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//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ParserFlatbuffersFixture.hpp"
TEST_SUITE("TensorflowLiteParser_Reshape")
{
struct ReshapeFixture : public ParserFlatbuffersFixture
{
explicit ReshapeFixture(const std::string& inputShape,
const std::string& outputShape,
const std::string& newShape)
{
m_JsonString = R"(
{
"version": 3,
"operator_codes": [ { "builtin_code": "RESHAPE" } ],
"subgraphs": [ {
"tensors": [
{)";
m_JsonString += R"(
"shape" : )" + inputShape + ",";
m_JsonString += R"(
"type": "UINT8",
"buffer": 0,
"name": "inputTensor",
"quantization": {
"min": [ 0.0 ],
"max": [ 255.0 ],
"scale": [ 1.0 ],
"zero_point": [ 0 ],
}
},
{)";
m_JsonString += R"(
"shape" : )" + outputShape;
m_JsonString += R"(,
"type": "UINT8",
"buffer": 1,
"name": "outputTensor",
"quantization": {
"min": [ 0.0 ],
"max": [ 255.0 ],
"scale": [ 1.0 ],
"zero_point": [ 0 ],
}
}
],
"inputs": [ 0 ],
"outputs": [ 1 ],
"operators": [
{
"opcode_index": 0,
"inputs": [ 0 ],
"outputs": [ 1 ],
"builtin_options_type": "ReshapeOptions",
"builtin_options": {)";
if (!newShape.empty())
{
m_JsonString += R"("new_shape" : )" + newShape;
}
m_JsonString += R"(},
"custom_options_format": "FLEXBUFFERS"
}
],
} ],
"buffers" : [ {}, {} ]
}
)";
}
};
struct ReshapeFixtureWithReshapeDims : ReshapeFixture
{
ReshapeFixtureWithReshapeDims() : ReshapeFixture("[ 1, 9 ]", "[ 3, 3 ]", "[ 3, 3 ]") {}
};
TEST_CASE_FIXTURE(ReshapeFixtureWithReshapeDims, "ParseReshapeWithReshapeDims")
{
SetupSingleInputSingleOutput("inputTensor", "outputTensor");
RunTest<2, armnn::DataType::QAsymmU8>(0,
{ 1, 2, 3, 4, 5, 6, 7, 8, 9 },
{ 1, 2, 3, 4, 5, 6, 7, 8, 9 });
CHECK((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
== armnn::TensorShape({3,3})));
}
struct ReshapeFixtureWithReshapeDimsFlatten : ReshapeFixture
{
ReshapeFixtureWithReshapeDimsFlatten() : ReshapeFixture("[ 3, 3 ]", "[ 9 ]", "[ -1 ]") {}
};
TEST_CASE_FIXTURE(ReshapeFixtureWithReshapeDimsFlatten, "ParseReshapeWithReshapeDimsFlatten")
{
SetupSingleInputSingleOutput("inputTensor", "outputTensor");
RunTest<1, armnn::DataType::QAsymmU8>(0,
{ 1, 2, 3, 4, 5, 6, 7, 8, 9 },
{ 1, 2, 3, 4, 5, 6, 7, 8, 9 });
CHECK((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
== armnn::TensorShape({9})));
}
struct ReshapeFixtureWithReshapeDimsFlattenTwoDims : ReshapeFixture
{
ReshapeFixtureWithReshapeDimsFlattenTwoDims() : ReshapeFixture("[ 3, 2, 3 ]", "[ 2, 9 ]", "[ 2, -1 ]") {}
};
TEST_CASE_FIXTURE(ReshapeFixtureWithReshapeDimsFlattenTwoDims, "ParseReshapeWithReshapeDimsFlattenTwoDims")
{
SetupSingleInputSingleOutput("inputTensor", "outputTensor");
RunTest<2, armnn::DataType::QAsymmU8>(0,
{ 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 },
{ 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 });
CHECK((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
== armnn::TensorShape({2,9})));
}
struct ReshapeFixtureWithReshapeDimsFlattenOneDim : ReshapeFixture
{
ReshapeFixtureWithReshapeDimsFlattenOneDim() : ReshapeFixture("[ 2, 9 ]", "[ 2, 3, 3 ]", "[ 2, -1, 3 ]") {}
};
TEST_CASE_FIXTURE(ReshapeFixtureWithReshapeDimsFlattenOneDim, "ParseReshapeWithReshapeDimsFlattenOneDim")
{
SetupSingleInputSingleOutput("inputTensor", "outputTensor");
RunTest<3, armnn::DataType::QAsymmU8>(0,
{ 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 },
{ 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 });
CHECK((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
== armnn::TensorShape({2,3,3})));
}
struct DynamicReshapeFixtureWithReshapeDimsFlattenOneDim : ReshapeFixture
{
DynamicReshapeFixtureWithReshapeDimsFlattenOneDim() : ReshapeFixture("[ 2, 9 ]",
"[ ]",
"[ 2, -1, 3 ]") {}
};
TEST_CASE_FIXTURE(DynamicReshapeFixtureWithReshapeDimsFlattenOneDim, "DynParseReshapeWithReshapeDimsFlattenOneDim")
{
SetupSingleInputSingleOutput("inputTensor", "outputTensor");
RunTest<3,
armnn::DataType::QAsymmU8,
armnn::DataType::QAsymmU8>(0,
{ { "inputTensor", { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 } } },
{ { "outputTensor", { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 } } },
true);
}
}
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