IVGCVSW-5400 'TfLiteDelegate: FLOOR operator support'
* Added FLOOR operator support to Arm NN TfLiteDelegate
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I986ce8c5a825f509e0f8b3d257fd5b60834c322f
diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt
index 74390c8..11bff48 100644
--- a/delegate/CMakeLists.txt
+++ b/delegate/CMakeLists.txt
@@ -149,6 +149,8 @@
src/test/ReshapeTest.cpp
src/test/ResizeTest.cpp
src/test/ResizeTestHelper.hpp
+ src/test/RoundTest.cpp
+ src/test/RoundTestHelper.hpp
src/test/SoftmaxTest.cpp
src/test/SoftmaxTestHelper.hpp
src/test/SpaceDepthTest.cpp
diff --git a/delegate/src/Round.hpp b/delegate/src/Round.hpp
index 3335d0b..1677607 100644
--- a/delegate/src/Round.hpp
+++ b/delegate/src/Round.hpp
@@ -5,8 +5,6 @@
#pragma once
-#include <armnn/utility/IgnoreUnused.hpp>
-
#include <tensorflow/lite/builtin_ops.h>
#include <tensorflow/lite/c/builtin_op_data.h>
#include <tensorflow/lite/c/common.h>
@@ -21,13 +19,55 @@
int nodeIndex,
int32_t operatorCode)
{
- armnn::IgnoreUnused(delegateData,
- tfLiteContext,
- tfLiteNode,
- nodeIndex,
- operatorCode);
+ TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+ TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
- return kTfLiteError;
+ const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+ const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
+ if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+ if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+ const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
+
+ bool isSupported = false;
+ auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+ {
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ tfLiteContext,
+ IsFloorSupported,
+ delegateData.m_Backends,
+ isSupported,
+ inputTensorInfo,
+ outInfo);
+ };
+
+ // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the
+ // support for the operator
+ // If supported, VisitFloorOperator will be called again to add the layer to the network as seen further below
+ if (!delegateData.m_Network)
+ {
+ validateFunc(outputTensorInfo, isSupported);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+ }
+
+ // Add a Floor layer
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddFloorLayer();
+ ARMNN_ASSERT(layer != nullptr);
+
+ armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+ outputSlot.SetTensorInfo(outputTensorInfo);
+
+ // Connect
+ return Connect(layer, tfLiteNode, delegateData);
}
} // namespace armnnDelegate
diff --git a/delegate/src/test/RoundTest.cpp b/delegate/src/test/RoundTest.cpp
new file mode 100644
index 0000000..9d323f3
--- /dev/null
+++ b/delegate/src/test/RoundTest.cpp
@@ -0,0 +1,72 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RoundTestHelper.hpp"
+
+#include <armnn_delegate.hpp>
+
+#include <flatbuffers/flatbuffers.h>
+#include <tensorflow/lite/schema/schema_generated.h>
+
+#include <doctest/doctest.h>
+
+namespace armnnDelegate
+{
+
+void FloorFp32Test(std::vector<armnn::BackendId>& backends)
+{
+ std::vector<int32_t> inputShape {1, 3, 2, 3};
+ std::vector<int32_t> outputShape {1, 3, 2, 3};
+
+ std::vector<float> inputValues { -37.5f, -15.2f, -8.76f, -2.0f, -1.5f, -1.3f, -0.5f, -0.4f, 0.0f,
+ 1.0f, 0.4f, 0.5f, 1.3f, 1.5f, 2.0f, 8.76f, 15.2f, 37.5f };
+
+ std::vector<float> expectedOutputValues { -38.0f, -16.0f, -9.0f, -2.0f, -2.0f, -2.0f, -1.0f, -1.0f, 0.0f,
+ 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 2.0f, 8.0f, 15.0f, 37.0f };
+
+ RoundTest<float>(tflite::BuiltinOperator_FLOOR,
+ ::tflite::TensorType_FLOAT32,
+ backends,
+ inputShape,
+ inputValues,
+ expectedOutputValues);
+}
+
+// FLOOR Test Suite
+TEST_SUITE("FLOOR_CpuRefTests")
+{
+
+TEST_CASE ("FLOOR_Fp32_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ FloorFp32Test(backends);
+}
+
+}
+
+TEST_SUITE("FLOOR_CpuAccTests")
+{
+
+TEST_CASE ("FLOOR_Fp32_CpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc};
+ FloorFp32Test(backends);
+}
+
+}
+
+TEST_SUITE("FLOOR_GpuAccTests")
+{
+
+TEST_CASE ("FLOOR_Fp32_GpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
+ FloorFp32Test(backends);
+}
+
+}
+// End of FLOOR Test Suite
+
+} // namespace armnnDelegate
\ No newline at end of file
diff --git a/delegate/src/test/RoundTestHelper.hpp b/delegate/src/test/RoundTestHelper.hpp
new file mode 100644
index 0000000..3a35ee0
--- /dev/null
+++ b/delegate/src/test/RoundTestHelper.hpp
@@ -0,0 +1,161 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "TestUtils.hpp"
+
+#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> CreateRoundTfLiteModel(tflite::BuiltinOperator roundOperatorCode,
+ tflite::TensorType tensorType,
+ const std::vector <int32_t>& tensorShape,
+ 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>, 2> tensors;
+ tensors[0] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(),
+ tensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("input"),
+ quantizationParameters);
+ tensors[1] = CreateTensor(flatBufferBuilder,
+ flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(),
+ tensorShape.size()),
+ tensorType,
+ 0,
+ flatBufferBuilder.CreateString("output"),
+ quantizationParameters);
+
+ const std::vector<int32_t> operatorInputs({0});
+ const std::vector<int32_t> operatorOutputs({1});
+
+ flatbuffers::Offset<Operator> roundOperator;
+ flatbuffers::Offset<flatbuffers::String> modelDescription;
+ flatbuffers::Offset<OperatorCode> operatorCode;
+
+ switch (roundOperatorCode)
+ {
+ case tflite::BuiltinOperator_FLOOR:
+ default:
+ roundOperator =
+ CreateOperator(flatBufferBuilder,
+ 0,
+ flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+ flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
+ modelDescription = flatBufferBuilder.CreateString("ArmnnDelegate: Floor Operator Model");
+ operatorCode = CreateOperatorCode(flatBufferBuilder, tflite::BuiltinOperator_FLOOR);
+ break;
+ }
+ const std::vector<int32_t> subgraphInputs({0});
+ const std::vector<int32_t> subgraphOutputs({1});
+ 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(&roundOperator, 1));
+
+ 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 RoundTest(tflite::BuiltinOperator roundOperatorCode,
+ tflite::TensorType tensorType,
+ std::vector<armnn::BackendId>& backends,
+ std::vector<int32_t>& shape,
+ std::vector<T>& inputValues,
+ std::vector<T>& expectedOutputValues,
+ float quantScale = 1.0f,
+ int quantOffset = 0)
+{
+ using namespace tflite;
+ std::vector<char> modelBuffer = CreateRoundTfLiteModel(roundOperatorCode,
+ tensorType,
+ shape,
+ quantScale,
+ quantOffset);
+
+ const Model* tfLiteModel = GetModel(modelBuffer.data());
+
+ // Create TfLite Interpreters
+ std::unique_ptr<Interpreter> armnnDelegate;
+ CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+ (&armnnDelegate) == kTfLiteOk);
+ CHECK(armnnDelegate != nullptr);
+ CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
+
+ std::unique_ptr<Interpreter> tfLiteDelegate;
+ CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+ (&tfLiteDelegate) == kTfLiteOk);
+ CHECK(tfLiteDelegate != nullptr);
+ CHECK(tfLiteDelegate->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(armnnDelegate->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
+
+ // Set input data
+ armnnDelegate::FillInput<T>(tfLiteDelegate, 0, inputValues);
+ armnnDelegate::FillInput<T>(armnnDelegate, 0, inputValues);
+
+ // Run EnqueWorkload
+ CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
+ CHECK(armnnDelegate->Invoke() == kTfLiteOk);
+
+ // Compare output data
+ armnnDelegate::CompareOutputData<T>(tfLiteDelegate,
+ armnnDelegate,
+ shape,
+ expectedOutputValues,
+ 0);
+
+ tfLiteDelegate.reset(nullptr);
+ armnnDelegate.reset(nullptr);
+}
+
+} // anonymous namespace
diff --git a/docs/01_03_delegate.dox b/docs/01_03_delegate.dox
index 7c7763a..73d8690 100644
--- a/docs/01_03_delegate.dox
+++ b/docs/01_03_delegate.dox
@@ -63,6 +63,8 @@
- FULLY_CONNECTED, Supported Fused Activation: RELU , RELU6 , TANH, NONE
+- FLOOR
+
- GATHER
- GREATER