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/*
* Copyright (c) 2016-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/CL/kernels/CLActivationLayerKernel.h"
#include "arm_compute/core/CL/CLCoreRuntimeContext.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/core/utils/helpers/float_ops.h"
#include "support/ToolchainSupport.h"
#include <cmath>
#include <set>
using 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);
static std::set<ActivationLayerInfo::ActivationFunction> quantized_supported_activations =
{
ActivationLayerInfo::ActivationFunction::RELU,
ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
ActivationLayerInfo::ActivationFunction::LOGISTIC,
ActivationLayerInfo::ActivationFunction::TANH
};
const DataType data_type = input->data_type();
const QuantizationInfo &oq_info = (output != nullptr) ? output->quantization_info() : input->quantization_info();
const ActivationLayerInfo::ActivationFunction f_act = act_info.activation();
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(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)));
// Checks performed when output is configured
if((output != nullptr) && (output->total_size() != 0))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
{
if(output != nullptr)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output, *input);
}
const unsigned int num_elems_processed_per_iteration = 16 / input->element_size();
Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
bool window_changed = false;
if(output != nullptr)
{
AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
window_changed = update_window_and_padding(win, input_access, output_access);
output_access.set_valid_region(win, input->valid_region());
}
else
{
window_changed = update_window_and_padding(win,
AccessWindowHorizontal(input, 0, num_elems_processed_per_iteration));
}
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
CLActivationLayerKernel::CLActivationLayerKernel(CLCoreRuntimeContext *ctx)
: _input(nullptr), _output(nullptr), _run_in_place(false), _ctx(ctx)
{
}
void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
_run_in_place = (output == nullptr) || (output == input);
if(output != nullptr)
{
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(),
*input->info()->clone());
}
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, act_info));
const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
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");
build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
build_opts.add_option(("-DACT=" + lower_string(string_from_activation_func(f_act))));
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)));
}
// Set quantization info build options
if(is_quantized)
{
const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();
// 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 scale and offset of the input and output if they have different quantization info
if(output != nullptr)
{
const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform();
if(iq_info != oq_info)
{
build_opts.add_option(("-DS2_VAL=" + float_to_string_with_full_precision(oq_info.scale)));
build_opts.add_option_if(is_data_type_quantized_asymmetric(dt), "-DO2_VAL=" + support::cpp11::to_string(oq_info.offset));
}
}
}
// Create kernel
std::string kernel_name = std::string("activation_layer");
if(is_quantized)
{
kernel_name += perform_activation_in_float ? std::string("_quant_f32") : std::string("_quant");
}
_kernel = create_opencl_kernel(_ctx, kernel_name, build_opts);
// Make sure _kernel is initialized before calling the parent's configure
_input = input;
_output = output;
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), (_run_in_place) ? nullptr : output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
// Set config_id for enabling LWS tuning
_config_id = "activation_layer_";
_config_id += lower_string(string_from_data_type(dt));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(1));
}
Status CLActivationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)
{
const bool run_in_place = (output == nullptr) || (output == input);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, act_info));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (run_in_place) ? nullptr : output->clone().get()).first);
return Status{};
}
void CLActivationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
Window slice = collapsed.first_slice_window_3D();
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice);
if(!_run_in_place)
{
add_3D_tensor_argument(idx, _output, slice);
}
enqueue(queue, *this, slice, lws_hint());
}
while(collapsed.slide_window_slice_3D(slice));
}
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