COMPMID-2991: Add support for QASYMM8_SIGNED in CL kernels/functions - part 2
Adding support for QASYMM8_SIGNED to the following CL kernels/functions:
- CLActivationLayerKernel/CLActivationLayer
- CLComparisonKernel/CLComparison
- CLConvertFullyConnectedWeightsKernel/CLConvertFullyConnectedWeights
- CLDeconvolutionLayerUpsampleKernel/CLDeconvolutionLayerUpsample
- CLDepthToSpaceLayerKernel/CLDepthToSpaceLayer
- CLDequantizationLayerKernel/CLDequantizationLayer
- CLGEMMMatrixVectorMultiplyKernel
- CLNormalizePlanarYUVLayerKernel
- CLPReluLayer
- CLPixelWiseMultiplicationKernel/CLPixelWiseMultiplication
- CLPoolingLayerKernel/CLPoolingLayer
Change-Id: I874bbb7c2b08baa9c5ff4c9e6bc8778b42a6bec5
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2539
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp
index 5062fd1..270eb78 100644
--- a/src/core/CL/kernels/CLActivationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -39,14 +39,14 @@
#include <cmath>
#include <set>
-using namespace arm_compute;
-
+namespace arm_compute
+{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QASYMM8, DataType::QSYMM16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16, DataType::F16, DataType::F32);
static std::set<ActivationLayerInfo::ActivationFunction> quantized_supported_activations =
{
@@ -63,12 +63,15 @@
ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(data_type) && (quantized_supported_activations.count(f_act) == 0),
"For Quantized data type only tanh, logistic, relu and lower/upper bounded relu are supported");
- ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 128)));
- ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, 0)));
+ ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8 && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 128)));
+ ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8 && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, 0)));
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_symmetric(data_type) && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 32768.f, 0)));
+ ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::TANH) && (oq_info != QuantizationInfo(1.f / 128.f, 0)));
+ ARM_COMPUTE_RETURN_ERROR_ON(data_type == DataType::QASYMM8_SIGNED && (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) && (oq_info != QuantizationInfo(1.f / 256.f, -128)));
+
// Checks performed when output is configured
if((output != nullptr) && (output->total_size() != 0))
{
@@ -135,27 +138,11 @@
const DataType dt = input->info()->data_type();
float a_const = act_info.a();
float b_const = act_info.b();
- int a_const_int = 0;
- int b_const_int = 0;
const ActivationLayerInfo::ActivationFunction f_act = act_info.activation();
const bool is_quantized = is_data_type_quantized(dt);
const bool perform_activation_in_float = (f_act == ActivationLayerInfo::ActivationFunction::LOGISTIC) || (f_act == ActivationLayerInfo::ActivationFunction::TANH);
- // Create quantized version of constants a, b if needed
- if(dt == DataType::QASYMM8)
- {
- const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();
- a_const_int = quantize_qasymm8(a_const, iq_info);
- b_const_int = quantize_qasymm8(b_const, iq_info);
- }
- else if(dt == DataType::QSYMM16)
- {
- const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();
- a_const_int = quantize_qsymm16(a_const, iq_info);
- b_const_int = quantize_qsymm16(b_const, iq_info);
- }
-
// Set build options
CLBuildOptions build_opts;
build_opts.add_option_if(perform_activation_in_float, "-DFLOAT_DOMAIN");
@@ -164,28 +151,59 @@
build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)));
build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
- // Set A, B constants in build options
- if(is_quantized && !perform_activation_in_float)
- {
- build_opts.add_option(("-DA_VAL=" + support::cpp11::to_string(a_const_int)));
- build_opts.add_option(("-DB_VAL=" + support::cpp11::to_string(b_const_int)));
- }
- else
- {
- build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const)));
- build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const)));
- }
+ std::string kernel_name = std::string("activation_layer");
// Set quantization info build options
if(is_quantized)
{
const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();
+ if(!perform_activation_in_float)
+ {
+ int a_const_int = 0;
+ int b_const_int = 0;
+
+ // Create quantized version of constants a, b if needed
+ switch(dt)
+ {
+ case DataType::QASYMM8:
+ {
+ a_const_int = quantize_qasymm8(a_const, iq_info);
+ b_const_int = quantize_qasymm8(b_const, iq_info);
+ }
+ break;
+ case DataType::QASYMM8_SIGNED:
+ {
+ a_const_int = quantize_qasymm8_signed(a_const, iq_info);
+ b_const_int = quantize_qasymm8_signed(b_const, iq_info);
+ }
+ break;
+ case DataType::QSYMM16:
+ {
+ a_const_int = quantize_qsymm16(a_const, iq_info);
+ b_const_int = quantize_qsymm16(b_const, iq_info);
+ }
+ break;
+ default:
+ break;
+ }
+ build_opts.add_option(("-DA_VAL=" + support::cpp11::to_string(a_const_int)));
+ build_opts.add_option(("-DB_VAL=" + support::cpp11::to_string(b_const_int)));
+ }
+ else
+ {
+ build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const)));
+ build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const)));
+ }
+
// Quantized value of 0 corresponds to the offset o1
build_opts.add_option(("-DCONST_0=" + (is_data_type_quantized_asymmetric(dt) ? support::cpp11::to_string(iq_info.offset) : "0")));
build_opts.add_option(("-DS1_VAL=" + float_to_string_with_full_precision(iq_info.scale)));
build_opts.add_option_if(is_data_type_quantized_asymmetric(dt), "-DO1_VAL=" + support::cpp11::to_string(iq_info.offset));
+ // Set correct kernel name
+ kernel_name += perform_activation_in_float ? std::string("_quant_f32") : std::string("_quant");
+
// Set scale and offset of the input and output if they have different quantization info
if(output != nullptr)
{
@@ -198,14 +216,14 @@
}
}
}
-
- // Create kernel
- std::string kernel_name = std::string("activation_layer");
- if(is_quantized)
+ else
{
- kernel_name += perform_activation_in_float ? std::string("_quant_f32") : std::string("_quant");
+ // Set A, B constants in build options for float types
+ build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(a_const)));
+ build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(b_const)));
}
+ // Create kernel
_kernel = create_opencl_kernel(_ctx, kernel_name, build_opts);
// Make sure _kernel is initialized before calling the parent's configure
_input = input;
@@ -254,3 +272,4 @@
}
while(collapsed.slide_window_slice_3D(slice));
}
+} // namespace arm_compute
diff --git a/src/core/CL/kernels/CLComparisonKernel.cpp b/src/core/CL/kernels/CLComparisonKernel.cpp
index 5570ecf..afee429 100644
--- a/src/core/CL/kernels/CLComparisonKernel.cpp
+++ b/src/core/CL/kernels/CLComparisonKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -52,12 +52,7 @@
Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output, ComparisonOperation operation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1,
- 1,
- DataType::U8, DataType::S8, DataType::QASYMM8,
- DataType::U16, DataType::S16,
- DataType::U32, DataType::S32,
- DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(input1.data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2);
ARM_COMPUTE_RETURN_ERROR_ON(supported_comparison_ops.count(operation) == 0);
@@ -132,7 +127,7 @@
build_opts.emplace("-DVEC_SIZE=" + support::cpp11::to_string(calculate_num_elems_processed_per_iteration(*input1->info())));
build_opts.emplace("-DOP=" + operation_name);
build_opts.emplace("-DOP_NAME=" + lower_string(operation_name));
- if(is_data_type_quantized_asymmetric(input1->info()->data_type()))
+ if(is_data_type_quantized(input1->info()->data_type()))
{
const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform();
diff --git a/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp b/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
index 8185676..7ec6841 100644
--- a/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
+++ b/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -64,7 +64,7 @@
// Set build options
CLBuildOptions build_opts;
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
build_opts.add_option("-DFACTOR_1=" + support::cpp11::to_string(factor_1));
build_opts.add_option("-DFACTOR_2=" + support::cpp11::to_string(factor_2));
@@ -79,18 +79,15 @@
Status CLConvertFullyConnectedWeightsKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape,
DataLayout data_layout)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1,
- DataType::U8, DataType::S8, DataType::QASYMM8,
- DataType::U16, DataType::S16,
- DataType::U32, DataType::S32,
- DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() != 2);
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != original_input_shape.total_size_lower(3));
ARM_COMPUTE_RETURN_ERROR_ON(data_layout == DataLayout::UNKNOWN);
// Checks performed when output is configured
- if((output != nullptr) && (output->total_size() != 0))
+ if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
index cd9552f..ee39203 100644
--- a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
+++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
@@ -32,8 +32,8 @@
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
-using namespace arm_compute;
-
+namespace arm_compute
+{
CLDeconvolutionLayerUpsampleKernel::CLDeconvolutionLayerUpsampleKernel()
: _input(nullptr), _output(nullptr), _info(), _data_layout(DataLayout::UNKNOWN)
{
@@ -45,7 +45,7 @@
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
@@ -82,7 +82,7 @@
// Create kernel
CLBuildOptions build_opts;
- build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
+ build_opts.add_option(("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())));
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_upsample", build_opts.options()));
constexpr unsigned int num_elems_processed_per_iteration = 1;
@@ -156,3 +156,4 @@
ARM_COMPUTE_ERROR("Unsupported data layout");
}
}
+} // namespace arm_compute
diff --git a/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp b/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
index 49a5590..f23f7ce 100644
--- a/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,6 +36,7 @@
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 2);
@@ -81,7 +82,7 @@
// Create kernel
CLBuildOptions build_opts;
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
build_opts.add_option("-DCHANNEL_SIZE=" + support::cpp11::to_string(input->info()->dimension(idx_channel)));
build_opts.add_option("-DBLOCK_SHAPE=" + support::cpp11::to_string(block_shape));
build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
diff --git a/src/core/CL/kernels/CLDequantizationLayerKernel.cpp b/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
index 60659fa..f85cb76 100644
--- a/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,7 +40,7 @@
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8, DataType::QSYMM16);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8, DataType::QSYMM16);
if(output->tensor_shape().total_size() > 0)
{
diff --git a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
index 9e5d677..c158937 100644
--- a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -90,11 +90,11 @@
_output = output;
// Check if is a quantized operation
- bool is_quantized = is_data_type_quantized_asymmetric(_input0->info()->data_type());
+ const bool is_quantized = is_data_type_quantized_asymmetric(_input0->info()->data_type());
// Create kernel
CLBuildOptions build_opts;
- build_opts.add_option_if(!is_quantized, "-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input0->info()->dimension(0)));
build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input0->info()->dimension(1)));
diff --git a/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
index b255ba3..220c2cd 100644
--- a/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
+++ b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -35,15 +35,15 @@
#include "support/ToolchainSupport.h"
-using namespace arm_compute;
-
+namespace arm_compute
+{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, std);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, std);
@@ -97,12 +97,8 @@
void CLNormalizePlanarYUVLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
-
- // Output tensor auto initialization if not yet initialized
- auto_init_if_empty(*output->info(), *input->info()->clone());
-
// Perform validation step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info()));
_input = input;
@@ -183,3 +179,4 @@
}
while(collapsed.slide_window_slice_3D(slice));
}
+} // namespace arm_compute
diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
index 50cdc9c..6bdb124 100644
--- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
+++ b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -50,10 +50,18 @@
ARM_COMPUTE_UNUSED(overflow_policy);
ARM_COMPUTE_UNUSED(rounding_policy);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input2);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1,
+ 1,
+ DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2,
+ 1,
+ DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(scale < 0, "Scale cannot be negative.");
const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape());
@@ -63,12 +71,17 @@
// Validate in case of configured output
if(output->total_size() > 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(output);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QASYMM8, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output,
+ 1,
+ DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S16, DataType::QSYMM16, DataType::F16,
+ DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8),
"Output can only be U8 if both inputs are U8");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QASYMM8 && (input1->data_type() != DataType::QASYMM8 || input2->data_type() != DataType::QASYMM8),
"Output can only be QASYMM8 if both inputs are QASYMM8");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QASYMM8_SIGNED && (input1->data_type() != DataType::QASYMM8_SIGNED || input2->data_type() != DataType::QASYMM8_SIGNED),
+ "Output can only be QASYMM8_SIGNED if both inputs are QASYMM8_SIGNED");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QSYMM16 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16),
"Output can only be QSYMM16 if both inputs are QSYMM16");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output");
@@ -99,6 +112,10 @@
{
set_data_type_if_unknown(*output, DataType::QASYMM8);
}
+ else if(input1->data_type() == DataType::QASYMM8_SIGNED)
+ {
+ set_data_type_if_unknown(*output, DataType::QASYMM8_SIGNED);
+ }
else if(input1->data_type() == DataType::QSYMM16)
{
set_data_type_if_unknown(*output, DataType::QSYMM16);
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
index e3f1114..2d75e5f 100644
--- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,7 +40,8 @@
#include <string>
#include <tuple>
-using namespace arm_compute;
+namespace arm_compute
+{
using namespace arm_compute::misc::shape_calculator;
namespace
@@ -57,19 +58,8 @@
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
- DataLayout data_layout = input->data_layout();
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- switch(data_layout)
- {
- case DataLayout::NCHW:
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
- break;
- case DataLayout::NHWC:
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
- break;
- default:
- ARM_COMPUTE_ERROR("Data layout not supported");
- }
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type() == PoolingType::L2),
"Unsupported combination of parameters!");
@@ -234,7 +224,25 @@
build_opts.add_option("-DPOOL_SIZE_X=" + support::cpp11::to_string(pool_size_x));
build_opts.add_option("-DPOOL_SIZE_Y=" + support::cpp11::to_string(pool_size_y));
- build_opts.add_option_if(data_type == DataType::F16, "-DFP16");
+ // Set the initial value for the pooling operation accordingly with the data type
+ if(pool_type == PoolingType::MAX)
+ {
+ if(is_data_type_quantized(data_type))
+ {
+ PixelValue type_min{};
+ std::tie(type_min, std::ignore) = get_min_max(data_type);
+ build_opts.add_option("-DINITIAL_VALUE=" + support::cpp11::to_string(type_min.get<int32_t>()));
+ }
+ else
+ {
+ build_opts.add_option("-DINITIAL_VALUE=" + float_to_string_with_full_precision(std::numeric_limits<float>::lowest()));
+ }
+ }
+ else
+ {
+ // Pool AVG and Pool L2 initial value
+ build_opts.add_option("-DINITIAL_VALUE=0");
+ }
const auto use_fp_mixed_precision = (data_type == DataType::F16) && pool_info.fp_mixed_precision();
const auto use_wider_accumulator = use_fp_mixed_precision && (pool_type != PoolingType::MAX);
@@ -389,3 +397,4 @@
ARM_COMPUTE_ERROR("Not implemented");
}
}
+} // namespace arm_compute