| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include <boost/test/unit_test.hpp> |
| #include "ParserFlatbuffersFixture.hpp" |
| #include "../TfLiteParser.hpp" |
| |
| #include <string> |
| #include <iostream> |
| |
| BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) |
| |
| struct DepthwiseConvolution2dFixture : public ParserFlatbuffersFixture |
| { |
| explicit DepthwiseConvolution2dFixture(const std::string& inputShape, |
| const std::string& outputShape, |
| const std::string& filterShape, |
| const std::string& filterData, |
| const std::string& strides, |
| const std::string& paddingType, |
| const std::string biasShape = "", |
| const std::string biasData = "") |
| { |
| std::string inputTensors = "[ 0, 2 ]"; |
| std::string biasTensor = ""; |
| std::string biasBuffer = ""; |
| if (biasShape.size() > 0 && biasData.size() > 0) |
| { |
| inputTensors = "[ 0, 2, 3 ]"; |
| biasTensor = R"( |
| { |
| "shape": )" + biasShape + R"( , |
| "type": "INT32", |
| "buffer": 3, |
| "name": "biasTensor", |
| "quantization": { |
| "min": [ 0.0 ], |
| "max": [ 255.0 ], |
| "scale": [ 1.0 ], |
| "zero_point": [ 0 ], |
| } |
| } )"; |
| biasBuffer = R"( |
| { "data": )" + biasData + R"(, }, )"; |
| } |
| m_JsonString = R"( |
| { |
| "version": 3, |
| "operator_codes": [ { "builtin_code": "DEPTHWISE_CONV_2D" } ], |
| "subgraphs": [ { |
| "tensors": [ |
| { |
| "shape": )" + inputShape + R"(, |
| "type": "UINT8", |
| "buffer": 0, |
| "name": "inputTensor", |
| "quantization": { |
| "min": [ 0.0 ], |
| "max": [ 255.0 ], |
| "scale": [ 1.0 ], |
| "zero_point": [ 0 ], |
| } |
| }, |
| { |
| "shape": )" + outputShape + R"(, |
| "type": "UINT8", |
| "buffer": 1, |
| "name": "outputTensor", |
| "quantization": { |
| "min": [ 0.0 ], |
| "max": [ 511.0 ], |
| "scale": [ 2.0 ], |
| "zero_point": [ 0 ], |
| } |
| }, |
| { |
| "shape": )" + filterShape + R"(, |
| "type": "UINT8", |
| "buffer": 2, |
| "name": "filterTensor", |
| "quantization": { |
| "min": [ 0.0 ], |
| "max": [ 255.0 ], |
| "scale": [ 1.0 ], |
| "zero_point": [ 0 ], |
| } |
| }, )" + biasTensor + R"( |
| ], |
| "inputs": [ 0 ], |
| "outputs": [ 1 ], |
| "operators": [ |
| { |
| "opcode_index": 0, |
| "inputs": )" + inputTensors + R"(, |
| "outputs": [ 1 ], |
| "builtin_options_type": "DepthwiseConv2DOptions", |
| "builtin_options": { |
| "padding": ")" + paddingType + R"(", |
| "stride_w": )" + strides+ R"(, |
| "stride_h": )" + strides+ R"(, |
| "depth_multiplier": 1, |
| "fused_activation_function": "NONE" |
| }, |
| "custom_options_format": "FLEXBUFFERS" |
| } |
| ], |
| } ], |
| "buffers" : [ |
| { }, |
| { }, |
| { "data": )" + filterData + R"(, }, )" |
| + biasBuffer + R"( |
| ] |
| } |
| )"; |
| SetupSingleInputSingleOutput("inputTensor", "outputTensor"); |
| } |
| }; |
| |
| struct DepthwiseConvolution2dSameFixture : DepthwiseConvolution2dFixture |
| { |
| DepthwiseConvolution2dSameFixture() |
| : DepthwiseConvolution2dFixture("[ 1, 3, 3, 1 ]", // inputShape |
| "[ 1, 3, 3, 1 ]", // outputShape |
| "[ 1, 3, 3, 1 ]", // filterShape |
| "[ 9,8,7, 6,5,4, 3,2,1 ]", // filterData |
| "1", // stride w and h |
| "SAME") // padding type |
| {} |
| }; |
| |
| BOOST_FIXTURE_TEST_CASE(ParseDepthwiseConv2DSame, DepthwiseConvolution2dSameFixture) |
| { |
| RunTest<4, armnn::DataType::QuantisedAsymm8>( |
| 0, |
| { 0, 1, 2, |
| 3, 4, 5, |
| 6, 7, 8 }, |
| // the expected values were generated using the example python implementation at |
| // https://eli.thegreenplace.net/2018/depthwise-separable-convolutions-for-machine-learning/ |
| // divide the expected values by the output scale, as it is not 1.0 |
| { 14/2, 35/2, 38/2, |
| 57/2, 120/2, 111/2, |
| 110/2, 197/2, 158/2 }); |
| } |
| |
| struct DepthwiseConvolution2dValidFixture : DepthwiseConvolution2dFixture |
| { |
| DepthwiseConvolution2dValidFixture () |
| : DepthwiseConvolution2dFixture("[ 1, 3, 3, 1 ]", // inputShape |
| "[ 1, 1, 1, 1 ]", // outputShape |
| "[ 1, 3, 3, 1 ]", // filterShape |
| "[ 9,8,7, 6,5,4, 3,2,1 ]", // filterData |
| "1", // stride w and h |
| "VALID") // padding type |
| {} |
| }; |
| |
| BOOST_FIXTURE_TEST_CASE(ParseDepthwiseConv2DValid, DepthwiseConvolution2dValidFixture) |
| { |
| RunTest<4, armnn::DataType::QuantisedAsymm8>( |
| 0, |
| { 0, 1, 2, |
| 3, 4, 5, |
| 6, 7, 8 }, |
| // divide the expected values by the output scale, as it is not 1.0 |
| { 120/2 }); |
| } |
| |
| struct DepthwiseConvolution2dSameBiasFixture : DepthwiseConvolution2dFixture |
| { |
| DepthwiseConvolution2dSameBiasFixture() |
| : DepthwiseConvolution2dFixture("[ 1, 3, 3, 1 ]", // inputShape |
| "[ 1, 3, 3, 1 ]", // outputShape |
| "[ 1, 3, 3, 1 ]", // filterShape |
| "[ 9,8,7, 6,5,4, 3,2,1 ]", // filterData |
| "1", // stride w and h |
| "SAME", // padding type |
| "[ 1 ]", // biasShape |
| "[ 10, 0, 0, 0 ]") // biasData |
| {} |
| }; |
| |
| BOOST_FIXTURE_TEST_CASE(ParseDepthwiseConv2DSameBias, DepthwiseConvolution2dSameBiasFixture) |
| { |
| RunTest<4, armnn::DataType::QuantisedAsymm8>( |
| 0, |
| { 0, 1, 2, |
| 3, 4, 5, |
| 6, 7, 8 }, |
| // divide the expected values by the output scale, as it is not 1.0 |
| { ( 14+10)/2, ( 35+10)/2, ( 38+10)/2, |
| ( 57+10)/2, (120+10)/2, (111+10)/2, |
| (110+10)/2, (197+10)/2, (158+10)/2 }); |
| } |
| |
| BOOST_AUTO_TEST_SUITE_END() |
