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add tests for 5 ops based on model zoo (#3062)

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* add tests for 5 ops based on model zoo

* remove unnecessary layers from the test

* add test case with merge_repeated=0

* remove unnecessary layers and add new test casae with do_softmax=0

* remove unnecessary layers from the test
This commit is contained in:
Bartek Szmelczynski 2020-11-16 13:19:31 +01:00 committed by GitHub
parent bb369f189a
commit e70b2bf469
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5 changed files with 771 additions and 0 deletions
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120
inference-engine/tests/functional/inference_engine/ngraph_reader/binary_convolution_tests.cpp Normal file
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// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadBinaryConvolutionNetwork) {
std::string model = R"V0G0N(
<net name="model_bin" version="10">
<layers>
<layer id="0" name="612/placeholder_port_0" type="Parameter" version="opset1">
<data shape="1,64,28,28" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</output>
</layer>
<layer id="1" name="626/Output_0/Data__const" type="Const" version="opset1">
<data offset="264" size="512" shape="64,64,1,1" element_type="u1"/>
<output>
<port id="0" precision="U1">
<dim>64</dim>
<dim>64</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
<layer id="2" name="627" type="BinaryConvolution" version="opset1">
<data strides="1,1" dilations="1,1" pads_begin="0,0" pads_end="0,0" output_padding="0,0" pad_value="-1.0" mode="xnor-popcount"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
<port id="1">
<dim>64</dim>
<dim>64</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</output>
</layer>
<layer id="3" name="627/sink_port_0" type="Result" version="opset1">
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
<edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="model_bin" version="7">
<layers>
<layer id="0" name="612/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</output>
</layer>
<layer id="1" name="627" type="BinaryConvolution" version="opset1">
<data group="1" strides="1,1" dilations="1,1" kernel="1,1" pads_begin="0,0" pads_end="0,0" output="64" pad_value="-1.0" mode="xnor-popcount" input="64"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>28</dim>
<dim>28</dim>
</port>
</output>
<blobs>
<weights offset="264" size="512" precision="U8"/>
</blobs>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 1288);
}

246
inference-engine/tests/functional/inference_engine/ngraph_reader/ctc_greedy_decoder_tests.cpp Normal file
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// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadCTCGreedyDecoderNetwork) {
std::string model = R"V0G0N(
<net name="ctcgreedydecoder" version="10">
<layers>
<layer id="0" name="CTCGreedyDecoder/placeholder_port_0" type="Parameter" version="opset1">
<data shape="20,8,128" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
</output>
</layer>
<layer id="1" name="Fill/Broadcast/Output_0/Data__const" type="Const" version="opset1">
<data offset="0" size="640" shape="20,8" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
</port>
</output>
</layer>
<layer id="2" name="CTCGreedyDecoder" type="CTCGreedyDecoder" version="opset1">
<data ctc_merge_repeated="1"/>
<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
<layer id="3" name="CTCGreedyDecoder/sink_port_0" type="Result" version="opset1">
<input>
<port id="0">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
<edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="ctcgreedydecoder" version="7">
<layers>
<layer id="0" name="CTCGreedyDecoder/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
</output>
</layer>
<layer id="1" name="Fill/Broadcast/Output_0/Data__const" type="Const" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
</port>
</output>
<blobs>
<custom offset="0" size="640" precision="FP32"/>
</blobs>
</layer>
<layer id="2" name="CTCGreedyDecoder" type="CTCGreedyDecoder" version="opset1">
<data ctc_merge_repeated="1"/>
<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 640);
}
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadCTCGreedyDecoderNoMergeNetwork) {
std::string model = R"V0G0N(
<net name="ctcgreedydecoder" version="10">
<layers>
<layer id="0" name="CTCGreedyDecoder/placeholder_port_0" type="Parameter" version="opset1">
<data shape="20,8,128" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
</output>
</layer>
<layer id="1" name="Fill/Broadcast/Output_0/Data__const" type="Const" version="opset1">
<data offset="0" size="640" shape="20,8" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
</port>
</output>
</layer>
<layer id="2" name="CTCGreedyDecoder" type="CTCGreedyDecoder" version="opset1">
<data ctc_merge_repeated="0"/>
<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
<layer id="3" name="CTCGreedyDecoder/sink_port_0" type="Result" version="opset1">
<input>
<port id="0">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
<edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="ctcgreedydecoder" version="7">
<layers>
<layer id="0" name="CTCGreedyDecoder/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
</output>
</layer>
<layer id="1" name="Fill/Broadcast/Output_0/Data__const" type="Const" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>20</dim>
<dim>8</dim>
</port>
</output>
<blobs>
<custom offset="0" size="640" precision="FP32"/>
</blobs>
</layer>
<layer id="2" name="CTCGreedyDecoder" type="CTCGreedyDecoder" version="opset1">
<data ctc_merge_repeated="0"/>
<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 640);
}

122
inference-engine/tests/functional/inference_engine/ngraph_reader/group_convolution_tests.cpp Normal file
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@ -0,0 +1,122 @@
// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadGroupConvolutionNetwork) {
std::string model = R"V0G0N(
<net name="GroupConvolution" version="10">
<layers>
<layer id="0" name="in1" type="Parameter" version="opset1">
<data shape="1,64,65,51" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</output>
</layer>
<layer id="1" name="const_val" type="Const" version="opset1">
<data offset="0" size="2304" shape="64,1,1,3,3" element_type="f32"/>
<output>
<port id="1" precision="FP32">
<dim>64</dim>
<dim>1</dim>
<dim>1</dim>
<dim>3</dim>
<dim>3</dim>
</port>
</output>
</layer>
<layer id="2" name="GroupConvolutionOp" type="GroupConvolution" version="opset1">
<data strides="1,1" dilations="1,1" pads_begin="1,1" pads_end="1,1" output_padding="0,0"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
<port id="1">
<dim>64</dim>
<dim>1</dim>
<dim>1</dim>
<dim>3</dim>
<dim>3</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</output>
</layer>
<layer id="3" name="140/sink_port_0" type="Result" version="opset1">
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
<edge from-layer="1" from-port="1" to-layer="2" to-port="1"/>
<edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="GroupConvolution" version="7">
<layers>
<layer id="0" name="in1" type="Input" version="opset1">
<data shape="1,64,65,51" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</output>
</layer>
<layer id="1" name="GroupConvolutionOp" type="Convolution" version="opset1">
<data group="64" strides="1,1" dilations="1,1" kernel="3,3" pads_begin="1,1" pads_end="1,1" output="64"/>
<input>
<port id="0">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</input>
<output>
<port id="2" precision="FP32">
<dim>1</dim>
<dim>64</dim>
<dim>65</dim>
<dim>51</dim>
</port>
</output>
<blobs>
<weights offset="0" size="2304" precision="FP32"/>
</blobs>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 2304);
}

185
inference-engine/tests/functional/inference_engine/ngraph_reader/region_yolo_tests.cpp Normal file
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// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadRegionYoloNetwork) {
std::string model = R"V0G0N(
<net name="frozen_graph" version="10">
<layers>
<layer id="0" name="yolo_out_postprocess/placeholder_port_0" type="Parameter" version="opset1">
<data element_type="f32" shape="1,125,13,13"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>125</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="1" name="yolo_out_postprocess/YoloRegion" type="RegionYolo" version="opset1">
<data coords="4" mask="0" classes="20" num="5" axis="1" end_axis="3" do_softmax="1" anchors="1.3221,1.73145,3.19275,4.00944,5.05587,8.09892,9.47112,4.84053,11.2364,10.0071"/>
<input>
<port id="0">
<dim>1</dim>
<dim>125</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>21125</dim>
</port>
</output>
</layer>
<layer id="2" name="364" type="Result" version="opset1">
<input>
<port id="0">
<dim>1</dim>
<dim>21125</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
<edge from-layer="1" from-port="1" to-layer="2" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="frozen_graph" version="7">
<layers>
<layer id="0" name="yolo_out_postprocess/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>125</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="1" name="yolo_out_postprocess/YoloRegion" type="RegionYolo" version="opset1">
<data coords="4" classes="20" num="5" axis="1" end_axis="3" do_softmax="1" mask="0" anchors="1.3221,1.73145,3.19275,4.00944,5.05587,8.09892,9.47112,4.84053,11.2364,10.0071"/>
<input>
<port id="0">
<dim>1</dim>
<dim>125</dim>
<dim>13</dim>
<dim>13</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>21125</dim>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 4);
}
TEST_F(NGraphReaderTests, ReadRegionYoloMaskNetwork) {
std::string model = R"V0G0N(
<net name="frozen_graph" version="10">
<layers>
<layer id="0" name="yolo_out_postprocess/placeholder_port_0" type="Parameter" version="opset1">
<data element_type="f32" shape="1,255,26,26"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="1" name="yolo_out_postprocess/YoloRegion" type="RegionYolo" version="opset1">
<data anchors="10,14,23,27,37,58,81,82,135,169,344,319" axis="1" classes="80" coords="4" do_softmax="0" end_axis="3" mask="0,1,2" num="6"/>
<input>
<port id="0">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="2" name="364" type="Result" version="opset1">
<input>
<port id="0">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
<edge from-layer="1" from-port="1" to-layer="2" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="frozen_graph" version="7">
<layers>
<layer id="0" name="yolo_out_postprocess/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="1" name="yolo_out_postprocess/YoloRegion" type="RegionYolo" version="opset1">
<data anchors="10,14,23,27,37,58,81,82,135,169,344,319" axis="1" classes="80" coords="4" do_softmax="0" end_axis="3" mask="0,1,2" num="6"/>
<input>
<port id="0">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>255</dim>
<dim>26</dim>
<dim>26</dim>>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7, 4);
}

98
inference-engine/tests/functional/inference_engine/ngraph_reader/reorg_yolo_tests.cpp Normal file
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// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ReadReorgYoloNetwork) {
std::string model = R"V0G0N(
<net name="frozen_graph" version="10">
<layers>
<layer id="0" name="yolov2/yolov2_feature/lower_features/downsample/placeholder_port_0" type="Parameter" version="opset1">
<data shape="1,26,64,26" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>26</dim>
<dim>64</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="1" name="yolov2/yolov2_feature/lower_features/downsample" type="ReorgYolo" version="opset2">
<data stride="2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>26</dim>
<dim>64</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>104</dim>
<dim>32</dim>
<dim>13</dim>
</port>
</output>
</layer>
<layer id="2" name="365" type="Result" version="opset1">
<input>
<port id="0">
<dim>1</dim>
<dim>104</dim>
<dim>32</dim>
<dim>13</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
<edge from-layer="1" from-port="1" to-layer="2" to-port="0"/>
</edges>
</net>
)V0G0N";
std::string modelV7 = R"V0G0N(
<net name="frozen_graph" version="7">
<layers>
<layer id="0" name="yolov2/yolov2_feature/lower_features/downsample/placeholder_port_0" type="Input" version="opset1">
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>26</dim>
<dim>64</dim>
<dim>26</dim>
</port>
</output>
</layer>
<layer id="1" name="yolov2/yolov2_feature/lower_features/downsample" type="ReorgYolo" version="opset2">
<data stride="2"/>
<input>
<port id="0">
<dim>1</dim>
<dim>26</dim>
<dim>64</dim>
<dim>26</dim>
</port>
</input>
<output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>104</dim>
<dim>32</dim>
<dim>13</dim>
</port>
</output>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
compareIRs(model, modelV7);
}