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| author | josh minor <josh.minor@arm.com> | 2019-11-13 10:55:17 -0600 |
|---|---|---|
| committer | Matteo Martincigh <matteo.martincigh@arm.com> | 2019-11-19 14:45:53 +0000 |
| commit | ba424d2aff70a13e1a16c4f9018a0bea4e5c11b3 (patch) | |
| tree | 35c3c0823764888341686110405dabba35a2a426 /src/armnnTfLiteParser/test/Slice.cpp | |
| parent | 52ec3463086a12282d8b833521e9e32d1055c6a6 (diff) | |
| download | armnn-ba424d2aff70a13e1a16c4f9018a0bea4e5c11b3.tar.gz | |
IVGCVSW-1530 Add TfLite slice parser and fix transpose perm vector creation
* TfLite slice parser and relevant tests added
* TfLite transpose parser logic added to translate Tf/np permutation
vector definitions to Armnn definitions
* TfLite transpose parser no permute data test modified to include
data for default permutation vector when none specified
Signed-off-by: josh minor <josh.minor@arm.com>
Change-Id: Iebd30971bd180593dc6b8f0d5be1d1bc61a3a5bf
Diffstat (limited to 'src/armnnTfLiteParser/test/Slice.cpp')
| -rw-r--r-- | src/armnnTfLiteParser/test/Slice.cpp | 176 |
1 files changed, 176 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/test/Slice.cpp b/src/armnnTfLiteParser/test/Slice.cpp new file mode 100644 index 0000000000..17d1b1a68c --- /dev/null +++ b/src/armnnTfLiteParser/test/Slice.cpp @@ -0,0 +1,176 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include <boost/test/unit_test.hpp> +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + +struct SliceFixture : public ParserFlatbuffersFixture +{ + explicit SliceFixture(const std::string & inputShape, + const std::string & outputShape, + const std::string & beginData, + const std::string & sizeData) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ + { + "builtin_code": "SLICE", + "version": 1 + } + ], + "subgraphs": [ + { + "tensors": [ + { + "shape": )" + inputShape + R"(, + "type": "FLOAT32", + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ + 0.0 + ], + "max": [ + 255.0 + ], + "details_type": 0, + "quantized_dimension": 0 + }, + "is_variable": false + }, + { + "shape": )" + outputShape + R"(, + "type": "FLOAT32", + "buffer": 1, + "name": "outputTensor", + "quantization": { + "details_type": 0, + "quantized_dimension": 0 + }, + "is_variable": false + })"; + m_JsonString += R"(, + { + "shape": [ + 3 + ], + "type": "INT32", + "buffer": 2, + "name": "beginTensor", + "quantization": { + } + })"; + m_JsonString += R"(, + { + "shape": [ + 3 + ], + "type": "INT32", + "buffer": 3, + "name": "sizeTensor", + "quantization": { + } + })"; + m_JsonString += R"(], + "inputs": [ + 0 + ], + "outputs": [ + 1 + ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ + 0, + 2, + 3)"; + m_JsonString += R"(], + "outputs": [ + 1 + ], + mutating_variable_inputs: [ + ] + } + ] + } + ], + "description": "TOCO Converted.", + "buffers": [ + { }, + { })"; + m_JsonString += R"(,{"data": )" + beginData + R"( })"; + m_JsonString += R"(,{"data": )" + sizeData + R"( })"; + m_JsonString += R"( + ] + } + )"; + SetupSingleInputSingleOutput("inputTensor", "outputTensor"); + } +}; + +struct SliceFixtureSingleDim : SliceFixture +{ + SliceFixtureSingleDim() : SliceFixture("[ 3, 2, 3 ]", + "[ 1, 1, 3 ]", + "[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]", + "[ 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(SliceSingleDim, SliceFixtureSingleDim) +{ + RunTest<3, armnn::DataType::Float32>( + 0, + {{"inputTensor", { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 }}}, + {{"outputTensor", { 3, 3, 3 }}}); + + BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape() + == armnn::TensorShape({1,1,3}))); +} + +struct SliceFixtureD123 : SliceFixture +{ + SliceFixtureD123() : SliceFixture("[ 3, 2, 3 ]", + "[ 1, 2, 3 ]", + "[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]", + "[ 1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(SliceD123, SliceFixtureD123) +{ + RunTest<3, armnn::DataType::Float32>( + 0, + {{"inputTensor", { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 }}}, + {{"outputTensor", { 3, 3, 3, 4, 4, 4 }}}); + + BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape() + == armnn::TensorShape({1,2,3}))); +} + +struct SliceFixtureD213 : SliceFixture +{ + SliceFixtureD213() : SliceFixture("[ 3, 2, 3 ]", + "[ 2, 1, 3 ]", + "[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]", + "[ 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(SliceD213, SliceFixtureD213) +{ + RunTest<3, armnn::DataType::Float32>( + 0, + {{"inputTensor", { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 }}}, + {{"outputTensor", { 3, 3, 3, 5, 5, 5 }}}); + + BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape() + == armnn::TensorShape({2,1,3}))); +} + +BOOST_AUTO_TEST_SUITE_END()
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