COMPMID-661: Add QASYMM8 support (and basic tests) to CLDepthwiseConvolution3x3 kernel (#28)
Change-Id: I51bebe74e3814c1245812ad575fe7854d460674f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/109864
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
diff --git a/tests/validation/CL/DepthwiseConvolution.cpp b/tests/validation/CL/DepthwiseConvolution.cpp
index 5f1bde8..ccd9c36 100644
--- a/tests/validation/CL/DepthwiseConvolution.cpp
+++ b/tests/validation/CL/DepthwiseConvolution.cpp
@@ -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 RelativeTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QASYMM8 */
} // namespace
TEST_SUITE(CL)
@@ -52,11 +53,13 @@
using CLDepthwiseConvolutionFixture = DepthwiseConvolutionValidationFixture<CLTensor, CLAccessor, CLDepthwiseConvolution, T>;
TEST_SUITE(Generic)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionFixture<float>, framework::DatasetMode::PRECOMMIT, datasets::SmallDepthwiseConvolutionDataset())
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionDataset(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionFixture<float>, framework::DatasetMode::NIGHTLY, datasets::LargeDepthwiseConvolutionDataset())
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionDataset(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
@@ -65,16 +68,44 @@
template <typename T>
using CLDepthwiseConvolutionFixture3x3 = DepthwiseConvolutionValidationFixture<CLTensor, CLAccessor, CLDepthwiseConvolution3x3, T>;
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::PRECOMMIT, datasets::SmallDepthwiseConvolutionDataset3x3())
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionDataset3x3(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::NIGHTLY, datasets::LargeDepthwiseConvolutionDataset3x3())
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionDataset3x3(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(CLAccessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END()
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+template <typename T>
+using CLDepthwiseConvolutionQuantizedFixture3x3 = DepthwiseConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDepthwiseConvolution3x3, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDepthwiseConvolutionQuantizedFixture3x3<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDepthwiseConvolutionDataset3x3(),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLDepthwiseConvolutionQuantizedFixture3x3<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDepthwiseConvolutionDataset3x3(),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+TEST_SUITE_END()
TEST_SUITE_END()
TEST_SUITE_END()
diff --git a/tests/validation/CPP/ConvolutionLayer.cpp b/tests/validation/CPP/ConvolutionLayer.cpp
index 95852b0..a767912 100644
--- a/tests/validation/CPP/ConvolutionLayer.cpp
+++ b/tests/validation/CPP/ConvolutionLayer.cpp
@@ -55,8 +55,8 @@
{
const T *in_ptr = in.data() + i_offset;
const T *w_ptr = weights.data() + w_offset;
- const T *b_ptr = bias.data() + b_offset;
- T *out_ptr = out.data() + o_offset;
+ const TB *b_ptr = bias.data() + b_offset;
+ T *out_ptr = out.data() + o_offset;
const int half_width_weights = width_weights / 2;
const int half_height_weights = height_weights / 2;
diff --git a/tests/validation/CPP/DepthwiseConvolution.cpp b/tests/validation/CPP/DepthwiseConvolution.cpp
index e29d014..ad06538 100644
--- a/tests/validation/CPP/DepthwiseConvolution.cpp
+++ b/tests/validation/CPP/DepthwiseConvolution.cpp
@@ -26,8 +26,13 @@
#include "ConvolutionLayer.h"
#include "Utils.h"
+#include "tests/validation/CPP/Utils.h"
+#include "tests/validation/CPP/UtilsQuantizedAsymm.h"
+#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
+#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
+
namespace arm_compute
{
namespace test
@@ -44,8 +49,8 @@
* - Padding, stride and output shape "match"
*
*/
-template <typename T>
-SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &biases, const TensorShape &dst_shape, const PadStrideInfo &conv_info)
+template <typename T, typename TB>
+SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &biases, const TensorShape &dst_shape, const PadStrideInfo &conv_info)
{
// Create reference
SimpleTensor<T> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position() };
@@ -97,7 +102,7 @@
}
coords.set(0, x);
coords.set(1, y);
- dst[out_pos++] = saturate_cast<T>(val + *static_cast<const T *>(biases(Coordinates(z))));
+ dst[out_pos++] = saturate_cast<T>(val + *static_cast<const TB *>(biases(Coordinates(z))));
}
}
}
@@ -106,6 +111,78 @@
return dst;
}
+template <>
+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)
+{
+ // Create reference
+ SimpleTensor<uint8_t> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position(), src.quantization_info() };
+
+ const int input_offset = -src.quantization_info().offset;
+ const float input_scale = src.quantization_info().scale;
+ const int weights_offset = -weights.quantization_info().offset;
+ const float weights_scale = weights.quantization_info().scale;
+ const int output_offset = dst.quantization_info().offset;
+ const float output_scale = dst.quantization_info().scale;
+
+ int output_multiplier;
+ int output_shift;
+ const float multiplier = input_scale * weights_scale / output_scale;
+ arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
+
+ // Compute reference
+ const int filter_width = weights.shape().x();
+ const int filter_height = weights.shape().y();
+ const int filter_plane = filter_width * filter_height;
+ const int input_width = src.shape().x();
+ const int input_height = src.shape().y();
+ const int input_depth = src.shape().z();
+
+ const int filter_half_size = filter_width / 2;
+ const int pad_x = std::min(filter_half_size, static_cast<int>(conv_info.pad().first));
+ const int pad_y = std::min(filter_half_size, static_cast<int>(conv_info.pad().second));
+ const int minimum_x = -pad_x + filter_half_size;
+ const int minimum_y = -pad_y + filter_half_size;
+
+ int out_pos = 0;
+ for(int z = 0; z < input_depth; ++z)
+ {
+ int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z)));
+ for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second)
+ {
+ for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first)
+ {
+ Coordinates coords(x, y, z);
+ int filter_offset = filter_plane * z;
+
+ uint32_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);
+ uint8_t w_val = *(weights.data() + filter_offset);
+ val += (in_val + input_offset) * (w_val + weights_offset);
+ ++filter_offset;
+ }
+ }
+ val += bias_val;
+ val = asymm_rounding_divide_by_pow2(asymm_int_mult(val, output_multiplier), output_shift);
+ val += output_offset;
+ val = std::max<int32_t>(val, 0);
+ val = std::min<int32_t>(val, 255);
+
+ // Store the result
+ dst[out_pos++] = val;
+ }
+ }
+ }
+
+ return dst;
+}
+
template SimpleTensor<float> depthwise_convolution(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &biases, const TensorShape &dst_shape,
const PadStrideInfo &conv_info);
} // namespace reference
diff --git a/tests/validation/CPP/DepthwiseConvolution.h b/tests/validation/CPP/DepthwiseConvolution.h
index e8c55b1..df743a5 100644
--- a/tests/validation/CPP/DepthwiseConvolution.h
+++ b/tests/validation/CPP/DepthwiseConvolution.h
@@ -35,8 +35,8 @@
{
namespace reference
{
-template <typename T>
-SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &biases, const TensorShape &dst_shape, const PadStrideInfo &conv_info);
+template <typename T, typename TB>
+SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &biases, const TensorShape &dst_shape, const PadStrideInfo &conv_info);
} // namespace reference
} // namespace validation
} // namespace test
diff --git a/tests/validation/NEON/DepthwiseConvolution.cpp b/tests/validation/NEON/DepthwiseConvolution.cpp
index 6e8aa46..b6719b5 100644
--- a/tests/validation/NEON/DepthwiseConvolution.cpp
+++ b/tests/validation/NEON/DepthwiseConvolution.cpp
@@ -87,18 +87,22 @@
template <typename T>
using NEDepthwiseConvolutionFixture3x3 = DepthwiseConvolutionValidationFixture<Tensor, Accessor, NEDepthwiseConvolution3x3, T>;
+TEST_SUITE(Float)
TEST_SUITE(F32)
TEST_SUITE(W3x3)
-FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::PRECOMMIT, datasets::SmallDepthwiseConvolutionDataset3x3())
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::ALL, combine(datasets::SmallDepthwiseConvolutionDataset3x3(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(Accessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::NIGHTLY, datasets::LargeDepthwiseConvolutionDataset3x3())
+FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthwiseConvolutionFixture3x3<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeDepthwiseConvolutionDataset3x3(), framework::dataset::make("DataType",
+ DataType::F32)))
{
validate(Accessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END()
TEST_SUITE_END()
+TEST_SUITE_END()
TEST_SUITE_END()
TEST_SUITE_END()
diff --git a/tests/validation/fixtures/DepthwiseConvolutionFixture.h b/tests/validation/fixtures/DepthwiseConvolutionFixture.h
index f49e76c..b1d31d6 100644
--- a/tests/validation/fixtures/DepthwiseConvolutionFixture.h
+++ b/tests/validation/fixtures/DepthwiseConvolutionFixture.h
@@ -43,14 +43,22 @@
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DepthwiseConvolutionValidationFixture : public framework::Fixture
+class DepthwiseConvolutionValidationGenericFixture : public framework::Fixture
{
public:
+ using TBias = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, int32_t, T>::type;
+
+public:
template <typename...>
- void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape out_shape, PadStrideInfo pad_stride_info)
+ void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info)
{
- _target = compute_target(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info);
- _reference = compute_reference(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info);
+ _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(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info);
+ _reference = compute_reference(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info);
}
protected:
@@ -59,28 +67,46 @@
{
switch(tensor.data_type())
{
+ case DataType::QASYMM8:
+ {
+ std::uniform_int_distribution<uint8_t> distribution(0, 10);
+ library->fill(tensor, distribution, i);
+ break;
+ }
case DataType::F32:
{
std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
library->fill(tensor, distribution, i);
break;
}
+ case DataType::S32:
+ {
+ std::uniform_int_distribution<int32_t> distribution(-1000, 1000);
+ library->fill(tensor, distribution, i);
+ break;
+ }
default:
library->fill_tensor_uniform(tensor, i);
}
}
- TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &output_shape, PadStrideInfo &pad_stride_info)
+ TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &output_shape, PadStrideInfo &pad_stride_info,
+ const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info)
{
// Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, DataType::F32);
- TensorType weights = create_tensor<TensorType>(weights_shape, DataType::F32);
- TensorType biases = create_tensor<TensorType>(biases_shape, DataType::F32);
- TensorType dst = create_tensor<TensorType>(output_shape, DataType::F32);
+ TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, quantization_info);
+ TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, 0, quantization_info);
+ TensorType biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, 0, quantization_info);
+ TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, quantization_info);
// Create Depthwise Convolution configure function
- FunctionType depthwise_convolution;
- depthwise_convolution.configure(&src, &weights, &biases, &dst, pad_stride_info);
+ FunctionType dwc;
+ dwc.configure(&src, &weights, &biases, &dst, pad_stride_info);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(biases.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
@@ -99,16 +125,17 @@
fill(AccessorType(biases), 2);
// Compute function
- depthwise_convolution.run();
+ dwc.run();
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &out_shape, const PadStrideInfo &pad_stride_info)
+ SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &out_shape, const PadStrideInfo &pad_stride_info,
+ const DataType data_type, const DataType bias_data_type, QuantizationInfo quantization_info)
{
- SimpleTensor<T> src(in_shape, DataType::F32);
- SimpleTensor<T> weights(weights_shape, DataType::F32);
- SimpleTensor<T> biases(biases_shape, DataType::F32);
+ 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 };
fill(src, 0);
fill(weights, 1);
@@ -117,8 +144,34 @@
return reference::depthwise_convolution(src, weights, biases, out_shape, pad_stride_info);
}
- TensorType _target{};
- SimpleTensor<T> _reference{};
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ DataType _data_type{};
+ QuantizationInfo _quantization_info{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DepthwiseConvolutionValidationFixture : public DepthwiseConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type)
+ {
+ DepthwiseConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info,
+ data_type, QuantizationInfo());
+ }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DepthwiseConvolutionValidationQuantizedFixture : public DepthwiseConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info)
+ {
+ DepthwiseConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info,
+ data_type, quantization_info);
+ }
};
} // namespace validation
} // namespace test
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
index 279a489..1ec4d31 100644
--- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
@@ -84,6 +84,12 @@
library->fill(tensor, distribution, i);
break;
}
+ case DataType::S32:
+ {
+ std::uniform_int_distribution<int32_t> distribution(-1000, 1000);
+ library->fill(tensor, distribution, i);
+ break;
+ }
default:
library->fill_tensor_uniform(tensor, i);
}