GitHub #557 wrong result in int8 model
* Added support for qasymms8 (int8) to ImageTensorGenerator
* Added qasymmu8 as alias for qasymm8 in ImageTensorGenerator
* Added support for qasymms8 (int8) to ExecuteNetwork
* Added qasymmu8 as alias for qasymm8 in ExecuteNetwork
* Set tflite to be the default model format in ImageTensorGenerator as
it's the only supported model format.
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: Ieda7b78e668ea390e3565cd65a41fe0a9c8a5b83
diff --git a/tests/ImageTensorGenerator/ImageTensorGenerator.cpp b/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
index a2110f9..b443255 100644
--- a/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
+++ b/tests/ImageTensorGenerator/ImageTensorGenerator.cpp
@@ -164,15 +164,16 @@
("f,model-format",
"Format of the intended model file that uses the images."
"Different formats have different image normalization styles."
+ "If unset, defaults to tflite."
"Accepted value (tflite)",
- cxxopts::value<std::string>(m_ModelFormat))
+ cxxopts::value<std::string>(m_ModelFormat)->default_value("tflite"))
("o,outfile",
"Output raw tensor file path",
cxxopts::value<std::string>(m_OutputFileName))
("z,output-type",
"The data type of the output tensors."
"If unset, defaults to \"float\" for all defined inputs. "
- "Accepted values (float, int or qasymm8)",
+ "Accepted values (float, int, qasymms8 or qasymmu8)",
cxxopts::value<std::string>(m_OutputType)->default_value("float"))
("new-width",
"Resize image to new width. Keep original width if unspecified",
@@ -254,10 +255,14 @@
{
return armnn::DataType::Signed32;
}
- else if (m_OutputType == "qasymm8")
+ else if (m_OutputType == "qasymm8" || m_OutputType == "qasymmu8")
{
return armnn::DataType::QAsymmU8;
}
+ else if (m_OutputType == "qasymms8")
+ {
+ return armnn::DataType::QAsymmS8;
+ }
else
{
throw armnn::Exception("Unsupported input type" + m_OutputType);
@@ -292,7 +297,8 @@
const unsigned int batchSize = 1;
const armnn::DataLayout outputLayout(cmdline.GetLayout());
- using TContainer = mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<uint8_t>>;
+ using TContainer = mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<uint8_t>,
+ std::vector<int8_t>>;
std::vector<TContainer> imageDataContainers;
const NormalizationParameters& normParams = GetNormalizationParameters(modelFormat, outputType);
try
@@ -307,6 +313,10 @@
imageDataContainers.push_back(PrepareImageTensor<uint8_t>(
imagePath, newWidth, newHeight, normParams, batchSize, outputLayout));
break;
+ case armnn::DataType::QAsymmS8:
+ imageDataContainers.push_back(PrepareImageTensor<int8_t>(
+ imagePath, newWidth, newHeight, normParams, batchSize, outputLayout));
+ break;
case armnn::DataType::Float32:
default:
imageDataContainers.push_back(PrepareImageTensor<float>(
diff --git a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp b/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
index 5aa2ca8..6d2e549 100644
--- a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
+++ b/tests/ImageTensorGenerator/ImageTensorGenerator.hpp
@@ -56,6 +56,10 @@
normParams.mean = { 128.0, 128.0, 128.0 };
break;
case armnn::DataType::QAsymmU8:
+ break;
+ case armnn::DataType::QAsymmS8:
+ normParams.mean = { 128.0, 128.0, 128.0 };
+ break;
default:
break;
}
@@ -138,7 +142,7 @@
return imageDataInt;
}
-// Prepare qasymm8 image tensor
+// Prepare qasymmu8 image tensor
template <>
std::vector<uint8_t> PrepareImageTensor<uint8_t>(const std::string& imagePath,
unsigned int newWidth,
@@ -158,6 +162,26 @@
return imageDataQasymm8;
}
+// Prepare qasymms8 image tensor
+template <>
+std::vector<int8_t> PrepareImageTensor<int8_t>(const std::string& imagePath,
+ unsigned int newWidth,
+ unsigned int newHeight,
+ const NormalizationParameters& normParams,
+ unsigned int batchSize,
+ const armnn::DataLayout& outputLayout)
+{
+ // Get float32 image tensor
+ std::vector<float> imageDataFloat =
+ PrepareImageTensor<float>(imagePath, newWidth, newHeight, normParams, batchSize, outputLayout);
+ std::vector<int8_t> imageDataQasymms8;
+ imageDataQasymms8.reserve(imageDataFloat.size());
+ // Convert to uint8 image tensor with static cast
+ std::transform(imageDataFloat.begin(), imageDataFloat.end(), std::back_inserter(imageDataQasymms8),
+ [](float val) { return static_cast<uint8_t>(val); });
+ return imageDataQasymms8;
+}
+
/** Write image tensor to ofstream
*
* @param[in] imageData Image tensor data
@@ -176,3 +200,11 @@
{
std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<int>(imageTensorFile, " "));
}
+
+// For int8_t image tensor, cast it to int before writing it to prevent writing data as characters instead of
+// numerical values
+template <>
+void WriteImageTensorImpl<int8_t>(const std::vector<int8_t>& imageData, std::ofstream& imageTensorFile)
+{
+ std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<int>(imageTensorFile, " "));
+}
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