IVGCVSW-7555 Restructure Delegate
* New folders created:
* common is for common code where TfLite API is not used
* classic is for existing delegate implementations
* opaque is for new opaque delegate implementation,
* tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed
diff --git a/delegate/test/DepthwiseConvolution2dTest.cpp b/delegate/test/DepthwiseConvolution2dTest.cpp
new file mode 100644
index 0000000..9ee589c
--- /dev/null
+++ b/delegate/test/DepthwiseConvolution2dTest.cpp
@@ -0,0 +1,282 @@
+//
+// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ConvolutionTestHelper.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 <schema_generated.h>
+#include <tensorflow/lite/version.h>
+
+#include <doctest/doctest.h>
+
+namespace armnnDelegate
+{
+
+void DepthwiseConv2dValidReluFp32Test(std::vector<armnn::BackendId>& backends)
+{
+ // Set input data
+ std::vector<int32_t> inputShape { 1, 3, 2, 2 };
+ std::vector<int32_t> filterShape { 1, 2, 2, 4 };
+ std::vector<int32_t> biasShape { 4 };
+ std::vector<int32_t> outputShape { 1, 3, 3, 1 };
+
+ static std::vector<float> inputValues =
+ {
+ 1, 2, 7, 8,
+ 3, 4, 9, 10,
+ 5, 6, 11, 12
+ };
+
+ std::vector<float> filterValues =
+ {
+ 1, 2, 3, 4,
+ -9, 10, -11, 12,
+ 5, 6, 7, 8,
+ 13, -14, 15, -16
+ };
+
+ std::vector<float> biasValues = { 1, 2, 3, 4 };
+
+ std::vector<float> expectedOutputValues =
+ {
+ 71, 0, 99, 0,
+ 91, 0, 127, 0
+ };
+
+ tflite::Padding padding = tflite::Padding_VALID;
+ int32_t depth_multiplier = 2;
+
+ ConvolutionTest<float>(tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+ ::tflite::TensorType_FLOAT32,
+ 1, // strideX
+ 1, // strideY
+ 1, // dilationX
+ 1, // dilationY
+ padding,
+ tflite::ActivationFunctionType_RELU,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues,
+ {1.0f}, // biasScale
+ {0}, // biasOffset
+ {1.0f}, // filterScale
+ {0}, // filterOffsets
+ 2.0f, // outputQuantScale
+ 0, // outputQuantOffset
+ 1.0f, // quantScale
+ 0, // quantOffset
+ depth_multiplier);
+}
+
+void DepthwiseConv2dSameUint8Test(std::vector<armnn::BackendId>& backends)
+{
+ // Set input data
+ std::vector<int32_t> inputShape { 1, 3, 3, 1 };
+ std::vector<int32_t> filterShape { 1, 3, 3, 1 };
+ std::vector<int32_t> biasShape { 1 } ;
+ std::vector<int32_t> outputShape { 1, 3, 3, 1 };
+
+ static std::vector<uint8_t> inputValues =
+ {
+ 0, 1, 2,
+ 3, 4, 5,
+ 6, 7, 8
+ };
+
+ std::vector<uint8_t> filterValues = { 9, 8, 7, 6, 5, 4, 3, 2, 1 };
+
+ std::vector<int32_t> biasValues = { 10 };
+
+ std::vector<uint8_t> expectedOutputValues =
+ {
+ 12, 23, 24, // ( 14+10)/2, ( 35+10)/2, ( 38+10)/2,
+ 34, 65, 61, // ( 57+10)/2, (120+10)/2, (111+10)/2,
+ 60, 104, 84 // (110+10)/2, (197+10)/2, (158+10)/2
+ };
+
+ tflite::Padding padding = tflite::Padding_SAME;
+
+ ConvolutionTest<uint8_t, int32_t>(tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+ ::tflite::TensorType_UINT8,
+ 1, // strideX
+ 1, // strideY
+ 1, // dilationX
+ 1, // dilationY
+ padding,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues);
+}
+
+void DepthwiseConv2dSameInt8PerChannelTest(std::vector<armnn::BackendId>& backends)
+{
+ // Set input data
+ std::vector<int32_t> inputShape { 1, 4, 4, 4 };
+ std::vector<int32_t> filterShape { 1, 2, 2, 16 };
+ std::vector<int32_t> biasShape {16} ;
+ std::vector<int32_t> outputShape { 1, 4, 4, 16 };
+
+ static std::vector<int8_t> inputValues =
+ {
+ 3,3,3,4, 4,4,0,0, 0,3,4,3, 0,2,2,3,
+ 3,0,3,0, 0,3,2,1, 4,1,2,2, 0,0,0,4,
+ 3,2,2,2, 2,1,0,4, 4,3,2,4, 3,2,0,0,
+ 4,1,4,4, 1,0,4,3, 3,2,0,3, 1,1,0,2
+ };
+
+ std::vector<int8_t> filterValues = { 12,20,10, 3, 2,24, 9,10, 5,16,30,12, 3,10, 4,32,
+ 8, 0,30, 3, 0,16,12,15,20,12, 0, 3, 9,20, 8, 8,
+ 12,15,20, 0, 0, 0, 3,15,15, 8,40,12, 9, 5, 2,24,
+ 4, 0, 0, 6, 6, 0, 3, 5,20, 8,20, 3, 6,15, 4, 0 };
+ std::vector<float> filterScales = { 0.25, 0.2, 0.1, 0.3333333333,
+ 0.5, 0.125, 0.33333333, 0.2,
+ 0.2, 0.25, 0.1, 0.333333333,
+ 0.3333333333, 0.2, 0.5, 0.125 };
+
+ int32_t filterQuantizationDim = 3;
+
+ int32_t depth_multiplier = 4;
+
+ std::vector<int32_t> biasValues = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
+
+ float inputScale = 1.0f;
+ std::vector<float> biasScales {};
+ std::vector<int64_t> biasOffsets {};
+ std::vector<int64_t> filterOffsets {};
+ for (const auto& filterScale: filterScales)
+ {
+ biasScales.push_back(inputScale * filterScale);
+ // filter and bias offset always needs to be zero for per channel. We don't support anything else
+ biasOffsets.push_back(0);
+ filterOffsets.push_back(0);
+ }
+
+ std::vector<int8_t> expectedOutputValues =
+ {
+ 26,21,21, 7,12,17,28,21,20,22,25,26, 6,11,10,16,
+ 16,16, 4,12, 7,18,28,27,30,20,12,14,16,19,17, 6,
+ 12,12, 8, 0, 3,13,18,15,18,26,20,26,26,32,28,21,
+ 0, 0, 0, 0, 2, 6, 6, 4, 2, 8, 6, 8,15,10,10,24,
+ 20,21, 9, 7, 3, 6,15,16,17,22,17,22,17,18,14, 7,
+ 18, 6,16,12,12,11,17,15,18,18,10,12,27,26,22,18,
+ 27,28,12,10, 7, 3, 8,13, 8,12,14,16,26,24,24,24,
+ 9, 9, 6, 0, 0, 0, 2, 6, 0, 0, 0, 0, 4, 8, 8,16,
+ 26,24,17, 7, 2, 8,11,10,30,24,30,28,32,33,30,24,
+ 20,11,16,12, 7, 9,17,13,20,14,16,18,31,36,33,29,
+ 28,25,19, 9, 6,13,20,19, 2, 8, 6, 8,17,17,15,25,
+ 12,15, 5, 3, 2, 6, 7, 7, 0, 0, 0, 0, 6, 2, 2, 6,
+ 14,16, 7, 5, 1, 3, 3, 2,20,28,12,20,13,20,20,19,
+ 9, 4,10, 4, 0, 4, 8, 6, 4,16,12,16,12,18,18,15,
+ 11,12, 6, 4, 2, 8,10, 7, 0, 0, 0, 0, 9,14,14,14,
+ 3, 4, 1, 1, 1, 3, 3, 2, 0, 0, 0, 0, 2, 4, 4, 8
+ };
+
+ tflite::Padding padding = tflite::Padding_SAME;
+
+ ConvolutionTest<int8_t, int32_t>(tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+ ::tflite::TensorType_INT8,
+ 1, // strideX
+ 1, // strideY
+ 1, // dilationX
+ 1, // dilationY
+ padding,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues,
+ biasScales,
+ biasOffsets,
+ filterScales,
+ filterOffsets,
+ 1.0f,
+ 0,
+ inputScale,
+ 0,
+ depth_multiplier,
+ filterQuantizationDim);
+}
+
+TEST_SUITE("DepthwiseConv2d_CpuRef_Tests")
+{
+
+TEST_CASE ("DepthwiseConv2d_Valid_Relu_Fp32_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ DepthwiseConv2dValidReluFp32Test(backends);
+}
+
+TEST_CASE ("DepthwiseConv2d_Same_Uint8_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ DepthwiseConv2dSameUint8Test(backends);
+}
+
+TEST_CASE ("DepthwiseConv2d_Same_Int8_PerChannelQuantization_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ DepthwiseConv2dSameInt8PerChannelTest(backends);
+}
+
+}//End of TEST_SUITE("DepthwiseConv2d_CpuRef_Tests")
+
+TEST_SUITE("DepthwiseConv2d_CpuAcc_Tests")
+{
+
+TEST_CASE ("DepthwiseConv2d_Valid_Relu_Fp32_CpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc};
+ DepthwiseConv2dValidReluFp32Test(backends);
+}
+
+TEST_CASE ("DepthwiseConv2d_Same_Uint8_CpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc};
+ DepthwiseConv2dSameUint8Test(backends);
+}
+
+}//End of TEST_SUITE("DepthwiseConv2d_CpuAcc_Tests")
+
+TEST_SUITE("DepthwiseConv2d_GpuAcc_Tests")
+{
+
+TEST_CASE ("DepthwiseConv2d_Valid_Relu_Fp32_GpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
+ DepthwiseConv2dValidReluFp32Test(backends);
+}
+
+TEST_CASE ("DepthwiseConv2d_Same_Uint8_GpuAcc_Test")
+{
+ std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
+ DepthwiseConv2dSameUint8Test(backends);
+}
+
+}//End of TEST_SUITE("DepthwiseConv2d_GpuAcc_Tests")
+
+} // namespace armnnDelegate
\ No newline at end of file