diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/core/CL/cl_kernels/gemmlowp.cl | 18 | ||||
-rw-r--r-- | src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp (renamed from src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp) | 85 | ||||
-rw-r--r-- | src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp | 107 |
3 files changed, 134 insertions, 76 deletions
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl index 8e7db9326f..3fba781ede 100644 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ b/src/core/CL/cl_kernels/gemmlowp.cl @@ -2042,9 +2042,9 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC #endif // defined(K_OFFSET) #if defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) -/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 +/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8/QASYMM8_SIGNED * - * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8 value. + * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8/QASYMM8_SIGNED value. * The following computations will be performed by the kernel: * * -# Add offset terms to final result @@ -2052,11 +2052,14 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC * -# Add bias to final result (if -DADD_BIAS is passed at compile time) * -# Shift the int32 accumulator by result_shift * -# Clamp the value between the specified min and max bounds (if -DMIN_BOUND and/or -DMAX_BOUND are passed at compile time) - * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. + * -# Clamp the resulting int32 values: + * -# - to the [0..255] range and cast to QASYMM8. + * -# - to the [-128..127] range and cast to QASYMM8_SIGNED. * * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET, -RESULT_MULT_INT and -DRESULT_SHIFT * * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time + * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. * These values can be used to implement "rectified linear unit" activation functions * @@ -2072,7 +2075,7 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8 + * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) @@ -2118,13 +2121,14 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), input_values >>= RESULT_SHIFT; #endif // RESULT_SHIFT < 0 - uchar4 res = convert_uchar4_sat(input_values); + VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4) + res = CONVERT_SAT(input_values, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4)); #if defined(MIN_BOUND) - res = max(res, (uchar4)MIN_BOUND); + res = max(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MIN_BOUND); #endif // defined(MIN_BOUND) #if defined(MAX_BOUND) - res = min(res, (uchar4)MAX_BOUND); + res = min(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MAX_BOUND); #endif // defined(MAX_BOUND) // Store the result diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp index d3211f6ee8..002af6b471 100644 --- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp +++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -21,27 +21,30 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" +#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" #include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "support/StringSupport.h" -using namespace arm_compute; - namespace arm_compute { namespace { -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->output_data_type != DataType::QASYMM8) && (output_stage->output_data_type != DataType::QASYMM8_SIGNED)); + 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) @@ -53,15 +56,18 @@ 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); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() != output_stage->output_data_type, "Mismatching output data type"); 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) +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output, DataType output_data_type) { + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output, input->clone()->set_data_type(output_data_type)); + constexpr unsigned int num_elems_processed_per_iteration = 4; // Configure kernel window @@ -72,13 +78,9 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen 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())); - } + 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) { @@ -89,65 +91,59 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } -} // namespace - -class Coordinates; -} // namespace arm_compute +} //namespace -CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel() - : _input(nullptr), _bias(nullptr), _output(nullptr) +CLGEMMLowpQuantizeDownInt32ScaleKernel::CLGEMMLowpQuantizeDownInt32ScaleKernel() + : _input(nullptr), _bias(nullptr), _output(nullptr), _output_stage(nullptr) { } -Status CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) +Status CLGEMMLowpQuantizeDownInt32ScaleKernel::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 CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min, - int max) +void CLGEMMLowpQuantizeDownInt32ScaleKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage) { // Perform validate step ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(DataType::QASYMM8)); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), - min, - max)); + output_stage)); - _input = input; - _bias = bias; - _output = output; + _input = input; + _bias = bias; + _output = output; + _output_stage = output_stage; // Set the arguments to pass at compile time + auto min = output_stage->gemmlowp_min_bound; + auto max = output_stage->gemmlowp_max_bound; CLBuildOptions build_opts; - build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(result_offset)); - build_opts.add_option("-DRESULT_MULT_INT=" + support::cpp11::to_string(result_mult_int)); - build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(result_shift)); - build_opts.add_option_if((min > 0), "-DMIN_BOUND=" + support::cpp11::to_string(min)); - build_opts.add_option_if((max < 255), "-DMAX_BOUND=" + support::cpp11::to_string(max)); + build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(output_stage->gemmlowp_offset)); + build_opts.add_option("-DRESULT_MULT_INT=" + support::cpp11::to_string(output_stage->gemmlowp_multiplier)); + build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(output_stage->gemmlowp_shift)); + build_opts.add_option_if((min > std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), + "-DMIN_BOUND=" + support::cpp11::to_string(min)); + build_opts.add_option_if((max < std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), + "-DMAX_BOUND=" + support::cpp11::to_string(max)); + build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type())); build_opts.add_option_if(bias != nullptr, "-DADD_BIAS"); // Create kernel _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down", build_opts.options())); // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info()); + auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), output_stage->output_data_type); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); } -void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, cl::CommandQueue &queue) +void CLGEMMLowpQuantizeDownInt32ScaleKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); @@ -173,3 +169,4 @@ void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, cl } while(collapsed.slide_window_slice_3D(slice)); } +}
\ No newline at end of file diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp index a1b7b23c62..e86f303ff4 100644 --- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp @@ -24,25 +24,36 @@ #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" #include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.h" -#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" #include "support/MemorySupport.h" namespace arm_compute { void CLGEMMLowpQuantizeDownInt32ToUint8Scale::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel>(); - 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<CLGEMMLowpQuantizeDownInt32ScaleKernel>(); + k->configure(input, bias, output, &info); _kernel = std::move(k); } Status CLGEMMLowpQuantizeDownInt32ToUint8Scale::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) { - return CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(input, bias, output, min, max); + GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); + info.gemmlowp_min_bound = min; + info.gemmlowp_max_bound = max; + + return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); } void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, @@ -108,45 +119,91 @@ Status CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITens void CLGEMMLowpOutputStage::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_ON(info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT); - switch(info.output_data_type) + switch(info.type) { - case DataType::QASYMM8: + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); - 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); + switch(info.output_data_type) + { + case DataType::QASYMM8: + { + auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); + 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<CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); + 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; + } + default: + ARM_COMPUTE_ERROR("Unsupported output data type."); + } break; } - case DataType::QASYMM8_SIGNED: + case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); - 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); + 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; + } + } break; } default: - ARM_COMPUTE_ERROR("Unsupported output data type."); + ARM_COMPUTE_ERROR("Unsupported GEMMLowpOutputStage type."); } - } Status CLGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED); - ARM_COMPUTE_RETURN_ERROR_ON(info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT); - switch(output->data_type()) + switch(info.type) { - case DataType::QASYMM8: - return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - case DataType::QASYMM8_SIGNED: - return CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: + { + switch(output->data_type()) + { + case DataType::QASYMM8: + return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case DataType::QASYMM8_SIGNED: + return CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::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."); + } + } + 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."); + } + } default: - return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type."); } - } -} // namespace arm_compute +} // namespace arm_compute
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