COMPMID-970 : Remove QS8 / QS16 support
Removed Fixed point position arguments from test sources
Change-Id: I8343724723b71611fd501ed34de0866d3fb60e7e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136382
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp
index f122f6d..4f97d7b 100644
--- a/tests/validation/CL/ActivationLayer.cpp
+++ b/tests/validation/CL/ActivationLayer.cpp
@@ -221,9 +221,6 @@
TEST_SUITE_END()
template <typename T>
-using CLActivationLayerFixedPointFixture = ActivationValidationFixedPointFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
-
-template <typename T>
using CLActivationLayerQuantizedFixture = ActivationValidationQuantizedFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
/** Input data sets. */
diff --git a/tests/validation/CL/ArithmeticAddition.cpp b/tests/validation/CL/ArithmeticAddition.cpp
index 0646c05..256d93f 100644
--- a/tests/validation/CL/ArithmeticAddition.cpp
+++ b/tests/validation/CL/ArithmeticAddition.cpp
@@ -202,9 +202,6 @@
}
TEST_SUITE_END()
-template <typename T>
-using CLArithmeticAdditionFixedPointFixture = ArithmeticAdditionValidationFixedPointFixture<CLTensor, CLAccessor, CLArithmeticAddition, T>;
-
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticAdditionFixture<half>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), ArithmeticAdditionFP16Dataset),
diff --git a/tests/validation/CL/ArithmeticSubtraction.cpp b/tests/validation/CL/ArithmeticSubtraction.cpp
index 4ba5387..b19d963 100644
--- a/tests/validation/CL/ArithmeticSubtraction.cpp
+++ b/tests/validation/CL/ArithmeticSubtraction.cpp
@@ -231,9 +231,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T1, typename T2 = T1, typename T3 = T1>
-using CLArithmeticSubtractionFixedPointFixture = ArithmeticSubtractionValidationFixedPointFixture<CLTensor, CLAccessor, CLArithmeticSubtraction, T1, T2, T3>;
-
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture<half>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), ArithmeticSubtractionFP16Dataset),
diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp
index de775bf..0d80ff7 100644
--- a/tests/validation/CL/BatchNormalizationLayer.cpp
+++ b/tests/validation/CL/BatchNormalizationLayer.cpp
@@ -67,9 +67,6 @@
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
shape0, shape1, epsilon, use_gamma, use_beta, dt, data_layout)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
-
TensorShape src_dst_shapes = shape0;
if(data_layout == DataLayout::NHWC)
{
@@ -77,12 +74,12 @@
}
// Create tensors
- CLTensor src = create_tensor<CLTensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- CLTensor dst = create_tensor<CLTensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- CLTensor mean = create_tensor<CLTensor>(shape1, dt, 1, fixed_point_position);
- CLTensor var = create_tensor<CLTensor>(shape1, dt, 1, fixed_point_position);
- CLTensor beta = create_tensor<CLTensor>(shape1, dt, 1, fixed_point_position);
- CLTensor gamma = create_tensor<CLTensor>(shape1, dt, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ CLTensor dst = create_tensor<CLTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ CLTensor mean = create_tensor<CLTensor>(shape1, dt, 1);
+ CLTensor var = create_tensor<CLTensor>(shape1, dt, 1);
+ CLTensor beta = create_tensor<CLTensor>(shape1, dt, 1);
+ CLTensor gamma = create_tensor<CLTensor>(shape1, dt, 1);
// Create and Configure function
CLBatchNormalizationLayer norm;
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 7fd29f4..30dd850 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -153,16 +153,13 @@
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -251,9 +248,6 @@
TEST_SUITE_END()
template <typename T>
-using CLGEMMConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
-
-template <typename T>
using CLGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
diff --git a/tests/validation/CL/DepthConvertLayer.cpp b/tests/validation/CL/DepthConvertLayer.cpp
index c6e9f75..ed1f54c 100644
--- a/tests/validation/CL/DepthConvertLayer.cpp
+++ b/tests/validation/CL/DepthConvertLayer.cpp
@@ -67,19 +67,15 @@
using CLDepthConvertLayerToU8Fixture = DepthConvertLayerValidationFixture<CLTensor, CLAccessor, CLDepthConvertLayer, T, uint8_t>;
template <typename T>
using CLDepthConvertLayerToU32Fixture = DepthConvertLayerValidationFixture<CLTensor, CLAccessor, CLDepthConvertLayer, T, uint32_t>;
-template <typename T>
-using CLDepthConvertLayerToFP32FixedPointFixture = DepthConvertLayerValidationFractionalBitsFixture<CLTensor, CLAccessor, CLDepthConvertLayer, T, float>;
TEST_SUITE(U8_to_U16)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })),
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::U16, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U16, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -117,11 +113,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -158,11 +152,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::S32, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U8, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::S32, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -200,11 +192,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::U16, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U16, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -241,11 +231,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::U16, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::U32, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::U16, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U32, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -282,11 +270,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::S16, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::S16, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
@@ -323,11 +309,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, DataType::S16, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(shape, DataType::S32, 1, fixed_point_position);
+ CLTensor src = create_tensor<CLTensor>(shape, DataType::S16, 1);
+ CLTensor dst = create_tensor<CLTensor>(shape, DataType::S32, 1);
// Create and Configure function
CLDepthConvertLayer depth_convert;
diff --git a/tests/validation/CL/DilatedConvolutionLayer.cpp b/tests/validation/CL/DilatedConvolutionLayer.cpp
index 4b22390..fdd6cc8 100644
--- a/tests/validation/CL/DilatedConvolutionLayer.cpp
+++ b/tests/validation/CL/DilatedConvolutionLayer.cpp
@@ -114,16 +114,13 @@
CNNDataTypes),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -204,9 +201,6 @@
TEST_SUITE_END()
template <typename T>
-using CLGEMMDilatedConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
-
-template <typename T>
using CLGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
TEST_SUITE(Quantized)
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index d8b2d7e..a796b6e 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -200,9 +200,6 @@
TEST_SUITE_END()
template <typename T>
-using CLDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
-
-template <typename T>
using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
template <typename T>
using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>;
diff --git a/tests/validation/CL/FullyConnectedLayer.cpp b/tests/validation/CL/FullyConnectedLayer.cpp
index 069d8a7..9958a88 100644
--- a/tests/validation/CL/FullyConnectedLayer.cpp
+++ b/tests/validation/CL/FullyConnectedLayer.cpp
@@ -69,10 +69,8 @@
CNNDataTypes),
src_shape, weights_shape, bias_shape, dst_shape, transpose_weights, reshape_weights, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
- const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- const QuantizationInfo quantization_info = is_data_type_quantized_asymmetric(data_type) ? QuantizationInfo(2.f / 255.f, 127) : QuantizationInfo();
+ const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
+ const QuantizationInfo quantization_info = is_data_type_quantized_asymmetric(data_type) ? QuantizationInfo(2.f / 255.f, 127) : QuantizationInfo();
TensorShape ws(weights_shape);
@@ -85,10 +83,10 @@
}
// Create tensors
- CLTensor src = create_tensor<CLTensor>(src_shape, data_type, 1, fixed_point_position, quantization_info);
- CLTensor weights = create_tensor<CLTensor>(ws, data_type, 1, fixed_point_position, quantization_info);
- CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, fixed_point_position, quantization_info);
- CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type, 1, fixed_point_position, quantization_info);
+ CLTensor src = create_tensor<CLTensor>(src_shape, data_type, 1, quantization_info);
+ CLTensor weights = create_tensor<CLTensor>(ws, data_type, 1, quantization_info);
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, quantization_info);
+ CLTensor dst = create_tensor<CLTensor>(dst_shape, data_type, 1, quantization_info);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -192,9 +190,6 @@
TEST_SUITE_END()
template <typename T>
-using CLFullyConnectedLayerFixedPointFixture = FullyConnectedLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLFullyConnectedLayer, T, false>;
-
-template <typename T>
using CLFullyConnectedLayerQuantizedFixture = FullyConnectedLayerValidationQuantizedFixture<CLTensor, CLAccessor, CLFullyConnectedLayer, T, false>;
TEST_SUITE(Quantized)
diff --git a/tests/validation/CL/GEMM.cpp b/tests/validation/CL/GEMM.cpp
index d066281..6391820 100644
--- a/tests/validation/CL/GEMM.cpp
+++ b/tests/validation/CL/GEMM.cpp
@@ -86,14 +86,11 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallGEMMDataset(), datasets::LargeGEMMDataset()), CNNDataTypes),
shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- CLTensor a = create_tensor<CLTensor>(shape_a, data_type, 1, fixed_point_position);
- CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, fixed_point_position);
- CLTensor c = create_tensor<CLTensor>(shape_c, data_type, 1, fixed_point_position);
- CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position);
+ CLTensor a = create_tensor<CLTensor>(shape_a, data_type, 1);
+ CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1);
+ CLTensor c = create_tensor<CLTensor>(shape_c, data_type, 1);
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -152,9 +149,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using CLGEMMFixedPointFixture = GEMMValidationFixedPointFixture<CLTensor, CLAccessor, CLGEMM, T>;
-
TEST_SUITE(OUTPUT_3D)
TEST_SUITE(Float)
TEST_SUITE(FP32)
diff --git a/tests/validation/CL/NormalizationLayer.cpp b/tests/validation/CL/NormalizationLayer.cpp
index f6a8e7a..a2dbaff 100644
--- a/tests/validation/CL/NormalizationLayer.cpp
+++ b/tests/validation/CL/NormalizationLayer.cpp
@@ -52,10 +52,6 @@
framework::dataset::make("NormalizationSize", 3, 9, 2)),
framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
framework::dataset::make("IsScaled", { true }));
-const auto NormalizationDatasetQS = combine(combine(combine(combine(datasets::TinyShapes(), datasets::NormalizationTypes()),
- framework::dataset::make("NormalizationSize", 3, 9, 2)),
- framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
- framework::dataset::make("IsScaled", { true }));
const auto NormalizationDatasetFP16 = combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("NormType", { NormType::IN_MAP_1D, NormType::CROSS_MAP })),
framework::dataset::make("NormalizationSize", 3, 9, 2)),
framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
@@ -135,9 +131,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using CLNormalizationLayerFixedPointFixture = NormalizationValidationFixedPointFixture<CLTensor, CLAccessor, CLNormalizationLayer, T>;
-
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp
index b28a5eb..0b8a11f 100644
--- a/tests/validation/CL/PoolingLayer.cpp
+++ b/tests/validation/CL/PoolingLayer.cpp
@@ -148,9 +148,6 @@
TEST_SUITE_END() // FP16
TEST_SUITE_END() // Float
-template <typename T>
-using CLPoolingLayerFixedPointFixture = PoolingLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
-
TEST_SUITE(Quantized)
template <typename T>
diff --git a/tests/validation/CL/SYSTEM/AlexNet.cpp b/tests/validation/CL/SYSTEM/AlexNet.cpp
index 75f8d19..9be6f2c 100644
--- a/tests/validation/CL/SYSTEM/AlexNet.cpp
+++ b/tests/validation/CL/SYSTEM/AlexNet.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -79,7 +79,7 @@
"cnn_data/alexnet_model/fc8_b.npy"
};
CLAlexNetModel network{};
- network.init(dt, 4, batches);
+ network.init(dt, batches);
network.build();
network.allocate();
network.fill(weight_files, bias_files);
diff --git a/tests/validation/CL/SoftmaxLayer.cpp b/tests/validation/CL/SoftmaxLayer.cpp
index b47f84f..66ca0b8 100644
--- a/tests/validation/CL/SoftmaxLayer.cpp
+++ b/tests/validation/CL/SoftmaxLayer.cpp
@@ -64,13 +64,11 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SoftmaxLayerSmallShapes(), datasets::SoftmaxLayerLargeShapes()), CNNDataTypes), shape, data_type)
{
- // Set fixed point position and quantization info if is allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
- const QuantizationInfo quantization_info = is_data_type_quantized_asymmetric(data_type) ? QuantizationInfo(1.f / 255.f, 0) : QuantizationInfo();
+ const QuantizationInfo quantization_info = is_data_type_quantized_asymmetric(data_type) ? QuantizationInfo(1.f / 255.f, 0) : QuantizationInfo();
// Create tensors
- CLTensor src = create_tensor<CLTensor>(shape, data_type, 1, fixed_point_position, quantization_info);
- CLTensor dst = create_tensor<CLTensor>(shape, data_type, 1, fixed_point_position, QuantizationInfo(1.f / 256.f, 0));
+ CLTensor src = create_tensor<CLTensor>(shape, data_type, 1, quantization_info);
+ CLTensor dst = create_tensor<CLTensor>(shape, data_type, 1, QuantizationInfo(1.f / 256.f, 0));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -167,9 +165,6 @@
TEST_SUITE_END()
template <typename T>
-using CLSoftmaxLayerFixedPointFixture = SoftmaxValidationFixedPointFixture<CLTensor, CLAccessor, CLSoftmaxLayer, T>;
-
-template <typename T>
using CLSoftmaxLayerQuantizedFixture = SoftmaxValidationQuantizedFixture<CLTensor, CLAccessor, CLSoftmaxLayer, T>;
TEST_SUITE(Quantized)
diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp
index f68ec8c..501afac 100644
--- a/tests/validation/CL/Winograd.cpp
+++ b/tests/validation/CL/Winograd.cpp
@@ -169,7 +169,7 @@
TensorShape shape_out = compute_winograd_input_transform_shape(tensor_info_in, winograd_info);
// Create tensors
- CLTensor in = create_tensor<CLTensor>(shape_in, data_type, 1, 0, QuantizationInfo(), data_layout);
+ CLTensor in = create_tensor<CLTensor>(shape_in, data_type, 1, QuantizationInfo(), data_layout);
CLTensor out = create_tensor<CLTensor>(shape_out, data_type);
ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -216,7 +216,7 @@
TensorShape shape_out = compute_winograd_input_transform_shape(tensor_info_in, winograd_info);
// Create tensors
- CLTensor in = create_tensor<CLTensor>(shape_in_nhwc, data_type, 1, 0, QuantizationInfo(), data_layout);
+ CLTensor in = create_tensor<CLTensor>(shape_in_nhwc, data_type, 1, QuantizationInfo(), data_layout);
CLTensor out = create_tensor<CLTensor>(shape_out, data_type);
ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -296,8 +296,8 @@
TensorShape shape_b = compute_winograd_filter_transform_shape(TensorInfo(shape_a, 1, data_type), winograd_info);
// Create tensors
- CLTensor a = create_tensor<CLTensor>(shape_a, data_type, 1, 0, QuantizationInfo(), data_layout);
- CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, 0, QuantizationInfo(), data_layout);
+ CLTensor a = create_tensor<CLTensor>(shape_a, data_type, 1, QuantizationInfo(), data_layout);
+ CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, QuantizationInfo(), data_layout);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -348,8 +348,8 @@
TensorShape shape_b = compute_winograd_filter_transform_shape(tensor_info_in, winograd_info);
// Create tensors
- CLTensor a = create_tensor<CLTensor>(shape_in_nhwc, data_type, 1, 0, QuantizationInfo(), data_layout);
- CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, 0, QuantizationInfo(), data_layout);
+ CLTensor a = create_tensor<CLTensor>(shape_in_nhwc, data_type, 1, QuantizationInfo(), data_layout);
+ CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, QuantizationInfo(), data_layout);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -444,7 +444,7 @@
// Create tensors
CLTensor a = create_tensor<CLTensor>(shape_a, data_type);
- CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, 0, QuantizationInfo(), winograd_info.output_data_layout);
+ CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, QuantizationInfo(), winograd_info.output_data_layout);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -481,7 +481,7 @@
// Create tensors
CLTensor a = create_tensor<CLTensor>(shape_a, data_type);
- CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, 0, QuantizationInfo(), winograd_info.output_data_layout);
+ CLTensor b = create_tensor<CLTensor>(shape_b, data_type, 1, QuantizationInfo(), winograd_info.output_data_layout);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/GLES_COMPUTE/ActivationLayer.cpp b/tests/validation/GLES_COMPUTE/ActivationLayer.cpp
index 23821d3..a8c7253 100644
--- a/tests/validation/GLES_COMPUTE/ActivationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/ActivationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -112,12 +112,9 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), CNNDataTypes), framework::dataset::make("InPlace", { false, true })),
shape, data_type, in_place)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = 0;
-
// Create tensors
- GCTensor src = create_tensor<GCTensor>(shape, data_type, 1, fixed_point_position);
- GCTensor dst = create_tensor<GCTensor>(shape, data_type, 1, fixed_point_position);
+ GCTensor src = create_tensor<GCTensor>(shape, data_type, 1);
+ GCTensor dst = create_tensor<GCTensor>(shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
index d22f1e9..3a3d1d7 100644
--- a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -67,9 +67,6 @@
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
shape0, shape1, epsilon, use_beta, use_gamma, dt, data_layout)
{
- // Set fixed point position data type allowed
- int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
-
TensorShape src_dst_shapes = shape0;
if(data_layout == DataLayout::NHWC)
{
@@ -77,12 +74,12 @@
}
// Create tensors
- GCTensor src = create_tensor<GCTensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- GCTensor dst = create_tensor<GCTensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- GCTensor mean = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
- GCTensor var = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
- GCTensor beta = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
- GCTensor gamma = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
+ GCTensor src = create_tensor<GCTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ GCTensor dst = create_tensor<GCTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ GCTensor mean = create_tensor<GCTensor>(shape1, dt, 1);
+ GCTensor var = create_tensor<GCTensor>(shape1, dt, 1);
+ GCTensor beta = create_tensor<GCTensor>(shape1, dt, 1);
+ GCTensor gamma = create_tensor<GCTensor>(shape1, dt, 1);
// Create and Configure function
GCBatchNormalizationLayer norm;
diff --git a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
index 0f81512..2961dc9 100644
--- a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp
@@ -70,16 +70,13 @@
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- GCTensor src = create_tensor<GCTensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- GCTensor weights = create_tensor<GCTensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- GCTensor bias = create_tensor<GCTensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- GCTensor dst = create_tensor<GCTensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ GCTensor src = create_tensor<GCTensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ GCTensor weights = create_tensor<GCTensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ GCTensor bias = create_tensor<GCTensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ GCTensor dst = create_tensor<GCTensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/GLES_COMPUTE/FullyConnectedLayer.cpp b/tests/validation/GLES_COMPUTE/FullyConnectedLayer.cpp
index 4040f46..49716dc 100644
--- a/tests/validation/GLES_COMPUTE/FullyConnectedLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/FullyConnectedLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -66,9 +66,6 @@
CNNDataTypes),
src_shape, weights_shape, bias_shape, dst_shape, transpose_weights, reshape_weights, data_type)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
TensorShape ws(weights_shape);
// Transpose weights if not done in the function
@@ -80,10 +77,10 @@
}
// Create tensors
- GCTensor src = create_tensor<GCTensor>(src_shape, data_type, 1, fixed_point_position);
- GCTensor weights = create_tensor<GCTensor>(ws, data_type, 1, fixed_point_position);
- GCTensor bias = create_tensor<GCTensor>(bias_shape, data_type, 1, fixed_point_position);
- GCTensor dst = create_tensor<GCTensor>(dst_shape, data_type, 1, fixed_point_position);
+ GCTensor src = create_tensor<GCTensor>(src_shape, data_type, 1);
+ GCTensor weights = create_tensor<GCTensor>(ws, data_type, 1);
+ GCTensor bias = create_tensor<GCTensor>(bias_shape, data_type, 1);
+ GCTensor dst = create_tensor<GCTensor>(dst_shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/GLES_COMPUTE/GEMM.cpp b/tests/validation/GLES_COMPUTE/GEMM.cpp
index 2abad32..6417143 100644
--- a/tests/validation/GLES_COMPUTE/GEMM.cpp
+++ b/tests/validation/GLES_COMPUTE/GEMM.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -59,14 +59,11 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallGEMMDataset(), datasets::LargeGEMMDataset()), CNNDataTypes),
shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- GCTensor a = create_tensor<GCTensor>(shape_a, data_type, 1, fixed_point_position);
- GCTensor b = create_tensor<GCTensor>(shape_b, data_type, 1, fixed_point_position);
- GCTensor c = create_tensor<GCTensor>(shape_c, data_type, 1, fixed_point_position);
- GCTensor dst = create_tensor<GCTensor>(output_shape, data_type, 1, fixed_point_position);
+ GCTensor a = create_tensor<GCTensor>(shape_a, data_type, 1);
+ GCTensor b = create_tensor<GCTensor>(shape_b, data_type, 1);
+ GCTensor c = create_tensor<GCTensor>(shape_c, data_type, 1);
+ GCTensor dst = create_tensor<GCTensor>(output_shape, data_type, 1);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/GLES_COMPUTE/SoftmaxLayer.cpp b/tests/validation/GLES_COMPUTE/SoftmaxLayer.cpp
index 2c28141..abc277a 100644
--- a/tests/validation/GLES_COMPUTE/SoftmaxLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/SoftmaxLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -59,12 +59,9 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SoftmaxLayerSmallShapes(), datasets::SoftmaxLayerLargeShapes()), CNNDataTypes), shape, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- GCTensor src = create_tensor<GCTensor>(shape, data_type, 1, fixed_point_position);
- GCTensor dst = create_tensor<GCTensor>(shape, data_type, 1, fixed_point_position);
+ GCTensor src = create_tensor<GCTensor>(shape, data_type, 1);
+ GCTensor dst = create_tensor<GCTensor>(shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp
index ff69b1c..8832fce 100644
--- a/tests/validation/Helpers.cpp
+++ b/tests/validation/Helpers.cpp
@@ -150,7 +150,7 @@
SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src)
{
const QuantizationInfo &quantization_info = src.quantization_info();
- SimpleTensor<float> dst{ src.shape(), DataType::F32, 1, 0, QuantizationInfo(), src.data_layout() };
+ SimpleTensor<float> dst{ src.shape(), DataType::F32, 1, QuantizationInfo(), src.data_layout() };
for(int i = 0; i < src.num_elements(); ++i)
{
@@ -161,7 +161,7 @@
SimpleTensor<uint8_t> convert_to_asymmetric(const SimpleTensor<float> &src, const QuantizationInfo &quantization_info)
{
- SimpleTensor<uint8_t> dst{ src.shape(), DataType::QASYMM8, 1, 0, quantization_info };
+ SimpleTensor<uint8_t> dst{ src.shape(), DataType::QASYMM8, 1, quantization_info };
for(int i = 0; i < src.num_elements(); ++i)
{
dst[i] = quantization_info.quantize(src[i], RoundingPolicy::TO_NEAREST_UP);
diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h
index 88262d5..2b4d277 100644
--- a/tests/validation/Helpers.h
+++ b/tests/validation/Helpers.h
@@ -52,14 +52,13 @@
/** Helper function to get the testing range for each activation layer.
*
- * @param[in] activation Activation function to test.
- * @param[in] data_type Data type.
- * @param[in] fixed_point_position Number of bits for the fractional part. Defaults to 1.
+ * @param[in] activation Activation function to test.
+ * @param[in] data_type Data type.
*
* @return A pair containing the lower upper testing bounds for a given function.
*/
template <typename T>
-std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, DataType data_type, int fixed_point_position = 0)
+std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, DataType data_type)
{
std::pair<T, T> bounds;
@@ -178,12 +177,12 @@
/** Helper function to get the testing range for batch normalization layer.
*
- * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 1.
+ * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 0.
*
* @return A pair containing the lower upper testing bounds.
*/
template <typename T>
-std::pair<T, T> get_batchnormalization_layer_test_bounds(int fixed_point_position = 1)
+std::pair<T, T> get_batchnormalization_layer_test_bounds(int fixed_point_position = 0)
{
const bool is_float = std::is_floating_point<T>::value;
std::pair<T, T> bounds;
diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp
index 289ca48..dee264c 100644
--- a/tests/validation/NEON/ActivationLayer.cpp
+++ b/tests/validation/NEON/ActivationLayer.cpp
@@ -90,12 +90,9 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), CNNDataTypes), framework::dataset::make("InPlace", { false, true })),
shape, data_type, in_place)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, data_type, 1);
+ Tensor dst = create_tensor<Tensor>(shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -196,9 +193,6 @@
TEST_SUITE_END()
template <typename T>
-using NEActivationLayerFixedPointFixture = ActivationValidationFixedPointFixture<Tensor, Accessor, NEActivationLayer, T>;
-
-template <typename T>
using NEActivationLayerQuantizedFixture = ActivationValidationQuantizedFixture<Tensor, Accessor, NEActivationLayer, T>;
/** Input data sets. */
diff --git a/tests/validation/NEON/ArithmeticAddition.cpp b/tests/validation/NEON/ArithmeticAddition.cpp
index b01e5d9..3632c3c 100644
--- a/tests/validation/NEON/ArithmeticAddition.cpp
+++ b/tests/validation/NEON/ArithmeticAddition.cpp
@@ -163,9 +163,6 @@
}
TEST_SUITE_END()
-template <typename T>
-using NEArithmeticAdditionFixedPointFixture = ArithmeticAdditionValidationFixedPointFixture<Tensor, Accessor, NEArithmeticAddition, T>;
-
TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(F16)
diff --git a/tests/validation/NEON/ArithmeticSubtraction.cpp b/tests/validation/NEON/ArithmeticSubtraction.cpp
index fc25465..210ed45 100644
--- a/tests/validation/NEON/ArithmeticSubtraction.cpp
+++ b/tests/validation/NEON/ArithmeticSubtraction.cpp
@@ -233,9 +233,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T1, typename T2 = T1, typename T3 = T1>
-using NEArithmeticSubtractionFixedPointFixture = ArithmeticSubtractionValidationFixedPointFixture<Tensor, Accessor, NEArithmeticSubtraction, T1, T2, T3>;
-
TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp
index 3a18a0a..ca13d26 100644
--- a/tests/validation/NEON/BatchNormalizationLayer.cpp
+++ b/tests/validation/NEON/BatchNormalizationLayer.cpp
@@ -68,9 +68,6 @@
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
shape0, shape1, epsilon, use_beta, use_gamma, dt, data_layout)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
-
TensorShape src_dst_shapes = shape0;
if(data_layout == DataLayout::NHWC)
{
@@ -78,12 +75,12 @@
}
// Create tensors
- Tensor src = create_tensor<Tensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- Tensor dst = create_tensor<Tensor>(src_dst_shapes, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- Tensor mean = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position);
- Tensor var = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position);
- Tensor beta = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position);
- Tensor gamma = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ Tensor dst = create_tensor<Tensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
+ Tensor mean = create_tensor<Tensor>(shape1, dt, 1);
+ Tensor var = create_tensor<Tensor>(shape1, dt, 1);
+ Tensor beta = create_tensor<Tensor>(shape1, dt, 1);
+ Tensor gamma = create_tensor<Tensor>(shape1, dt, 1);
// Create and Configure function
NEBatchNormalizationLayer norm;
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp
index 94b38c2..591d142 100644
--- a/tests/validation/NEON/ConvolutionLayer.cpp
+++ b/tests/validation/NEON/ConvolutionLayer.cpp
@@ -154,16 +154,13 @@
{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -246,9 +243,6 @@
TEST_SUITE_END()
template <typename T>
-using NEGEMMConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>;
-
-template <typename T>
using NEGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>;
const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
diff --git a/tests/validation/NEON/DepthConvertLayer.cpp b/tests/validation/NEON/DepthConvertLayer.cpp
index 2bd3db7..78070d0 100644
--- a/tests/validation/NEON/DepthConvertLayer.cpp
+++ b/tests/validation/NEON/DepthConvertLayer.cpp
@@ -66,19 +66,15 @@
using NEDepthConvertLayerToU8Fixture = DepthConvertLayerValidationFixture<Tensor, Accessor, NEDepthConvertLayer, T, uint8_t>;
template <typename T>
using NEDepthConvertLayerToU32Fixture = DepthConvertLayerValidationFixture<Tensor, Accessor, NEDepthConvertLayer, T, uint32_t>;
-template <typename T>
-using NEDepthConvertLayerToFP32FixedPointFixture = DepthConvertLayerValidationFractionalBitsFixture<Tensor, Accessor, NEDepthConvertLayer, T, float>;
TEST_SUITE(U8_to_U16)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })),
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U16, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U16, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -116,11 +112,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::S16, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::S16, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -157,11 +151,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::S32, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::U8, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::S32, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -199,11 +191,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U16, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U8, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::U16, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U8, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -240,11 +230,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U16, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U32, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::U16, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U32, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -281,11 +269,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::S16, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U8, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::S16, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::U8, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
@@ -322,11 +308,9 @@
DepthConvertLayerShiftDataset),
shape, policy, shift)
{
- int fixed_point_position = 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::S16, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, DataType::S32, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, DataType::S16, 1);
+ Tensor dst = create_tensor<Tensor>(shape, DataType::S32, 1);
// Create and Configure function
NEDepthConvertLayer depth_convert;
diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp
index e703c67..7cfffc0 100644
--- a/tests/validation/NEON/DilatedConvolutionLayer.cpp
+++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp
@@ -106,16 +106,13 @@
CNNDataTypes),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
- Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor bias = create_tensor<Tensor>(bias_shape, bias_data_type, 1, QuantizationInfo(2.f / 255.f, 127));
+ Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, QuantizationInfo(2.f / 255.f, 127));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -198,9 +195,6 @@
TEST_SUITE_END()
template <typename T>
-using NEGEMMDilatedConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>;
-
-template <typename T>
using NEGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>;
TEST_SUITE(Quantized)
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp
index 4995d88..bf5b33c 100644
--- a/tests/validation/NEON/DirectConvolutionLayer.cpp
+++ b/tests/validation/NEON/DirectConvolutionLayer.cpp
@@ -173,9 +173,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using NEDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFixedPointFixture<Tensor, Accessor, NEDirectConvolutionLayer, T>;
-
const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
{
ActivationLayerInfo(),
diff --git a/tests/validation/NEON/FullyConnectedLayer.cpp b/tests/validation/NEON/FullyConnectedLayer.cpp
index 3adcf61..174778b 100644
--- a/tests/validation/NEON/FullyConnectedLayer.cpp
+++ b/tests/validation/NEON/FullyConnectedLayer.cpp
@@ -68,9 +68,6 @@
CNNDataTypes),
src_shape, weights_shape, bias_shape, dst_shape, transpose_weights, reshape_weights, data_type)
{
- // Set fixed point position data type allowed
- int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
TensorShape ws(weights_shape);
// Transpose weights if not done in the function
@@ -92,10 +89,10 @@
}
// Create tensors
- Tensor src = create_tensor<Tensor>(src_shape, data_type, 1, fixed_point_position);
- Tensor weights = create_tensor<Tensor>(ws, data_type, 1, fixed_point_position);
- Tensor bias = create_tensor<Tensor>(bias_shape, data_type, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(dst_shape, data_type, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(src_shape, data_type, 1);
+ Tensor weights = create_tensor<Tensor>(ws, data_type, 1);
+ Tensor bias = create_tensor<Tensor>(bias_shape, data_type, 1);
+ Tensor dst = create_tensor<Tensor>(dst_shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -192,9 +189,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using NEFullyConnectedLayerFixedPointFixture = FullyConnectedLayerValidationFixedPointFixture<Tensor, Accessor, NEFullyConnectedLayer, T, true>;
-
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/NEON/GEMM.cpp b/tests/validation/NEON/GEMM.cpp
index e0f63a8..9c64131 100644
--- a/tests/validation/NEON/GEMM.cpp
+++ b/tests/validation/NEON/GEMM.cpp
@@ -98,14 +98,11 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallGEMMDataset(), datasets::LargeGEMMDataset()), CNNDataTypes),
shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- Tensor a = create_tensor<Tensor>(shape_a, data_type, 1, fixed_point_position);
- Tensor b = create_tensor<Tensor>(shape_b, data_type, 1, fixed_point_position);
- Tensor c = create_tensor<Tensor>(shape_c, data_type, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, fixed_point_position);
+ Tensor a = create_tensor<Tensor>(shape_a, data_type, 1);
+ Tensor b = create_tensor<Tensor>(shape_b, data_type, 1);
+ Tensor c = create_tensor<Tensor>(shape_c, data_type, 1);
+ Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1);
ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -153,9 +150,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using NEGEMMFixedPointFixture = GEMMValidationFixedPointFixture<Tensor, Accessor, NEGEMM, T>;
-
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/NEON/NormalizationLayer.cpp b/tests/validation/NEON/NormalizationLayer.cpp
index 8c66611..02cca0b 100644
--- a/tests/validation/NEON/NormalizationLayer.cpp
+++ b/tests/validation/NEON/NormalizationLayer.cpp
@@ -50,9 +50,6 @@
constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
/** Input data set. */
-const auto NormalizationDatasetQS = combine(combine(combine(combine(datasets::TinyShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
- framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
- framework::dataset::make("IsScaled", { true }));
const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
framework::dataset::make("IsScaled", { true }));
@@ -132,9 +129,6 @@
TEST_SUITE_END()
TEST_SUITE_END()
-template <typename T>
-using NENormalizationLayerFixedPointFixture = NormalizationValidationFixedPointFixture<Tensor, Accessor, NENormalizationLayer, T>;
-
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/NEON/PoolingLayer.cpp b/tests/validation/NEON/PoolingLayer.cpp
index 8762f1f..bbfca46 100644
--- a/tests/validation/NEON/PoolingLayer.cpp
+++ b/tests/validation/NEON/PoolingLayer.cpp
@@ -50,11 +50,6 @@
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
framework::dataset::make("ExcludePadding", { true, false }));
-/** Input data set for quantized data types */
-const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
- framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
- framework::dataset::make("ExcludePadding", { false }));
-
/** Input data set for asymmetric data type */
const auto PoolingLayerDatasetQASYMM8 = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3), Size2D(4, 4), Size2D(9, 9), Size2D(3, 7), Size2D(7, 8) })),
@@ -159,9 +154,6 @@
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
TEST_SUITE_END() // Float
-template <typename T>
-using NEPoolingLayerFixedPointFixture = PoolingLayerValidationFixedPointFixture<Tensor, Accessor, NEPoolingLayer, T>;
-
TEST_SUITE(Quantized)
template <typename T>
diff --git a/tests/validation/NEON/SYSTEM/AlexNet.cpp b/tests/validation/NEON/SYSTEM/AlexNet.cpp
index 3fa19e4..adcfe72 100644
--- a/tests/validation/NEON/SYSTEM/AlexNet.cpp
+++ b/tests/validation/NEON/SYSTEM/AlexNet.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -80,7 +80,7 @@
};
NEAlexNetModel network{};
- network.init(dt, 4, batches);
+ network.init(dt, batches);
network.build();
network.allocate();
network.fill(weight_files, bias_files);
diff --git a/tests/validation/NEON/Scale.cpp b/tests/validation/NEON/Scale.cpp
index 8940259..5f5cfdd 100644
--- a/tests/validation/NEON/Scale.cpp
+++ b/tests/validation/NEON/Scale.cpp
@@ -159,8 +159,8 @@
shape_scaled.set(idx_height, src_shape[idx_height] * scale_y);
// Create tensors
- Tensor src = create_tensor<Tensor>(src_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- Tensor dst = create_tensor<Tensor>(shape_scaled, data_type, 1, 0, QuantizationInfo(), data_layout);
+ Tensor src = create_tensor<Tensor>(src_shape, data_type, 1, QuantizationInfo(), data_layout);
+ Tensor dst = create_tensor<Tensor>(shape_scaled, data_type, 1, QuantizationInfo(), data_layout);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/NEON/SoftmaxLayer.cpp b/tests/validation/NEON/SoftmaxLayer.cpp
index b6efc8f..8c0d46b 100644
--- a/tests/validation/NEON/SoftmaxLayer.cpp
+++ b/tests/validation/NEON/SoftmaxLayer.cpp
@@ -66,12 +66,9 @@
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SoftmaxLayerSmallShapes(), datasets::SoftmaxLayerLargeShapes()), CNNDataTypes), shape, data_type)
{
- // Set fixed point position data type allowed
- const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
-
// Create tensors
- Tensor src = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
- Tensor dst = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
+ Tensor src = create_tensor<Tensor>(shape, data_type, 1);
+ Tensor dst = create_tensor<Tensor>(shape, data_type, 1);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -156,9 +153,6 @@
TEST_SUITE_END()
template <typename T>
-using NESoftmaxLayerFixedPointFixture = SoftmaxValidationFixedPointFixture<Tensor, Accessor, NESoftmaxLayer, T>;
-
-template <typename T>
using NESoftmaxLayerQuantizedFixture = SoftmaxValidationQuantizedFixture<Tensor, Accessor, NESoftmaxLayer, T>;
TEST_SUITE(Quantized)
diff --git a/tests/validation/fixtures/ActivationLayerFixture.h b/tests/validation/fixtures/ActivationLayerFixture.h
index e212c7b..d29d67c 100644
--- a/tests/validation/fixtures/ActivationLayerFixture.h
+++ b/tests/validation/fixtures/ActivationLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,17 +47,16 @@
{
public:
template <typename...>
- void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+ void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type, QuantizationInfo quantization_info)
{
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_type = data_type;
_function = function;
ActivationLayerInfo info(function, alpha_beta, alpha_beta);
- _target = compute_target(shape, in_place, info, data_type, fractional_bits, quantization_info);
- _reference = compute_reference(shape, info, data_type, fractional_bits, quantization_info);
+ _target = compute_target(shape, in_place, info, data_type, quantization_info);
+ _reference = compute_reference(shape, info, data_type, quantization_info);
}
protected:
@@ -80,17 +79,17 @@
{
int min_bound = 0;
int max_bound = 0;
- std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type, _fractional_bits);
+ std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type);
std::uniform_int_distribution<> distribution(min_bound, max_bound);
library->fill(tensor, distribution, 0);
}
}
- TensorType compute_target(const TensorShape &shape, bool in_place, ActivationLayerInfo info, DataType data_type, int fixed_point_position, QuantizationInfo quantization_info)
+ TensorType compute_target(const TensorShape &shape, bool in_place, ActivationLayerInfo info, DataType data_type, QuantizationInfo quantization_info)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, quantization_info);
- TensorType dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, quantization_info);
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info);
+ TensorType dst = create_tensor<TensorType>(shape, data_type, 1, quantization_info);
// Create and configure function
FunctionType act_layer;
@@ -128,10 +127,10 @@
}
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, ActivationLayerInfo info, DataType data_type, int fixed_point_position, QuantizationInfo quantization_info)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, ActivationLayerInfo info, DataType data_type, QuantizationInfo quantization_info)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> src{ shape, data_type, 1, quantization_info };
// Fill reference
fill(src);
@@ -141,7 +140,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
DataType _data_type{};
ActivationLayerInfo::ActivationFunction _function{};
@@ -154,18 +152,7 @@
template <typename...>
void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type)
{
- ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, 0, QuantizationInfo());
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ActivationValidationFixedPointFixture : public ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type, int fractional_bits)
- {
- ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, fractional_bits, QuantizationInfo());
+ ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, QuantizationInfo());
}
};
@@ -176,7 +163,7 @@
template <typename...>
void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type, QuantizationInfo quantization_info)
{
- ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, 0, quantization_info);
+ ActivationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, quantization_info);
}
};
diff --git a/tests/validation/fixtures/ArithmeticAdditionFixture.h b/tests/validation/fixtures/ArithmeticAdditionFixture.h
index 99a5677..6d529a8 100644
--- a/tests/validation/fixtures/ArithmeticAdditionFixture.h
+++ b/tests/validation/fixtures/ArithmeticAdditionFixture.h
@@ -45,11 +45,11 @@
{
public:
template <typename...>
- void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits,
+ void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy,
QuantizationInfo quantization_info)
{
- _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, quantization_info);
- _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, quantization_info);
+ _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, quantization_info);
+ _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, quantization_info);
}
protected:
@@ -60,12 +60,12 @@
}
TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy,
- int fixed_point_position, QuantizationInfo quantization_info)
+ QuantizationInfo quantization_info)
{
// Create tensors
- TensorType ref_src1 = create_tensor<TensorType>(shape0, data_type0, 1, fixed_point_position, quantization_info);
- TensorType ref_src2 = create_tensor<TensorType>(shape1, data_type1, 1, fixed_point_position, quantization_info);
- TensorType dst = create_tensor<TensorType>(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, fixed_point_position, quantization_info);
+ TensorType ref_src1 = create_tensor<TensorType>(shape0, data_type0, 1, quantization_info);
+ TensorType ref_src2 = create_tensor<TensorType>(shape1, data_type1, 1, quantization_info);
+ TensorType dst = create_tensor<TensorType>(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, quantization_info);
// Create and configure function
FunctionType add;
@@ -95,11 +95,11 @@
}
SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy,
- int fixed_point_position, QuantizationInfo quantization_info)
+ QuantizationInfo quantization_info)
{
// Create reference
- SimpleTensor<T> ref_src1{ shape0, data_type0, 1, fixed_point_position, quantization_info };
- SimpleTensor<T> ref_src2{ shape1, data_type1, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> ref_src1{ shape0, data_type0, 1, quantization_info };
+ SimpleTensor<T> ref_src2{ shape1, data_type1, 1, quantization_info };
// Fill reference
fill(ref_src1, 0);
@@ -117,9 +117,9 @@
{
public:
template <typename...>
- void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits)
+ void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, 0, QuantizationInfo());
+ ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, QuantizationInfo());
}
};
@@ -130,7 +130,7 @@
template <typename...>
void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, 0, QuantizationInfo());
+ ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, QuantizationInfo());
}
};
@@ -139,9 +139,9 @@
{
public:
template <typename...>
- void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits)
+ void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, QuantizationInfo());
+ ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, QuantizationInfo());
}
};
@@ -152,7 +152,7 @@
template <typename...>
void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- ArithmeticAdditionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type0, data_type1, output_data_type, convert_policy, 0);
+ ArithmeticAdditionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type0, data_type1, output_data_type, convert_policy);
}
};
@@ -163,7 +163,7 @@
template <typename...>
void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, QuantizationInfo quantization_info)
{
- ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, 0, quantization_info);
+ ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, quantization_info);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/ArithmeticSubtractionFixture.h b/tests/validation/fixtures/ArithmeticSubtractionFixture.h
index ba0dd14..04bb53a 100644
--- a/tests/validation/fixtures/ArithmeticSubtractionFixture.h
+++ b/tests/validation/fixtures/ArithmeticSubtractionFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -45,11 +45,10 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits)
+ void setup(TensorShape shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- _fractional_bits = fractional_bits;
- _target = compute_target(shape, data_type0, data_type1, output_data_type, convert_policy, fractional_bits);
- _reference = compute_reference(shape, data_type0, data_type1, output_data_type, convert_policy, fractional_bits);
+ _target = compute_target(shape, data_type0, data_type1, output_data_type, convert_policy);
+ _reference = compute_reference(shape, data_type0, data_type1, output_data_type, convert_policy);
}
protected:
@@ -59,12 +58,12 @@
library->fill_tensor_uniform(tensor, i);
}
- TensorType compute_target(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fixed_point_position)
+ TensorType compute_target(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
// Create tensors
- TensorType ref_src1 = create_tensor<TensorType>(shape, data_type0, 1, fixed_point_position);
- TensorType ref_src2 = create_tensor<TensorType>(shape, data_type1, 1, fixed_point_position);
- TensorType dst = create_tensor<TensorType>(shape, output_data_type, 1, fixed_point_position);
+ TensorType ref_src1 = create_tensor<TensorType>(shape, data_type0, 1);
+ TensorType ref_src2 = create_tensor<TensorType>(shape, data_type1, 1);
+ TensorType dst = create_tensor<TensorType>(shape, output_data_type, 1);
// Create and configure function
FunctionType sub;
@@ -93,11 +92,11 @@
return dst;
}
- SimpleTensor<T3> compute_reference(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fixed_point_position)
+ SimpleTensor<T3> compute_reference(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
// Create reference
- SimpleTensor<T1> ref_src1{ shape, data_type0, 1, fixed_point_position };
- SimpleTensor<T2> ref_src2{ shape, data_type1, 1, fixed_point_position };
+ SimpleTensor<T1> ref_src1{ shape, data_type0, 1 };
+ SimpleTensor<T2> ref_src2{ shape, data_type1, 1 };
// Fill reference
fill(ref_src1, 0);
@@ -108,7 +107,6 @@
TensorType _target{};
SimpleTensor<T3> _reference{};
- int _fractional_bits{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T1, typename T2 = T1, typename T3 = T1>
class ArithmeticSubtractionValidationFixture : public ArithmeticSubtractionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2, T3>
@@ -117,7 +115,7 @@
template <typename...>
void setup(TensorShape shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy)
{
- ArithmeticSubtractionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2, T3>::setup(shape, data_type0, data_type1, output_data_type, convert_policy, 0);
+ ArithmeticSubtractionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2, T3>::setup(shape, data_type0, data_type1, output_data_type, convert_policy);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
index b7e32a6..bc3b488 100644
--- a/tests/validation/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
@@ -45,15 +45,14 @@
{
public:
template <typename...>
- void setup(TensorShape shape0, TensorShape shape1, float epsilon, bool use_beta, bool use_gamma, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout, int fractional_bits)
+ void setup(TensorShape shape0, TensorShape shape1, float epsilon, bool use_beta, bool use_gamma, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout)
{
- _fractional_bits = fractional_bits;
- _data_type = dt;
- _use_beta = use_beta;
- _use_gamma = use_gamma;
+ _data_type = dt;
+ _use_beta = use_beta;
+ _use_gamma = use_gamma;
- _target = compute_target(shape0, shape1, epsilon, act_info, dt, data_layout, fractional_bits);
- _reference = compute_reference(shape0, shape1, epsilon, act_info, dt, fractional_bits);
+ _target = compute_target(shape0, shape1, epsilon, act_info, dt, data_layout);
+ _reference = compute_reference(shape0, shape1, epsilon, act_info, dt);
}
protected:
@@ -93,7 +92,7 @@
{
int min_bound = 0;
int max_bound = 0;
- std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds<T>(_fractional_bits);
+ std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds<T>();
std::uniform_int_distribution<> distribution(min_bound, max_bound);
std::uniform_int_distribution<> distribution_var(0, max_bound);
library->fill(src_tensor, distribution, 0);
@@ -115,12 +114,12 @@
else
{
// Fill with default value 1
- library->fill_tensor_value(gamma_tensor, static_cast<T>(1 << (_fractional_bits)));
+ library->fill_tensor_value(gamma_tensor, static_cast<T>(1));
}
}
}
- TensorType compute_target(TensorShape shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout, int fixed_point_position)
+ TensorType compute_target(TensorShape shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout)
{
if(data_layout == DataLayout::NHWC)
{
@@ -128,12 +127,12 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(shape0, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- TensorType dst = create_tensor<TensorType>(shape0, dt, 1, fixed_point_position, QuantizationInfo(), data_layout);
- TensorType mean = create_tensor<TensorType>(shape1, dt, 1, fixed_point_position);
- TensorType var = create_tensor<TensorType>(shape1, dt, 1, fixed_point_position);
- TensorType beta = create_tensor<TensorType>(shape1, dt, 1, fixed_point_position);
- TensorType gamma = create_tensor<TensorType>(shape1, dt, 1, fixed_point_position);
+ TensorType src = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout);
+ TensorType dst = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout);
+ TensorType mean = create_tensor<TensorType>(shape1, dt, 1);
+ TensorType var = create_tensor<TensorType>(shape1, dt, 1);
+ TensorType beta = create_tensor<TensorType>(shape1, dt, 1);
+ TensorType gamma = create_tensor<TensorType>(shape1, dt, 1);
// Create and configure function
FunctionType norm;
@@ -172,24 +171,23 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
+ SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt)
{
// Create reference
- SimpleTensor<T> ref_src{ shape0, dt, 1, fixed_point_position };
- SimpleTensor<T> ref_mean{ shape1, dt, 1, fixed_point_position };
- SimpleTensor<T> ref_var{ shape1, dt, 1, fixed_point_position };
- SimpleTensor<T> ref_beta{ shape1, dt, 1, fixed_point_position };
- SimpleTensor<T> ref_gamma{ shape1, dt, 1, fixed_point_position };
+ SimpleTensor<T> ref_src{ shape0, dt, 1 };
+ SimpleTensor<T> ref_mean{ shape1, dt, 1 };
+ SimpleTensor<T> ref_var{ shape1, dt, 1 };
+ SimpleTensor<T> ref_beta{ shape1, dt, 1 };
+ SimpleTensor<T> ref_gamma{ shape1, dt, 1 };
// Fill reference
fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma);
- return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info, fixed_point_position);
+ return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info);
}
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
DataType _data_type{};
bool _use_beta{};
bool _use_gamma{};
@@ -202,7 +200,7 @@
template <typename...>
void setup(TensorShape shape0, TensorShape shape1, float epsilon, bool use_beta, bool use_gamma, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout)
{
- BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, use_beta, use_gamma, act_info, dt, data_layout, 0);
+ BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, use_beta, use_gamma, act_info, dt, data_layout);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 00ca077..7ba2583 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -57,12 +57,11 @@
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights,
- DataType data_type, DataLayout data_layout, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
+ DataType data_type, DataLayout data_layout, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
{
_data_type = data_type;
_is_quantized = is_data_type_quantized_asymmetric(data_type);
_bias_data_type = _is_quantized ? DataType::S32 : data_type;
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_layout = data_layout;
@@ -117,10 +116,10 @@
TensorShape reshaped_weights_shape(weights_shape);
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, _fractional_bits, _quantization_info, _data_layout);
- TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, _data_type, 1, _fractional_bits, _quantization_info, _data_layout);
- TensorType bias = create_tensor<TensorType>(bias_shape, _bias_data_type, 1, _fractional_bits, _quantization_info, _data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, _fractional_bits, _quantization_info, _data_layout);
+ TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, _quantization_info, _data_layout);
+ TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, _data_type, 1, _quantization_info, _data_layout);
+ TensorType bias = create_tensor<TensorType>(bias_shape, _bias_data_type, 1, _quantization_info, _data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, _quantization_info, _data_layout);
// Create and configure function
FunctionType conv;
@@ -157,9 +156,9 @@
const Size2D &dilation, const ActivationLayerInfo act_info)
{
// Create reference
- SimpleTensor<T> src{ input_shape, _data_type, 1, _fractional_bits, _quantization_info };
- SimpleTensor<T> weights{ weights_shape, _data_type, 1, _fractional_bits, _quantization_info };
- SimpleTensor<TBias> bias{ bias_shape, _bias_data_type, 1, _fractional_bits, _quantization_info };
+ SimpleTensor<T> src{ input_shape, _data_type, 1, _quantization_info };
+ SimpleTensor<T> weights{ weights_shape, _data_type, 1, _quantization_info };
+ SimpleTensor<TBias> bias{ bias_shape, _bias_data_type, 1, _quantization_info };
// Fill reference
fill(src, 0);
@@ -176,7 +175,6 @@
DataType _data_type{};
DataType _bias_data_type{};
DataLayout _data_layout{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
bool _is_quantized = false;
};
@@ -189,7 +187,7 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
DataLayout data_layout, ActivationLayerInfo act_info)
{
- ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, data_layout, 0,
+ ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, data_layout,
QuantizationInfo(), act_info);
}
};
@@ -200,11 +198,11 @@
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
- int fractional_bits, ActivationLayerInfo act_info)
+ ActivationLayerInfo act_info)
{
ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type,
DataLayout::NCHW,
- fractional_bits, QuantizationInfo(), act_info);
+ QuantizationInfo(), act_info);
}
};
@@ -217,7 +215,7 @@
DataLayout data_layout, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
{
ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights,
- data_type, data_layout, 0, quantization_info, act_info);
+ data_type, data_layout, quantization_info, act_info);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/DeconvolutionLayerFixture.h b/tests/validation/fixtures/DeconvolutionLayerFixture.h
index 137068a..12ce9ce 100644
--- a/tests/validation/fixtures/DeconvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DeconvolutionLayerFixture.h
@@ -45,13 +45,12 @@
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info,
- const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type, int fractional_bits)
+ const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type)
{
- _fractional_bits = fractional_bits;
- _data_type = data_type;
+ _data_type = data_type;
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, fractional_bits);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
}
protected:
@@ -70,13 +69,13 @@
}
TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape,
- const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type, int fixed_point_position)
+ const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
- TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1, fixed_point_position);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1);
+ TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1);
// Create and configure function
FunctionType conv;
@@ -110,12 +109,12 @@
}
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape,
- const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> inner_border, DataType data_type, int fixed_point_position)
+ const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> inner_border, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position };
- SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position };
- SimpleTensor<T> bias{ bias_shape, data_type, 1, fixed_point_position };
+ SimpleTensor<T> src{ input_shape, data_type, 1 };
+ SimpleTensor<T> weights{ weights_shape, data_type, 1 };
+ SimpleTensor<T> bias{ bias_shape, data_type, 1 };
// Fill reference
fill(src, 0);
@@ -127,7 +126,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
DataType _data_type{};
};
@@ -146,7 +144,7 @@
const std::pair<unsigned int, unsigned int> inner_border(inner_border_right, inner_border_top);
auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, inner_border.first, inner_border.second, sx, sy);
TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape);
- DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type, 0);
+ DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
}
};
diff --git a/tests/validation/fixtures/DepthConcatenateLayerFixture.h b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
index 6e112c7..76b56ad 100644
--- a/tests/validation/fixtures/DepthConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
@@ -102,12 +102,12 @@
for(const auto &shape : shapes)
{
- srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1, _fractional_bits));
+ srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1));
src_ptrs.emplace_back(&srcs.back());
}
TensorShape dst_shape = calculate_depth_concatenate_shape(shapes);
- TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, _fractional_bits);
+ TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
FunctionType depth_concat;
@@ -151,7 +151,7 @@
int i = 0;
for(const auto &shape : shapes)
{
- srcs.emplace_back(shape, data_type, 1, _fractional_bits);
+ srcs.emplace_back(shape, data_type, 1);
fill(srcs.back(), i++);
}
@@ -160,9 +160,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
-
-private:
- int _fractional_bits{ 1 };
};
} // namespace validation
} // namespace test
diff --git a/tests/validation/fixtures/DepthConvertLayerFixture.h b/tests/validation/fixtures/DepthConvertLayerFixture.h
index 4b4e959..eb1c083 100644
--- a/tests/validation/fixtures/DepthConvertLayerFixture.h
+++ b/tests/validation/fixtures/DepthConvertLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -45,12 +45,11 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fractional_bits)
+ void setup(TensorShape shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift)
{
- _shift = shift;
- _fractional_bits = fractional_bits;
- _target = compute_target(shape, dt_in, dt_out, policy, shift, fractional_bits);
- _reference = compute_reference(shape, dt_in, dt_out, policy, shift, fractional_bits);
+ _shift = shift;
+ _target = compute_target(shape, dt_in, dt_out, policy, shift);
+ _reference = compute_reference(shape, dt_in, dt_out, policy, shift);
}
protected:
@@ -60,11 +59,11 @@
library->fill_tensor_uniform(tensor, i);
}
- TensorType compute_target(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fixed_point_position)
+ TensorType compute_target(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, dt_in, 1, static_cast<int>(fixed_point_position));
- TensorType dst = create_tensor<TensorType>(shape, dt_out, 1, static_cast<int>(fixed_point_position));
+ TensorType src = create_tensor<TensorType>(shape, dt_in, 1);
+ TensorType dst = create_tensor<TensorType>(shape, dt_out, 1);
// Create and configure function
FunctionType depth_convert;
@@ -89,10 +88,10 @@
return dst;
}
- SimpleTensor<T2> compute_reference(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift, uint32_t fixed_point_position)
+ SimpleTensor<T2> compute_reference(const TensorShape &shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift)
{
// Create reference
- SimpleTensor<T1> src{ shape, dt_in, 1, static_cast<int>(fixed_point_position) };
+ SimpleTensor<T1> src{ shape, dt_in, 1 };
// Fill reference
fill(src, 0);
@@ -102,7 +101,6 @@
TensorType _target{};
SimpleTensor<T2> _reference{};
- int _fractional_bits{};
int _shift{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T1, typename T2>
@@ -112,7 +110,7 @@
template <typename...>
void setup(TensorShape shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t shift)
{
- DepthConvertLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2>::setup(shape, dt_in, dt_out, policy, shift, 0);
+ DepthConvertLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2>::setup(shape, dt_in, dt_out, policy, shift);
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T1, typename T2>
@@ -120,9 +118,9 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType dt_in, DataType dt_out, ConvertPolicy policy, uint32_t fractional_bits)
+ void setup(TensorShape shape, DataType dt_in, DataType dt_out, ConvertPolicy policy)
{
- DepthConvertLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2>::setup(shape, dt_in, dt_out, policy, 0, fractional_bits);
+ DepthConvertLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T1, T2>::setup(shape, dt_in, dt_out, policy, 0);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
index 2f01f43..5428154 100644
--- a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
@@ -115,10 +115,10 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, quantization_info, data_layout);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, 0, quantization_info, data_layout);
- TensorType biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, 0, quantization_info, data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, quantization_info, data_layout);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, quantization_info, data_layout);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, quantization_info, data_layout);
+ TensorType biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, quantization_info, data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, quantization_info, data_layout);
// Create Depthwise Convolution configure function
FunctionType dwc;
@@ -155,9 +155,9 @@
unsigned int depth_multiplier,
const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info)
{
- SimpleTensor<T> src{ in_shape, data_type, 1, 0, quantization_info };
- SimpleTensor<T> weights{ weights_shape, data_type, 1, 0, quantization_info };
- SimpleTensor<TBias> biases{ biases_shape, bias_data_type, 1, 0, quantization_info };
+ SimpleTensor<T> src{ in_shape, data_type, 1, quantization_info };
+ SimpleTensor<T> weights{ weights_shape, data_type, 1, quantization_info };
+ SimpleTensor<TBias> biases{ biases_shape, bias_data_type, 1, quantization_info };
fill(src, 0);
fill(weights, 1);
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
index 38ddf33..9a58167 100644
--- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
@@ -54,11 +54,10 @@
public:
template <typename...>
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels,
- DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout)
+ DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout)
{
ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN);
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_type = data_type;
@@ -67,30 +66,29 @@
const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- TensorInfo input_info = TensorInfo(input_shape, 1, data_type, _fractional_bits);
- TensorInfo weights_info = TensorInfo(weights_shape, 1, data_type, _fractional_bits);
+ TensorInfo input_info = TensorInfo(input_shape, 1, data_type);
+ TensorInfo weights_info = TensorInfo(weights_shape, 1, data_type);
const TensorShape output_shape = compute_deep_convolution_shape(input_info, weights_info, info);
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info, act_info, data_layout);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info, act_info);
}
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
- DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout)
+ DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info, DataLayout data_layout)
{
ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN);
ARM_COMPUTE_UNUSED(dilation);
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_type = data_type;
const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info, data_layout);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info, act_info, data_layout);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info, act_info);
}
protected:
@@ -124,7 +122,7 @@
}
TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info, const DataLayout &data_layout)
+ DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info, const DataLayout &data_layout)
{
if(data_layout == DataLayout::NHWC)
{
@@ -134,10 +132,10 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info, data_layout);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position, quantization_info, data_layout);
- TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, fixed_point_position, quantization_info);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position, quantization_info, data_layout);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, quantization_info, data_layout);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, quantization_info, data_layout);
+ TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, quantization_info);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, quantization_info, data_layout);
// Create and configure function
FunctionType conv;
@@ -171,12 +169,12 @@
}
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
+ DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position, quantization_info };
- SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position, quantization_info };
- SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> src{ input_shape, data_type, 1, quantization_info };
+ SimpleTensor<T> weights{ weights_shape, data_type, 1, quantization_info };
+ SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, quantization_info };
// Fill reference
fill(src, 0);
@@ -190,7 +188,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
DataType _data_type{};
};
@@ -203,7 +200,7 @@
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, ActivationLayerInfo act_info,
DataLayout data_layout)
{
- DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo(),
+ DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, QuantizationInfo(),
act_info, data_layout);
}
};
@@ -213,10 +210,10 @@
{
public:
template <typename...>
- void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits,
+ void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type,
ActivationLayerInfo act_info)
{
- DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, fractional_bits,
+ DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
QuantizationInfo(), act_info, DataLayout::NCHW);
}
};
@@ -229,7 +226,7 @@
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info,
ActivationLayerInfo act_info)
{
- DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info,
+ DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, quantization_info,
act_info, DataLayout::NCHW);
}
};
@@ -242,7 +239,7 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
{
- DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info,
+ DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, quantization_info,
act_info, DataLayout::NCHW);
}
};
@@ -255,7 +252,7 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
DataType data_type, ActivationLayerInfo act_info)
{
- DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo(),
+ DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, QuantizationInfo(),
act_info, DataLayout::NCHW);
}
};
diff --git a/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h b/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h
index 09b6d83..144c7b7 100644
--- a/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h
+++ b/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h
@@ -50,9 +50,8 @@
public:
template <typename...>
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels,
- DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+ DataType data_type, QuantizationInfo quantization_info)
{
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_type = data_type;
@@ -62,24 +61,23 @@
const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info);
const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
}
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
- DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+ DataType data_type, QuantizationInfo quantization_info)
{
ARM_COMPUTE_UNUSED(dilation_x, dilation_y);
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_data_type = data_type;
const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
}
protected:
@@ -113,16 +111,16 @@
}
TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info)
+ DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position, quantization_info);
- TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, fixed_point_position, quantization_info);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position, quantization_info);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, quantization_info);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, quantization_info);
+ TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, quantization_info);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, quantization_info);
TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info);
- TensorType dst1 = create_tensor<TensorType>(output_shape1, data_type, 1, fixed_point_position, quantization_info);
+ TensorType dst1 = create_tensor<TensorType>(output_shape1, data_type, 1, quantization_info);
// Create and configure function
FunctionType conv;
@@ -164,14 +162,14 @@
}
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info)
+ DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position, quantization_info };
- SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position, quantization_info };
- SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> src{ input_shape, data_type, 1, quantization_info };
+ SimpleTensor<T> weights{ weights_shape, data_type, 1, quantization_info };
+ SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, quantization_info };
- SimpleTensor<T> dst{ output_shape, data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> dst{ output_shape, data_type, 1, quantization_info };
TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info);
// Fill reference
@@ -185,7 +183,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
DataType _data_type{};
@@ -212,7 +209,7 @@
template <typename...>
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type)
{
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0,
+ DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
QuantizationInfo());
}
};
@@ -222,10 +219,9 @@
{
public:
template <typename...>
- void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits)
+ void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type)
{
DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
- fractional_bits,
QuantizationInfo());
}
};
@@ -237,7 +233,7 @@
template <typename...>
void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info)
{
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0,
+ DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
quantization_info);
}
};
@@ -250,7 +246,7 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
DataType data_type, QuantizationInfo quantization_info)
{
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type, 0,
+ DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type,
quantization_info);
}
};
@@ -263,7 +259,7 @@
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
DataType data_type)
{
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type, 0,
+ DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type,
QuantizationInfo());
}
};
diff --git a/tests/validation/fixtures/DropoutLayerFixture.h b/tests/validation/fixtures/DropoutLayerFixture.h
index 3a077db..771de30 100644
--- a/tests/validation/fixtures/DropoutLayerFixture.h
+++ b/tests/validation/fixtures/DropoutLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -97,7 +97,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
};
} // namespace validation
} // namespace test
diff --git a/tests/validation/fixtures/FlattenLayerFixture.h b/tests/validation/fixtures/FlattenLayerFixture.h
index ef94ea8..f273e93 100644
--- a/tests/validation/fixtures/FlattenLayerFixture.h
+++ b/tests/validation/fixtures/FlattenLayerFixture.h
@@ -53,10 +53,8 @@
template <typename...>
void setup(TensorShape shape, DataType data_type)
{
- _fractional_bits = is_data_type_fixed_point(data_type) ? 4 : 0;
-
TensorShape shape_flatten;
- TensorInfo input_info(shape, 1, data_type, _fractional_bits);
+ TensorInfo input_info(shape, 1, data_type);
shape_flatten = compute_im2col_flatten_shape(&input_info);
_target = compute_target(shape, shape_flatten, data_type);
@@ -68,24 +66,15 @@
template <typename U>
void fill(U &&tensor)
{
- if(_fractional_bits == 0)
- {
- std::uniform_real_distribution<> distribution(-1.f, 1.f);
- library->fill(tensor, distribution, 0);
- }
- else
- {
- const int one_fixed = 1 << _fractional_bits;
- std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
- library->fill(tensor, distribution, 0);
- }
+ std::uniform_real_distribution<> distribution(-1.f, 1.f);
+ library->fill(tensor, distribution, 0);
}
TensorType compute_target(const TensorShape &shape, const TensorShape &shape_flatten, DataType data_type)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, _fractional_bits);
- TensorType dst = create_tensor<TensorType>(shape_flatten, data_type, 1, _fractional_bits);
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1);
+ TensorType dst = create_tensor<TensorType>(shape_flatten, data_type, 1);
// Create and configure function
FunctionType flatten_layer;
@@ -113,7 +102,7 @@
SimpleTensor<T> compute_reference(const TensorShape &shape, const TensorShape &shape_flatten, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, _fractional_bits };
+ SimpleTensor<T> src{ shape, data_type, 1 };
// Fill reference
fill(src);
@@ -123,7 +112,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
};
} // namespace validation
} // namespace test
diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h
index f23fc20..895e43b 100644
--- a/tests/validation/fixtures/FullyConnectedLayerFixture.h
+++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -54,14 +54,13 @@
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights,
- DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+ DataType data_type, QuantizationInfo quantization_info)
{
ARM_COMPUTE_UNUSED(weights_shape);
ARM_COMPUTE_UNUSED(bias_shape);
_data_type = data_type;
_bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_target = compute_target(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights);
@@ -126,10 +125,10 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, _fractional_bits, _quantization_info);
- TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, _data_type, 1, _fractional_bits, _quantization_info);
- TensorType bias = create_tensor<TensorType>(bias_shape, _bias_data_type, 1, _fractional_bits, _quantization_info);
- TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, _fractional_bits, _quantization_info);
+ TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, _quantization_info);
+ TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, _data_type, 1, _quantization_info);
+ TensorType bias = create_tensor<TensorType>(bias_shape, _bias_data_type, 1, _quantization_info);
+ TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, _quantization_info);
// Create and configure function.
FunctionType fc;
@@ -158,7 +157,7 @@
if(!reshape_weights || !transpose_weights)
{
TensorShape tmp_shape(weights_shape);
- RawTensor tmp(tmp_shape, _data_type, 1, _fractional_bits);
+ RawTensor tmp(tmp_shape, _data_type, 1);
// Fill with original shape
fill(tmp, 1);
@@ -199,9 +198,9 @@
bool reshape_weights)
{
// Create reference
- SimpleTensor<T> src{ input_shape, _data_type, 1, _fractional_bits, _quantization_info };
- SimpleTensor<T> weights{ weights_shape, _data_type, 1, _fractional_bits, _quantization_info };
- SimpleTensor<TBias> bias{ bias_shape, _bias_data_type, 1, _fractional_bits, _quantization_info };
+ SimpleTensor<T> src{ input_shape, _data_type, 1, _quantization_info };
+ SimpleTensor<T> weights{ weights_shape, _data_type, 1, _quantization_info };
+ SimpleTensor<TBias> bias{ bias_shape, _bias_data_type, 1, _quantization_info };
// Fill reference
fill(src, 0);
@@ -215,7 +214,6 @@
SimpleTensor<T> _reference{};
DataType _data_type{};
DataType _bias_data_type{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
};
@@ -228,7 +226,7 @@
{
FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
reshape_weights, data_type,
- 0, QuantizationInfo());
+ QuantizationInfo());
}
};
@@ -237,11 +235,11 @@
{
public:
template <typename...>
- void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type, int fractional_bits)
+ void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type)
{
FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
reshape_weights, data_type,
- fractional_bits, QuantizationInfo());
+ QuantizationInfo());
}
};
@@ -255,7 +253,7 @@
{
FullyConnectedLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
reshape_weights, data_type,
- 0, quantization_info);
+ quantization_info);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
index 8dd2998..e4762cc 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -47,13 +47,12 @@
{
public:
template <typename...>
- void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, DataType data_type, int fractional_bits)
+ void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, DataType data_type)
{
- _fractional_bits = fractional_bits;
- _data_type = data_type;
+ _data_type = data_type;
- _target = compute_target(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, fractional_bits);
- _reference = compute_reference(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, fractional_bits);
+ _target = compute_target(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type);
+ _reference = compute_reference(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type);
}
protected:
@@ -75,13 +74,13 @@
}
TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
- DataType data_type, int fixed_point_position)
+ DataType data_type)
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
- TensorType b = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
- TensorType c = create_tensor<TensorType>(shape_c, data_type, 1, fixed_point_position);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position);
+ TensorType a = create_tensor<TensorType>(shape_a, data_type, 1);
+ TensorType b = create_tensor<TensorType>(shape_b, data_type, 1);
+ TensorType c = create_tensor<TensorType>(shape_c, data_type, 1);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1);
// Create and configure function
FunctionType gemm;
@@ -120,12 +119,12 @@
}
SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
- DataType data_type, int fixed_point_position)
+ DataType data_type)
{
// Create reference
- SimpleTensor<T> a{ shape_a, data_type, 1, fixed_point_position };
- SimpleTensor<T> b{ shape_b, data_type, 1, fixed_point_position };
- SimpleTensor<T> c{ shape_c, data_type, 1, fixed_point_position };
+ SimpleTensor<T> a{ shape_a, data_type, 1 };
+ SimpleTensor<T> b{ shape_b, data_type, 1 };
+ SimpleTensor<T> c{ shape_c, data_type, 1 };
// Fill reference
fill(a, 0);
@@ -137,7 +136,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
DataType _data_type{};
};
@@ -148,7 +146,7 @@
template <typename...>
void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, DataType data_type)
{
- GEMMValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, 0);
+ GEMMValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/GEMMInterleave4x4Fixture.h b/tests/validation/fixtures/GEMMInterleave4x4Fixture.h
index 1f0a742..9ad730c 100644
--- a/tests/validation/fixtures/GEMMInterleave4x4Fixture.h
+++ b/tests/validation/fixtures/GEMMInterleave4x4Fixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,14 +47,13 @@
{
public:
template <typename...>
- void setup(size_t x, size_t y, DataType data_type, int fractional_bits)
+ void setup(size_t x, size_t y, DataType data_type)
{
- _fractional_bits = fractional_bits;
- _data_type = data_type;
+ _data_type = data_type;
const TensorShape shape_a(x, y);
const TensorShape shape_b(static_cast<size_t>(x * 4.f), static_cast<size_t>(std::ceil(y / 4.f)));
- _target = compute_target(shape_a, shape_b, data_type, fractional_bits);
- _reference = compute_reference(shape_a, shape_b, data_type, fractional_bits);
+ _target = compute_target(shape_a, shape_b, data_type);
+ _reference = compute_reference(shape_a, shape_b, data_type);
}
protected:
@@ -76,11 +75,11 @@
}
}
- TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type, int fixed_point_position)
+ TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type)
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
- TensorType b = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
+ TensorType a = create_tensor<TensorType>(shape_a, data_type, 1);
+ TensorType b = create_tensor<TensorType>(shape_b, data_type, 1);
// Create and configure function
FunctionType f;
@@ -105,11 +104,11 @@
return b;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type, int fixed_point_position)
+ SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type)
{
// Create reference
- SimpleTensor<T> a{ shape_a, data_type, 1, fixed_point_position };
- SimpleTensor<T> b{ shape_b, data_type, 1, fixed_point_position };
+ SimpleTensor<T> a{ shape_a, data_type, 1 };
+ SimpleTensor<T> b{ shape_b, data_type, 1 };
// Fill reference
fill(a, 0);
@@ -120,7 +119,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
DataType _data_type{};
};
@@ -131,7 +129,7 @@
template <typename...>
void setup(size_t x, size_t y, DataType data_type)
{
- GEMMInterleave4x4ValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(x, y, data_type, 0);
+ GEMMInterleave4x4ValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(x, y, data_type);
}
};
diff --git a/tests/validation/fixtures/GEMMTranspose1xWFixture.h b/tests/validation/fixtures/GEMMTranspose1xWFixture.h
index d83d5e9..48fa55e 100644
--- a/tests/validation/fixtures/GEMMTranspose1xWFixture.h
+++ b/tests/validation/fixtures/GEMMTranspose1xWFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017, 2018 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,15 +47,14 @@
{
public:
template <typename...>
- void setup(size_t x, size_t y, DataType data_type, int fractional_bits)
+ void setup(size_t x, size_t y, DataType data_type)
{
- _fractional_bits = fractional_bits;
- _data_type = data_type;
+ _data_type = data_type;
const TensorShape shape_a(x, y);
const unsigned int transpose_w = 16 / data_size_from_type(data_type);
const TensorShape shape_b(static_cast<size_t>(y * transpose_w), static_cast<size_t>(std::ceil(x / static_cast<float>(transpose_w))));
- _target = compute_target(shape_a, shape_b, data_type, fractional_bits);
- _reference = compute_reference(shape_a, shape_b, data_type, fractional_bits);
+ _target = compute_target(shape_a, shape_b, data_type);
+ _reference = compute_reference(shape_a, shape_b, data_type);
}
protected:
@@ -77,11 +76,11 @@
}
}
- TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type, int fixed_point_position)
+ TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type)
{
// Create tensors
- TensorType a = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
- TensorType b = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
+ TensorType a = create_tensor<TensorType>(shape_a, data_type, 1);
+ TensorType b = create_tensor<TensorType>(shape_b, data_type, 1);
// Create and configure function
FunctionType f;
@@ -107,10 +106,10 @@
return b;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type, int fixed_point_position)
+ SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type)
{
// Create reference
- SimpleTensor<T> a{ shape_a, data_type, 1, fixed_point_position };
+ SimpleTensor<T> a{ shape_a, data_type, 1 };
// Fill reference
fill(a, 0);
@@ -120,7 +119,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
DataType _data_type{};
};
@@ -131,7 +129,7 @@
template <typename...>
void setup(size_t x, size_t y, DataType data_type)
{
- GEMMTranspose1xWValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(x, y, data_type, 0);
+ GEMMTranspose1xWValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(x, y, data_type);
}
};
diff --git a/tests/validation/fixtures/Im2ColFixture.h b/tests/validation/fixtures/Im2ColFixture.h
index 6e532e7..6abea27 100644
--- a/tests/validation/fixtures/Im2ColFixture.h
+++ b/tests/validation/fixtures/Im2ColFixture.h
@@ -81,8 +81,8 @@
TensorType compute_target(const TensorShape &input_shape, const TensorShape &output_shape, DataType data_type)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, _quant_info, _data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, _quant_info);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, _quant_info, _data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, _quant_info);
// Create and configure function
FunctionType im2col_func;
@@ -110,8 +110,8 @@
void compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, 0, _quant_info, _data_layout };
- _reference = SimpleTensor<T>(output_shape, data_type, 1, 0, _quant_info, DataLayout::NCHW);
+ SimpleTensor<T> src{ input_shape, data_type, 1, _quant_info, _data_layout };
+ _reference = SimpleTensor<T>(output_shape, data_type, 1, _quant_info, DataLayout::NCHW);
// Fill reference
fill(src);
reference::im2col<T>(src, _reference, _kernel_dims, _conv_info, _has_bias);
diff --git a/tests/validation/fixtures/NormalizationLayerFixture.h b/tests/validation/fixtures/NormalizationLayerFixture.h
index e7d83c7..f4f9c64 100644
--- a/tests/validation/fixtures/NormalizationLayerFixture.h
+++ b/tests/validation/fixtures/NormalizationLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -43,40 +43,30 @@
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class NormalizationValidationFixedPointFixture : public framework::Fixture
+class NormalizationValidationGenericFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, bool is_scaled, DataType data_type, int fractional_bits)
+ void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, bool is_scaled, DataType data_type)
{
- _fractional_bits = fractional_bits;
NormalizationLayerInfo info(norm_type, norm_size, 5, beta, 1.f, is_scaled);
- _target = compute_target(shape, info, data_type, fractional_bits);
- _reference = compute_reference(shape, info, data_type, fractional_bits);
+ _target = compute_target(shape, info, data_type);
+ _reference = compute_reference(shape, info, data_type);
}
protected:
template <typename U>
void fill(U &&tensor)
{
- if(_fractional_bits == 0)
- {
- library->fill_tensor_uniform(tensor, 0);
- }
- else
- {
- const int one_fixed = 1 << _fractional_bits;
- std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
- library->fill(tensor, distribution, 0);
- }
+ library->fill_tensor_uniform(tensor, 0);
}
- TensorType compute_target(const TensorShape &shape, NormalizationLayerInfo info, DataType data_type, int fixed_point_position = 0)
+ TensorType compute_target(const TensorShape &shape, NormalizationLayerInfo info, DataType data_type)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
- TensorType dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1);
+ TensorType dst = create_tensor<TensorType>(shape, data_type, 1);
// Create and configure function
FunctionType norm_layer;
@@ -101,10 +91,10 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, NormalizationLayerInfo info, DataType data_type, int fixed_point_position = 0)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, NormalizationLayerInfo info, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position };
+ SimpleTensor<T> src{ shape, data_type, 1 };
// Fill reference
fill(src);
@@ -114,17 +104,16 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class NormalizationValidationFixture : public NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+class NormalizationValidationFixture : public NormalizationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, bool is_scaled, DataType data_type)
{
- NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, norm_type, norm_size, beta, is_scaled, data_type, 0);
+ NormalizationValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, norm_type, norm_size, beta, is_scaled, data_type);
}
};
} // namespace validation
diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
index 27b033a..2453954 100644
--- a/tests/validation/fixtures/PoolingLayerFixture.h
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -47,14 +47,13 @@
{
public:
template <typename...>
- void setup(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type, DataLayout data_layout, int fractional_bits, QuantizationInfo quantization_info)
+ void setup(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type, DataLayout data_layout, QuantizationInfo quantization_info)
{
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
_pool_info = pool_info;
- _target = compute_target(shape, pool_info, data_type, data_layout, fractional_bits, quantization_info);
- _reference = compute_reference(shape, pool_info, data_type, fractional_bits, quantization_info);
+ _target = compute_target(shape, pool_info, data_type, data_layout, quantization_info);
+ _reference = compute_reference(shape, pool_info, data_type, quantization_info);
}
protected:
@@ -72,14 +71,14 @@
}
else
{
- const int one_fixed = 1 << _fractional_bits;
+ const int one_fixed = 1;
std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
library->fill(tensor, distribution, 0);
}
}
TensorType compute_target(TensorShape shape, PoolingLayerInfo info,
- DataType data_type, DataLayout data_layout, int fixed_point_position, QuantizationInfo quantization_info)
+ DataType data_type, DataLayout data_layout, QuantizationInfo quantization_info)
{
// Change shape in case of NHWC.
if(data_layout == DataLayout::NHWC)
@@ -88,7 +87,7 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, quantization_info, data_layout);
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info, data_layout);
TensorType dst;
// Create and configure function
@@ -115,10 +114,10 @@
}
SimpleTensor<T> compute_reference(const TensorShape &shape, PoolingLayerInfo info,
- DataType data_type, int fixed_point_position, QuantizationInfo quantization_info)
+ DataType data_type, QuantizationInfo quantization_info)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> src{ shape, data_type, 1, quantization_info };
// Fill reference
fill(src);
@@ -128,7 +127,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
PoolingLayerInfo _pool_info{};
};
@@ -141,7 +139,7 @@
void setup(TensorShape shape, PoolingType pool_type, Size2D pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, DataLayout data_layout)
{
PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, pad_stride_info, exclude_padding),
- data_type, data_layout, 0, QuantizationInfo());
+ data_type, data_layout, QuantizationInfo());
}
};
@@ -150,10 +148,10 @@
{
public:
template <typename...>
- void setup(TensorShape shape, PoolingType pool_type, Size2D pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, int fractional_bits)
+ void setup(TensorShape shape, PoolingType pool_type, Size2D pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type)
{
PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, pad_stride_info, exclude_padding),
- data_type, DataLayout::NCHW, fractional_bits, QuantizationInfo());
+ data_type, DataLayout::NCHW, QuantizationInfo());
}
};
@@ -166,7 +164,7 @@
QuantizationInfo quantization_info, DataLayout data_layout = DataLayout::NCHW)
{
PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, pad_stride_info, exclude_padding),
- data_type, data_layout, 0, quantization_info);
+ data_type, data_layout, quantization_info);
}
};
@@ -177,7 +175,7 @@
template <typename...>
void setup(TensorShape src_shape, PoolingLayerInfo pool_info, DataType data_type)
{
- PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(src_shape, pool_info, data_type, DataLayout::NCHW, 0, QuantizationInfo());
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(src_shape, pool_info, data_type, DataLayout::NCHW, QuantizationInfo());
}
};
@@ -188,7 +186,7 @@
template <typename...>
void setup(TensorShape shape, PoolingType pool_type, DataType data_type, DataLayout data_layout = DataLayout::NCHW)
{
- PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type), data_type, DataLayout::NCHW, 0, QuantizationInfo());
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type), data_type, DataLayout::NCHW, QuantizationInfo());
}
};
diff --git a/tests/validation/fixtures/ScaleFixture.h b/tests/validation/fixtures/ScaleFixture.h
index 05e1bf5..5413147 100644
--- a/tests/validation/fixtures/ScaleFixture.h
+++ b/tests/validation/fixtures/ScaleFixture.h
@@ -100,7 +100,7 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, _data_type, 1, 0, QuantizationInfo(), data_layout);
+ TensorType src = create_tensor<TensorType>(shape, _data_type, 1, QuantizationInfo(), data_layout);
const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
@@ -108,7 +108,7 @@
TensorShape shape_scaled(shape);
shape_scaled.set(idx_width, shape[idx_width] * scale_x);
shape_scaled.set(idx_height, shape[idx_height] * scale_y);
- TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, 0, QuantizationInfo(), data_layout);
+ TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, QuantizationInfo(), data_layout);
// Create and configure function
FunctionType scale;
@@ -137,7 +137,7 @@
InterpolationPolicy policy, BorderMode border_mode, T constant_border_value, SamplingPolicy sampling_policy)
{
// Create reference
- SimpleTensor<T> src{ shape, _data_type, 1, 0, QuantizationInfo() };
+ SimpleTensor<T> src{ shape, _data_type, 1, QuantizationInfo() };
// Fill reference
fill(src);
diff --git a/tests/validation/fixtures/SoftmaxLayerFixture.h b/tests/validation/fixtures/SoftmaxLayerFixture.h
index c2ab2e2..59ce519 100644
--- a/tests/validation/fixtures/SoftmaxLayerFixture.h
+++ b/tests/validation/fixtures/SoftmaxLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,13 +47,12 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type, int fractional_bits, QuantizationInfo quantization_info, float beta)
+ void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, float beta)
{
- _fractional_bits = fractional_bits;
_quantization_info = quantization_info;
- _target = compute_target(shape, data_type, fractional_bits, quantization_info, beta);
- _reference = compute_reference(shape, data_type, fractional_bits, quantization_info, beta);
+ _target = compute_target(shape, data_type, quantization_info, beta);
+ _reference = compute_reference(shape, data_type, quantization_info, beta);
}
protected:
@@ -72,18 +71,18 @@
}
else
{
- const int one_fixed = 1 << _fractional_bits;
+ const int one_fixed = 1;
std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
library->fill(tensor, distribution, 0);
}
}
- TensorType compute_target(const TensorShape &shape, DataType data_type, int fixed_point_position,
+ TensorType compute_target(const TensorShape &shape, DataType data_type,
QuantizationInfo quantization_info, float beta)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, quantization_info);
- TensorType dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, QuantizationInfo(1.f / 256, 0));
+ TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info);
+ TensorType dst = create_tensor<TensorType>(shape, data_type, 1, QuantizationInfo(1.f / 256, 0));
// Create and configure function
FunctionType smx_layer;
@@ -108,11 +107,11 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, int fixed_point_position,
+ SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type,
QuantizationInfo quantization_info, float beta)
{
// Create reference
- SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position, quantization_info };
+ SimpleTensor<T> src{ shape, data_type, 1, quantization_info };
// Fill reference
fill(src);
@@ -122,7 +121,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
- int _fractional_bits{};
QuantizationInfo _quantization_info{};
};
@@ -135,7 +133,6 @@
{
SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
data_type,
- 0,
QuantizationInfo(),
beta);
}
@@ -146,11 +143,10 @@
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type, int fixed_point_position)
+ void setup(TensorShape shape, DataType data_type)
{
SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
data_type,
- fixed_point_position,
QuantizationInfo(),
1.0f);
}
@@ -165,7 +161,6 @@
{
SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape,
data_type,
- 0,
quantization_info,
beta);
}
diff --git a/tests/validation/fixtures/WidthConcatenateLayerFixture.h b/tests/validation/fixtures/WidthConcatenateLayerFixture.h
index cf9b12e..caad0fe 100644
--- a/tests/validation/fixtures/WidthConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/WidthConcatenateLayerFixture.h
@@ -92,12 +92,12 @@
for(const auto &shape : shapes)
{
- srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1, _fractional_bits));
+ srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1));
src_ptrs.emplace_back(&srcs.back());
}
TensorShape dst_shape = misc::shape_calculator::calculate_width_concatenate_shape(src_ptrs);
- TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, _fractional_bits);
+ TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
FunctionType width_concat;
@@ -141,7 +141,7 @@
int i = 0;
for(const auto &shape : shapes)
{
- srcs.emplace_back(shape, data_type, 1, _fractional_bits);
+ srcs.emplace_back(shape, data_type, 1);
fill(srcs.back(), i++);
}
@@ -150,9 +150,6 @@
TensorType _target{};
SimpleTensor<T> _reference{};
-
-private:
- int _fractional_bits{ 1 };
};
} // namespace validation
} // namespace test
diff --git a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
index ac168eb..f1660e6 100644
--- a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
@@ -201,10 +201,10 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, QuantizationInfo(), data_layout);
+ TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1, QuantizationInfo(), data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo(), data_layout);
// Create and configure function
FunctionType conv;
@@ -340,8 +340,8 @@
permute(input_shape, PermutationVector(2U, 0U, 1U));
}
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, QuantizationInfo());
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo());
// Create and configure function
FunctionType transf;
@@ -369,7 +369,7 @@
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataLayout data_layout, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, 0, QuantizationInfo() };
+ SimpleTensor<T> src{ input_shape, data_type, 1, QuantizationInfo() };
// Fill reference
fill(src, 0, -1.f, 1.f);
@@ -424,8 +424,8 @@
}
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, QuantizationInfo(), data_layout);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, QuantizationInfo());
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo());
// Create and configure function
FunctionType filter_transform;
@@ -452,7 +452,7 @@
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataLayout data_layout, DataType data_type)
{
// Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, 0, QuantizationInfo() };
+ SimpleTensor<T> src{ input_shape, data_type, 1, QuantizationInfo() };
// Fill reference
fill(src, 0, -1.f, 1.f);
@@ -502,7 +502,7 @@
// Create tensors
TensorType src = create_tensor<TensorType>(input_shape, data_type);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, QuantizationInfo(), winograd_info.output_data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo(), winograd_info.output_data_layout);
// Create and configure function
FunctionType output_transform;
diff --git a/tests/validation/reference/AbsoluteDifference.cpp b/tests/validation/reference/AbsoluteDifference.cpp
index f518e67..f9fce5b 100644
--- a/tests/validation/reference/AbsoluteDifference.cpp
+++ b/tests/validation/reference/AbsoluteDifference.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,7 +24,6 @@
#include "AbsoluteDifference.h"
#include "arm_compute/core/Types.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
diff --git a/tests/validation/reference/Accumulate.cpp b/tests/validation/reference/Accumulate.cpp
index 29a2007..7f34be9 100644
--- a/tests/validation/reference/Accumulate.cpp
+++ b/tests/validation/reference/Accumulate.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,7 +24,6 @@
#include "Accumulate.h"
#include "arm_compute/core/Types.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
diff --git a/tests/validation/reference/ActivationLayer.cpp b/tests/validation/reference/ActivationLayer.cpp
index df7f653..9455eff 100644
--- a/tests/validation/reference/ActivationLayer.cpp
+++ b/tests/validation/reference/ActivationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,7 +24,6 @@
#include "ActivationLayer.h"
#include "arm_compute/core/Types.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
@@ -39,7 +38,7 @@
SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
{
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
// Compute reference
const T a(info.a());
@@ -92,68 +91,6 @@
return dst;
}
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
-SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
-{
- using namespace fixed_point_arithmetic;
-
- // Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
-
- // Compute reference
- const int fixed_point_position = src.fixed_point_position();
- const fixed_point<T> a(info.a(), fixed_point_position);
- const fixed_point<T> b(info.b(), fixed_point_position);
- const fixed_point<T> const_0(0, fixed_point_position);
- const fixed_point<T> const_1(1, fixed_point_position);
-
- for(int i = 0; i < src.num_elements(); ++i)
- {
- fixed_point<T> x(src[i], fixed_point_position, true);
-
- switch(info.activation())
- {
- case ActivationLayerInfo::ActivationFunction::ABS:
- dst[i] = abs(x).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::LINEAR:
- dst[i] = add(b, mul(a, x)).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::LOGISTIC:
- dst[i] = (const_1 / (const_1 + exp(-x))).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::RELU:
- dst[i] = max(const_0, x).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
- dst[i] = min(a, max(const_0, x)).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
- dst[i] = min(a, max(b, x)).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
- dst[i] = (x > const_0) ? x.raw() : mul(a, x).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
- dst[i] = log(const_1 + exp(x)).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::SQRT:
- dst[i] = (const_1 / inv_sqrt(x)).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::SQUARE:
- dst[i] = mul(x, x).raw();
- break;
- case ActivationLayerInfo::ActivationFunction::TANH:
- dst[i] = mul(a, tanh(mul(b, x))).raw();
- break;
- default:
- ARM_COMPUTE_ERROR("Unsupported activation function");
- }
- }
-
- return dst;
-}
-
template <>
SimpleTensor<uint8_t> activation_layer<uint8_t>(const SimpleTensor<uint8_t> &src, ActivationLayerInfo info)
{
@@ -165,8 +102,6 @@
template SimpleTensor<float> activation_layer(const SimpleTensor<float> &src, ActivationLayerInfo info);
template SimpleTensor<half> activation_layer(const SimpleTensor<half> &src, ActivationLayerInfo info);
-template SimpleTensor<qint8_t> activation_layer(const SimpleTensor<qint8_t> &src, ActivationLayerInfo info);
-template SimpleTensor<qint16_t> activation_layer(const SimpleTensor<qint16_t> &src, ActivationLayerInfo info);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/ArithmeticAddition.cpp b/tests/validation/reference/ArithmeticAddition.cpp
index f26838d..4569277 100644
--- a/tests/validation/reference/ArithmeticAddition.cpp
+++ b/tests/validation/reference/ArithmeticAddition.cpp
@@ -24,7 +24,6 @@
#include "ArithmeticAddition.h"
#include "arm_compute/core/Types.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
diff --git a/tests/validation/reference/ArithmeticDivision.cpp b/tests/validation/reference/ArithmeticDivision.cpp
index 934e890..0102231 100644
--- a/tests/validation/reference/ArithmeticDivision.cpp
+++ b/tests/validation/reference/ArithmeticDivision.cpp
@@ -24,7 +24,6 @@
#include "ArithmeticDivision.h"
#include "arm_compute/core/Types.h"
-#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
diff --git a/tests/validation/reference/BatchNormalizationLayer.cpp b/tests/validation/reference/BatchNormalizationLayer.cpp
index c8badac..3d1a6ed 100644
--- a/tests/validation/reference/BatchNormalizationLayer.cpp
+++ b/tests/validation/reference/BatchNormalizationLayer.cpp
@@ -36,56 +36,11 @@
{
namespace reference
{
-// Batch Normalization Layer for fixed point type
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type *>
-SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- ActivationLayerInfo act_info, int fixed_point_position)
-{
- ARM_COMPUTE_UNUSED(act_info);
- SimpleTensor<T> result(src.shape(), src.data_type());
-
- const auto cols = static_cast<int>(src.shape()[0]);
- const auto rows = static_cast<int>(src.shape()[1]);
- const auto depth = static_cast<int>(src.shape()[2]);
- const int upper_dims = src.shape().total_size() / (cols * rows * depth);
-
- for(int r = 0; r < upper_dims; ++r)
- {
- for(int i = 0; i < depth; ++i)
- {
- for(int k = 0; k < rows; ++k)
- {
- for(int l = 0; l < cols; ++l)
- {
- const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth;
-
- fixed_point_arithmetic::fixed_point<T> src_qs(src[pos], fixed_point_position, true);
- fixed_point_arithmetic::fixed_point<T> var_qs(var[i], fixed_point_position, true);
- fixed_point_arithmetic::fixed_point<T> mean_qs(mean[i], fixed_point_position, true);
- fixed_point_arithmetic::fixed_point<T> beta_qs(beta[i], fixed_point_position, true);
- fixed_point_arithmetic::fixed_point<T> gamma_qs(gamma[i], fixed_point_position, true);
- fixed_point_arithmetic::fixed_point<T> epsilon_qs(epsilon, fixed_point_position);
-
- auto denominator = fixed_point_arithmetic::inv_sqrt(var_qs + epsilon_qs);
- auto numerator = src_qs - mean_qs;
- auto x_bar = numerator * denominator;
- x_bar = beta_qs + x_bar * gamma_qs;
- result[pos] = x_bar.raw();
- }
- }
- }
- }
-
- return result;
-}
-
// Batch Normalization Layer for floating point type
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- ActivationLayerInfo act_info, int fixed_point_position)
+ ActivationLayerInfo act_info)
{
- ARM_COMPUTE_UNUSED(fixed_point_position);
-
SimpleTensor<T> result(src.shape(), src.data_type());
const auto cols = static_cast<int>(src.shape()[0]);
@@ -119,14 +74,10 @@
return result;
}
template SimpleTensor<float> batch_normalization_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &var, const SimpleTensor<float> &beta,
- const SimpleTensor<float> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
-template SimpleTensor<int8_t> batch_normalization_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &mean, const SimpleTensor<int8_t> &var, const SimpleTensor<int8_t> &beta,
- const SimpleTensor<int8_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
-template SimpleTensor<int16_t> batch_normalization_layer(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &mean, const SimpleTensor<int16_t> &var, const SimpleTensor<int16_t> &beta,
- const SimpleTensor<int16_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
+ const SimpleTensor<float> &gamma, float epsilon, ActivationLayerInfo act_info);
template SimpleTensor<half> batch_normalization_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &var,
const SimpleTensor<half> &beta,
- const SimpleTensor<half> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
+ const SimpleTensor<half> &gamma, float epsilon, ActivationLayerInfo act_info);
} // namespace reference
} // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.h b/tests/validation/reference/BatchNormalizationLayer.h
index 329909d..b45d820 100644
--- a/tests/validation/reference/BatchNormalizationLayer.h
+++ b/tests/validation/reference/BatchNormalizationLayer.h
@@ -37,13 +37,11 @@
{
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- ActivationLayerInfo act_info,
- int fixed_point_position);
+ ActivationLayerInfo act_info);
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
- ActivationLayerInfo act_info,
- int fixed_point_position);
+ ActivationLayerInfo act_info);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/ChannelShuffle.cpp b/tests/validation/reference/ChannelShuffle.cpp
index c4d8d50..b8aa920 100644
--- a/tests/validation/reference/ChannelShuffle.cpp
+++ b/tests/validation/reference/ChannelShuffle.cpp
@@ -39,7 +39,7 @@
SimpleTensor<T> channel_shuffle(const SimpleTensor<T> &src, int num_groups)
{
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), src.num_channels(), src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), src.num_channels(), src.quantization_info() };
const int M = src.shape()[0];
const int N = src.shape()[1];
diff --git a/tests/validation/reference/ConvolutionLayer.cpp b/tests/validation/reference/ConvolutionLayer.cpp
index fe558ba..00c839d 100644
--- a/tests/validation/reference/ConvolutionLayer.cpp
+++ b/tests/validation/reference/ConvolutionLayer.cpp
@@ -108,7 +108,7 @@
const Size2D &dilation)
{
// Create reference
- SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.quantization_info() };
if(src.data_layout() == DataLayout::NHWC)
{
@@ -128,10 +128,6 @@
const PadStrideInfo &info, const Size2D &dilation);
template SimpleTensor<half> convolution_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &output_shape,
const PadStrideInfo &info, const Size2D &dilation);
-template SimpleTensor<qint8_t> convolution_layer(const SimpleTensor<qint8_t> &src, const SimpleTensor<qint8_t> &weights, const SimpleTensor<qint8_t> &bias, const TensorShape &output_shape,
- const PadStrideInfo &info, const Size2D &dilation);
-template SimpleTensor<qint16_t> convolution_layer(const SimpleTensor<qint16_t> &src, const SimpleTensor<qint16_t> &weights, const SimpleTensor<qint16_t> &bias, const TensorShape &output_shape,
- const PadStrideInfo &info, const Size2D &dilation);
template SimpleTensor<uint8_t> convolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
const PadStrideInfo &info, const Size2D &dilation);
} // namespace reference
diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp
index 3543708..d073bbf 100644
--- a/tests/validation/reference/DeconvolutionLayer.cpp
+++ b/tests/validation/reference/DeconvolutionLayer.cpp
@@ -46,7 +46,7 @@
int out_y = src.shape().y() + (src.shape().y() - 1) * (stride_y - 1) + a.second + 2 * info.pad().second;
scaled_shape.set(0, out_x);
scaled_shape.set(1, out_y);
- SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1 };
const int width_in = src.shape().x();
const int height_in = src.shape().y();
diff --git a/tests/validation/reference/DepthConcatenateLayer.cpp b/tests/validation/reference/DepthConcatenateLayer.cpp
index 9a72484..c9a2352 100644
--- a/tests/validation/reference/DepthConcatenateLayer.cpp
+++ b/tests/validation/reference/DepthConcatenateLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -95,8 +95,6 @@
template SimpleTensor<float> depthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs);
template SimpleTensor<half> depthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs);
-template SimpleTensor<qint8_t> depthconcatenate_layer(const std::vector<SimpleTensor<qint8_t>> &srcs);
-template SimpleTensor<qint16_t> depthconcatenate_layer(const std::vector<SimpleTensor<qint16_t>> &srcs);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/DepthConvertLayer.cpp b/tests/validation/reference/DepthConvertLayer.cpp
index dd095b8..0220077 100644
--- a/tests/validation/reference/DepthConvertLayer.cpp
+++ b/tests/validation/reference/DepthConvertLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,44 +36,6 @@
{
namespace reference
{
-template < typename T1, typename T2, typename std::enable_if < std::is_integral<T1>::value &&std::is_floating_point<T2>::value, int >::type >
-SimpleTensor<T2> depth_convert(const SimpleTensor<T1> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift)
-{
- ARM_COMPUTE_UNUSED(policy);
- ARM_COMPUTE_UNUSED(shift);
-
- using namespace fixed_point_arithmetic;
- SimpleTensor<T2> result(src.shape(), dt_out);
-
- const int fixed_point_position = src.fixed_point_position();
-
- for(int i = 0; i < src.num_elements(); ++i)
- {
- result[i] = static_cast<float>(fixed_point<T1>(src[i], fixed_point_position, true));
- }
-
- return result;
-}
-
-template < typename T1, typename T2, typename std::enable_if < std::is_floating_point<T1>::value &&std::is_integral<T2>::value, int >::type >
-SimpleTensor<T2> depth_convert(const SimpleTensor<T1> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift)
-{
- ARM_COMPUTE_UNUSED(policy);
- ARM_COMPUTE_UNUSED(shift);
-
- using namespace fixed_point_arithmetic;
- SimpleTensor<T2> result(src.shape(), dt_out, 1, src.fixed_point_position());
-
- const int fixed_point_position = result.fixed_point_position();
-
- for(int i = 0; i < src.num_elements(); ++i)
- {
- result[i] = fixed_point<T2>(src[i], fixed_point_position).raw();
- }
-
- return result;
-}
-
template < typename T1, typename T2, typename std::enable_if < std::is_integral<T1>::value &&std::is_integral<T2>::value &&!std::is_same<T1, T2>::value, int >::type >
SimpleTensor<T2> depth_convert(const SimpleTensor<T1> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift)
{
@@ -126,20 +88,6 @@
return result;
}
-template < typename T1, typename T2, typename std::enable_if < std::is_floating_point<T1>::value &&is_floating_point<T2>::value, int >::type >
-SimpleTensor<T2> depth_convert(const SimpleTensor<T1> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift)
-{
- ARM_COMPUTE_UNUSED(policy);
- ARM_COMPUTE_UNUSED(shift);
-
- SimpleTensor<T2> result(src.shape(), dt_out);
-
- for(int i = 0; i < src.num_elements(); ++i)
- {
- result[i] = static_cast<T2>(src[i]);
- }
-}
-
template SimpleTensor<uint16_t> depth_convert(const SimpleTensor<uint8_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
template SimpleTensor<int16_t> depth_convert(const SimpleTensor<uint8_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
template SimpleTensor<int32_t> depth_convert(const SimpleTensor<uint8_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
@@ -147,10 +95,6 @@
template SimpleTensor<uint32_t> depth_convert(const SimpleTensor<uint16_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
template SimpleTensor<uint8_t> depth_convert(const SimpleTensor<int16_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
template SimpleTensor<int32_t> depth_convert(const SimpleTensor<int16_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
-template SimpleTensor<float> depth_convert(const SimpleTensor<int8_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
-template SimpleTensor<float> depth_convert(const SimpleTensor<int16_t> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
-template SimpleTensor<int8_t> depth_convert(const SimpleTensor<float> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
-template SimpleTensor<int16_t> depth_convert(const SimpleTensor<float> &src, DataType dt_out, ConvertPolicy policy, uint32_t shift);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/DepthwiseConvolutionLayer.cpp b/tests/validation/reference/DepthwiseConvolutionLayer.cpp
index 10c617e..d8f3cba 100644
--- a/tests/validation/reference/DepthwiseConvolutionLayer.cpp
+++ b/tests/validation/reference/DepthwiseConvolutionLayer.cpp
@@ -53,7 +53,7 @@
SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &biases, const TensorShape &dst_shape, const PadStrideInfo &conv_info,
unsigned int depth_multiplier)
{
- SimpleTensor<T> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ dst_shape, src.data_type(), 1 };
// Compute reference
const int filter_width = weights.shape().x();
@@ -122,7 +122,7 @@
SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &biases, const TensorShape &dst_shape,
const PadStrideInfo &conv_info, unsigned int depth_multiplier)
{
- SimpleTensor<uint8_t> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<uint8_t> dst{ dst_shape, src.data_type(), 1, src.quantization_info() };
// Create reference
const int input_offset = -src.quantization_info().offset;
diff --git a/tests/validation/reference/FlattenLayer.cpp b/tests/validation/reference/FlattenLayer.cpp
index 44f4d93..e140d75 100644
--- a/tests/validation/reference/FlattenLayer.cpp
+++ b/tests/validation/reference/FlattenLayer.cpp
@@ -36,7 +36,7 @@
template <typename T>
SimpleTensor<T> flatten_layer(const SimpleTensor<T> &src, const TensorShape &shape_flatten)
{
- SimpleTensor<T> dst(shape_flatten, src.data_type(), 1, src.fixed_point_position());
+ SimpleTensor<T> dst(shape_flatten, src.data_type(), 1);
// Note: Since the reference implementation does not use padding bytes, we can copy directly the content of the source tensor
std::copy(src.data(), src.data() + src.num_elements(), dst.data());
@@ -46,8 +46,6 @@
template SimpleTensor<float> flatten_layer(const SimpleTensor<float> &src, const TensorShape &shape_flatten);
template SimpleTensor<half> flatten_layer(const SimpleTensor<half> &src, const TensorShape &shape_flatten);
-template SimpleTensor<qint8_t> flatten_layer(const SimpleTensor<qint8_t> &src, const TensorShape &shape_flatten);
-template SimpleTensor<qint16_t> flatten_layer(const SimpleTensor<qint16_t> &src, const TensorShape &shape_flatten);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/FullyConnectedLayer.cpp b/tests/validation/reference/FullyConnectedLayer.cpp
index 5384715..3ef10ea 100644
--- a/tests/validation/reference/FullyConnectedLayer.cpp
+++ b/tests/validation/reference/FullyConnectedLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -44,10 +44,8 @@
// Vector matrix multiply for floating point
template < typename T, typename TB, typename std::enable_if < is_floating_point<T>::value &&is_floating_point<TB>::value, int >::type = 0 >
void vector_matrix_multiply(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &dst, int offset_src, int offset_dst, int cols_weights,
- int rows_weights, uint8_t fixed_point_position)
+ int rows_weights)
{
- ARM_COMPUTE_UNUSED(fixed_point_position);
-
const T *src_ptr = src.data() + offset_src;
const T *weights_ptr = weights.data();
const TB *bias_ptr = bias.data();
@@ -60,57 +58,16 @@
}
}
-// Vector matrix multiply for fixed point type
-template < typename T, typename TB, typename std::enable_if < std::is_integral<T>::value &&std::is_integral<TB>::value, int >::type = 0 >
-void vector_matrix_multiply(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &dst, int offset_src, int offset_dst, int cols_weights,
- int rows_weights, uint8_t fixed_point_position)
+// Vector matrix multiply for quantized type
+template < typename T, typename TB, typename std::enable_if < std::is_same<T, uint8_t>::value &&std::is_same<TB, int32_t>::value, int >::type = 0 >
+void vector_matrix_multiply(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, SimpleTensor<T> &dst, int offset_src, int offset_dst,
+ int cols_weights, int rows_weights)
{
const T *src_ptr = src.data() + offset_src;
const T *weights_ptr = weights.data();
const TB *bias_ptr = bias.data();
T *dst_ptr = dst.data() + offset_dst;
- using namespace fixed_point_arithmetic;
- using promoted_type = fixed_point_arithmetic::traits::promote_t<T>;
-
- for(int y = 0; y < rows_weights; ++y)
- {
- // Reset accumulator
- fixed_point<promoted_type> acc(0, fixed_point_position);
-
- for(int x = 0; x < cols_weights; ++x)
- {
- const fixed_point<promoted_type> i_value(src_ptr[x], fixed_point_position, true);
- const fixed_point<promoted_type> w_value(weights_ptr[x], fixed_point_position, true);
- acc = acc + i_value * w_value;
- }
-
- // Get the bias
- const fixed_point<T> b(bias_ptr[y], fixed_point_position, true);
-
- // Convert back and accumulate the bias
- fixed_point<T> res(acc);
- res = res + b;
-
- // Store the result
- dst_ptr[y] = res.raw();
-
- weights_ptr += cols_weights;
- }
-}
-
-// Vector matrix multiply for quantized type
-template <>
-void vector_matrix_multiply(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, SimpleTensor<uint8_t> &dst, int offset_src, int offset_dst,
- int cols_weights, int rows_weights, uint8_t fixed_point_position)
-{
- ARM_COMPUTE_UNUSED(fixed_point_position);
-
- const uint8_t *src_ptr = src.data() + offset_src;
- const uint8_t *weights_ptr = weights.data();
- const int32_t *bias_ptr = bias.data();
- uint8_t *dst_ptr = dst.data() + offset_dst;
-
const int input_offset = -src.quantization_info().offset;
const float input_scale = src.quantization_info().scale;
const int weights_offset = -weights.quantization_info().offset;
@@ -141,7 +98,7 @@
acc = utility::clamp<int32_t>(acc, 0, 255);
// Store the result
- dst_ptr[y] = static_cast<uint8_t>(acc);
+ dst_ptr[y] = static_cast<T>(acc);
weights_ptr += cols_weights;
}
@@ -152,7 +109,7 @@
SimpleTensor<T> fully_connected_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &dst_shape)
{
// Create reference
- SimpleTensor<T> dst{ TensorShape{ dst_shape }, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<T> dst{ TensorShape{ dst_shape }, src.data_type(), 1, src.quantization_info() };
// Sanity checks
const int num_batch_dimensions = std::max(0, static_cast<int>(dst_shape.num_dimensions()) - 1);
@@ -183,8 +140,7 @@
offset_in,
offset_out,
cols_weights,
- rows_weights,
- src.fixed_point_position());
+ rows_weights);
}
return dst;
@@ -192,8 +148,6 @@
template SimpleTensor<float> fully_connected_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &dst_shape);
template SimpleTensor<half> fully_connected_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &dst_shape);
-template SimpleTensor<qint8_t> fully_connected_layer(const SimpleTensor<qint8_t> &src, const SimpleTensor<qint8_t> &weights, const SimpleTensor<qint8_t> &bias, const TensorShape &dst_shape);
-template SimpleTensor<qint16_t> fully_connected_layer(const SimpleTensor<qint16_t> &src, const SimpleTensor<qint16_t> &weights, const SimpleTensor<qint16_t> &bias, const TensorShape &dst_shape);
template SimpleTensor<uint8_t> fully_connected_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &dst_shape);
} // namespace reference
} // namespace validation
diff --git a/tests/validation/reference/GEMM.cpp b/tests/validation/reference/GEMM.cpp
index f9dcfcb..7378ada 100644
--- a/tests/validation/reference/GEMM.cpp
+++ b/tests/validation/reference/GEMM.cpp
@@ -38,7 +38,7 @@
SimpleTensor<T> gemm(const SimpleTensor<T> &a, const SimpleTensor<T> &b, const SimpleTensor<T> &c, float alpha, float beta)
{
// Create reference
- SimpleTensor<T> dst{ c.shape(), c.data_type(), 1, c.fixed_point_position() };
+ SimpleTensor<T> dst{ c.shape(), c.data_type(), 1 };
// Compute reference
const int M = a.shape().y();
@@ -91,7 +91,7 @@
using namespace fixed_point_arithmetic;
// Create reference
- SimpleTensor<T> dst{ c.shape(), c.data_type(), 1, c.fixed_point_position() };
+ SimpleTensor<T> dst{ c.shape(), c.data_type(), 1 };
// Compute reference
using promoted_type = fixed_point_arithmetic::traits::promote_t<T>;
@@ -156,8 +156,6 @@
template SimpleTensor<float> gemm(const SimpleTensor<float> &a, const SimpleTensor<float> &b, const SimpleTensor<float> &c, float alpha, float beta);
template SimpleTensor<half> gemm(const SimpleTensor<half> &a, const SimpleTensor<half> &b, const SimpleTensor<half> &c, float alpha, float beta);
-template SimpleTensor<qint8_t> gemm(const SimpleTensor<qint8_t> &a, const SimpleTensor<qint8_t> &b, const SimpleTensor<qint8_t> &c, float alpha, float beta);
-template SimpleTensor<qint16_t> gemm(const SimpleTensor<qint16_t> &a, const SimpleTensor<qint16_t> &b, const SimpleTensor<qint16_t> &c, float alpha, float beta);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/LocallyConnected.cpp b/tests/validation/reference/LocallyConnected.cpp
index 08e3f02..ecc582b 100644
--- a/tests/validation/reference/LocallyConnected.cpp
+++ b/tests/validation/reference/LocallyConnected.cpp
@@ -41,7 +41,7 @@
SimpleTensor<T> locally_connected(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape, const PadStrideInfo &info)
{
// Create reference
- SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.quantization_info() };
// Compute reference
const int width_in = src.shape().x();
diff --git a/tests/validation/reference/NormalizationLayer.cpp b/tests/validation/reference/NormalizationLayer.cpp
index 226af96..85872c8 100644
--- a/tests/validation/reference/NormalizationLayer.cpp
+++ b/tests/validation/reference/NormalizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -38,7 +38,7 @@
SimpleTensor<T> normalization_layer(const SimpleTensor<T> &src, NormalizationLayerInfo info)
{
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
// Compute reference
const uint32_t norm_size = info.norm_size();
@@ -152,7 +152,7 @@
using namespace fixed_point_arithmetic;
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
// Compute reference
const int fixed_point_position = src.fixed_point_position();
@@ -267,8 +267,6 @@
template SimpleTensor<float> normalization_layer(const SimpleTensor<float> &src, NormalizationLayerInfo info);
template SimpleTensor<half> normalization_layer(const SimpleTensor<half> &src, NormalizationLayerInfo info);
-template SimpleTensor<qint8_t> normalization_layer(const SimpleTensor<qint8_t> &src, NormalizationLayerInfo info);
-template SimpleTensor<qint16_t> normalization_layer(const SimpleTensor<qint16_t> &src, NormalizationLayerInfo info);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/Permute.cpp b/tests/validation/reference/Permute.cpp
index bbb2e8d..29c3c5c 100644
--- a/tests/validation/reference/Permute.cpp
+++ b/tests/validation/reference/Permute.cpp
@@ -42,7 +42,7 @@
permute(dst_shape, perm);
// Create reference
- SimpleTensor<T> dst{ dst_shape, src.data_type(), src.num_channels(), src.fixed_point_position(), src.quantization_info() };
+ SimpleTensor<T> dst{ dst_shape, src.data_type(), src.num_channels(), src.quantization_info() };
// Compute reference
for(int i = 0; i < src.num_elements(); ++i)
diff --git a/tests/validation/reference/PoolingLayer.cpp b/tests/validation/reference/PoolingLayer.cpp
index 6973454..e9054b9 100644
--- a/tests/validation/reference/PoolingLayer.cpp
+++ b/tests/validation/reference/PoolingLayer.cpp
@@ -44,7 +44,7 @@
ARM_COMPUTE_ERROR_ON(info.is_global_pooling() && (src.shape().x() != src.shape().y()));
// Create reference
- SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type(), src.fixed_point_position()), info), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type(), src.fixed_point_position()), info), src.data_type(), 1 };
const int pool_size_x = info.is_global_pooling() ? src.shape().x() : info.pool_size().width;
const int pool_size_y = info.is_global_pooling() ? src.shape().y() : info.pool_size().height;
@@ -152,128 +152,6 @@
return dst;
}
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
-SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, const PoolingLayerInfo &info)
-{
- ARM_COMPUTE_ERROR_ON(info.is_global_pooling() && (src.shape().x() != src.shape().y()));
-
- const auto w_src = static_cast<int>(src.shape()[0]);
- const auto h_src = static_cast<int>(src.shape()[1]);
- const int upper_dims = src.shape().total_size() / (w_src * h_src);
-
- const int pool_size_x = info.is_global_pooling() ? src.shape().x() : info.pool_size().width;
- const int pool_size_y = info.is_global_pooling() ? src.shape().y() : info.pool_size().height;
- PoolingType type = info.pool_type();
- int pool_stride_x = info.pad_stride_info().stride().first;
- int pool_stride_y = info.pad_stride_info().stride().second;
- int pad_left = info.pad_stride_info().pad_left();
- int pad_top = info.pad_stride_info().pad_top();
- int pad_right = info.pad_stride_info().pad_right();
- int pad_bottom = info.pad_stride_info().pad_bottom();
- bool exclude_padding = info.exclude_padding();
-
- // Create reference
- SimpleTensor<T> dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type(), src.fixed_point_position()), info), src.data_type(), 1, src.fixed_point_position() };
-
- const auto w_dst = static_cast<int>(dst.shape()[0]);
- const auto h_dst = static_cast<int>(dst.shape()[1]);
-
- if(type == PoolingType::MAX)
- {
- for(int r = 0; r < upper_dims; ++r)
- {
- for(int h = 0; h < h_dst; ++h)
- {
- for(int w = 0; w < w_dst; ++w)
- {
- int wstart = w * pool_stride_x - pad_left;
- int hstart = h * pool_stride_y - pad_top;
- int wend = std::min(wstart + pool_size_x, w_src);
- int hend = std::min(hstart + pool_size_y, h_src);
- wstart = std::max(wstart, 0);
- hstart = std::max(hstart, 0);
-
- T max_val = std::numeric_limits<T>::lowest();
- for(int y = hstart; y < hend; ++y)
- {
- for(int x = wstart; x < wend; ++x)
- {
- const T val = src[r * h_src * w_src + y * w_src + x];
- if(val > max_val)
- {
- max_val = val;
- }
- }
- }
-
- dst[r * h_dst * w_dst + h * w_dst + w] = max_val;
- }
- }
- }
- }
- else // Average or l2 pooling
- {
- for(int r = 0; r < upper_dims; ++r)
- {
- for(int h = 0; h < h_dst; ++h)
- {
- for(int w = 0; w < w_dst; ++w)
- {
- int wstart = w * pool_stride_x - pad_left;
- int hstart = h * pool_stride_y - pad_top;
- int wend = std::min(wstart + pool_size_x, w_src + pad_right);
- int hend = std::min(hstart + pool_size_y, h_src + pad_bottom);
- int pool = (hend - hstart) * (wend - wstart);
- wstart = std::max(wstart, 0);
- hstart = std::max(hstart, 0);
- wend = std::min(wend, w_src);
- hend = std::min(hend, h_src);
- // Exclude padding pixels from the average
- if(exclude_padding)
- {
- pool = (hend - hstart) * (wend - wstart);
- }
-
- using namespace fixed_point_arithmetic;
-
- const int fixed_point_position = src.fixed_point_position();
- const fixed_point<T> const_1(1, fixed_point_position);
- const fixed_point<T> invpool_fp(1.f / static_cast<float>(pool), fixed_point_position);
- fixed_point<T> avg_val(0, fixed_point_position, true);
-
- if(type == PoolingType::AVG)
- {
- for(int y = hstart; y < hend; ++y)
- {
- for(int x = wstart; x < wend; ++x)
- {
- const fixed_point<T> in_fp(src[r * h_src * w_src + y * w_src + x], fixed_point_position, true);
- avg_val = add(avg_val, in_fp);
- }
- }
- dst[r * h_dst * w_dst + h * w_dst + w] = mul(avg_val, invpool_fp).raw();
- }
- else
- {
- for(int y = hstart; y < hend; ++y)
- {
- for(int x = wstart; x < wend; ++x)
- {
- const fixed_point<T> in_fp(src[r * h_src * w_src + y * w_src + x], fixed_point_position, true);
- avg_val = add(avg_val, mul(in_fp, in_fp));
- }
- }
- auto res = div(const_1, (inv_sqrt(mul(avg_val, invpool_fp))));
- dst[r * h_dst * w_dst + h * w_dst + w] = res.raw();
- }
- }
- }
- }
- }
-
- return dst;
-}
-
template <>
SimpleTensor<uint8_t> pooling_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const PoolingLayerInfo &info)
{
@@ -285,8 +163,6 @@
template SimpleTensor<float> pooling_layer(const SimpleTensor<float> &src, const PoolingLayerInfo &info);
template SimpleTensor<half> pooling_layer(const SimpleTensor<half> &src, const PoolingLayerInfo &info);
-template SimpleTensor<qint8_t> pooling_layer(const SimpleTensor<qint8_t> &src, const PoolingLayerInfo &info);
-template SimpleTensor<qint16_t> pooling_layer(const SimpleTensor<qint16_t> &src, const PoolingLayerInfo &info);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/SoftmaxLayer.cpp b/tests/validation/reference/SoftmaxLayer.cpp
index 90b9b1f..ae4bcd8 100644
--- a/tests/validation/reference/SoftmaxLayer.cpp
+++ b/tests/validation/reference/SoftmaxLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -38,7 +38,7 @@
SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta)
{
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
// Compute reference
const int cols = src.shape()[0];
@@ -79,7 +79,7 @@
using namespace fixed_point_arithmetic;
// Create reference
- SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+ SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
// Compute reference
const int cols = src.shape()[0];
@@ -128,8 +128,6 @@
template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta);
template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta);
-template SimpleTensor<qint8_t> softmax_layer(const SimpleTensor<qint8_t> &src, float beta);
-template SimpleTensor<qint16_t> softmax_layer(const SimpleTensor<qint16_t> &src, float beta);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/reference/WidthConcatenateLayer.cpp b/tests/validation/reference/WidthConcatenateLayer.cpp
index fe79b4a..5b89934 100644
--- a/tests/validation/reference/WidthConcatenateLayer.cpp
+++ b/tests/validation/reference/WidthConcatenateLayer.cpp
@@ -85,8 +85,6 @@
template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs);
template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs);
-template SimpleTensor<qint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<qint8_t>> &srcs);
-template SimpleTensor<qint16_t> widthconcatenate_layer(const std::vector<SimpleTensor<qint16_t>> &srcs);
} // namespace reference
} // namespace validation
} // namespace test