diff options
Diffstat (limited to 'src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.cpp | 166 |
1 files changed, 166 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.cpp b/src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.cpp new file mode 100644 index 0000000000..187c517088 --- /dev/null +++ b/src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.cpp @@ -0,0 +1,166 @@ +/* + * Copyright (c) 2020 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/CL/kernels/CLQLSTMLayerNormalizationKernel.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" +#include "support/StringSupport.h" + +namespace arm_compute +{ +namespace +{ +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input); + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output, *input); + + const uint32_t temp_num_elems_processed_per_iteration = max_cl_vector_width / input->element_size(); + /* If width is less then step, then make step same as width to avoid global size being step instead of actual width. */ + /* Or we should fix in arm_compute::enqueue() or arm_compute::calculate_max_window(). */ + const uint32_t num_elems_processed_per_iteration = (input->dimension(0) < temp_num_elems_processed_per_iteration) ? input->dimension(0) : temp_num_elems_processed_per_iteration; + + // This kernel doesn't need padding + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape())); + + return std::make_pair(Status{}, win); +} +Status validate_arguments(const ITensorInfo *input, ITensorInfo *output, const ITensorInfo *weight, const ITensorInfo *bias) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weight, bias, output); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Input tensor cannot have more than 2 dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(weight->num_dimensions() > 1, "Weight tensor cannot have more than 1 dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->num_dimensions() > 1, "Bias tensor cannot have more than 1 dimensions"); + + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QSYMM16); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weight, 1, DataType::QSYMM16); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32); + + ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().x() != weight->tensor_shape().x()); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(weight, bias); + + // Checks performed when output is configured + if(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{}; +} +} // namespace + +CLQLSTMLayerNormalizationKernel::CLQLSTMLayerNormalizationKernel() + : _input(nullptr), _weight(nullptr), _bias(nullptr), _output(nullptr) +{ +} + +void CLQLSTMLayerNormalizationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *weight, const ICLTensor *bias) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weight, bias, output); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), weight->info(), bias->info())); + + _input = input; + _weight = weight; + _bias = bias; + _output = output; + + const uint32_t num_elems_processed_per_iteration = max_cl_vector_width / input->info()->element_size(); + + int32_t output_multiplier{}; + int32_t output_shift{}; + const UniformQuantizationInfo quan_info = _weight->info()->quantization_info().uniform(); + const Status status = quantization::calculate_quantized_multiplier(quan_info.scale, &output_multiplier, &output_shift); + output_shift *= -1; + + // Set build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); + build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0))); + build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); + build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + build_opts.add_option("-DMIN_BOUND=" + support::cpp11::to_string(std::get<0>(quantization::get_min_max_values_from_quantized_data_type(input->info()->data_type())))); + build_opts.add_option("-DMAX_BOUND=" + support::cpp11::to_string(std::get<1>(quantization::get_min_max_values_from_quantized_data_type(input->info()->data_type())))); + + // Create kernel + _kernel = create_kernel(compile_context, "qlstm_layer_normalization", build_opts.options()); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + // Set config_id for enabling LWS tuning + _config_id = "qlstm_layer_normalization_"; + _config_id += lower_string(string_from_data_type(input->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(1)); +} + +void CLQLSTMLayerNormalizationKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *weight, const ICLTensor *bias) +{ + configure(CLKernelLibrary::get().get_compile_context(), input, output, weight, bias); +} + +Status CLQLSTMLayerNormalizationKernel::validate(const ITensorInfo *input, ITensorInfo *output, const ITensorInfo *weight, const ITensorInfo *bias) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, weight, bias)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first); + return Status{}; +} + +void CLQLSTMLayerNormalizationKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window slice = window.first_slice_window_2D(); + // Set slice step equal to width to force gws[0] to 1, as each thread normalizes across all rows + slice.set_dimension_step(Window::DimX, _input->info()->dimension(0)); + + Window weight_window; + Window weight_slice; + + weight_window.use_tensor_dimensions(_weight->info()->tensor_shape()); + weight_slice = weight_window.first_slice_window_1D(); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, slice); + add_1D_tensor_argument(idx, _weight, weight_slice); + add_1D_tensor_argument(idx, _bias, weight_slice); + add_2D_tensor_argument(idx, _output, slice); + + enqueue(queue, *this, slice, lws_hint()); + } + while(window.slide_window_slice_2D(slice)); +} +} // namespace arm_compute |