COMPMID-791: Adds support of QASYMM8 in NEDepthwiseConvolution3x3
Change-Id: I1a9ed6c3420ddf8978aeaad48d9915333b006b49
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/116374
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/validation/CL/DepthwiseConvolutionLayer.cpp b/tests/validation/CL/DepthwiseConvolutionLayer.cpp
index 92a2773..43e04fb 100644
--- a/tests/validation/CL/DepthwiseConvolutionLayer.cpp
+++ b/tests/validation/CL/DepthwiseConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -43,7 +43,7 @@
namespace
{
constexpr RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-constexpr RelativeTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */
+constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */
} // namespace
TEST_SUITE(CL)
@@ -96,13 +96,13 @@
TEST_SUITE(W3x3)
FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) })))
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) })))
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
{
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
diff --git a/tests/validation/NEON/DepthwiseConvolutionLayer.cpp b/tests/validation/NEON/DepthwiseConvolutionLayer.cpp
index 420c974..e8c7715 100644
--- a/tests/validation/NEON/DepthwiseConvolutionLayer.cpp
+++ b/tests/validation/NEON/DepthwiseConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -42,7 +42,8 @@
{
namespace
{
-constexpr RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+constexpr RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */
} // namespace
TEST_SUITE(NEON)
@@ -125,6 +126,28 @@
TEST_SUITE_END()
+template <typename T>
+using NEDepthwiseConvolutionLayerQuantizedFixture3x3 = DepthwiseConvolutionLayerValidationQuantizedFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer3x3, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+{
+ validate(Accessor(_target), _reference, tolerance_qasymm8);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionLayerQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, 10) })))
+{
+ validate(Accessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+TEST_SUITE_END()
+
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
diff --git a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
index fc48bce..df5436f 100644
--- a/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -34,6 +34,8 @@
#include "tests/validation/Helpers.h"
#include "tests/validation/reference/DepthwiseConvolutionLayer.h"
+#include "utils/Utils.h"
+
#include <random>
namespace arm_compute
@@ -82,7 +84,7 @@
}
case DataType::S32:
{
- std::uniform_int_distribution<int32_t> distribution(-1000, 1000);
+ std::uniform_int_distribution<int32_t> distribution(-100, 100);
library->fill(tensor, distribution, i);
break;
}
@@ -136,7 +138,7 @@
{
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, data_type, 1, 0, quantization_info };
+ SimpleTensor<TBias> biases{ biases_shape, bias_data_type, 1, 0, quantization_info };
fill(src, 0);
fill(weights, 1);
diff --git a/tests/validation/reference/DepthwiseConvolutionLayer.cpp b/tests/validation/reference/DepthwiseConvolutionLayer.cpp
index 08caa8e..6ca347f 100644
--- a/tests/validation/reference/DepthwiseConvolutionLayer.cpp
+++ b/tests/validation/reference/DepthwiseConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -156,17 +156,17 @@
{
for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first)
{
- Coordinates coords(x, y, z);
+ Coordinates coords(x, y, z, r);
int filter_offset = filter_plane * z;
- uint32_t val = 0;
+ int32_t val = 0;
for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j)
{
for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i)
{
coords.set(0, i);
coords.set(1, j);
- auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, 0);
+ auto in_val = tensor_elem_at<uint8_t>(src, coords, BorderMode::CONSTANT, -input_offset);
uint8_t w_val = *(weights.data() + filter_offset);
val += (in_val + input_offset) * (w_val + weights_offset);
++filter_offset;