blob: 7d8fc7ec7fd2366abe42f26b942dfa6147a7339a [file] [log] [blame]
/*
* Copyright (c) 2019-2022 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 "src/core/NEON/kernels/NEMeanStdDevNormalizationKernel.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Window.h"
#include "src/core/CPP/Validate.h"
#include "src/core/NEON/NEMath.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/common/Registrars.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/cpu/kernels/meanstddevnorm/list.h"
namespace arm_compute
{
namespace
{
struct MeanStdDevNormSelectorData
{
DataType dt;
};
using MeanStdDevNormSelctorPtr = std::add_pointer<bool(const MeanStdDevNormSelectorData &data)>::type;
using MeanStdDevNormUKernelPtr = std::add_pointer<void(ITensor *input, ITensor *output, float epsilon, const Window &window)>::type;
struct MeanStdDevNormKernel
{
const char *name;
const MeanStdDevNormSelctorPtr is_selected;
MeanStdDevNormUKernelPtr ukernel;
};
static const MeanStdDevNormKernel available_kernels[] =
{
{
"fp32_neon_meanstddevnorm",
[](const MeanStdDevNormSelectorData & data) { return data.dt == DataType::F32; },
REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_meanstddevnorm)
},
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
{
"fp16_neon_meanstddevnorm",
[](const MeanStdDevNormSelectorData & data) { return data.dt == DataType::F16; },
REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_meanstddevnorm)
},
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
};
/** Micro-kernel selector
*
* @param[in] data Selection data passed to help pick the appropriate micro-kernel
*
* @return A matching micro-kernel else nullptr
*/
const MeanStdDevNormKernel *get_implementation(const MeanStdDevNormSelectorData &data)
{
for(const auto &uk : available_kernels)
{
if(uk.is_selected(data))
{
return &uk;
}
}
return nullptr;
}
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
{
ARM_COMPUTE_UNUSED(epsilon);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Input tensor cannot have more than 2 dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
// 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);
}
// This kernel doesn't need padding. A left-over for loop on dimension X, we cannot have any read or write out of memory
// For this reason num_elems_processed_per_iteration is set to 1
Window win = calculate_max_window(*input, Steps());
return std::make_pair(Status{}, win);
}
} // namespace
NEMeanStdDevNormalizationKernel::NEMeanStdDevNormalizationKernel()
: _input(nullptr), _output(nullptr), _epsilon(1e-8f)
{
}
void NEMeanStdDevNormalizationKernel::configure(ITensor *input, ITensor *output, float epsilon)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_ERROR_THROW_ON(NEMeanStdDevNormalizationKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, epsilon));
_input = input;
_output = (output == nullptr) ? input : output;
_epsilon = epsilon;
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), (output == nullptr) ? nullptr : output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICPPKernel::configure(win_config.second);
}
Status NEMeanStdDevNormalizationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, epsilon));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (output != nullptr) ? output->clone().get() : nullptr).first);
return Status{};
}
void NEMeanStdDevNormalizationKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
const auto *uk = get_implementation(MeanStdDevNormSelectorData{ _output->info()->data_type() });
ARM_COMPUTE_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
uk->ukernel(_input, _output, _epsilon, window);
}
} // namespace arm_compute