diff options
Diffstat (limited to 'src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.cpp | 389 |
1 files changed, 389 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.cpp b/src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.cpp new file mode 100644 index 0000000000..40abdb1672 --- /dev/null +++ b/src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.cpp @@ -0,0 +1,389 @@ +/* + * Copyright (c) 2017 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/NEDirectConvolutionLayerOutputStageKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/NEON/NEFixedPoint.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include <arm_neon.h> +#include <cstddef> +#include <cstdint> + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::QS32, DataType::F32); + + if(bias != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::QS32, DataType::F32); + + if(is_data_type_quantized(input->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS8 && bias->data_type() != DataType::QS8, "Wrong data type for bias"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS16 && bias->data_type() != DataType::QS8, "Wrong data type for bias"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS32 && bias->data_type() != DataType::QS16, "Wrong data type for bias"); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); + } + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, bias); + ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(!is_data_type_quantized(input->data_type()), "Calling output stage kernel with floating point arguments"); + } + + // Checks performed when output is configured + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QS8, DataType::QS16, DataType::F32); + if(is_data_type_quantized(input->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS8 && output->data_type() != DataType::QS8, "Wrong data type for output"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS16 && output->data_type() != DataType::QS8, "Wrong data type for output"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QS32 && output->data_type() != DataType::QS16, "Wrong data type for output"); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); + } + + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output) +{ + bool window_changed = false; + const unsigned int num_elems_processed_per_iteration = 16 / element_size_from_data_type(input->data_type()); + + // Configure kernel window + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + + if(output != nullptr && (output->total_size() != 0)) + { + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + + if(bias == nullptr) + { + window_changed = update_window_and_padding(win, input_access, output_access); + } + else + { + AccessWindowStatic bias_access(bias, 0, 0, bias->dimension(0), bias->dimension(1)); + window_changed = update_window_and_padding(win, input_access, output_access, bias_access); + } + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + } + else + { + if(bias == nullptr) + { + window_changed = update_window_and_padding(win, input_access); + } + else + { + AccessWindowStatic bias_access(bias, 0, 0, bias->dimension(0), bias->dimension(1)); + window_changed = update_window_and_padding(win, input_access, bias_access); + } + + input_access.set_valid_region(win, ValidRegion(Coordinates(), input->tensor_shape())); + } + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} + +// Internal load +inline float32x4_t internal_vld1q(const float *in) +{ + return vld1q_f32(in); +} +inline qint8x16_t internal_vld1q(const qint8_t *in) +{ + return vld1q_qs8(in); +} +inline qint16x8_t internal_vld1q(const qint16_t *in) +{ + return vld1q_qs16(in); +} + +inline qint32x4_t internal_vld1q(const qint32_t *in) +{ + return vld1q_s32(in); +} + +// Internal store +inline void internal_vst1q(float *p, const float32x4_t &v) +{ + vst1q_f32(p, v); +} +inline void internal_vst1q(qint8_t *p, const qint8x16_t &v) +{ + vst1q_qs8(p, v); +} +inline void internal_vst1q(qint8_t *p, const qint16x8_t &v) +{ + vst1_qs8(p, vqmovn_s16(v)); +} +inline void internal_vst1q(qint16_t *p, const qint16x8_t &v) +{ + vst1q_qs16(p, v); +} + +inline void internal_vst1q(qint32_t *p, const qint32x4_t &v) +{ + vst1q_s32(p, v); +} + +inline void internal_vst1q(qint16_t *p, const qint32x4_t &v) +{ + vst1_qs16(p, vqmovn_qs32(v)); +} + +// Internal vdup +inline float32x4_t internal_vdupq_n(float v) +{ + return vdupq_n_f32(v); +} +inline qint8x16_t internal_vdupq_n(qint8_t v) +{ + return vdupq_n_qs8(v); +} +inline qint16x8_t internal_vdupq_n(qint16_t v) +{ + return vdupq_n_qs16(v); +} + +inline qint32x4_t internal_vdupq_n(qint32_t v) +{ + return vdupq_n_qs32(v); +} + +// Internal vadd +inline float32x4_t internal_vqaddq(const float32x4_t &x, const float32x4_t &y) +{ + return vaddq_f32(x, y); +} +inline qint8x16_t internal_vqaddq(const qint8x16_t &x, const qint8x16_t &y) +{ + return vqaddq_qs8(x, y); +} +inline qint16x8_t internal_vqaddq(const qint16x8_t &x, const qint16x8_t &y) +{ + return vqaddq_qs16(x, y); +} +inline qint32x4_t internal_vqaddq(const qint32x4_t &x, const qint32x4_t &y) +{ + return vqaddq_qs32(x, y); +} + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +inline float16x8_t internal_vld1q(const float16_t *in) +{ + return vld1q_f16(in); +} +inline void internal_vst1q(float16_t *p, const float16x8_t &v) +{ + vst1q_f16(p, v); +} +inline float16x8_t internal_vdupq_n(float16_t v) +{ + return vdupq_n_f16(v); +} +inline float16x8_t internal_vqaddq(const float16x8_t &x, const float16x8_t &y) +{ + return vaddq_f16(x, y); +} +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +template <typename T1, typename T2, bool in_place, bool has_bias> +void output_stage(ITensor *input, const ITensor *bias, const Window window, ITensor *output) +{ + Iterator in(input, window); + + if(in_place) // In place accumulate + { + execute_window_loop(window, [&](const Coordinates & id) + { + // Get bias and pointer to input + const auto in_ptr = reinterpret_cast<T1 *>(in.ptr()); + + // Accumulate bias + if(has_bias) + { + const auto vb = internal_vdupq_n(static_cast<T1>(*reinterpret_cast<const T2 *>(bias->ptr_to_element(Coordinates(id.z()))))); + internal_vst1q(in_ptr, internal_vqaddq(internal_vld1q(in_ptr), vb)); + } + else + { + internal_vst1q(in_ptr, internal_vld1q(in_ptr)); + } + }, + in); + } + else // Out of place accumulate + { + Iterator out(output, window); + execute_window_loop(window, [&](const Coordinates & id) + { + // Get bias and pointer to input + const auto in_ptr = reinterpret_cast<const T1 *>(in.ptr()); + const auto out_ptr = reinterpret_cast<T2 *>(out.ptr()); + + // Accumulate bias + if(has_bias) + { + const auto vb = internal_vdupq_n(static_cast<T1>(*reinterpret_cast<const T2 *>(bias->ptr_to_element(Coordinates(id.z()))))); + internal_vst1q(out_ptr, internal_vqaddq(internal_vld1q(in_ptr), vb)); + } + else + { + internal_vst1q(out_ptr, internal_vld1q(in_ptr)); + } + }, + in, out); + } +} +} // namespace + +NEDirectConvolutionLayerOutputStageKernel::NEDirectConvolutionLayerOutputStageKernel() + : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr) +{ +} + +void NEDirectConvolutionLayerOutputStageKernel::configure(ITensor *input, const ITensor *bias, ITensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input); + + // Auto-initialize output output if required + if(output != nullptr) + { + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output->info(), *input->info()); + } + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias == nullptr) ? nullptr : bias->info(), (output == nullptr) ? nullptr : output->info())); + + _func = nullptr; + _bias = bias; + _input = input; + _output = output; + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), (bias == nullptr) ? nullptr : bias->info(), (output == nullptr) ? nullptr : output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + INEKernel::configure(win_config.second); + + // Set appropriate function + switch(input->info()->data_type()) + { + case DataType::QS8: + { + if(bias == nullptr) + { + _func = (output == nullptr) ? &output_stage<qint8_t, qint8_t, true, false> : &output_stage<qint8_t, qint8_t, false, false>; + } + else + { + _func = (output == nullptr) ? &output_stage<qint8_t, qint8_t, true, true> : &output_stage<qint8_t, qint8_t, false, true>; + } + break; + } + case DataType::QS16: + { + if(bias != nullptr && bias->info()->data_type() == DataType::QS8) + { + _func = (output == nullptr) ? &output_stage<qint16_t, qint8_t, true, true> : &output_stage<qint16_t, qint8_t, false, true>; + } + else if(bias == nullptr) + { + _func = (output == nullptr) ? &output_stage<qint16_t, qint8_t, true, false> : &output_stage<qint16_t, qint8_t, false, false>; + } + else + { + ARM_COMPUTE_ERROR("Not implemented"); + } + break; + } + case DataType::QS32: + { + _func = (output == nullptr) ? &output_stage<qint32_t, qint16_t, true, true> : &output_stage<qint32_t, qint16_t, false, true>; + break; + } +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + case DataType::F16: + { + _func = (output == nullptr) ? &output_stage<float16_t, float16_t, true, true> : &output_stage<float16_t, float16_t, false, true>; + break; + } +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + case DataType::F32: + { + _func = (output == nullptr) ? &output_stage<float, float, true, true> : &output_stage<float, float, false, true>; + break; + } + default: + { + ARM_COMPUTE_ERROR("Unsupported combination of types among the inputs."); + break; + } + } +} + +Status NEDirectConvolutionLayerOutputStageKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), bias->clone().get(), output == nullptr ? nullptr : output->clone().get()).first); + + return Status{}; +} + +void NEDirectConvolutionLayerOutputStageKernel::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); + ARM_COMPUTE_ERROR_ON(_func == nullptr); + + (*_func)(_input, _bias, window, _output); +} |