Fixing compare output feature in ExecuteNetwork
The -A -B -C options in execute network were attempting to calculate
the RMS error over output tensors. However, the calculation was mixing
tensor elements and bytes when doing the calculation. This patch
changes the calculation to use a per byte RMS error calculation.
Signed-off-by: Colm Donelan <colm.donelan@arm.com>
Change-Id: If30230a16cfed1a8804b4d54ed1abcd371f26664
diff --git a/tests/ExecuteNetwork/TfliteExecutor.cpp b/tests/ExecuteNetwork/TfliteExecutor.cpp
index fc9c21a..f365623 100644
--- a/tests/ExecuteNetwork/TfliteExecutor.cpp
+++ b/tests/ExecuteNetwork/TfliteExecutor.cpp
@@ -230,45 +230,9 @@
for (unsigned int outputIndex = 0; outputIndex < m_TfLiteInterpreter->outputs().size(); ++outputIndex)
{
auto tfLiteDelegateOutputId = m_TfLiteInterpreter->outputs()[outputIndex];
- float result = 0;
- switch (m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->type)
- {
- case kTfLiteFloat32:
- {
- result = ComputeRMSE<float>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
- otherOutput[outputIndex],
- m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
-
- break;
- }
- case kTfLiteInt32:
- {
- result = ComputeRMSE<int32_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
- otherOutput[outputIndex],
- m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
- break;
- }
- case kTfLiteUInt8:
- {
- result = ComputeRMSE<uint8_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
- otherOutput[outputIndex],
- m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
- break;
- }
- case kTfLiteInt8:
- {
- result = ComputeRMSE<int8_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
- otherOutput[outputIndex],
- m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
- break;
- }
- default:
- {
- }
- }
-
- std::cout << "RMSE of "
- << m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->name
- << ": " << result << std::endl;
+ size_t size = m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes;
+ double result = ComputeByteLevelRMSE(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
+ otherOutput[outputIndex], size);
+ std::cout << "Byte level root mean square error: " << result << "\n";
}
};