src/core/NEON/kernels/NEDequantizationLayerKernel.cpp - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2017-2019 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/NEON/kernels/NEDequantizationLayerKernel.h"

 #include "arm_compute/core/AccessWindowStatic.h"
 #include "arm_compute/core/CPP/Validate.h"
 #include "arm_compute/core/Error.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/NEON/NEAsymm.h"
 #include "arm_compute/core/NEON/NESymm.h"
 #include "arm_compute/core/NEON/wrapper/wrapper.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"

 #include <arm_neon.h>

 namespace arm_compute
 {
 namespace
 {
 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, DataType::QSYMM16);

     if(output->tensor_shape().total_size() > 0)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(output);
         ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
     }

     return Status{};
 }

 std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
 {
     // Configure kernel window
     Window win = calculate_max_window(*input, Steps());

     // Output tensor auto initialization if not yet initialized
     auto_init_if_empty(*output, input->tensor_shape(), 1, DataType::F32);

     // NEDequantizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped
     Coordinates coord;
     coord.set_num_dimensions(output->num_dimensions());
     output->set_valid_region(ValidRegion(coord, output->tensor_shape()));

     return std::make_tuple(Status{}, win);
 }

 template <typename T>
 inline void store_result(T *ptr, const float32x4x4_t &v)
 {
     ARM_COMPUTE_UNUSED(ptr, v);
 }

 template <>
 inline void store_result<float>(float *ptr, const float32x4x4_t &v)
 {
     wrapper::vstore(ptr, v.val[0]);
     wrapper::vstore(ptr + 4, v.val[1]);
     wrapper::vstore(ptr + 8, v.val[2]);
     wrapper::vstore(ptr + 12, v.val[3]);
 }

 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 template <>
 inline void store_result<float16_t>(float16_t *ptr, const float32x4x4_t &v)
 {
     wrapper::vstore(ptr, vcombine_f16(vcvt_f16_f32(v.val[0]), vcvt_f16_f32(v.val[1])));
     wrapper::vstore(ptr + 8, vcombine_f16(vcvt_f16_f32(v.val[2]), vcvt_f16_f32(v.val[3])));
 }
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */

 template <typename T>
 inline void store_result(T *ptr, const float32x4x2_t &v)
 {
     ARM_COMPUTE_UNUSED(ptr, v);
 }

 template <>
 inline void store_result<float>(float *ptr, const float32x4x2_t &v)
 {
     wrapper::vstore(ptr, v.val[0]);
     wrapper::vstore(ptr + 4, v.val[1]);
 }

 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 template <>
 inline void store_result<float16_t>(float16_t *ptr, const float32x4x2_t &v)
 {
     wrapper::vstore(ptr, vcombine_f16(vcvt_f16_f32(v.val[0]), vcvt_f16_f32(v.val[1])));
 }
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */

 template <typename T>
 void run_dequantization_qasymm8(const ITensor *input, ITensor *output, const Window &window)
 {
     const UniformQuantizationInfo &qinfo  = input->info()->quantization_info().uniform();
     const float                    scale  = qinfo.scale;
     const int32_t                  offset = qinfo.offset;

     const int  window_step_x  = 16;
     const auto window_start_x = static_cast<int>(window.x().start());
     const auto window_end_x   = static_cast<int>(window.x().end());

     // Collapse window and reset first dimension to handle tail calculations manually
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

     // Create iterators
     Iterator in(input, win_collapsed);
     Iterator out(output, win_collapsed);

     execute_window_loop(win_collapsed, [&](const Coordinates &)
     {
         const auto in_ptr  = reinterpret_cast<const uint8_t *>(in.ptr());
         const auto out_ptr = reinterpret_cast<T *>(out.ptr());

         int x = window_start_x;
         for(; x <= (window_end_x - window_step_x); x += window_step_x)
         {
             const auto vin  = wrapper::vloadq(in_ptr + x);
             const auto vdeq = vdequantize(vin, scale, offset);

             store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
         }

         // Compute left-over elements
         for(; x < window_end_x; ++x)
         {
             uint8_t val    = *(in_ptr + x);
             *(out_ptr + x) = static_cast<T>(dequantize(val, scale, offset));
         }
     },
     in, out);
 }

 template <typename T>
 void run_dequantization_qsymm8(const ITensor *input, ITensor *output, const Window &window)
 {
     const UniformQuantizationInfo &qinfo = input->info()->quantization_info().uniform();
     const float                    scale = qinfo.scale;

     const int  window_step_x  = 16;
     const auto window_start_x = static_cast<int>(window.x().start());
     const auto window_end_x   = static_cast<int>(window.x().end());

     // Collapse window and reset first dimension to handle tail calculations manually
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

     // Create iterators
     Iterator in(input, win_collapsed);
     Iterator out(output, win_collapsed);

     execute_window_loop(win_collapsed, [&](const Coordinates &)
     {
         const auto in_ptr  = reinterpret_cast<const int8_t *>(in.ptr());
         const auto out_ptr = reinterpret_cast<T *>(out.ptr());

         int x = window_start_x;
         for(; x <= (window_end_x - window_step_x); x += window_step_x)
         {
             const auto vin  = wrapper::vloadq(in_ptr + x);
             const auto vdeq = vdequantize(vin, scale);

             store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
         }

         // Compute left-over elements
         for(; x < window_end_x; ++x)
         {
             int8_t val     = *(in_ptr + x);
             *(out_ptr + x) = static_cast<T>(dequantize(val, scale));
         }
     },
     in, out);
 }

 template <typename T>
 void run_dequantization_qsymm16(const ITensor *input, ITensor *output, const Window &window)
 {
     const UniformQuantizationInfo &qinfo = input->info()->quantization_info().uniform();
     const float                    scale = qinfo.scale;

     const int  window_step_x  = 8;
     const auto window_start_x = static_cast<int>(window.x().start());
     const auto window_end_x   = static_cast<int>(window.x().end());

     // Collapse window and reset first dimension to handle tail calculations manually
     Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
     win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

     // Create iterators
     Iterator in(input, win_collapsed);
     Iterator out(output, win_collapsed);

     execute_window_loop(win_collapsed, [&](const Coordinates &)
     {
         const auto in_ptr  = reinterpret_cast<const int16_t *>(in.ptr());
         const auto out_ptr = reinterpret_cast<T *>(out.ptr());

         int x = window_start_x;
         for(; x <= (window_end_x - window_step_x); x += window_step_x)
         {
             const auto vin  = wrapper::vloadq(in_ptr + x);
             const auto vdeq = vdequantize_int16(vin, scale);

             store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
         }

         // Compute left-over elements
         for(; x < window_end_x; ++x)
         {
             int16_t val    = *(in_ptr + x);
             *(out_ptr + x) = static_cast<T>(dequantize_qsymm16(val, scale));
         }
     },
     in, out);
 }

 template <typename T>
 void run_dequantization_core(const ITensor *input, ITensor *output, const Window &window)
 {
     switch(input->info()->data_type())
     {
         case DataType::QASYMM8:
             run_dequantization_qasymm8<T>(input, output, window);
             break;
         case DataType::QSYMM8:
             run_dequantization_qsymm8<T>(input, output, window);
             break;
         case DataType::QSYMM16:
             run_dequantization_qsymm16<T>(input, output, window);
             break;
         default:
             ARM_COMPUTE_ERROR("Unsupported data type.");
     }
 }
 } // namespace

 NEDequantizationLayerKernel::NEDequantizationLayerKernel()
     : _input(nullptr), _output(nullptr)
 {
 }

 void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *output)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));

     _input  = input;
     _output = output;

     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info());

     ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));

     INEKernel::configure(std::get<1>(win_config));
 }

 Status NEDequantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
     ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
     return Status{};
 }

 void NEDequantizationLayerKernel::run(const Window &window, const ThreadInfo &info)
 {
     ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

     switch(_output->info()->data_type())
     {
         case DataType::F32:
             run_dequantization_core<float>(_input, _output, window);
             break;
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
         case DataType::F16:
             run_dequantization_core<float16_t>(_input, _output, window);
             break;
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
         default:
             ARM_COMPUTE_ERROR("Unsupported data type.");
     }
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2017-2019 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/NEON/kernels/NEDequantizationLayerKernel.h"

	#include "arm_compute/core/AccessWindowStatic.h"
	#include "arm_compute/core/CPP/Validate.h"
	#include "arm_compute/core/Error.h"
	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/NEON/NEAsymm.h"
	#include "arm_compute/core/NEON/NESymm.h"
	#include "arm_compute/core/NEON/wrapper/wrapper.h"
	#include "arm_compute/core/Utils.h"
	#include "arm_compute/core/Validate.h"
	#include "arm_compute/core/Window.h"

	#include <arm_neon.h>

	namespace arm_compute
	{
	namespace
	{
	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, DataType::QSYMM16);

	if(output->tensor_shape().total_size() > 0)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(output);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
	}

	return Status{};
	}

	std::tuple<Status, Window> validate_and_configure_window(ITensorInfo input, ITensorInfo output)
	{
	// Configure kernel window
	Window win = calculate_max_window(*input, Steps());

	// Output tensor auto initialization if not yet initialized
	auto_init_if_empty(*output, input->tensor_shape(), 1, DataType::F32);

	// NEDequantizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped
	Coordinates coord;
	coord.set_num_dimensions(output->num_dimensions());
	output->set_valid_region(ValidRegion(coord, output->tensor_shape()));

	return std::make_tuple(Status{}, win);
	}

	template <typename T>
	inline void store_result(T *ptr, const float32x4x4_t &v)
	{
	ARM_COMPUTE_UNUSED(ptr, v);
	}

	template <>
	inline void store_result<float>(float *ptr, const float32x4x4_t &v)
	{
	wrapper::vstore(ptr, v.val[0]);
	wrapper::vstore(ptr + 4, v.val[1]);
	wrapper::vstore(ptr + 8, v.val[2]);
	wrapper::vstore(ptr + 12, v.val[3]);
	}

	#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
	template <>
	inline void store_result<float16_t>(float16_t *ptr, const float32x4x4_t &v)
	{
	wrapper::vstore(ptr, vcombine_f16(vcvt_f16_f32(v.val[0]), vcvt_f16_f32(v.val[1])));
	wrapper::vstore(ptr + 8, vcombine_f16(vcvt_f16_f32(v.val[2]), vcvt_f16_f32(v.val[3])));
	}
	#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */

	template <typename T>
	inline void store_result(T *ptr, const float32x4x2_t &v)
	{
	ARM_COMPUTE_UNUSED(ptr, v);
	}

	template <>
	inline void store_result<float>(float *ptr, const float32x4x2_t &v)
	{
	wrapper::vstore(ptr, v.val[0]);
	wrapper::vstore(ptr + 4, v.val[1]);
	}

	#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
	template <>
	inline void store_result<float16_t>(float16_t *ptr, const float32x4x2_t &v)
	{
	wrapper::vstore(ptr, vcombine_f16(vcvt_f16_f32(v.val[0]), vcvt_f16_f32(v.val[1])));
	}
	#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */

	template <typename T>
	void run_dequantization_qasymm8(const ITensor input, ITensor output, const Window &window)
	{
	const UniformQuantizationInfo &qinfo = input->info()->quantization_info().uniform();
	const float scale = qinfo.scale;
	const int32_t offset = qinfo.offset;

	const int window_step_x = 16;
	const auto window_start_x = static_cast<int>(window.x().start());
	const auto window_end_x = static_cast<int>(window.x().end());

	// Collapse window and reset first dimension to handle tail calculations manually
	Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
	win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

	// Create iterators
	Iterator in(input, win_collapsed);
	Iterator out(output, win_collapsed);

	execute_window_loop(win_collapsed, [&](const Coordinates &)
	{
	const auto in_ptr = reinterpret_cast<const uint8_t *>(in.ptr());
	const auto out_ptr = reinterpret_cast<T *>(out.ptr());

	int x = window_start_x;
	for(; x <= (window_end_x - window_step_x); x += window_step_x)
	{
	const auto vin = wrapper::vloadq(in_ptr + x);
	const auto vdeq = vdequantize(vin, scale, offset);

	store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
	}

	// Compute left-over elements
	for(; x < window_end_x; ++x)
	{
	uint8_t val = *(in_ptr + x);
	*(out_ptr + x) = static_cast<T>(dequantize(val, scale, offset));
	}
	},
	in, out);
	}

	template <typename T>
	void run_dequantization_qsymm8(const ITensor input, ITensor output, const Window &window)
	{
	const UniformQuantizationInfo &qinfo = input->info()->quantization_info().uniform();
	const float scale = qinfo.scale;

	const int window_step_x = 16;
	const auto window_start_x = static_cast<int>(window.x().start());
	const auto window_end_x = static_cast<int>(window.x().end());

	// Collapse window and reset first dimension to handle tail calculations manually
	Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
	win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

	// Create iterators
	Iterator in(input, win_collapsed);
	Iterator out(output, win_collapsed);

	execute_window_loop(win_collapsed, [&](const Coordinates &)
	{
	const auto in_ptr = reinterpret_cast<const int8_t *>(in.ptr());
	const auto out_ptr = reinterpret_cast<T *>(out.ptr());

	int x = window_start_x;
	for(; x <= (window_end_x - window_step_x); x += window_step_x)
	{
	const auto vin = wrapper::vloadq(in_ptr + x);
	const auto vdeq = vdequantize(vin, scale);

	store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
	}

	// Compute left-over elements
	for(; x < window_end_x; ++x)
	{
	int8_t val = *(in_ptr + x);
	*(out_ptr + x) = static_cast<T>(dequantize(val, scale));
	}
	},
	in, out);
	}

	template <typename T>
	void run_dequantization_qsymm16(const ITensor input, ITensor output, const Window &window)
	{
	const UniformQuantizationInfo &qinfo = input->info()->quantization_info().uniform();
	const float scale = qinfo.scale;

	const int window_step_x = 8;
	const auto window_start_x = static_cast<int>(window.x().start());
	const auto window_end_x = static_cast<int>(window.x().end());

	// Collapse window and reset first dimension to handle tail calculations manually
	Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
	win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

	// Create iterators
	Iterator in(input, win_collapsed);
	Iterator out(output, win_collapsed);

	execute_window_loop(win_collapsed, [&](const Coordinates &)
	{
	const auto in_ptr = reinterpret_cast<const int16_t *>(in.ptr());
	const auto out_ptr = reinterpret_cast<T *>(out.ptr());

	int x = window_start_x;
	for(; x <= (window_end_x - window_step_x); x += window_step_x)
	{
	const auto vin = wrapper::vloadq(in_ptr + x);
	const auto vdeq = vdequantize_int16(vin, scale);

	store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
	}

	// Compute left-over elements
	for(; x < window_end_x; ++x)
	{
	int16_t val = *(in_ptr + x);
	*(out_ptr + x) = static_cast<T>(dequantize_qsymm16(val, scale));
	}
	},
	in, out);
	}

	template <typename T>
	void run_dequantization_core(const ITensor input, ITensor output, const Window &window)
	{
	switch(input->info()->data_type())
	{
	case DataType::QASYMM8:
	run_dequantization_qasymm8<T>(input, output, window);
	break;
	case DataType::QSYMM8:
	run_dequantization_qsymm8<T>(input, output, window);
	break;
	case DataType::QSYMM16:
	run_dequantization_qsymm16<T>(input, output, window);
	break;
	default:
	ARM_COMPUTE_ERROR("Unsupported data type.");
	}
	}
	} // namespace

	NEDequantizationLayerKernel::NEDequantizationLayerKernel()
	: _input(nullptr), _output(nullptr)
	{
	}

	void NEDequantizationLayerKernel::configure(const ITensor input, ITensor output)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));

	_input = input;
	_output = output;

	// Configure kernel window
	auto win_config = validate_and_configure_window(input->info(), output->info());

	ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));

	INEKernel::configure(std::get<1>(win_config));
	}

	Status NEDequantizationLayerKernel::validate(const ITensorInfo input, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
	ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
	return Status{};
	}

	void NEDequantizationLayerKernel::run(const Window &window, const ThreadInfo &info)
	{
	ARM_COMPUTE_UNUSED(info);
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);

	switch(_output->info()->data_type())
	{
	case DataType::F32:
	run_dequantization_core<float>(_input, _output, window);
	break;
	#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
	case DataType::F16:
	run_dequantization_core<float16_t>(_input, _output, window);
	break;
	#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
	default:
	ARM_COMPUTE_ERROR("Unsupported data type.");
	}
	}
	} // namespace arm_compute