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authorFrancisMurtagh <francis.murtagh@arm.com>2018-12-06 15:26:04 +0000
committerMatteo Martincigh <matteo.martincigh@arm.com>2018-12-06 15:48:16 +0000
commitf005e313e501a28669e214fd05db04c12c8af7fc (patch)
tree6acc10eff98ce306c6b54d6b53df7602a1a8c31f /src/armnnTfParser
parentba8815f4c38966cc15bb5bcd0960fdd23d89e365 (diff)
downloadarmnn-f005e313e501a28669e214fd05db04c12c8af7fc.tar.gz
IVGCVSW-2277 Remove the input swizzling from ParsePooling2d
* Remove input swizzling from ParsePooling2D and add parameterized tests for NCHW, NHWC and Padding="SAME". Change-Id: I4786fcc31b6ac46bf19d887f007963eb924f0f9f
Diffstat (limited to 'src/armnnTfParser')
-rw-r--r--src/armnnTfParser/TfParser.cpp94
-rw-r--r--src/armnnTfParser/test/Pooling.cpp99
2 files changed, 133 insertions, 60 deletions
diff --git a/src/armnnTfParser/TfParser.cpp b/src/armnnTfParser/TfParser.cpp
index c00722c4ad..d5372a598b 100644
--- a/src/armnnTfParser/TfParser.cpp
+++ b/src/armnnTfParser/TfParser.cpp
@@ -2304,68 +2304,73 @@ ParsedTfOperationPtr TfParser::ParsePooling2d(const tensorflow::NodeDef& nodeDef
std::vector<uint32_t> ksize = ReadMandatoryNodeUint32ListAttribute(nodeDef, "ksize"); // size of pool windows
Pooling2dDescriptor pooling2dDescriptor;
- pooling2dDescriptor.m_PoolType = pooltype;
- pooling2dDescriptor.m_PaddingMethod = PaddingMethod::Exclude;
+ pooling2dDescriptor.m_PoolType = pooltype;
+ pooling2dDescriptor.m_PaddingMethod = PaddingMethod::Exclude;
pooling2dDescriptor.m_OutputShapeRounding = OutputShapeRounding::Floor;
CHECK_DATA_FORMAT(nodeDef, dataFormat, "Pooling2D");
+ DataLayout dataLayout = dataFormat == "NHWC" ? DataLayout::NHWC : DataLayout::NCHW;
+ pooling2dDescriptor.m_DataLayout = dataLayout;
+ DataLayoutIndexed dataLayoutIndexed(dataLayout);
- if (dataFormat == "NHWC")
- {
- pooling2dDescriptor.m_StrideX = strides[2];
- pooling2dDescriptor.m_StrideY = strides[1];
- pooling2dDescriptor.m_PoolWidth = ksize[2];
- pooling2dDescriptor.m_PoolHeight = ksize[1];
- // Swizzles input to supported memory layout.
- inputTensorInfo = armnnUtils::Permuted(inputSlot.GetTensorInfo(), NHWCToArmNN);
- }
- else if (dataFormat == "NCHW")
- {
- pooling2dDescriptor.m_StrideX = strides[3];
- pooling2dDescriptor.m_StrideY = strides[2];
- pooling2dDescriptor.m_PoolWidth = ksize[3];
- pooling2dDescriptor.m_PoolHeight = ksize[2];
- }
+ pooling2dDescriptor.m_StrideX = strides[dataLayoutIndexed.GetWidthIndex()];
+ pooling2dDescriptor.m_StrideY = strides[dataLayoutIndexed.GetHeightIndex()];
+ pooling2dDescriptor.m_PoolWidth = ksize[dataLayoutIndexed.GetWidthIndex()];
+ pooling2dDescriptor.m_PoolHeight = ksize[dataLayoutIndexed.GetHeightIndex()];
- uint32_t inputHeight = inputTensorInfo.GetShape()[2];
- uint32_t inputWidth = inputTensorInfo.GetShape()[3];
+ uint32_t inputHeight = inputTensorInfo.GetShape()[dataLayoutIndexed.GetHeightIndex()];
+ uint32_t inputWidth = inputTensorInfo.GetShape()[dataLayoutIndexed.GetWidthIndex()];
bool padding = false;
TensorInfo outputInfo;
+ unsigned int outputHeight = 0;
+ unsigned int outputWidth = 0;
CHECK_PADDING_TYPE(nodeDef, paddingString);
if (paddingString == "SAME")
{
padding = true;
- outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0],
- inputTensorInfo.GetShape()[1],
- static_cast<uint32_t>(ceil(
- static_cast<float>(inputHeight) /
- static_cast<float>(pooling2dDescriptor.m_StrideY))),
- static_cast<uint32_t>(ceil(
- static_cast<float>(inputWidth) /
- static_cast<float>(pooling2dDescriptor.m_StrideX)))
- }, DataType::Float32);
+
+ outputHeight = static_cast<uint32_t>(ceil(static_cast<float>(inputHeight) /
+ static_cast<float>(pooling2dDescriptor.m_StrideY)));
+ outputWidth = static_cast<uint32_t>(ceil(static_cast<float>(inputWidth) /
+ static_cast<float>(pooling2dDescriptor.m_StrideX)));
}
else if (paddingString == "VALID")
{
padding = false;
- outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0],
- inputTensorInfo.GetShape()[1],
- static_cast<uint32_t>(ceil(
- static_cast<float>(inputHeight - pooling2dDescriptor.m_PoolHeight + 1) /
- static_cast<float>(pooling2dDescriptor.m_StrideY))),
- static_cast<uint32_t>(ceil(
- static_cast<float>(inputWidth - pooling2dDescriptor.m_PoolWidth + 1) /
- static_cast<float>(pooling2dDescriptor.m_StrideX)))
- }, DataType::Float32);
+
+ outputHeight = static_cast<uint32_t>(ceil(
+ static_cast<float>(inputHeight - pooling2dDescriptor.m_PoolHeight + 1) /
+ static_cast<float>(pooling2dDescriptor.m_StrideY)));
+ outputWidth = static_cast<uint32_t>(ceil(
+ static_cast<float>(inputWidth - pooling2dDescriptor.m_PoolWidth + 1) /
+ static_cast<float>(pooling2dDescriptor.m_StrideX)));
+ }
+
+ switch (dataLayout)
+ {
+ case DataLayout::NHWC:
+ outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0],
+ outputHeight,
+ outputWidth,
+ inputTensorInfo.GetShape()[3] },
+ DataType::Float32);
+ break;
+ case DataLayout::NCHW:
+ outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0],
+ inputTensorInfo.GetShape()[1],
+ outputHeight,
+ outputWidth },
+ DataType::Float32);
+ break;
}
CalcPadding(inputWidth, pooling2dDescriptor.m_PoolWidth, pooling2dDescriptor.m_StrideX,
- pooling2dDescriptor.m_PadLeft, pooling2dDescriptor.m_PadRight, padding);
+ pooling2dDescriptor.m_PadLeft, pooling2dDescriptor.m_PadRight, padding);
CalcPadding(inputHeight, pooling2dDescriptor.m_PoolHeight, pooling2dDescriptor.m_StrideY,
- pooling2dDescriptor.m_PadTop, pooling2dDescriptor.m_PadBottom, padding);
+ pooling2dDescriptor.m_PadTop, pooling2dDescriptor.m_PadBottom, padding);
IConnectableLayer* layer = m_Network->AddPooling2dLayer(pooling2dDescriptor, nodeDef.name().c_str());
@@ -2381,14 +2386,7 @@ ParsedTfOperationPtr TfParser::ParsePooling2d(const tensorflow::NodeDef& nodeDef
layer->GetOutputSlot(0).SetTensorInfo(outputInfo);
- if (dataFormat == "NHWC")
- {
- layer = SwizzleInDeswizzleOut(*m_Network, inputSlot, *layer, nodeDef.name());
- }
- else
- {
- inputSlot.Connect(layer->GetInputSlot(0));
- }
+ inputSlot.Connect(layer->GetInputSlot(0));
return std::make_unique<SingleLayerParsedTfOperation>(this, nodeDef, layer);
}
diff --git a/src/armnnTfParser/test/Pooling.cpp b/src/armnnTfParser/test/Pooling.cpp
index 346599fb43..f6de44c95f 100644
--- a/src/armnnTfParser/test/Pooling.cpp
+++ b/src/armnnTfParser/test/Pooling.cpp
@@ -11,7 +11,7 @@ BOOST_AUTO_TEST_SUITE(TensorflowParser)
struct Pooling2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser>
{
- explicit Pooling2dFixture(const char* poolingtype)
+ explicit Pooling2dFixture(const char* poolingtype, std::string dataLayout, std::string paddingOption)
{
m_Prototext = "node {\n"
" name: \"Placeholder\"\n"
@@ -50,24 +50,40 @@ struct Pooling2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser
" attr {\n"
" key: \"data_format\"\n"
" value {\n"
- " s: \"NHWC\"\n"
+ " s: \"");
+ m_Prototext.append(dataLayout);
+ m_Prototext.append("\"\n"
" }\n"
" }\n"
" attr {\n"
" key: \"ksize\"\n"
" value {\n"
" list {\n"
- " i: 1\n"
+
+ " i: 1\n");
+ if(dataLayout == "NHWC")
+ {
+ m_Prototext.append(" i: 2\n"
" i: 2\n"
+ " i: 1\n");
+ }
+ else
+ {
+ m_Prototext.append(" i: 1\n"
" i: 2\n"
- " i: 1\n"
+ " i: 2\n");
+ }
+ m_Prototext.append(
" }\n"
" }\n"
" }\n"
" attr {\n"
" key: \"padding\"\n"
" value {\n"
- " s: \"VALID\"\n"
+ " s: \"");
+ m_Prototext.append(paddingOption);
+ m_Prototext.append(
+ "\"\n"
" }\n"
" }\n"
" attr {\n"
@@ -83,29 +99,88 @@ struct Pooling2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser
" }\n"
"}\n");
- SetupSingleInputSingleOutput({ 1, 2, 2, 1 }, "Placeholder", poolingtype);
+ if(dataLayout == "NHWC")
+ {
+ SetupSingleInputSingleOutput({ 1, 2, 2, 1 }, "Placeholder", poolingtype);
+ }
+ else
+ {
+ SetupSingleInputSingleOutput({ 1, 1, 2, 2 }, "Placeholder", poolingtype);
+ }
}
};
-struct MaxPoolFixture : Pooling2dFixture
+struct MaxPoolFixtureNhwcValid : Pooling2dFixture
{
- MaxPoolFixture() : Pooling2dFixture("MaxPool") {}
+ MaxPoolFixtureNhwcValid() : Pooling2dFixture("MaxPool", "NHWC", "VALID") {}
};
-BOOST_FIXTURE_TEST_CASE(ParseMaxPool, MaxPoolFixture)
+BOOST_FIXTURE_TEST_CASE(ParseMaxPoolNhwcValid, MaxPoolFixtureNhwcValid)
{
RunTest<4>({1.0f, 2.0f, 3.0f, -4.0f}, {3.0f});
}
+struct MaxPoolFixtureNchwValid : Pooling2dFixture
+{
+ MaxPoolFixtureNchwValid() : Pooling2dFixture("MaxPool", "NCHW", "VALID") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseMaxPoolNchwValid, MaxPoolFixtureNchwValid)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, -4.0f}, {3.0f});
+}
+
+struct MaxPoolFixtureNhwcSame : Pooling2dFixture
+{
+ MaxPoolFixtureNhwcSame() : Pooling2dFixture("MaxPool", "NHWC", "SAME") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseMaxPoolNhwcSame, MaxPoolFixtureNhwcSame)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, -4.0f}, {3.0f, 2.0f, 3.0f, -4.0f});
+}
+
+struct MaxPoolFixtureNchwSame : Pooling2dFixture
+{
+ MaxPoolFixtureNchwSame() : Pooling2dFixture("MaxPool", "NCHW", "SAME") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseMaxPoolNchwSame, MaxPoolFixtureNchwSame)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, -4.0f}, {3.0f, 2.0f, 3.0f, -4.0f});
+}
+
+struct AvgPoolFixtureNhwcValid : Pooling2dFixture
+{
+ AvgPoolFixtureNhwcValid() : Pooling2dFixture("AvgPool", "NHWC", "VALID") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseAvgPoolNhwcValid, AvgPoolFixtureNhwcValid)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, 4.0f}, {2.5f});
+}
-struct AvgPoolFixture : Pooling2dFixture
+struct AvgPoolFixtureNchwValid : Pooling2dFixture
{
- AvgPoolFixture() : Pooling2dFixture("AvgPool") {}
+ AvgPoolFixtureNchwValid() : Pooling2dFixture("AvgPool", "NCHW", "VALID") {}
};
-BOOST_FIXTURE_TEST_CASE(ParseAvgPool, AvgPoolFixture)
+BOOST_FIXTURE_TEST_CASE(ParseAvgPoolNchwValid, AvgPoolFixtureNchwValid)
{
RunTest<4>({1.0f, 2.0f, 3.0f, 4.0f}, {2.5f});
}
+struct AvgPoolFixtureNhwcSame : Pooling2dFixture
+{
+ AvgPoolFixtureNhwcSame() : Pooling2dFixture("AvgPool", "NHWC", "SAME") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseAvgPoolNhwcSame, AvgPoolFixtureNhwcSame)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, 4.0f}, {2.5f, 3.0f, 3.5f, 4.0f});
+}
+
+struct AvgPoolFixtureNchwSame : Pooling2dFixture
+{
+ AvgPoolFixtureNchwSame() : Pooling2dFixture("AvgPool", "NCHW", "SAME") {}
+};
+BOOST_FIXTURE_TEST_CASE(ParseAvgPoolNchwSame, AvgPoolFixtureNchwSame)
+{
+ RunTest<4>({1.0f, 2.0f, 3.0f, 4.0f}, {2.5f, 3.0f, 3.5f, 4.0f});
+}
BOOST_AUTO_TEST_SUITE_END()