| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include <boost/test/unit_test.hpp> |
| #include "armnnTfParser/ITfParser.hpp" |
| #include "ParserPrototxtFixture.hpp" |
| |
| #include <array> |
| #include <string> |
| #include <iostream> |
| |
| BOOST_AUTO_TEST_SUITE(TensorflowParser) |
| |
| struct Convolution2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> |
| { |
| explicit Convolution2dFixture(const std::string& dataLayout, const std::string& paddingType) |
| : Convolution2dFixture(dataLayout, paddingType, 1) |
| {} |
| |
| // Dilation: 0 - dilations attribute is not included; |
| // Dilation: >0 - dilations attribute set to [1,v,v,1], where v is the value of the dilation arg |
| explicit Convolution2dFixture(const std::string& dataLayout, const std::string& paddingType, |
| int stride, int dilation = 0) |
| { |
| std::string strideString (" i: 1 \n" |
| " i: 1 \n"); |
| if (dataLayout == "NHWC") |
| { |
| strideString.append(" i: " + std::to_string(stride) + " \n" |
| " i: 1 \n"); |
| } |
| else // dataLayout == "NCHW" |
| { |
| strideString.append(" i: 1 \n" |
| " i: " + std::to_string(stride) + " \n"); |
| } |
| |
| std::string dilationString; |
| if (dataLayout == "NHWC") |
| { |
| dilationString.append(" i: 1 \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: 1 \n"); |
| } |
| else // dataLayout == "NCHW" |
| { |
| dilationString.append(" i: 1 \n" |
| " i: 1 \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: " + std::to_string(dilation) + " \n"); |
| } |
| |
| m_Prototext = "node { \n" |
| " name: \"graphInput\" \n" |
| " op: \"Placeholder\" \n" |
| " attr { \n" |
| " key: \"dtype\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"shape\" \n" |
| " value { \n" |
| " shape { \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| " node { \n" |
| " name: \"Const_1\" \n" |
| " op: \"Const\" \n" |
| " attr { \n" |
| " key: \"dtype\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"value\" \n" |
| " value { \n" |
| " tensor { \n" |
| " dtype: DT_FLOAT \n" |
| " tensor_shape { \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " dim { \n" |
| " size: 3 \n" |
| " } \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " } \n" |
| " tensor_content: \"\\000\\000\\000?\\000\\000\\200?\\000\\000\\000?\" \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| "} \n" |
| "node { \n" |
| " name: \"potato\" \n" |
| " op: \"Conv2D\" \n" |
| " input: \"graphInput\" \n" |
| " input: \"Const_1\" \n" |
| " attr { \n" |
| " key: \"T\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"data_format\" \n" |
| " value { \n" |
| " s: \""; |
| m_Prototext.append(dataLayout); |
| m_Prototext.append("\"\n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"padding\" \n" |
| " value { \n" |
| " s: \""); |
| m_Prototext.append(paddingType); |
| m_Prototext.append("\"\n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"strides\" \n" |
| " value { \n" |
| " list { \n"); |
| m_Prototext.append(strideString); |
| |
| m_Prototext.append(" } \n" |
| " } \n" |
| " } \n"); |
| |
| if (dilation > 0) |
| { |
| m_Prototext.append(" attr { \n" |
| " key: \"dilations\" \n" |
| " value { \n" |
| " list { \n"); |
| m_Prototext.append(dilationString); |
| |
| m_Prototext.append(" } \n" |
| " } \n" |
| " } \n"); |
| } |
| m_Prototext.append(" attr { \n" |
| " key: \"use_cudnn_on_gpu\" \n" |
| " value { \n" |
| " b: false \n" |
| " } \n" |
| " } \n" |
| "} \n"); |
| |
| // Manual height computation based on stride parameter. |
| ARMNN_ASSERT_MSG(stride == 1 || stride == 2, "Add support for strides other than 1 or 2."); |
| std::array<unsigned int, 4> dims; |
| if (dataLayout == "NHWC") |
| { |
| dims = { 1u, (stride == 2 ? 3u : 2u), 3u, 1u }; |
| } |
| else // dataLayout == "NCHW" |
| { |
| dims = { 1u, 1u, (stride == 2 ? 3u : 2u), 3u }; |
| } |
| |
| SetupSingleInputSingleOutput(armnn::TensorShape(4, dims.data()), "graphInput", "potato"); |
| } |
| }; |
| |
| struct Convolution2dNhwcSameFixture : Convolution2dFixture |
| { |
| Convolution2dNhwcSameFixture() : Convolution2dFixture("NHWC", "SAME", 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dNhwcSame, Convolution2dNhwcSameFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); |
| } |
| |
| struct Convolution2dNchwSameFixture : Convolution2dFixture |
| { |
| Convolution2dNchwSameFixture() : Convolution2dFixture("NCHW", "SAME", 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dNchwSame, Convolution2dNchwSameFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); |
| } |
| |
| |
| struct Convolution2dNhwcValidFixture : Convolution2dFixture |
| { |
| Convolution2dNhwcValidFixture() : Convolution2dFixture("NHWC", "VALID", 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dNhwcValid, Convolution2dNhwcValidFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {4, 10}); |
| } |
| |
| struct Convolution2dNchwValidFixture : Convolution2dFixture |
| { |
| Convolution2dNchwValidFixture() : Convolution2dFixture("NCHW", "VALID", 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dNchwValid, Convolution2dNchwValidFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {4, 10}); |
| } |
| |
| |
| struct Convolution2dStride2NhwcSameFixture : Convolution2dFixture |
| { |
| Convolution2dStride2NhwcSameFixture() : Convolution2dFixture("NHWC", "SAME", 2){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NhwcSame, Convolution2dStride2NhwcSameFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {2, 4, 6.5, 8.5, 11, 13}); |
| } |
| |
| struct Convolution2dStride2NchwSameFixture : Convolution2dFixture |
| { |
| Convolution2dStride2NchwSameFixture() : Convolution2dFixture("NCHW", "SAME", 2){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NchwSame, Convolution2dStride2NchwSameFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {2, 4, 6.5, 8.5, 11, 13}); |
| } |
| |
| |
| struct Convolution2dStride2NhwcValidFixture : Convolution2dFixture |
| { |
| Convolution2dStride2NhwcValidFixture() : Convolution2dFixture("NHWC", "VALID", 2){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NhwcValid, Convolution2dStride2NhwcValidFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {4, 10, 16}); |
| } |
| |
| struct Convolution2dStride2NchwValidFixture : Convolution2dFixture |
| { |
| Convolution2dStride2NchwValidFixture() : Convolution2dFixture("NCHW", "VALID", 2){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NchwValid, Convolution2dStride2NchwValidFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {4, 10, 16}); |
| } |
| |
| |
| struct Convolution2dDilation1NhwcFixture : Convolution2dFixture |
| { |
| Convolution2dDilation1NhwcFixture() : Convolution2dFixture("NHWC", "SAME", 1, 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dDilation1Nhwc, Convolution2dDilation1NhwcFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); |
| } |
| |
| struct Convolution2dDilation1NchwFixture : Convolution2dFixture |
| { |
| Convolution2dDilation1NchwFixture() : Convolution2dFixture("NCHW", "SAME", 1, 1){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dDilation1Nchw, Convolution2dDilation1NchwFixture) |
| { |
| RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); |
| } |
| |
| struct Convolution2dDilationFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> |
| { |
| explicit Convolution2dDilationFixture(const std::string& dataLayout, const std::string& paddingType) |
| : Convolution2dDilationFixture(dataLayout, paddingType, 1) |
| {} |
| |
| explicit Convolution2dDilationFixture(const std::string& dataLayout, const std::string& paddingType, |
| int stride, int dilation = 0) |
| { |
| std::string strideString; |
| if (dataLayout == "NHWC") |
| { |
| strideString.append(" i: 1 \n" |
| " i: " + std::to_string(stride) + " \n" |
| " i: " + std::to_string(stride) + " \n" |
| " i: 1 \n"); |
| } |
| else // dataLayout == "NCHW" |
| { |
| strideString.append(" i: 1 \n" |
| " i: 1 \n" |
| " i: " + std::to_string(stride) + " \n" |
| " i: " + std::to_string(stride) + " \n"); |
| } |
| |
| std::string dilationString; |
| if (dataLayout == "NHWC") |
| { |
| dilationString.append(" i: 1 \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: 1 \n"); |
| } |
| else // dataLayout == "NCHW" |
| { |
| dilationString.append(" i: 1 \n" |
| " i: 1 \n" |
| " i: " + std::to_string(dilation) + " \n" |
| " i: " + std::to_string(dilation) + " \n"); |
| } |
| |
| m_Prototext = "node { \n" |
| " name: \"graphInput\" \n" |
| " op: \"Placeholder\" \n" |
| " attr { \n" |
| " key: \"dtype\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"shape\" \n" |
| " value { \n" |
| " shape { \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| " node { \n" |
| " name: \"Const_1\" \n" |
| " op: \"Const\" \n" |
| " attr { \n" |
| " key: \"dtype\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"value\" \n" |
| " value { \n" |
| " tensor { \n" |
| " dtype: DT_FLOAT \n" |
| " tensor_shape { \n" |
| " dim { \n" |
| " size: 3 \n" |
| " } \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " dim { \n" |
| " size: 1 \n" |
| " } \n" |
| " } \n" |
| " tensor_content: \"\\001\\000\\000?\\000\\000\\000?\\001\\000\\000?\" \n" |
| " } \n" |
| " } \n" |
| " } \n" |
| "} \n" |
| "node { \n" |
| " name: \"potato\" \n" |
| " op: \"Conv2D\" \n" |
| " input: \"graphInput\" \n" |
| " input: \"Const_1\" \n" |
| " attr { \n" |
| " key: \"T\" \n" |
| " value { \n" |
| " type: DT_FLOAT \n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"data_format\" \n" |
| " value { \n" |
| " s: \""; |
| m_Prototext.append(dataLayout); |
| m_Prototext.append("\"\n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"padding\" \n" |
| " value { \n" |
| " s: \""); |
| m_Prototext.append(paddingType); |
| m_Prototext.append("\"\n" |
| " } \n" |
| " } \n" |
| " attr { \n" |
| " key: \"strides\" \n" |
| " value { \n" |
| " list { \n"); |
| m_Prototext.append(strideString); |
| |
| m_Prototext.append(" } \n" |
| " } \n" |
| " } \n"); |
| |
| if (dilation > 0) |
| { |
| m_Prototext.append(" attr { \n" |
| " key: \"dilations\" \n" |
| " value { \n" |
| " list { \n"); |
| m_Prototext.append(dilationString); |
| |
| m_Prototext.append(" } \n" |
| " } \n" |
| " } \n"); |
| } |
| m_Prototext.append(" attr { \n" |
| " key: \"use_cudnn_on_gpu\" \n" |
| " value { \n" |
| " b: false \n" |
| " } \n" |
| " } \n" |
| "} \n"); |
| |
| // Manual height computation based on stride parameter. |
| std::array<unsigned int, 4> dims = { 1u, 1u, 6u, 6u };; |
| |
| SetupSingleInputSingleOutput(armnn::TensorShape(4, dims.data()), "graphInput", "potato"); |
| } |
| }; |
| |
| struct Convolution2dDilation2NchwValidFixture : Convolution2dDilationFixture |
| { |
| Convolution2dDilation2NchwValidFixture() : Convolution2dDilationFixture("NCHW", "VALID", 1, 2){} |
| }; |
| BOOST_FIXTURE_TEST_CASE(ParseConv2dDilation2NchwValid, Convolution2dDilation2NchwValidFixture) |
| { |
| RunTest<4>({1.0, 2.0, 3.0, 4.0, 5.0, 6.0, |
| 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, |
| 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, |
| 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, |
| 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, |
| 7.0, 8.0, 9.0, 10.0, 11.0, 12.0}, |
| {1.5f, 3.0f, 4.5f, 6.0f, 7.5f, 9.0f, 10.5f, 12.f, 13.5f, 15.0f, 16.5f, 18.0f}); |
| } |
| |
| |
| BOOST_AUTO_TEST_SUITE_END() |
