diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp (renamed from src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp) | 222 | ||||
-rw-r--r-- | src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp | 34 | ||||
-rw-r--r-- | src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp | 147 |
3 files changed, 188 insertions, 215 deletions
diff --git a/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp b/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp index a68e4e7efb..80ba2aff93 100644 --- a/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp +++ b/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -21,29 +21,32 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.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/wrapper/wrapper.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include <arm_neon.h> #include <cstddef> #include <cstdint> -using namespace arm_compute; - -namespace +namespace arm_compute { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON(min > max); + + ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_max_bound > std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))); + ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_min_bound < std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) + || output_stage->gemmlowp_min_bound > output_stage->gemmlowp_max_bound); // Check biases if exist if(bias != nullptr) @@ -55,46 +58,17 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, con if(output->total_size() != 0) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); + if(output->data_type() != output_stage->output_data_type && (output_stage->output_data_type == DataType::QASYMM8 || output_stage->output_data_type == DataType::QASYMM8_SIGNED)) + { + ARM_COMPUTE_RETURN_ERROR_MSG("Mismatching data types"); + } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); } return Status{}; } -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output) -{ - // Note: This kernel performs 16 elements per iteration. - // However, since we use a left-over for loop, we cannot have any read or write out of memory - // For this reason num_elems_processed_per_iteration is set to 1 - constexpr unsigned int num_elems_processed_per_iteration = 1; - - // Configure kernel window - Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); - - AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win, - input_access); - - if(output->total_size() != 0) - { - AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, output_result_access); - - output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - } - - if(bias != nullptr) - { - AccessWindowStatic bias_access(bias, 0, 0, bias->dimension(0), bias->dimension(1)); - window_changed = window_changed || update_window_and_padding(win, bias_access); - } - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} - inline void scale_input(int32x4x4_t &in_s32, int32x4_t result_offset_s32, int32_t result_mult_int) { // Add the offset terms to GEMM's result @@ -110,23 +84,32 @@ inline void scale_input(int32x4x4_t &in_s32, int32x4_t result_offset_s32, int32_ in_s32.val[3] = vmulq_n_s32(in_s32.val[3], result_mult_int); } -template <bool is_bounded_relu> -inline uint8x16_t finalize_quantization(int32x4x4_t &in_s32, int32x4_t result_shift_s32, uint8x16_t min_u8, uint8x16_t max_u8) +template <typename T> +inline typename std::enable_if<std::is_same<T, uint8_t>::value, + typename wrapper::traits::neon_vector<T, 16>::type>::type + convert_to_8bit(const int16x8x2_t in_s16) +{ + return wrapper::vcombine(wrapper::vqmovun(in_s16.val[0]), wrapper::vqmovun(in_s16.val[1])); +} + +template <typename T> +inline typename std::enable_if<std::is_same<T, int8_t>::value, + typename wrapper::traits::neon_vector<T, 16>::type>::type + convert_to_8bit(const int16x8x2_t in_s16) { - const static int32x4_t zero_s32 = vdupq_n_s32(0); + return wrapper::vcombine(wrapper::vqmovn(in_s16.val[0]), wrapper::vqmovn(in_s16.val[1])); +} +template <typename T> +inline typename wrapper::traits::neon_vector<T, 16>::type finalize_quantization(int32x4x4_t &in_s32, int32x4_t result_shift_s32, typename wrapper::traits::neon_vector<T, 16>::type min, + typename wrapper::traits::neon_vector<T, 16>::type max) +{ // Shift final result (negative value shift right) in_s32.val[0] = vshlq_s32(in_s32.val[0], result_shift_s32); in_s32.val[1] = vshlq_s32(in_s32.val[1], result_shift_s32); in_s32.val[2] = vshlq_s32(in_s32.val[2], result_shift_s32); in_s32.val[3] = vshlq_s32(in_s32.val[3], result_shift_s32); - // Saturate negative values - in_s32.val[0] = vmaxq_s32(in_s32.val[0], zero_s32); - in_s32.val[1] = vmaxq_s32(in_s32.val[1], zero_s32); - in_s32.val[2] = vmaxq_s32(in_s32.val[2], zero_s32); - in_s32.val[3] = vmaxq_s32(in_s32.val[3], zero_s32); - // Convert S32 to S16 const int16x8x2_t in_s16 = { @@ -136,38 +119,33 @@ inline uint8x16_t finalize_quantization(int32x4x4_t &in_s32, int32x4_t result_sh } }; - // Convert S16 to U8 - uint8x16_t out_u8 = vcombine_u8(vqmovun_s16(in_s16.val[0]), vqmovun_s16(in_s16.val[1])); + // Convert S16 to S8 or U8 + typename wrapper::traits::neon_vector<T, 16>::type out = convert_to_8bit<T>(in_s16); - if(is_bounded_relu) - { - out_u8 = vmaxq_u8(out_u8, min_u8); - out_u8 = vminq_u8(out_u8, max_u8); - } + out = wrapper::vmax(out, min); + out = wrapper::vmin(out, max); - return out_u8; + return out; } -} // namespace -namespace arm_compute -{ class Coordinates; -} // namespace arm_compute -template <bool is_bounded_relu> -void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window) +template <typename T> +void NEGEMMLowpQuantizeDownInt32ScaleKernel::run(const Window &window) { - const int32x4_t result_offset_s32 = vdupq_n_s32(_result_offset); - const int32x4_t result_shift_s32 = vdupq_n_s32(-_result_shift); - const uint8x16_t min_u8 = vdupq_n_u8(static_cast<uint8_t>(_min)); - const uint8x16_t max_u8 = vdupq_n_u8(static_cast<uint8_t>(_max)); + using VectorType = typename wrapper::traits::neon_vector<T, 16>::type; - ARM_COMPUTE_UNUSED(min_u8); - ARM_COMPUTE_UNUSED(max_u8); + const int32x4_t result_offset_s32 = vdupq_n_s32(_output_stage->gemmlowp_offset); + const int32x4_t result_shift_s32 = vdupq_n_s32(-_output_stage->gemmlowp_shift); + 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()); - 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()); + const int clamp_min = (_is_bounded_relu) ? _output_stage->gemmlowp_min_bound : std::numeric_limits<T>::lowest(); + const int clamp_max = (_is_bounded_relu) ? _output_stage->gemmlowp_max_bound : std::numeric_limits<T>::max(); + + VectorType min = wrapper::vdup_n(static_cast<T>(clamp_min), wrapper::traits::vector_128_tag{}); + VectorType max = wrapper::vdup_n(static_cast<T>(clamp_max), wrapper::traits::vector_128_tag{}); Window win(window); win.set(Window::DimX, Window::Dimension(0, 1, 1)); @@ -215,9 +193,9 @@ void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window) in_s32.val[3] = vaddq_s32(in_s32.val[3], bias_s32.val[3]); // Add the offset terms to GEMM's result and multiply by result_mult_int - scale_input(in_s32, result_offset_s32, _result_mult_int); + scale_input(in_s32, result_offset_s32, _output_stage->gemmlowp_multiplier); - vst1q_u8(out.ptr() + x, finalize_quantization<is_bounded_relu>(in_s32, result_shift_s32, min_u8, max_u8)); + wrapper::vstore(reinterpret_cast<T *>(out.ptr() + x), finalize_quantization<T>(in_s32, result_shift_s32, min, max)); } // Compute left-over elements @@ -227,17 +205,10 @@ void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window) int in_value = *(reinterpret_cast<const int *>(in.ptr()) + x); // Quantize - in_value = ((in_value + bias_value + _result_offset) * _result_mult_int) >> _result_shift; + in_value = ((in_value + bias_value + _output_stage->gemmlowp_offset) * _output_stage->gemmlowp_multiplier) >> _output_stage->gemmlowp_shift; - // Finalize and store the result - if(is_bounded_relu) - { - *(out.ptr() + x) = static_cast<uint8_t>(std::max(_min, std::min(_max, in_value))); - } - else - { - *(out.ptr() + x) = static_cast<uint8_t>(std::max(0, std::min(255, in_value))); - } + // Store the result + *(out.ptr() + x) = static_cast<T>(utility::clamp<int>(in_value, clamp_min, clamp_max)); } }, in, bias, out); @@ -261,9 +232,9 @@ void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window) }; // Add the offset terms to GEMM's result and multiply by result_mult_int - scale_input(in_s32, result_offset_s32, _result_mult_int); + scale_input(in_s32, result_offset_s32, _output_stage->gemmlowp_multiplier); - vst1q_u8(out.ptr() + x, finalize_quantization<is_bounded_relu>(in_s32, result_shift_s32, min_u8, max_u8)); + wrapper::vstore(reinterpret_cast<T *>(out.ptr() + x), finalize_quantization<T>(in_s32, result_shift_s32, min, max)); } // Compute left-over elements @@ -272,74 +243,74 @@ void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window) int in_value = *(reinterpret_cast<const int *>(in.ptr()) + x); // Quantize - in_value = ((in_value + _result_offset) * _result_mult_int) >> _result_shift; + in_value = ((in_value + _output_stage->gemmlowp_offset) * _output_stage->gemmlowp_multiplier) >> _output_stage->gemmlowp_shift; - // Finalize and store the result - if(is_bounded_relu) - { - *(out.ptr() + x) = static_cast<uint8_t>(std::max(_min, std::min(_max, in_value))); - } - else - { - *(out.ptr() + x) = static_cast<uint8_t>(std::max(0, std::min(255, in_value))); - } + // Store the result + *(out.ptr() + x) = static_cast<T>(utility::clamp<int>(in_value, clamp_min, clamp_max)); } }, in, out); } } -NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel() - : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr), _result_offset(0), _result_mult_int(0), _result_shift(0), _min(0), _max(0) +NEGEMMLowpQuantizeDownInt32ScaleKernel::NEGEMMLowpQuantizeDownInt32ScaleKernel() + : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr), _output_stage(nullptr), _is_bounded_relu(false) { } -void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min, int max) +void NEGEMMLowpQuantizeDownInt32ScaleKernel::configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo *output_stage) { // Perform validate step - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, output_stage); // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(DataType::QASYMM8)); + auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(output_stage->output_data_type)); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), - min, - max)); - - _input = input; - _bias = bias; - _output = output; - _result_offset = result_offset; - _result_mult_int = result_mult_int; - _result_shift = result_shift; - _min = min; - _max = max; + output_stage)); + + _input = input; + _bias = bias; + _output = output; + _output_stage = output_stage; // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - INEKernel::configure(win_config.second); + Window win = calculate_max_window(*input->info(), Steps()); + Coordinates coord; + coord.set_num_dimensions(output->info()->num_dimensions()); + output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); + + INEKernel::configure(win); // Check if we need to clamp the result using min and max - const bool is_bounded_relu = !(min <= 0 && max >= 255); - _func = is_bounded_relu ? &NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run<true> : &NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run<false>; + _is_bounded_relu = ((_output_stage->gemmlowp_min_bound != _output_stage->gemmlowp_max_bound) + && !(_output_stage->gemmlowp_min_bound == std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) + && _output_stage->gemmlowp_max_bound == std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)))); + if(_output_stage->output_data_type == DataType::QASYMM8) + { + _func = &NEGEMMLowpQuantizeDownInt32ScaleKernel::run<uint8_t>; + } + else if(_output_stage->output_data_type == DataType::QASYMM8_SIGNED) + { + _func = &NEGEMMLowpQuantizeDownInt32ScaleKernel::run<int8_t>; + } + else + { + ARM_COMPUTE_ERROR("Data type not supported"); + } } -Status NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) +Status NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, min, max)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), - (bias != nullptr) ? bias->clone().get() : nullptr, - output->clone().get()) - .first); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, output_stage)); return Status{}; } -void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, const ThreadInfo &info) +void NEGEMMLowpQuantizeDownInt32ScaleKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); @@ -347,3 +318,4 @@ void NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, co (this->*_func)(window); } +} // namespace arm_compute
\ No newline at end of file diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp index fbd1820098..2114d39866 100644 --- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp @@ -156,22 +156,9 @@ void CLGEMMLowpOutputStage::configure(const ICLTensor *input, const ICLTensor *b } case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - switch(info.output_data_type) - { - case DataType::QASYMM8: - case DataType::QASYMM8_SIGNED: - { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleKernel>(); - k->configure(input, bias, output, &info); - _kernel = std::move(k); - break; - } - default: - { - ARM_COMPUTE_ERROR("Unsupported output data type."); - break; - } - } + auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleKernel>(); + k->configure(input, bias, output, &info); + _kernel = std::move(k); break; } case GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT: @@ -206,22 +193,9 @@ Status CLGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorIn } } case GEMMLowpOutputStageType::QUANTIZE_DOWN: - { - switch(output->data_type()) - { - case DataType::QASYMM8: - case DataType::QASYMM8_SIGNED: - { - return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); - } - default: - return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); - } - } + return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); case GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT: - { return CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel::validate(input, bias, output, &info); - } default: return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type."); } diff --git a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp index 42d2ffce58..43ca7b3fbb 100644 --- a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp @@ -24,10 +24,10 @@ #include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h" #include "arm_compute/core/ITensor.h" +#include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" -#include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" #include "arm_compute/core/Validate.h" #include "support/MemorySupport.h" @@ -35,14 +35,25 @@ namespace arm_compute { void NEGEMMLowpQuantizeDownInt32ToUint8Scale::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel>(); - k->configure(input, bias, output, result_offset, result_mult_int, result_shift, min, max); + GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); + info.gemmlowp_offset = result_offset; + info.gemmlowp_multiplier = result_mult_int; + info.gemmlowp_shift = result_shift; + info.gemmlowp_min_bound = min; + info.gemmlowp_max_bound = max; + + auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); + k->configure(input, bias, output, &info); _kernel = std::move(k); } Status NEGEMMLowpQuantizeDownInt32ToUint8Scale::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) { - return NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(input, bias, output, min, max); + GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); + info.gemmlowp_min_bound = min; + info.gemmlowp_max_bound = max; + + return NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); } void NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, @@ -89,53 +100,63 @@ void NEGEMMLowpOutputStage::configure(const ITensor *input, const ITensor *bias, ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(NEGEMMLowpOutputStage::validate(input->info(), bias != nullptr ? bias->info() : nullptr, output->info(), info)); - if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN) + switch(info.type) { - switch(output->info()->data_type()) + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: { - case DataType::QASYMM8: + switch(info.output_data_type) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel>(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); - break; + case DataType::QASYMM8: + { + auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); + k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + _kernel = std::move(k); + break; + } + case DataType::QASYMM8_SIGNED: + { + auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); + k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + _kernel = std::move(k); + break; + } + case DataType::QSYMM16: + { + auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); + k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + _kernel = std::move(k); + break; + } + default: + { + ARM_COMPUTE_ERROR("Unsupported output data type."); + break; + } } - default: - ARM_COMPUTE_ERROR("Unsupported output data type."); + break; } - } - else if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT) - { - switch(output->info()->data_type()) + case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - case DataType::QASYMM8: - { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); - break; - } - case DataType::QASYMM8_SIGNED: - { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); - break; - } - case DataType::QSYMM16: + switch(info.output_data_type) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); - break; + case DataType::QASYMM8: + case DataType::QASYMM8_SIGNED: + { + auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); + k->configure(input, bias, output, &info); + _kernel = std::move(k); + break; + } + default: + { + ARM_COMPUTE_ERROR("Unsupported output data type."); + break; + } } - default: - ARM_COMPUTE_ERROR("Unsupported output data type."); + break; } - } - else - { - ARM_COMPUTE_ERROR("Unsupported output stage quantization type."); + default: + ARM_COMPUTE_ERROR("Unsupported GEMMLowpOutputStage type."); } } @@ -147,29 +168,35 @@ Status NEGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorIn ARM_COMPUTE_RETURN_ERROR_ON((info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN) && (info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)); - if(info.type == GEMMLowpOutputStageType::QUANTIZE_DOWN) + switch(info.type) { - switch(output->data_type()) + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: { - case DataType::QASYMM8: - return NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - default: - return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + switch(output->data_type()) + { + case DataType::QASYMM8: + return NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case DataType::QASYMM8_SIGNED: + return NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case DataType::QSYMM16: + return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + default: + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + } } - } - else - { - switch(output->data_type()) + case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - case DataType::QASYMM8: - return NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - case DataType::QASYMM8_SIGNED: - return NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - case DataType::QSYMM16: - return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - default: - return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + switch(output->data_type()) + { + case DataType::QASYMM8: + case DataType::QASYMM8_SIGNED: + return NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); + default: + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + } } + default: + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type."); } } } // namespace arm_compute |