aboutsummaryrefslogtreecommitdiff
path: root/delegate/src/test/ComparisonTestHelper.hpp
diff options
context:
space:
mode:
Diffstat (limited to 'delegate/src/test/ComparisonTestHelper.hpp')
-rw-r--r--delegate/src/test/ComparisonTestHelper.hpp236
1 files changed, 236 insertions, 0 deletions
diff --git a/delegate/src/test/ComparisonTestHelper.hpp b/delegate/src/test/ComparisonTestHelper.hpp
new file mode 100644
index 0000000000..0011c763a0
--- /dev/null
+++ b/delegate/src/test/ComparisonTestHelper.hpp
@@ -0,0 +1,236 @@
+//
+// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn_delegate.hpp>
+
+#include <flatbuffers/flatbuffers.h>
+#include <tensorflow/lite/interpreter.h>
+#include <tensorflow/lite/kernels/register.h>
+#include <tensorflow/lite/model.h>
+#include <tensorflow/lite/schema/schema_generated.h>
+#include <tensorflow/lite/version.h>
+
+#include <doctest/doctest.h>
+
+namespace
+{
+
+std::vector<char> CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode,
+ tflite::TensorType tensorType,
+ const std::vector <int32_t>& input0TensorShape,
+ const std::vector <int32_t>& input1TensorShape,
+ const std::vector <int32_t>& outputTensorShape,
+ float quantScale = 1.0f,
+ int quantOffset = 0)
+{
+ using namespace tflite;
+ flatbuffers::FlatBufferBuilder flatBufferBuilder;
+
+ std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
+ buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})));
+
+ auto quantizationParameters =
+ CreateQuantizationParameters(flatBufferBuilder,
+ 0,
+ 0,
+ flatBufferBuilder.CreateVector<float>({ quantScale }),
+ flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
+
+ std::array<flatbuffers::Offset<Tensor>, 3> tensors;
+ tensors[0] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(),
+ input0TensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("input_0"),
+ quantizationParameters);
+ tensors[1] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(),
+ input1TensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("input_1"),
+ quantizationParameters);
+ tensors[2] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+ outputTensorShape.size()),
+ ::tflite::TensorType_BOOL,
+ 0);
+
+ // create operator
+ tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;;
+ flatbuffers::Offset<void> operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
+ switch (comparisonOperatorCode)
+ {
+ case BuiltinOperator_EQUAL:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;
+ operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
+ break;
+ }
+ case BuiltinOperator_NOT_EQUAL:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_NotEqualOptions;
+ operatorBuiltinOptions = CreateNotEqualOptions(flatBufferBuilder).Union();
+ break;
+ }
+ case BuiltinOperator_GREATER:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_GreaterOptions;
+ operatorBuiltinOptions = CreateGreaterOptions(flatBufferBuilder).Union();
+ break;
+ }
+ case BuiltinOperator_GREATER_EQUAL:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_GreaterEqualOptions;
+ operatorBuiltinOptions = CreateGreaterEqualOptions(flatBufferBuilder).Union();
+ break;
+ }
+ case BuiltinOperator_LESS:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_LessOptions;
+ operatorBuiltinOptions = CreateLessOptions(flatBufferBuilder).Union();
+ break;
+ }
+ case BuiltinOperator_LESS_EQUAL:
+ {
+ operatorBuiltinOptionsType = BuiltinOptions_LessEqualOptions;
+ operatorBuiltinOptions = CreateLessEqualOptions(flatBufferBuilder).Union();
+ break;
+ }
+ default:
+ break;
+ }
+ const std::vector<int32_t> operatorInputs{ {0, 1} };
+ const std::vector<int32_t> operatorOutputs{{2}};
+ flatbuffers::Offset <Operator> comparisonOperator =
+ CreateOperator(flatBufferBuilder,
+ 0,
+ flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+ flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+ operatorBuiltinOptionsType,
+ operatorBuiltinOptions);
+
+ const std::vector<int> subgraphInputs{ {0, 1} };
+ const std::vector<int> subgraphOutputs{{2}};
+ flatbuffers::Offset <SubGraph> subgraph =
+ CreateSubGraph(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
+ flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
+ flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
+ flatBufferBuilder.CreateVector(&comparisonOperator, 1));
+
+ flatbuffers::Offset <flatbuffers::String> modelDescription =
+ flatBufferBuilder.CreateString("ArmnnDelegate: Comparison Operator Model");
+ flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, comparisonOperatorCode);
+
+ flatbuffers::Offset <Model> flatbufferModel =
+ CreateModel(flatBufferBuilder,
+ TFLITE_SCHEMA_VERSION,
+ flatBufferBuilder.CreateVector(&operatorCode, 1),
+ flatBufferBuilder.CreateVector(&subgraph, 1),
+ modelDescription,
+ flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
+
+ flatBufferBuilder.Finish(flatbufferModel);
+
+ return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
+ flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
+}
+
+template <typename T>
+void ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode,
+ tflite::TensorType tensorType,
+ std::vector<armnn::BackendId>& backends,
+ std::vector<int32_t>& input0Shape,
+ std::vector<int32_t>& input1Shape,
+ std::vector<int32_t>& outputShape,
+ std::vector<T>& input0Values,
+ std::vector<T>& input1Values,
+ std::vector<bool>& expectedOutputValues,
+ float quantScale = 1.0f,
+ int quantOffset = 0)
+{
+ using namespace tflite;
+ std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode,
+ tensorType,
+ input0Shape,
+ input1Shape,
+ outputShape,
+ quantScale,
+ quantOffset);
+
+ const Model* tfLiteModel = GetModel(modelBuffer.data());
+ // Create TfLite Interpreters
+ std::unique_ptr<Interpreter> armnnDelegateInterpreter;
+ CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+ (&armnnDelegateInterpreter) == kTfLiteOk);
+ CHECK(armnnDelegateInterpreter != nullptr);
+ CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
+
+ std::unique_ptr<Interpreter> tfLiteInterpreter;
+ CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+ (&tfLiteInterpreter) == kTfLiteOk);
+ CHECK(tfLiteInterpreter != nullptr);
+ CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk);
+
+ // Create the ArmNN Delegate
+ armnnDelegate::DelegateOptions delegateOptions(backends);
+ std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
+ theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
+ armnnDelegate::TfLiteArmnnDelegateDelete);
+ CHECK(theArmnnDelegate != nullptr);
+ // Modify armnnDelegateInterpreter to use armnnDelegate
+ CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
+
+ // Set input data
+ auto tfLiteDelegateInput0Id = tfLiteInterpreter->inputs()[0];
+ auto tfLiteDelageInput0Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput0Id);
+ for (unsigned int i = 0; i < input0Values.size(); ++i)
+ {
+ tfLiteDelageInput0Data[i] = input0Values[i];
+ }
+
+ auto tfLiteDelegateInput1Id = tfLiteInterpreter->inputs()[1];
+ auto tfLiteDelageInput1Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput1Id);
+ for (unsigned int i = 0; i < input1Values.size(); ++i)
+ {
+ tfLiteDelageInput1Data[i] = input1Values[i];
+ }
+
+ auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0];
+ auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput0Id);
+ for (unsigned int i = 0; i < input0Values.size(); ++i)
+ {
+ armnnDelegateInput0Data[i] = input0Values[i];
+ }
+
+ auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1];
+ auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput1Id);
+ for (unsigned int i = 0; i < input1Values.size(); ++i)
+ {
+ armnnDelegateInput1Data[i] = input1Values[i];
+ }
+
+ // Run EnqueWorkload
+ CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
+ CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
+ // Compare output data
+ auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
+ auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<bool>(tfLiteDelegateOutputId);
+ auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
+ auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<bool>(armnnDelegateOutputId);
+
+ for (size_t i = 0; i < expectedOutputValues.size(); i++)
+ {
+ CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]);
+ CHECK(tfLiteDelageOutputData[i] == expectedOutputValues[i]);
+ CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]);
+ }
+}
+
+} // anonymous namespace \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-10 07:41:51 +0000