Revert "Revert "IVGCVSW-6650 Refactor ExecuteNetwork""

This reverts commit 1a7f033768acb27da11503bd29abb468d2e77f9e.

List of fixes to be able to add this code again:
* "emplacing_back" the vector inputTensors into the vector m_InputTensorsVec outside the for loop
* GetIOInfo() uses IOptimizedNetwork instead of INetwork, where the infered shapes are not saved
* Add missing data type Signed32 to SetupInputsAndOutputs()
* PrintOutputTensors() prints the actual output without dequantizing
* Add profilingDetailsMethod as input in networkProperties in ArmNNExecutor constructor
* Fix typos



Change-Id: I91de166f87228282db3efa27431fe91458834442

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ic6634d48892d11e5f146cdf285e1e333e93e9937
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>

1 files changed, 3 insertions, 131 deletions

diff --git a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
index cc75bb4323..f341c30738 100644
--- a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
@@ -1,76 +1,15 @@
 //
-// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
 #include "ExecuteNetworkParams.hpp"
 
 #include "NetworkExecutionUtils/NetworkExecutionUtils.hpp"
-#include <InferenceModel.hpp>
 #include <armnn/Logging.hpp>
 
 #include <fmt/format.h>
-
-bool IsModelBinary(const std::string& modelFormat)
-{
-    // Parse model binary flag from the model-format string we got from the command-line
-    if (modelFormat.find("binary") != std::string::npos)
-    {
-        return true;
-    }
-    else if (modelFormat.find("txt") != std::string::npos || modelFormat.find("text") != std::string::npos)
-    {
-        return false;
-    }
-    else
-    {
-        throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. "
-                                                          "Please include 'binary' or 'text'",
-                                                          modelFormat));
-    }
-}
-
-void CheckModelFormat(const std::string& modelFormat)
-{
-    // Forward to implementation based on the parser type
-    if (modelFormat.find("armnn") != std::string::npos)
-    {
-#if defined(ARMNN_SERIALIZER)
-#else
-        throw armnn::InvalidArgumentException("Can't run model in armnn format without a "
-                                              "built with serialization support.");
-#endif
-    }
-    else if (modelFormat.find("onnx") != std::string::npos)
-    {
-#if defined(ARMNN_ONNX_PARSER)
-#else
-        throw armnn::InvalidArgumentException("Can't run model in onnx format without a "
-                                              "built with Onnx parser support.");
-#endif
-    }
-    else if (modelFormat.find("tflite") != std::string::npos)
-    {
-#if defined(ARMNN_TF_LITE_PARSER)
-        if (!IsModelBinary(modelFormat))
-        {
-            throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. Only 'binary' "
-                                                              "format supported for tflite files",
-                                                              modelFormat));
-        }
-#elif defined(ARMNN_TFLITE_DELEGATE)
-#else
-        throw armnn::InvalidArgumentException("Can't run model in tflite format without a "
-                                              "built with Tensorflow Lite parser support.");
-#endif
-    }
-    else
-    {
-        throw armnn::InvalidArgumentException(fmt::format("Unknown model format: '{}'. "
-                                                          "Please include 'tflite' or 'onnx'",
-                                                          modelFormat));
-    }
-}
+#include <armnnUtils/Filesystem.hpp>
 
 void CheckClTuningParameter(const int& tuningLevel,
                             const std::string& tuningPath,
@@ -105,7 +44,6 @@ void CheckClTuningParameter(const int& tuningLevel,
             ARMNN_LOG(warning) << "To use Cl Tuning the compute device GpuAcc needs to be active.";
         }
     }
-
 }
 
 void ExecuteNetworkParams::ValidateParams()
@@ -120,7 +58,6 @@ void ExecuteNetworkParams::ValidateParams()
                              << invalidBackends;
         }
     }
-
     CheckClTuningParameter(m_TuningLevel, m_TuningPath, m_ComputeDevices);
 
     if (m_EnableBf16TurboMode && m_EnableFp16TurboMode)
@@ -129,10 +66,6 @@ void ExecuteNetworkParams::ValidateParams()
                                               "enabled at the same time.");
     }
 
-    m_IsModelBinary = IsModelBinary(m_ModelFormat);
-
-    CheckModelFormat(m_ModelFormat);
-
     // Check input tensor shapes
     if ((m_InputTensorShapes.size() != 0) &&
         (m_InputTensorShapes.size() != m_InputNames.size()))
@@ -157,68 +90,6 @@ void ExecuteNetworkParams::ValidateParams()
                                 m_InputNames.size(),
                                 m_InputTensorDataFilePaths.size()));
         }
-        else if (m_InputTensorDataFilePaths.size() % m_InputNames.size() != 0)
-        {
-            throw armnn::InvalidArgumentException(
-                    fmt::format("According to the number of input names the user provided the network has {} "
-                                "inputs. The user specified {} input-tensor-data file paths which is not "
-                                "divisible by the number of inputs.",
-                                m_InputNames.size(),
-                                m_InputTensorDataFilePaths.size()));
-        }
-    }
-
-    if (m_InputTypes.size() == 0)
-    {
-        //Defaults the value of all inputs to "float"
-        m_InputTypes.assign(m_InputNames.size(), "float");
-    }
-    else if ((m_InputTypes.size() != 0) &&
-             (m_InputTypes.size() != m_InputNames.size()))
-    {
-        throw armnn::InvalidArgumentException("input-name and input-type must have the same amount of elements.");
-    }
-
-    // Make sure that the number of input files given is divisible by the number of inputs of the model
-    if (!(m_InputTensorDataFilePaths.size() % m_InputNames.size() == 0))
-    {
-        throw armnn::InvalidArgumentException(
-                fmt::format("The number of input-tensor-data files ({0}) is not divisible by the "
-                            "number of inputs ({1} according to the number of input names).",
-                            m_InputTensorDataFilePaths.size(),
-                            m_InputNames.size()));
-    }
-
-    if (m_OutputTypes.size() == 0)
-    {
-        //Defaults the value of all outputs to "float"
-        m_OutputTypes.assign(m_OutputNames.size(), "float");
-    }
-    else if ((m_OutputTypes.size() != 0) &&
-             (m_OutputTypes.size() != m_OutputNames.size()))
-    {
-        throw armnn::InvalidArgumentException("output-name and output-type must have the same amount of elements.");
-    }
-
-    // Make sure that the number of output files given is equal to the number of outputs of the model
-    // or equal to the number of outputs of the model multiplied with the number of iterations
-    if (!m_OutputTensorFiles.empty())
-    {
-        if ((m_OutputTensorFiles.size() != m_OutputNames.size()) &&
-            (m_OutputTensorFiles.size() != m_OutputNames.size() * m_Iterations))
-        {
-            std::stringstream errmsg;
-            auto numOutputs = m_OutputNames.size();
-            throw armnn::InvalidArgumentException(
-                    fmt::format("The user provided {0} output-tensor files. The only allowed number of output-tensor "
-                                "files is the number of outputs of the network ({1} according to the number of "
-                                "output names) or the number of outputs multiplied with the number of times the "
-                                "network should be executed (NumOutputs * NumIterations = {1} * {2} = {3}).",
-                                m_OutputTensorFiles.size(),
-                                numOutputs,
-                                m_Iterations,
-                                numOutputs*m_Iterations));
-        }
     }
 
     // Check that threshold time is not less than zero
@@ -310,4 +181,5 @@ armnnDelegate::DelegateOptions ExecuteNetworkParams::ToDelegateOptions() const
 
     return delegateOptions;
 }
+
 #endif