IVGCVSW-6989 "Merged experimental/armnn_shim_sl"
* Updated Serializer CMakeLists.txt to build armnnSerializerObj
* Added constant tensors as input support to SL
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I22f6cf50147d99a01f7fe70d7446b114a4c57af3
diff --git a/shim/sl/canonical/CanonicalUtils.hpp b/shim/sl/canonical/CanonicalUtils.hpp
new file mode 100644
index 0000000..a509684
--- /dev/null
+++ b/shim/sl/canonical/CanonicalUtils.hpp
@@ -0,0 +1,123 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+#include <armnn/ArmNN.hpp>
+
+#include <CpuExecutor.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <vector>
+#include <string>
+#include <fstream>
+#include <iomanip>
+
+namespace armnn_driver
+{
+
+using namespace android::nn;
+
+extern const armnn::PermutationVector g_DontPermute;
+
+template <typename OperandType>
+class UnsupportedOperand: public std::runtime_error
+{
+public:
+ UnsupportedOperand(const OperandType type)
+ : std::runtime_error("Operand type is unsupported")
+ , m_type(type)
+ {}
+
+ OperandType m_type;
+};
+
+/// Swizzles tensor data in @a input according to the dimension mappings.
+void SwizzleAndroidNn4dTensorToArmNn(armnn::TensorInfo& tensor,
+ const void* input,
+ void* output,
+ const armnn::PermutationVector& mappings);
+
+/// Returns a pointer to a specific location in a pool`
+void* GetMemoryFromPool(DataLocation location,
+ const std::vector<android::nn::RunTimePoolInfo>& memPools);
+
+void* GetMemoryFromPointer(const Request::Argument& requestArg);
+
+armnn::TensorInfo GetTensorInfoForOperand(const Operand& operand);
+
+std::string GetOperandSummary(const Operand& operand);
+
+bool isQuantizedOperand(const OperandType& operandType);
+
+std::string GetModelSummary(const Model& model);
+
+void DumpTensor(const std::string& dumpDir,
+ const std::string& requestName,
+ const std::string& tensorName,
+ const armnn::ConstTensor& tensor);
+
+void DumpJsonProfilingIfRequired(bool gpuProfilingEnabled,
+ const std::string& dumpDir,
+ armnn::NetworkId networkId,
+ const armnn::IProfiler* profiler);
+
+std::string ExportNetworkGraphToDotFile(const armnn::IOptimizedNetwork& optimizedNetwork,
+ const std::string& dumpDir);
+
+std::string SerializeNetwork(const armnn::INetwork& network,
+ const std::string& dumpDir,
+ std::vector<uint8_t>& dataCacheData,
+ bool dataCachingActive = true);
+
+void RenameExportedFiles(const std::string& existingSerializedFileName,
+ const std::string& existingDotFileName,
+ const std::string& dumpDir,
+ const armnn::NetworkId networkId);
+
+void RenameFile(const std::string& existingName,
+ const std::string& extension,
+ const std::string& dumpDir,
+ const armnn::NetworkId networkId);
+
+/// Checks if a tensor info represents a dynamic tensor
+bool IsDynamicTensor(const armnn::TensorInfo& outputInfo);
+
+/// Checks for ArmNN support of dynamic tensors.
+bool AreDynamicTensorsSupported(void);
+
+std::string GetFileTimestamp();
+
+inline OutputShape ComputeShape(const armnn::TensorInfo& info)
+{
+ OutputShape shape;
+
+ armnn::TensorShape tensorShape = info.GetShape();
+ // Android will expect scalars as a zero dimensional tensor
+ if(tensorShape.GetDimensionality() == armnn::Dimensionality::Scalar)
+ {
+ shape.dimensions = std::vector<uint32_t>{};
+ }
+ else
+ {
+ std::vector<uint32_t> dimensions;
+ const unsigned int numDims = tensorShape.GetNumDimensions();
+ dimensions.resize(numDims);
+ for (unsigned int outputIdx = 0u; outputIdx < numDims; ++outputIdx)
+ {
+ dimensions[outputIdx] = tensorShape[outputIdx];
+ }
+ shape.dimensions = dimensions;
+ }
+
+ shape.isSufficient = true;
+
+ return shape;
+}
+
+void CommitPools(std::vector<::android::nn::RunTimePoolInfo>& memPools);
+
+} // namespace armnn_driver