id=\"29\" name=\"fire5/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
 830             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 831             "            <input>"
 832             "                <port id=\"0\">"
 833             "                    <dim>1</dim>"
 834             "                    <dim>128</dim>"
 835             "                    <dim>28</dim>"
 836             "                    <dim>28</dim>"
 837             "                </port>"
 838             "            </input>"
 839             "            <output>"
 840             "                <port id=\"1\">"
 841             "                    <dim>1</dim>"
 842             "                    <dim>128</dim>"
 843             "                    <dim>28</dim>"
 844             "                    <dim>28</dim>"
 845             "                </port>"
 846             "            </output>"
 847             "        </layer>"
 848             "        <layer id=\"30\" name=\"fire5/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
 849             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"128\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 850             "            <input>"
 851             "                <port id=\"0\">"
 852             "                    <dim>1</dim>"
 853             "                    <dim>32</dim>"
 854             "                    <dim>28</dim>"
 855             "                    <dim>28</dim>"
 856             "                </port>"
 857             "            </input>"
 858             "            <output>"
 859             "                <port id=\"3\">"
 860             "                    <dim>1</dim>"
 861             "                    <dim>128</dim>"
 862             "                    <dim>28</dim>"
 863             "                    <dim>28</dim>"
 864             "                </port>"
 865             "            </output>"
 866             "            <blobs>"
 867             "                <weights offset=\"333696\" size=\"147456\"/>"
 868             "                <biases offset=\"481152\" size=\"512\"/>"
 869             "            </blobs>"
 870             "        </layer>"
 871             "        <layer id=\"31\" name=\"fire5/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
 872             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 873             "            <input>"
 874             "                <port id=\"0\">"
 875             "                    <dim>1</dim>"
 876             "                    <dim>128</dim>"
 877             "                    <dim>28</dim>"
 878             "                    <dim>28</dim>"
 879             "                </port>"
 880             "            </input>"
 881             "            <output>"
 882             "                <port id=\"1\">"
 883             "                    <dim>1</dim>"
 884             "                    <dim>128</dim>"
 885             "                    <dim>28</dim>"
 886             "                    <dim>28</dim>"
 887             "                </port>"
 888             "            </output>"
 889             "        </layer>"
 890             "        <layer id=\"32\" name=\"fire5/concat\" precision=\"FP32\" type=\"Concat\">"
 891             "            <data axis=\"1\"/>"
 892             "            <input>"
 893             "                <port id=\"0\">"
 894             "                    <dim>1</dim>"
 895             "                    <dim>128</dim>"
 896             "                    <dim>28</dim>"
 897             "                    <dim>28</dim>"
 898             "                </port>"
 899             "                <port id=\"1\">"
 900             "                    <dim>1</dim>"
 901             "                    <dim>128</dim>"
 902             "                    <dim>28</dim>"
 903             "                    <dim>28</dim>"
 904             "                </port>"
 905             "            </input>"
 906             "            <output>"
 907             "                <port id=\"2\">"
 908             "                    <dim>1</dim>"
 909             "                    <dim>256</dim>"
 910             "                    <dim>28</dim>"
 911             "                    <dim>28</dim>"
 912             "                </port>"
 913             "            </output>"
 914             "        </layer>"
 915             "        <layer id=\"33\" name=\"pool5\" precision=\"FP32\" type=\"Pooling\">"
 916             "            <data exclude-pad=\"false\" kernel-x=\"3\" kernel-y=\"3\" pad-x=\"0\" pad-y=\"0\" pool-method=\"max\" rounding_type=\"ceil\" stride=\"1,1,2,2\" stride-x=\"2\" stride-y=\"2\"/>"
 917             "            <input>"
 918             "                <port id=\"0\">"
 919             "                    <dim>1</dim>"
 920             "                    <dim>256</dim>"
 921             "                    <dim>28</dim>"
 922             "                    <dim>28</dim>"
 923             "                </port>"
 924             "            </input>"
 925             "            <output>"
 926             "                <port id=\"1\">"
 927             "                    <dim>1</dim>"
 928             "                    <dim>256</dim>"
 929             "                    <dim>14</dim>"
 930             "                    <dim>14</dim>"
 931             "                </port>"
 932             "            </output>"
 933             "        </layer>"
 934             "        <layer id=\"34\" name=\"fire6/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
 935             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"48\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 936             "            <input>"
 937             "                <port id=\"0\">"
 938             "                    <dim>1</dim>"
 939             "                    <dim>256</dim>"
 940             "                    <dim>14</dim>"
 941             "                    <dim>14</dim>"
 942             "                </port>"
 943             "            </input>"
 944             "            <output>"
 945             "                <port id=\"3\">"
 946             "                    <dim>1</dim>"
 947             "                    <dim>48</dim>"
 948             "                    <dim>14</dim>"
 949             "                    <dim>14</dim>"
 950             "                </port>"
 951             "            </output>"
 952             "            <blobs>"
 953             "                <weights offset=\"481664\" size=\"49152\"/>"
 954             "                <biases offset=\"530816\" size=\"192\"/>"
 955             "            </blobs>"
 956             "        </layer>"
 957             "        <layer id=\"35\" name=\"fire6/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
 958             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
 959             "            <input>"
 960             "                <port id=\"0\">"
 961             "                    <dim>1</dim>"
 962             "                    <dim>48</dim>"
 963             "                    <dim>14</dim>"
 964             "                    <dim>14</dim>"
 965             "                </port>"
 966             "            </input>"
 967             "            <output>"
 968             "                <port id=\"1\">"
 969             "                    <dim>1</dim>"
 970             "                    <dim>48</dim>"
 971             "                    <dim>14</dim>"
 972             "                    <dim>14</dim>"
 973             "                </port>"
 974             "            </output>"
 975             "        </layer>"
 976             "        <layer id=\"36\" name=\"fire6/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
 977             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"192\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
 978             "            <input>"
 979             "                <port id=\"0\">"
 980             "                    <dim>1</dim>"
 981             "                    <dim>48</dim>"
 982             "                    <dim>14</dim>"
 983             "                    <dim>14</dim>"
 984             "                </port>"
 985             "            </input>"
 986             "            <output>"
 987             "                <port id=\"3\">"
 988             "                    <dim>1</dim>"
 989             "                    <dim>192</dim>"
 990             "                    <dim>14</dim>"
 991             "                    <dim>14</dim>"
 992             "                </port>"
 993             "            </output>"
 994             "            <blobs>"
 995             "                <weights offset=\"531008\" size=\"36864\"/>"
 996             "                <biases offset=\"567872\" size=\"768\"/>"
 997             "            </blobs>"
 998             "        </layer>"
 999             "        <layer id=\"37\" name=\"fire6/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
1000             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1001             "            <input>"
1002             "                <port id=\"0\">"
1003             "                    <dim>1</dim>"
1004             "                    <dim>192</dim>"
1005             "                    <dim>14</dim>"
1006             "                    <dim>14</dim>"
1007             "                </port>"
1008             "            </input>"
1009             "            <output>"
1010             "                <port id=\"1\">"
1011             "                    <dim>1</dim>"
1012             "                    <dim>192</dim>"
1013             "                    <dim>14</dim>"
1014             "                    <dim>14</dim>"
1015             "                </port>"
1016             "            </output>"
1017             "        </layer>"
1018             "        <layer id=\"38\" name=\"fire6/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
1019             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"192\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1020             "            <input>"
1021             "                <port id=\"0\">"
1022             "                    <dim>1</dim>"
1023             "                    <dim>48</dim>"
1024             "                    <dim>14</dim>"
1025             "                    <dim>14</dim>"
1026             "                </port>"
1027             "            </input>"
1028             "            <output>"
1029             "                <port id=\"3\">"
1030             "                    <dim>1</dim>"
1031             "                    <dim>192</dim>"
1032             "                    <dim>14</dim>"
1033             "                    <dim>14</dim>"
1034             "                </port>"
1035             "            </output>"
1036             "            <blobs>"
1037             "                <weights offset=\"568640\" size=\"331776\"/>"
1038             "                <biases offset=\"900416\" size=\"768\"/>"
1039             "            </blobs>"
1040             "        </layer>"
1041             "        <layer id=\"39\" name=\"fire6/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
1042             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1043             "            <input>"
1044             "                <port id=\"0\">"
1045             "                    <dim>1</dim>"
1046             "                    <dim>192</dim>"
1047             "                    <dim>14</dim>"
1048             "                    <dim>14</dim>"
1049             "                </port>"
1050             "            </input>"
1051             "            <output>"
1052             "                <port id=\"1\">"
1053             "                    <dim>1</dim>"
1054             "                    <dim>192</dim>"
1055             "                    <dim>14</dim>"
1056             "                    <dim>14</dim>"
1057             "                </port>"
1058             "            </output>"
1059             "        </layer>"
1060             "        <layer id=\"40\" name=\"fire6/concat\" precision=\"FP32\" type=\"Concat\">"
1061             "            <data axis=\"1\"/>"
1062             "            <input>"
1063             "                <port id=\"0\">"
1064             "                    <dim>1</dim>"
1065             "                    <dim>192</dim>"
1066             "                    <dim>14</dim>"
1067             "                    <dim>14</dim>"
1068             "                </port>"
1069             "                <port id=\"1\">"
1070             "                    <dim>1</dim>"
1071             "                    <dim>192</dim>"
1072             "                    <dim>14</dim>"
1073             "                    <dim>14</dim>"
1074             "                </port>"
1075             "            </input>"
1076             "            <output>"
1077             "                <port id=\"2\">"
1078             "                    <dim>1</dim>"
1079             "                    <dim>384</dim>"
1080             "                    <dim>14</dim>"
1081             "                    <dim>14</dim>"
1082             "                </port>"
1083             "            </output>"
1084             "        </layer>"
1085             "        <layer id=\"41\" name=\"fire7/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
1086             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"48\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1087             "            <input>"
1088             "                <port id=\"0\">"
1089             "                    <dim>1</dim>"
1090             "                    <dim>384</dim>"
1091             "                    <dim>14</dim>"
1092             "                    <dim>14</dim>"
1093             "                </port>"
1094             "            </input>"
1095             "            <output>"
1096             "                <port id=\"3\">"
1097             "                    <dim>1</dim>"
1098             "                    <dim>48</dim>"
1099             "                    <dim>14</dim>"
1100             "                    <dim>14</dim>"
1101             "                </port>"
1102             "            </output>"
1103             "            <blobs>"
1104             "                <weights offset=\"901184\" size=\"73728\"/>"
1105             "                <biases offset=\"974912\" size=\"192\"/>"
1106             "            </blobs>"
1107             "        </layer>"
1108             "        <layer id=\"42\" name=\"fire7/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
1109             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1110             "            <input>"
1111             "                <port id=\"0\">"
1112             "                    <dim>1</dim>"
1113             "                    <dim>48</dim>"
1114             "                    <dim>14</dim>"
1115             "                    <dim>14</dim>"
1116             "                </port>"
1117             "            </input>"
1118             "            <output>"
1119             "                <port id=\"1\">"
1120             "                    <dim>1</dim>"
1121             "                    <dim>48</dim>"
1122             "                    <dim>14</dim>"
1123             "                    <dim>14</dim>"
1124             "                </port>"
1125             "            </output>"
1126             "        </layer>"
1127             "        <layer id=\"43\" name=\"fire7/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
1128             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"192\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1129             "            <input>"
1130             "                <port id=\"0\">"
1131             "                    <dim>1</dim>"
1132             "                    <dim>48</dim>"
1133             "                    <dim>14</dim>"
1134             "                    <dim>14</dim>"
1135             "                </port>"
1136             "            </input>"
1137             "            <output>"
1138             "                <port id=\"3\">"
1139             "                    <dim>1</dim>"
1140             "                    <dim>192</dim>"
1141             "                    <dim>14</dim>"
1142             "                    <dim>14</dim>"
1143             "                </port>"
1144             "            </output>"
1145             "            <blobs>"
1146             "                <weights offset=\"975104\" size=\"36864\"/>"
1147             "                <biases offset=\"1011968\" size=\"768\"/>"
1148             "            </blobs>"
1149             "        </layer>"
1150             "        <layer id=\"44\" name=\"fire7/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
1151             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1152             "            <input>"
1153             "                <port id=\"0\">"
1154             "                    <dim>1</dim>"
1155             "                    <dim>192</dim>"
1156             "                    <dim>14</dim>"
1157             "                    <dim>14</dim>"
1158             "                </port>"
1159             "            </input>"
1160             "            <output>"
1161             "                <port id=\"1\">"
1162             "                    <dim>1</dim>"
1163             "                    <dim>192</dim>"
1164             "                    <dim>14</dim>"
1165             "                    <dim>14</dim>"
1166             "                </port>"
1167             "            </output>"
1168             "        </layer>"
1169             "        <layer id=\"45\" name=\"fire7/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
1170             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"192\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1171             "            <input>"
1172             "                <port id=\"0\">"
1173             "                    <dim>1</dim>"
1174             "                    <dim>48</dim>"
1175             "                    <dim>14</dim>"
1176             "                    <dim>14</dim>"
1177             "                </port>"
1178             "            </input>"
1179             "            <output>"
1180             "                <port id=\"3\">"
1181             "                    <dim>1</dim>"
1182             "                    <dim>192</dim>"
1183             "                    <dim>14</dim>"
1184             "                    <dim>14</dim>"
1185             "                </port>"
1186             "            </output>"
1187             "            <blobs>"
1188             "                <weights offset=\"1012736\" size=\"331776\"/>"
1189             "                <biases offset=\"1344512\" size=\"768\"/>"
1190             "            </blobs>"
1191             "        </layer>"
1192             "        <layer id=\"46\" name=\"fire7/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
1193             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1194             "            <input>"
1195             "                <port id=\"0\">"
1196             "                    <dim>1</dim>"
1197             "                    <dim>192</dim>"
1198             "                    <dim>14</dim>"
1199             "                    <dim>14</dim>"
1200             "                </port>"
1201             "            </input>"
1202             "            <output>"
1203             "                <port id=\"1\">"
1204             "                    <dim>1</dim>"
1205             "                    <dim>192</dim>"
1206             "                    <dim>14</dim>"
1207             "                    <dim>14</dim>"
1208             "                </port>"
1209             "            </output>"
1210             "        </layer>"
1211             "        <layer id=\"47\" name=\"fire7/concat\" precision=\"FP32\" type=\"Concat\">"
1212             "            <data axis=\"1\"/>"
1213             "            <input>"
1214             "                <port id=\"0\">"
1215             "                    <dim>1</dim>"
1216             "                    <dim>192</dim>"
1217             "                    <dim>14</dim>"
1218             "                    <dim>14</dim>"
1219             "                </port>"
1220             "                <port id=\"1\">"
1221             "                    <dim>1</dim>"
1222             "                    <dim>192</dim>"
1223             "                    <dim>14</dim>"
1224             "                    <dim>14</dim>"
1225             "                </port>"
1226             "            </input>"
1227             "            <output>"
1228             "                <port id=\"2\">"
1229             "                    <dim>1</dim>"
1230             "                    <dim>384</dim>"
1231             "                    <dim>14</dim>"
1232             "                    <dim>14</dim>"
1233             "                </port>"
1234             "            </output>"
1235             "        </layer>"
1236             "        <layer id=\"48\" name=\"fire8/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
1237             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"64\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1238             "            <input>"
1239             "                <port id=\"0\">"
1240             "                    <dim>1</dim>"
1241             "                    <dim>384</dim>"
1242             "                    <dim>14</dim>"
1243             "                    <dim>14</dim>"
1244             "                </port>"
1245             "            </input>"
1246             "            <output>"
1247             "                <port id=\"3\">"
1248             "                    <dim>1</dim>"
1249             "                    <dim>64</dim>"
1250             "                    <dim>14</dim>"
1251             "                    <dim>14</dim>"
1252             "                </port>"
1253             "            </output>"
1254             "            <blobs>"
1255             "                <weights offset=\"1345280\" size=\"98304\"/>"
1256             "                <biases offset=\"1443584\" size=\"256\"/>"
1257             "            </blobs>"
1258             "        </layer>"
1259             "        <layer id=\"49\" name=\"fire8/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
1260             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1261             "            <input>"
1262             "                <port id=\"0\">"
1263             "                    <dim>1</dim>"
1264             "                    <dim>64</dim>"
1265             "                    <dim>14</dim>"
1266             "                    <dim>14</dim>"
1267             "                </port>"
1268             "            </input>"
1269             "            <output>"
1270             "                <port id=\"1\">"
1271             "                    <dim>1</dim>"
1272             "                    <dim>64</dim>"
1273             "                    <dim>14</dim>"
1274             "                    <dim>14</dim>"
1275             "                </port>"
1276             "            </output>"
1277             "        </layer>"
1278             "        <layer id=\"50\" name=\"fire8/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
1279             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"256\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1280             "            <input>"
1281             "                <port id=\"0\">"
1282             "                    <dim>1</dim>"
1283             "                    <dim>64</dim>"
1284             "                    <dim>14</dim>"
1285             "                    <dim>14</dim>"
1286             "                </port>"
1287             "            </input>"
1288             "            <output>"
1289             "                <port id=\"3\">"
1290             "                    <dim>1</dim>"
1291             "                    <dim>256</dim>"
1292             "                    <dim>14</dim>"
1293             "                    <dim>14</dim>"
1294             "                </port>"
1295             "            </output>"
1296             "            <blobs>"
1297             "                <weights offset=\"1443840\" size=\"65536\"/>"
1298             "                <biases offset=\"1509376\" size=\"1024\"/>"
1299             "            </blobs>"
1300             "        </layer>"
1301             "        <layer id=\"51\" name=\"fire8/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
1302             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1303             "            <input>"
1304             "                <port id=\"0\">"
1305             "                    <dim>1</dim>"
1306             "                    <dim>256</dim>"
1307             "                    <dim>14</dim>"
1308             "                    <dim>14</dim>"
1309             "                </port>"
1310             "            </input>"
1311             "            <output>"
1312             "                <port id=\"1\">"
1313             "                    <dim>1</dim>"
1314             "                    <dim>256</dim>"
1315             "                    <dim>14</dim>"
1316             "                    <dim>14</dim>"
1317             "                </port>"
1318             "            </output>"
1319             "        </layer>"
1320             "        <layer id=\"52\" name=\"fire8/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
1321             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"256\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1322             "            <input>"
1323             "                <port id=\"0\">"
1324             "                    <dim>1</dim>"
1325             "                    <dim>64</dim>"
1326             "                    <dim>14</dim>"
1327             "                    <dim>14</dim>"
1328             "                </port>"
1329             "            </input>"
1330             "            <output>"
1331             "                <port id=\"3\">"
1332             "                    <dim>1</dim>"
1333             "                    <dim>256</dim>"
1334             "                    <dim>14</dim>"
1335             "                    <dim>14</dim>"
1336             "                </port>"
1337             "            </output>"
1338             "            <blobs>"
1339             "                <weights offset=\"1510400\" size=\"589824\"/>"
1340             "                <biases offset=\"2100224\" size=\"1024\"/>"
1341             "            </blobs>"
1342             "        </layer>"
1343             "        <layer id=\"53\" name=\"fire8/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
1344             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1345             "            <input>"
1346             "                <port id=\"0\">"
1347             "                    <dim>1</dim>"
1348             "                    <dim>256</dim>"
1349             "                    <dim>14</dim>"
1350             "                    <dim>14</dim>"
1351             "                </port>"
1352             "            </input>"
1353             "            <output>"
1354             "                <port id=\"1\">"
1355             "                    <dim>1</dim>"
1356             "                    <dim>256</dim>"
1357             "                    <dim>14</dim>"
1358             "                    <dim>14</dim>"
1359             "                </port>"
1360             "            </output>"
1361             "        </layer>"
1362             "        <layer id=\"54\" name=\"fire8/concat\" precision=\"FP32\" type=\"Concat\">"
1363             "            <data axis=\"1\"/>"
1364             "            <input>"
1365             "                <port id=\"0\">"
1366             "                    <dim>1</dim>"
1367             "                    <dim>256</dim>"
1368             "                    <dim>14</dim>"
1369             "                    <dim>14</dim>"
1370             "                </port>"
1371             "                <port id=\"1\">"
1372             "                    <dim>1</dim>"
1373             "                    <dim>256</dim>"
1374             "                    <dim>14</dim>"
1375             "                    <dim>14</dim>"
1376             "                </port>"
1377             "            </input>"
1378             "            <output>"
1379             "                <port id=\"2\">"
1380             "                    <dim>1</dim>"
1381             "                    <dim>512</dim>"
1382             "                    <dim>14</dim>"
1383             "                    <dim>14</dim>"
1384             "                </port>"
1385             "            </output>"
1386             "        </layer>"
1387             "        <layer id=\"55\" name=\"fire9/squeeze1x1\" precision=\"FP32\" type=\"Convolution\">"
1388             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"64\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1389             "            <input>"
1390             "                <port id=\"0\">"
1391             "                    <dim>1</dim>"
1392             "                    <dim>512</dim>"
1393             "                    <dim>14</dim>"
1394             "                    <dim>14</dim>"
1395             "                </port>"
1396             "            </input>"
1397             "            <output>"
1398             "                <port id=\"3\">"
1399             "                    <dim>1</dim>"
1400             "                    <dim>64</dim>"
1401             "                    <dim>14</dim>"
1402             "                    <dim>14</dim>"
1403             "                </port>"
1404             "            </output>"
1405             "            <blobs>"
1406             "                <weights offset=\"2101248\" size=\"131072\"/>"
1407             "                <biases offset=\"2232320\" size=\"256\"/>"
1408             "            </blobs>"
1409             "        </layer>"
1410             "        <layer id=\"56\" name=\"fire9/relu_squeeze1x1\" precision=\"FP32\" type=\"ReLU\">"
1411             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1412             "            <input>"
1413             "                <port id=\"0\">"
1414             "                    <dim>1</dim>"
1415             "                    <dim>64</dim>"
1416             "                    <dim>14</dim>"
1417             "                    <dim>14</dim>"
1418             "                </port>"
1419             "            </input>"
1420             "            <output>"
1421             "                <port id=\"1\">"
1422             "                    <dim>1</dim>"
1423             "                    <dim>64</dim>"
1424             "                    <dim>14</dim>"
1425             "                    <dim>14</dim>"
1426             "                </port>"
1427             "            </output>"
1428             "        </layer>"
1429             "        <layer id=\"57\" name=\"fire9/expand1x1\" precision=\"FP32\" type=\"Convolution\">"
1430             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"256\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1431             "            <input>"
1432             "                <port id=\"0\">"
1433             "                    <dim>1</dim>"
1434             "                    <dim>64</dim>"
1435             "                    <dim>14</dim>"
1436             "                    <dim>14</dim>"
1437             "                </port>"
1438             "            </input>"
1439             "            <output>"
1440             "                <port id=\"3\">"
1441             "                    <dim>1</dim>"
1442             "                    <dim>256</dim>"
1443             "                    <dim>14</dim>"
1444             "                    <dim>14</dim>"
1445             "                </port>"
1446             "            </output>"
1447             "            <blobs>"
1448             "                <weights offset=\"2232576\" size=\"65536\"/>"
1449             "                <biases offset=\"2298112\" size=\"1024\"/>"
1450             "            </blobs>"
1451             "        </layer>"
1452             "        <layer id=\"58\" name=\"fire9/relu_expand1x1\" precision=\"FP32\" type=\"ReLU\">"
1453             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1454             "            <input>"
1455             "                <port id=\"0\">"
1456             "                    <dim>1</dim>"
1457             "                    <dim>256</dim>"
1458             "                    <dim>14</dim>"
1459             "                    <dim>14</dim>"
1460             "                </port>"
1461             "            </input>"
1462             "            <output>"
1463             "                <port id=\"1\">"
1464             "                    <dim>1</dim>"
1465             "                    <dim>256</dim>"
1466             "                    <dim>14</dim>"
1467             "                    <dim>14</dim>"
1468             "                </port>"
1469             "            </output>"
1470             "        </layer>"
1471             "        <layer id=\"59\" name=\"fire9/expand3x3\" precision=\"FP32\" type=\"Convolution\">"
1472             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"3\" kernel-y=\"3\" output=\"256\" pad-x=\"1\" pad-y=\"1\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1473             "            <input>"
1474             "                <port id=\"0\">"
1475             "                    <dim>1</dim>"
1476             "                    <dim>64</dim>"
1477             "                    <dim>14</dim>"
1478             "                    <dim>14</dim>"
1479             "                </port>"
1480             "            </input>"
1481             "            <output>"
1482             "                <port id=\"3\">"
1483             "                    <dim>1</dim>"
1484             "                    <dim>256</dim>"
1485             "                    <dim>14</dim>"
1486             "                    <dim>14</dim>"
1487             "                </port>"
1488             "            </output>"
1489             "            <blobs>"
1490             "                <weights offset=\"2299136\" size=\"589824\"/>"
1491             "                <biases offset=\"2888960\" size=\"1024\"/>"
1492             "            </blobs>"
1493             "        </layer>"
1494             "        <layer id=\"60\" name=\"fire9/relu_expand3x3\" precision=\"FP32\" type=\"ReLU\">"
1495             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1496             "            <input>"
1497             "                <port id=\"0\">"
1498             "                    <dim>1</dim>"
1499             "                    <dim>256</dim>"
1500             "                    <dim>14</dim>"
1501             "                    <dim>14</dim>"
1502             "                </port>"
1503             "            </input>"
1504             "            <output>"
1505             "                <port id=\"1\">"
1506             "                    <dim>1</dim>"
1507             "                    <dim>256</dim>"
1508             "                    <dim>14</dim>"
1509             "                    <dim>14</dim>"
1510             "                </port>"
1511             "            </output>"
1512             "        </layer>"
1513             "        <layer id=\"61\" name=\"fire9/concat\" precision=\"FP32\" type=\"Concat\">"
1514             "            <data axis=\"1\"/>"
1515             "            <input>"
1516             "                <port id=\"0\">"
1517             "                    <dim>1</dim>"
1518             "                    <dim>256</dim>"
1519             "                    <dim>14</dim>"
1520             "                    <dim>14</dim>"
1521             "                </port>"
1522             "                <port id=\"1\">"
1523             "                    <dim>1</dim>"
1524             "                    <dim>256</dim>"
1525             "                    <dim>14</dim>"
1526             "                    <dim>14</dim>"
1527             "                </port>"
1528             "            </input>"
1529             "            <output>"
1530             "                <port id=\"2\">"
1531             "                    <dim>1</dim>"
1532             "                    <dim>512</dim>"
1533             "                    <dim>14</dim>"
1534             "                    <dim>14</dim>"
1535             "                </port>"
1536             "            </output>"
1537             "        </layer>"
1538             "        <layer id=\"62\" name=\"conv10\" precision=\"FP32\" type=\"Convolution\">"
1539             "            <data dilation-x=\"1\" dilation-y=\"1\" group=\"1\" kernel-x=\"1\" kernel-y=\"1\" output=\"1000\" pad-x=\"0\" pad-y=\"0\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1540             "            <input>"
1541             "                <port id=\"0\">"
1542             "                    <dim>1</dim>"
1543             "                    <dim>512</dim>"
1544             "                    <dim>14</dim>"
1545             "                    <dim>14</dim>"
1546             "                </port>"
1547             "            </input>"
1548             "            <output>"
1549             "                <port id=\"3\">"
1550             "                    <dim>1</dim>"
1551             "                    <dim>1000</dim>"
1552             "                    <dim>14</dim>"
1553             "                    <dim>14</dim>"
1554             "                </port>"
1555             "            </output>"
1556             "            <blobs>"
1557             "                <weights offset=\"2889984\" size=\"2048000\"/>"
1558             "                <biases offset=\"4937984\" size=\"4000\"/>"
1559             "            </blobs>"
1560             "        </layer>"
1561             "        <layer id=\"63\" name=\"relu_conv10\" precision=\"FP32\" type=\"ReLU\">"
1562             "            <data engine=\"caffe.ReLUParameter.DEFAULT\" negative_slope=\"0.0\"/>"
1563             "            <input>"
1564             "                <port id=\"0\">"
1565             "                    <dim>1</dim>"
1566             "                    <dim>1000</dim>"
1567             "                    <dim>14</dim>"
1568             "                    <dim>14</dim>"
1569             "                </port>"
1570             "            </input>"
1571             "            <output>"
1572             "                <port id=\"1\">"
1573             "                    <dim>1</dim>"
1574             "                    <dim>1000</dim>"
1575             "                    <dim>14</dim>"
1576             "                    <dim>14</dim>"
1577             "                </port>"
1578             "            </output>"
1579             "        </layer>"
1580             "        <layer id=\"64\" name=\"pool10\" precision=\"FP32\" type=\"Pooling\">"
1581             "            <data exclude-pad=\"false\" kernel-x=\"14\" kernel-y=\"14\" pad-x=\"0\" pad-y=\"0\" pool-method=\"avg\" rounding_type=\"ceil\" stride=\"1,1,1,1\" stride-x=\"1\" stride-y=\"1\"/>"
1582             "            <input>"
1583             "                <port id=\"0\">"
1584             "                    <dim>1</dim>"
1585             "                    <dim>1000</dim>"
1586             "                    <dim>14</dim>"
1587             "                    <dim>14</dim>"
1588             "                </port>"
1589             "            </input>"
1590             "            <output>"
1591             "                <port id=\"1\">"
1592             "                    <dim>1</dim>"
1593             "                    <dim>1000</dim>"
1594             "                    <dim>1</dim>"
1595             "                    <dim>1</dim>"
1596             "                </port>"
1597             "            </output>"
1598             "        </layer>"
1599             "        <layer id=\"65\" name=\"prob\" precision=\"FP32\" type=\"SoftMax\">"
1600             "            <data axis=\"1\"/>"
1601             "            <input>"
1602             "                <port id=\"0\">"
1603             "                    <dim>1</dim>"
1604             "                    <dim>1000</dim>"
1605             "                    <dim>1</dim>"
1606             "                    <dim>1</dim>"
1607             "                </port>"
1608             "            </input>"
1609             "            <output>"
1610             "                <port id=\"1\">"
1611             "                    <dim>1</dim>"
1612             "                    <dim>1000</dim>"
1613             "                    <dim>1</dim>"
1614             "                    <dim>1</dim>"
1615             "                </port>"
1616             "            </output>"
1617             "        </layer>"
1618             "    </layers>"
1619             "    <edges>"
1620             "        <edge from-layer=\"0\" from-port=\"0\" to-layer=\"1\" to-port=\"0\"/>"
1621             "        <edge from-layer=\"1\" from-port=\"3\" to-layer=\"2\" to-port=\"0\"/>"
1622             "        <edge from-layer=\"2\" from-port=\"1\" to-layer=\"3\" to-port=\"0\"/>"
1623             "        <edge from-layer=\"3\" from-port=\"1\" to-layer=\"4\" to-port=\"0\"/>"
1624             "        <edge from-layer=\"4\" from-port=\"3\" to-layer=\"5\" to-port=\"0\"/>"
1625             "        <edge from-layer=\"5\" from-port=\"1\" to-layer=\"6\" to-port=\"0\"/>"
1626             "        <edge from-layer=\"6\" from-port=\"3\" to-layer=\"7\" to-port=\"0\"/>"
1627             "        <edge from-layer=\"5\" from-port=\"1\" to-layer=\"8\" to-port=\"0\"/>"
1628             "        <edge from-layer=\"8\" from-port=\"3\" to-layer=\"9\" to-port=\"0\"/>"
1629             "        <edge from-layer=\"7\" from-port=\"1\" to-layer=\"10\" to-port=\"0\"/>"
1630             "        <edge from-layer=\"9\" from-port=\"1\" to-layer=\"10\" to-port=\"1\"/>"
1631             "        <edge from-layer=\"10\" from-port=\"2\" to-layer=\"11\" to-port=\"0\"/>"
1632             "        <edge from-layer=\"11\" from-port=\"3\" to-layer=\"12\" to-port=\"0\"/>"
1633             "        <edge from-layer=\"11\" from-port=\"4\" to-layer=\"8\" to-port=\"1\"/>"
1634             "        <edge from-layer=\"12\" from-port=\"1\" to-layer=\"13\" to-port=\"0\"/>"
1635             "        <edge from-layer=\"13\" from-port=\"3\" to-layer=\"14\" to-port=\"0\"/>"
1636             "        <edge from-layer=\"12\" from-port=\"1\" to-layer=\"15\" to-port=\"0\"/>"
1637             "        <edge from-layer=\"15\" from-port=\"3\" to-layer=\"16\" to-port=\"0\"/>"
1638             "        <edge from-layer=\"14\" from-port=\"1\" to-layer=\"17\" to-port=\"0\"/>"
1639             "        <edge from-layer=\"16\" from-port=\"1\" to-layer=\"17\" to-port=\"1\"/>"
1640             "        <edge from-layer=\"17\" from-port=\"2\" to-layer=\"18\" to-port=\"0\"/>"
1641             "        <edge from-layer=\"18\" from-port=\"1\" to-layer=\"19\" to-port=\"0\"/>"
1642             "        <edge from-layer=\"19\" from-port=\"3\" to-layer=\"20\" to-port=\"0\"/>"
1643             "        <edge from-layer=\"20\" from-port=\"1\" to-layer=\"21\" to-port=\"0\"/>"
1644             "        <edge from-layer=\"21\" from-port=\"3\" to-layer=\"22\" to-port=\"0\"/>"
1645             "        <edge from-layer=\"20\" from-port=\"1\" to-layer=\"23\" to-port=\"0\"/>"
1646             "        <edge from-layer=\"23\" from-port=\"3\" to-layer=\"24\" to-port=\"0\"/>"
1647             "        <edge from-layer=\"22\" from-port=\"1\" to-layer=\"25\" to-port=\"0\"/>"
1648             "        <edge from-layer=\"24\" from-port=\"1\" to-layer=\"25\" to-port=\"1\"/>"
1649             "        <edge from-layer=\"25\" from-port=\"2\" to-layer=\"26\" to-port=\"0\"/>"
1650             "        <edge from-layer=\"26\" from-port=\"3\" to-layer=\"27\" to-port=\"0\"/>"
1651             "        <edge from-layer=\"27\" from-port=\"1\" to-layer=\"28\" to-port=\"0\"/>"
1652             "        <edge from-layer=\"28\" from-port=\"3\" to-layer=\"29\" to-port=\"0\"/>"
1653             "        <edge from-layer=\"27\" from-port=\"1\" to-layer=\"30\" to-port=\"0\"/>"
1654             "        <edge from-layer=\"30\" from-port=\"3\" to-layer=\"31\" to-port=\"0\"/>"
1655             "        <edge from-layer=\"29\" from-port=\"1\" to-layer=\"32\" to-port=\"0\"/>"
1656             "        <edge from-layer=\"31\" from-port=\"1\" to-layer=\"32\" to-port=\"1\"/>"
1657             "        <edge from-layer=\"32\" from-port=\"2\" to-layer=\"33\" to-port=\"0\"/>"
1658             "        <edge from-layer=\"33\" from-port=\"1\" to-layer=\"34\" to-port=\"0\"/>"
1659             "        <edge from-layer=\"34\" from-port=\"3\" to-layer=\"35\" to-port=\"0\"/>"
1660             "        <edge from-layer=\"35\" from-port=\"1\" to-layer=\"36\" to-port=\"0\"/>"
1661             "        <edge from-layer=\"36\" from-port=\"3\" to-layer=\"37\" to-port=\"0\"/>"
1662             "        <edge from-layer=\"35\" from-port=\"1\" to-layer=\"38\" to-port=\"0\"/>"
1663             "        <edge from-layer=\"38\" from-port=\"3\" to-layer=\"39\" to-port=\"0\"/>"
1664             "        <edge from-layer=\"37\" from-port=\"1\" to-layer=\"40\" to-port=\"0\"/>"
1665             "        <edge from-layer=\"39\" from-port=\"1\" to-layer=\"40\" to-port=\"1\"/>"
1666             "        <edge from-layer=\"40\" from-port=\"2\" to-layer=\"41\" to-port=\"0\"/>"
1667             "        <edge from-layer=\"41\" from-port=\"3\" to-layer=\"42\" to-port=\"0\"/>"
1668             "        <edge from-layer=\"42\" from-port=\"1\" to-layer=\"43\" to-port=\"0\"/>"
1669             "        <edge from-layer=\"43\" from-port=\"3\" to-layer=\"44\" to-port=\"0\"/>"
1670             "        <edge from-layer=\"42\" from-port=\"1\" to-layer=\"45\" to-port=\"0\"/>"
1671             "        <edge from-layer=\"45\" from-port=\"3\" to-layer=\"46\" to-port=\"0\"/>"
1672             "        <edge from-layer=\"44\" from-port=\"1\" to-layer=\"47\" to-port=\"0\"/>"
1673             "        <edge from-layer=\"46\" from-port=\"1\" to-layer=\"47\" to-port=\"1\"/>"
1674             "        <edge from-layer=\"47\" from-port=\"2\" to-layer=\"48\" to-port=\"0\"/>"
1675             "        <edge from-layer=\"48\" from-port=\"3\" to-layer=\"49\" to-port=\"0\"/>"
1676             "        <edge from-layer=\"49\" from-port=\"1\" to-layer=\"50\" to-port=\"0\"/>"
1677             "        <edge from-layer=\"50\" from-port=\"3\" to-layer=\"51\" to-port=\"0\"/>"
1678             "        <edge from-layer=\"49\" from-port=\"1\" to-layer=\"52\" to-port=\"0\"/>"
1679             "        <edge from-layer=\"52\" from-port=\"3\" to-layer=\"53\" to-port=\"0\"/>"
1680             "        <edge from-layer=\"51\" from-port=\"1\" to-layer=\"54\" to-port=\"0\"/>"
1681             "        <edge from-layer=\"53\" from-port=\"1\" to-layer=\"54\" to-port=\"1\"/>"
1682             "        <edge from-layer=\"54\" from-port=\"2\" to-layer=\"55\" to-port=\"0\"/>"
1683             "        <edge from-layer=\"55\" from-port=\"3\" to-layer=\"56\" to-port=\"0\"/>"
1684             "        <edge from-layer=\"56\" from-port=\"1\" to-layer=\"57\" to-port=\"0\"/>"
1685             "        <edge from-layer=\"57\" from-port=\"3\" to-layer=\"58\" to-port=\"0\"/>"
1686             "        <edge from-layer=\"56\" from-port=\"1\" to-layer=\"59\" to-port=\"0\"/>"
1687             "        <edge from-layer=\"59\" from-port=\"3\" to-layer=\"60\" to-port=\"0\"/>"
1688             "        <edge from-layer=\"58\" from-port=\"1\" to-layer=\"61\" to-port=\"0\"/>"
1689             "        <edge from-layer=\"60\" from-port=\"1\" to-layer=\"61\" to-port=\"1\"/>"
1690             "        <edge from-layer=\"61\" from-port=\"2\" to-layer=\"62\" to-port=\"0\"/>"
1691             "        <edge from-layer=\"62\" from-port=\"3\" to-layer=\"63\" to-port=\"0\"/>"
1692             "        <edge from-layer=\"63\" from-port=\"1\" to-layer=\"64\" to-port=\"0\"/>"
1693             "        <edge from-layer=\"64\" from-port=\"1\" to-layer=\"65\" to-port=\"0\"/>"
1694             "    </edges>"
1695             "</net>";
1696     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
1697
1698     ASSERT_EQ(GENERAL_ERROR, reader.ReadNetwork(model.data(), model.length(), &resp));
1699 }
1700
1701 TEST_F(CNNNetReaderImplTest, canRead3DConvolution) {
1702     std::string model =
1703             "<net batch=\"1\" name=\"Convolution_only\" version=\"3\">"
1704             "    <layers>"
1705             "        <layer id=\"0\" name=\"1\" precision=\"FP32\" type=\"Input\">"
1706             "            <output>"
1707             "                <port id=\"0\">"
1708             "                    <dim>1</dim>"
1709             "                    <dim>3</dim>"
1710             "                    <dim>16</dim>"
1711             "                    <dim>112</dim>"
1712             "                    <dim>112</dim>"
1713             "                </port>"
1714             "            </output>"
1715             "        </layer>"
1716             "        <layer id=\"1\" name=\"3D_conv\" precision=\"FP32\" type=\"Convolution\">"
1717             "            <data dilations=\"1,3,5\" group=\"1\" kernel=\"1,3,5\" output=\"64\" pads_begin=\"1,3,5\" pads_end=\"1,3,5\" strides=\"1,3,5\"/>"
1718             "            <input>"
1719             "                <port id=\"0\">"
1720             "                    <dim>1</dim>"
1721             "                    <dim>3</dim>"
1722             "                    <dim>16</dim>"
1723             "                    <dim>112</dim>"
1724             "                    <dim>112</dim>"
1725             "                </port>"
1726             "            </input>"
1727             "            <output>"
1728             "                <port id=\"1\">"
1729             "                    <dim>1</dim>"
1730             "                    <dim>64</dim>"
1731             "                    <dim>16</dim>"
1732             "                    <dim>56</dim>"
1733             "                    <dim>56</dim>"
1734             "                </port>"
1735             "            </output>"
1736             "            <blobs>"
1737             "                <weights offset=\"0\" size=\"263424\"/>"
1738             "                <biases offset=\"263424\" size=\"256\"/>"
1739             "            </blobs>"
1740             "        </layer>"
1741             "    </layers>"
1742             "    <edges>"
1743             "        <edge from-layer=\"0\" from-port=\"0\" to-layer=\"1\" to-port=\"0\"/>"
1744             "    </edges>"
1745             "</net>";
1746
1747     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
1748     ASSERT_EQ(OK, reader.ReadNetwork(model.data(), model.length(), &resp));
1749     ResponseDesc resp;
1750     auto network = reader.getNetwork(&resp);
1751
1752     CNNLayerPtr layer;
1753     ASSERT_EQ(OK, network->getLayerByName("3D_conv", layer, nullptr));
1754     auto* conv = dynamic_cast<ConvolutionLayer*>(layer.get());
1755     ASSERT_NE(nullptr, conv);
1756     ASSERT_EQ(conv->_kernel[X_AXIS], 5);
1757     ASSERT_EQ(conv->_kernel[Y_AXIS], 3);
1758     ASSERT_EQ(conv->_kernel[Z_AXIS], 1);
1759     ASSERT_EQ(conv->_dilation[X_AXIS], 5);
1760     ASSERT_EQ(conv->_dilation[Y_AXIS], 3);
1761     ASSERT_EQ(conv->_dilation[Z_AXIS], 1);
1762     ASSERT_EQ(conv->_stride[X_AXIS], 5);
1763     ASSERT_EQ(conv->_stride[Y_AXIS], 3);
1764     ASSERT_EQ(conv->_stride[Z_AXIS], 1);
1765     ASSERT_EQ(conv->_padding[X_AXIS], 5);
1766     ASSERT_EQ(conv->_padding[Y_AXIS], 3);
1767     ASSERT_EQ(conv->_padding[Z_AXIS], 1);
1768     ASSERT_EQ(conv->_pads_end[X_AXIS], 5);
1769     ASSERT_EQ(conv->_pads_end[Y_AXIS], 3);
1770     ASSERT_EQ(conv->_pads_end[Z_AXIS], 1);
1771 }
1772
1773 TEST_F(CNNNetReaderImplTest, canRead3DPooling) {
1774     std::string model =
1775             "<net batch=\"1\" name=\"Pooling_only\" version=\"3\">"
1776             "    <layers>"
1777             "        <layer id=\"0\" name=\"1\" precision=\"FP32\" type=\"Input\">"
1778             "            <output>"
1779             "                <port id=\"0\">"
1780             "                    <dim>1</dim>"
1781             "                    <dim>3</dim>"
1782             "                    <dim>16</dim>"
1783             "                    <dim>112</dim>"
1784             "                    <dim>112</dim>"
1785             "                </port>"
1786             "            </output>"
1787             "        </layer>"
1788             "        <layer id=\"1\" name=\"3D_pooling\" precision=\"FP32\" type=\"Pooling\">"
1789             "            <data exclude-pad=\"true\" kernel=\"1,3,5\" pads_begin=\"1,3,5\" pads_end=\"1,3,5\" pool-method=\"max\" rounding_type=\"ceil\" strides=\"1,3,5\"/>"
1790             "            <input>"
1791             "                <port id=\"0\">"
1792             "                    <dim>1</dim>"
1793             "                    <dim>3</dim>"
1794             "                    <dim>16</dim>"
1795             "                    <dim>112</dim>"
1796             "                    <dim>112</dim>"
1797             "                </port>"
1798             "            </input>"
1799             "            <output>"
1800             "                <port id=\"1\">"
1801             "                    <dim>1</dim>"
1802             "                    <dim>64</dim>"
1803             "                    <dim>8</dim>"
1804             "                    <dim>28</dim>"
1805             "                    <dim>28</dim>"
1806             "                </port>"
1807             "            </output>"
1808             "        </layer>"
1809             "    </layers>"
1810             "    <edges>"
1811             "        <edge from-layer=\"0\" from-port=\"0\" to-layer=\"1\" to-port=\"0\"/>"
1812             "    </edges>"
1813             "</net>";
1814
1815     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
1816     ASSERT_EQ(OK, reader.ReadNetwork(model.data(), model.length(), &resp));
1817     ResponseDesc resp;
1818     auto network = reader.getNetwork(&resp);
1819
1820     CNNLayerPtr layer;
1821
1822     ASSERT_EQ(OK, network->getLayerByName("3D_pooling", layer, nullptr));
1823     auto* pool = dynamic_cast<PoolingLayer*>(layer.get());
1824     ASSERT_NE(nullptr, pool);
1825     ASSERT_EQ(pool->_kernel[X_AXIS], 5);
1826     ASSERT_EQ(pool->_kernel[Y_AXIS], 3);
1827     ASSERT_EQ(pool->_kernel[Z_AXIS], 1);
1828     ASSERT_EQ(pool->_stride[X_AXIS], 5);
1829     ASSERT_EQ(pool->_stride[Y_AXIS], 3);
1830     ASSERT_EQ(pool->_stride[Z_AXIS], 1);
1831     ASSERT_EQ(pool->_padding[X_AXIS], 5);
1832     ASSERT_EQ(pool->_padding[Y_AXIS], 3);
1833     ASSERT_EQ(pool->_padding[Z_AXIS], 1);
1834     ASSERT_EQ(pool->_pads_end[X_AXIS], 5);
1835     ASSERT_EQ(pool->_pads_end[Y_AXIS], 3);
1836     ASSERT_EQ(pool->_pads_end[Z_AXIS], 1);
1837 }
1838
1839 TEST_F(CNNNetReaderImplTest, canParseWithoutInput_1to2) {
1840     std::string model = R"V0G0N(
1841 <net batch="1" name="SimpleNet" version="2">
1842     <layers>
1843         <layer id="1" name="Boo" precision="FP32" type="Split">
1844             <data operation="sum"/>
1845             <input>
1846                 <port id="0">
1847                     <dim>2</dim>
1848                     <dim>16</dim>
1849                 </port>
1850             </input>
1851             <output>
1852                 <port id="1">
1853                     <dim>1</dim>
1854                     <dim>16</dim>
1855                 </port>
1856                 <port id="2">
1857                     <dim>1</dim>
1858                     <dim>16</dim>
1859                 </port>
1860             </output>
1861         </layer>
1862     </layers>
1863 </net>
1864     )V0G0N";
1865
1866     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
1867     sts = reader.ReadNetwork(model.data(), model.length(), &resp);
1868     ASSERT_EQ(GENERAL_ERROR, sts) << resp.msg;
1869 }
1870
1871 TEST_F(CNNNetReaderImplTest, canParseWithoutInput_2to1) {
1872     std::string model = R"V0G0N(
1873 <net batch="1" name="SimpleNet" version="2">
1874     <layers>
1875         <layer id="1" name="Foo" precision="FP32" type="Eltwise">
1876             <data operation="sum"/>
1877             <input>
1878                 <port id="0">
1879                     <dim>1</dim>
1880                     <dim>16</dim>
1881                 </port>
1882                 <port id="1">
1883                     <dim>1</dim>
1884                     <dim>16</dim>
1885                 </port>
1886             </input>
1887             <output>
1888                 <port id="2">
1889                     <dim>1</dim>
1890                     <dim>16</dim>
1891                 </port>
1892             </output>
1893         </layer>
1894     </layers>
1895 </net>
1896     )V0G0N";
1897
1898     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
1899     sts = reader.ReadNetwork(model.data(), model.length(), &resp);
1900     ASSERT_EQ(GENERAL_ERROR, sts) << resp.msg;
1901 }
1902
1903 TEST_F(CNNNetReaderImplTest, canParseSimpleTI) {
1904     std::string model = R"V0G0N(
1905 <net batch="1" name="Simple_TI" version="4">
1906     <layers>
1907         <layer id="0" name="input" precision="FP32" type="Input">
1908             <output>
1909                 <port id="0">
1910                     <dim>1</dim>
1911                     <dim>5</dim>
1912                     <dim>16</dim>
1913                 </port>
1914             </output>
1915         </layer>
1916         <layer id="1" name="Bias" precision="FP32" type="Const">
1917             <output>
1918                 <port id="0">
1919                     <dim>1</dim>
1920                     <dim>16</dim>
1921                 </port>
1922             </output>
1923             <blobs>
1924                 <custom offset="0" size="64"/>
1925             </blobs>
1926         </layer>
1927         <layer id="2" name="SomeTI" precision="FP32" type="TensorIterator">
1928             <input>
1929                 <port id="0">
1930                     <dim>1</dim>
1931                     <dim>5</dim>
1932                     <dim>16</dim>
1933                 </port>
1934                 <port id="1">
1935                     <dim>1</dim>
1936                     <dim>16</dim>
1937                 </port>
1938             </input>
1939             <output>
1940                 <port id="3">
1941                     <dim>1</dim>
1942                     <dim>5</dim>
1943                     <dim>16</dim>
1944                 </port>
1945             </output>
1946             <port_map>
1947                 <input  external_port_id="0" internal_layer_id="0" internal_port_id="0" axis="1" />
1948                 <input  external_port_id="1" internal_layer_id="1" internal_port_id="1"/>
1949                 <output external_port_id="3" internal_layer_id="2" internal_port_id="1" axis="1" />
1950             </port_map>
1951             <back_edges>
1952                 <edge from-layer="1" from-port="2" to-layer="1" to-port="1"/>
1953             </back_edges>
1954             <body>
1955                 <layers>
1956                     <layer id="0" name="TI_reshape_in" precision="FP32" type="Reshape">
1957                         <data axis="0" dim="1,512" num_axes="-1"/>
1958                         <input>
1959                             <port id="0">
1960                                 <dim>1</dim>
1961                                 <dim>1</dim>
1962                                 <dim>16</dim>
1963                             </port>
1964                         </input>
1965                         <output>
1966                             <port id="1">
1967                                 <dim>1</dim>
1968                                 <dim>16</dim>
1969                             </port>
1970                         </output>
1971                     </layer>
1972                     <layer id="1" name="TI_sum" precision="FP32" type="Eltwise">
1973                         <data operation="sum"/>
1974                         <input>
1975                             <port id="0">
1976                                 <dim>1</dim>
1977                                 <dim>16</dim>
1978                             </port>
1979                             <port id="1">
1980                                 <dim>1</dim>
1981                                 <dim>16</dim>
1982                             </port>
1983                         </input>
1984                         <output>
1985                             <port id="2">
1986                                 <dim>1</dim>
1987                                 <dim>16</dim>
1988                             </port>
1989                         </output>
1990                     </layer>
1991                     <layer id="2" name="TI_reshape_out" precision="FP32" type="Reshape">
1992                         <data axis="0" dim="1,1,256" num_axes="-1"/>
1993                         <input>
1994                             <port id="0">
1995                                 <dim>1</dim>
1996                                 <dim>16</dim>
1997                             </port>
1998                         </input>
1999                         <output>
2000                             <port id="1">
2001                                 <dim>1</dim>
2002                                 <dim>1</dim>
2003                                 <dim>16</dim>
2004                             </port>
2005                         </output>
2006                     </layer>
2007                 </layers>
2008                 <edges>
2009                     <edge from-layer="0" from-port="1" to-layer="1" to-port="0"/>
2010                     <edge from-layer="1" from-port="2" to-layer="2" to-port="0"/>
2011                 </edges>
2012             </body>
2013         </layer>
2014     </layers>
2015     <edges>
2016         <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
2017         <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
2018     </edges>
2019 </net>
2020     )V0G0N";
2021
2022     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
2023     sts = reader.ReadNetwork(model.data(), model.length(), &resp);
2024     ASSERT_EQ(OK, sts) << resp.msg;
2025
2026     auto network = reader.getNetwork(&resp);
2027     ASSERT_NE(nullptr, network) << resp.msg;
2028
2029     CNNLayerPtr layer;
2030     sts = network->getLayerByName("SomeTI", layer, &resp);
2031     ASSERT_EQ(OK, sts) << resp.msg;
2032
2033     auto* ti = dynamic_cast<TensorIterator*>(layer.get());
2034     ASSERT_NE(nullptr, ti);
2035     ASSERT_EQ(ti->type, "TensorIterator");
2036
2037     //  Check Input port mapping
2038     ASSERT_EQ(ti->input_port_map.size(), 2);
2039     int i = ti->input_port_map[0].axis == 1 ? 0 : 1;
2040     ASSERT_EQ(ti->input_port_map[i].axis, 1);
2041     ASSERT_EQ(ti->input_port_map[i].stride, 1);
2042     ASSERT_EQ(ti->input_port_map[i].start, 0);
2043     ASSERT_EQ(ti->input_port_map[i].end, -1);
2044     ASSERT_EQ(ti->input_port_map[i].part_size, 1);
2045     ASSERT_EQ(ti->input_port_map[1 - i].axis, -1);
2046     ASSERT_EQ(ti->input_port_map[1 - i].stride, 1);
2047     ASSERT_EQ(ti->input_port_map[1 - i].start, 0);
2048     ASSERT_EQ(ti->input_port_map[1 - i].end, -1);
2049     ASSERT_EQ(ti->input_port_map[1 - i].part_size, 1);
2050
2051     //  Check Output port mapping
2052     ASSERT_EQ(ti->output_port_map.size(), 1);
2053     ASSERT_EQ(ti->output_port_map[0].axis, 1);
2054     ASSERT_EQ(ti->output_port_map[0].stride, 1);
2055     ASSERT_EQ(ti->output_port_map[0].start, 0);
2056     ASSERT_EQ(ti->output_port_map[0].end, -1);
2057     ASSERT_EQ(ti->output_port_map[0].part_size, 1);
2058
2059     //  No back edges
2060     ASSERT_EQ(ti->back_edges.size(), 1);
2061     ASSERT_EQ(ti->back_edges[0].from, 0);
2062     ASSERT_EQ(ti->back_edges[0].to, 1);
2063     ASSERT_EQ(ti->back_edges[0].axis, -1);
2064     ASSERT_EQ(ti->back_edges[0].stride, 1);
2065     ASSERT_EQ(ti->back_edges[0].start, 0);
2066     ASSERT_EQ(ti->back_edges[0].end, -1);
2067     ASSERT_EQ(ti->back_edges[0].part_size, 1);
2068 }
2069
2070 TEST_F(CNNNetReaderImplTest, canParseScalar) {
2071     std::string model = R"V0G0N(
2072 <net batch="1" name="SimpleNet" version="2">
2073     <layers>
2074         <layer id="0" name="input" precision="FP32" type="Input">
2075             <output>
2076                 <port id="0">
2077                     <dim>1</dim>
2078                     <dim>5</dim>
2079                     <dim>16</dim>
2080                 </port>
2081             </output>
2082         </layer>
2083         <layer id="1" name="scalar" precision="FP32" type="Const">
2084             <output>
2085                 <port id="0"/>
2086             </output>
2087             <blobs>
2088                 <custom offset="0" size="4"/>
2089             </blobs>
2090         </layer>
2091         <layer id="2" name="reshape" precision="FP32" type="Reshape">
2092             <input>
2093                 <port id="0">
2094                     <dim>1</dim>
2095                     <dim>5</dim>
2096                     <dim>16</dim>
2097                 </port>
2098                 <port id="1"/>
2099             </input>
2100             <output>
2101                 <port id="2">
2102                     <dim>90</dim>
2103                 </port>
2104             </output>
2105         </layer>
2106     </layers>
2107     <edges>
2108         <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
2109         <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
2110     </edges>
2111 </net>
2112     )V0G0N";
2113
2114     CNNNetReaderImpl reader(make_shared<V2FormatParserCreator>());
2115     sts = reader.ReadNetwork(model.data(), model.length(), &resp);
2116     ASSERT_EQ(OK, sts) << resp.msg;
2117     auto blob = make_shared_blob<uint8_t>(TensorDesc(Precision::U8, {4}, Layout::C));
2118     blob->allocate();
2119     auto buffer = blob->buffer().as<float*>();
2120     float SCALAR_VALUE = 90;
2121     buffer[0] = SCALAR_VALUE;
2122
2123     sts = reader.SetWeights(blob, &resp);
2124     ASSERT_EQ(OK, sts) << resp.msg;
2125
2126     auto net = reader.getNetwork(&resp);
2127
2128     ASSERT_NE(nullptr, net) << resp.msg;
2129     CNNLayerPtr layer;
2130     sts = net->getLayerByName("scalar", layer, &resp);
2131     ASSERT_EQ(OK, sts) << resp.msg;
2132     ASSERT_NE(nullptr, layer.get());
2133     ASSERT_EQ(layer->type, "Const");
2134     auto actualBlob = layer->blobs.begin()->second;
2135     ASSERT_EQ(actualBlob->buffer().as<float*>()[0], SCALAR_VALUE);
2136     auto scalarDesc = layer->outData[0]->getTensorDesc();
2137     ASSERT_TRUE(scalarDesc.getDims().empty());
2138     ASSERT_EQ(scalarDesc.getLayout(), SCALAR);
2139     ASSERT_EQ(scalarDesc.getPrecision(), Precision::FP32);
2140 }