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Diffstat (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp')
-rw-r--r--src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp468
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diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
deleted file mode 100644
index fe72260e3b..0000000000
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ /dev/null
@@ -1,468 +0,0 @@
-/*
- * Copyright (c) 2018-2020 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/CLDepthwiseConvolutionLayer3x3NHWCKernel.h"
-
-#include "arm_compute/core/AccessWindowStatic.h"
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/CLKernelLibrary.h"
-#include "arm_compute/core/CL/CLValidate.h"
-#include "arm_compute/core/CL/ICLKernel.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/Error.h"
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
-#include "support/StringSupport.h"
-
-namespace arm_compute
-{
-namespace
-{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation,
- const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8 || input->data_type() == DataType::QASYMM8_SIGNED)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC),
- "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported");
- ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC
-
- ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1);
- ARM_COMPUTE_RETURN_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 4);
-
- ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
-
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
- const size_t weights_width = 3;
- const size_t weights_height = 3;
-
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
- *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
- if(is_qasymm)
- {
- DepthwiseConvolutionReshapeInfo info;
- info.c0 = 4;
- ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(0) / info.c0) != weights_width * weights_height);
-
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32);
- ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1);
- ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1);
-
- if(is_data_type_quantized_per_channel(weights->data_type()))
- {
- ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_multipliers->dimension(0));
- ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_shifts->dimension(0));
- }
- else
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
- ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0));
- ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0));
- }
- }
- else
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
- ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height));
- }
-
- if(biases != nullptr)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[0]);
- if(is_qasymm)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32);
- }
- else
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases);
- }
-
- ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1);
- }
-
- if(output->total_size() != 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
- }
-
- return Status{};
-}
-
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
- ITensorInfo *output_multipliers, ITensorInfo *output_shifts)
-{
- const size_t weights_width = 3;
- const size_t weights_height = 3;
-
- // Get convolved dimensions
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
- *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
-
- auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_quantization_info(output->quantization_info()));
-
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
- const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1);
-
- const unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
- const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : (8 / input->element_size());
- const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2;
- const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast<float>(conv_info.stride().first));
-
- BorderSize border_size;
- border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
-
- // Configure kernel window
- Window win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration));
-
- AccessWindowStatic input_access(input, 0, -border_size.top, ceil_to_multiple(input->dimension(0), num_elems_accessed_per_iteration),
- ceil_to_multiple(input->dimension(1) + border_size.bottom, num_rows_read_per_iteration));
- AccessWindowRectangle output_access(output, 0, 0, num_elems_accessed_per_iteration, num_rows_written_per_iteration);
-
- bool window_changed = false;
-
- if(is_qasymm)
- {
- if((output_multipliers != nullptr) && (output_shifts != nullptr))
- {
- AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, num_elems_accessed_per_iteration);
- AccessWindowHorizontal output_shifts_access(output_shifts, 0, num_elems_accessed_per_iteration);
- window_changed = window_changed || update_window_and_padding(win, input_access, output_access, output_multipliers_access, output_shifts_access);
- }
- else
- {
- Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input");
- return std::make_pair(err, win);
- }
- }
- else
- {
- AccessWindowStatic weights_access(weights, 0, 0, ceil_to_multiple(weights->dimension(0), num_elems_accessed_per_iteration), weights->dimension(1));
- window_changed = update_window_and_padding(win, input_access, weights_access, output_access);
- }
-
- if(bias != nullptr)
- {
- AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration);
- window_changed = window_changed || update_window_and_padding(win, bias_access);
- }
- output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
-
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
- return std::make_pair(err, win);
-}
-} // namespace
-
-CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel()
- : _num_rows_processed_per_iteration(1), _num_planes_processed_per_iteration(1)
-{
-}
-
-BorderSize CLDepthwiseConvolutionLayer3x3NHWCKernel::border_size() const
-{
- return _border_size;
-}
-
-void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
- const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
-{
- configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts);
-}
-
-void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
- const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
- conv_info, depth_multiplier, act_info, dilation,
- (output_multipliers != nullptr) ? output_multipliers->info() : nullptr,
- (output_shifts != nullptr) ? output_shifts->info() : nullptr));
- auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(),
- conv_info, depth_multiplier, dilation,
- (output_multipliers != nullptr) ? output_multipliers->info() : nullptr,
- (output_shifts != nullptr) ? output_shifts->info() : nullptr);
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-
- const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
- const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1);
-
- const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type());
- const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel;
-
- _input = input;
- _output = output;
- _weights = weights;
- _biases = biases;
- _conv_stride_y = conv_info.stride().second;
- _num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
- _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
- _output_multipliers = output_multipliers;
- _output_shifts = output_shifts;
- _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
-
- // If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1
- if(is_dot8_supported && _is_quantized)
- {
- _num_planes_processed_per_iteration = 1;
- }
-
- _border_size = BorderSize(_is_quantized && is_stride_1 ? 0 : conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
-
- const unsigned int num_elems_accessed_per_iteration = _is_quantized ? 4 : (8 / input->info()->element_size());
-
- CLBuildOptions build_opts;
- build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation())));
- build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
- build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration));
- build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
- build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
- build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
- build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
- build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
-
- if(_is_quantized)
- {
- const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform();
- const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform();
- const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform();
-
- build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
- build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset));
- build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset));
- build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset));
- build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset));
- build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION");
- build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8");
-
- // Compute non-per-channel multiplier and shift anyway to make OpenCL kernel simpler
- float multiplier = iq_info.scale * wq_info.scale / oq_info.scale;
- int output_multiplier = 0;
- int output_shift = 0;
- quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
- build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
- build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
-
- if(act_info.enabled())
- {
- const int a_val = quantize_qasymm8(act_info.a(), oq_info);
- const int b_val = quantize_qasymm8(act_info.b(), oq_info);
- const int o1 = oq_info.offset;
-
- build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val));
- build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val));
- build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1));
-
- const float s1 = iq_info.scale;
- build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1));
- build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1));
- }
-
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
- build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type()));
- build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type()));
- }
- else
- {
- build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a()));
- build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b()));
- build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type()));
- }
-
- if(is_stride_1_dilation_1)
- {
- build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(_num_rows_processed_per_iteration));
- build_opts.add_option("-DNUM_PLANES_PROCESSED=" + support::cpp11::to_string(_num_planes_processed_per_iteration));
- build_opts.add_option("-DDST_DIM_2=" + support::cpp11::to_string(_output->info()->dimension(2)));
- }
- else
- {
- build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_info.stride().first));
- build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y));
- }
- build_opts.add_option_if(_input->info()->tensor_shape().total_size_upper(3) > 1,
- "-DDST_DEPTH=" + support::cpp11::to_string(static_cast<int>(std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration)))));
-
- std::string kernel_name;
- // Create kernel
- if(_is_quantized)
- {
- kernel_name = std::string("dwc_3x3_reshaped_quantized8");
- kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : "");
- kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
- kernel_name += "_nhwc";
- }
- else
- {
- kernel_name = std::string("depthwise_convolution_3x3_nhwc");
- kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
- }
-
- build_opts.add_option_if(input->info()->data_type() == DataType::F16, "-DIS_F16");
- build_opts.add_option_if(input->info()->data_type() == DataType::F32, "-DIS_F32");
-
- ICLKernel::configure_internal(win_config.second);
- _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
-
- // Set config_id for enabling LWS tuning
- _config_id = kernel_name;
- _config_id += "_";
- _config_id += support::cpp11::to_string(input->info()->dimension(0));
- _config_id += "_";
- _config_id += support::cpp11::to_string(input->info()->dimension(1));
- _config_id += "_";
- _config_id += support::cpp11::to_string(input->info()->dimension(2));
- _config_id += "_";
- _config_id += support::cpp11::to_string(output->info()->dimension(0));
- _config_id += "_";
- _config_id += support::cpp11::to_string(output->info()->dimension(1));
- _config_id += "_";
- _config_id += string_from_data_type(input->info()->data_type());
-}
-
-Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
- const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
-{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(),
- biases != nullptr ? biases->clone().get() : nullptr,
- output->clone().get(), conv_info, depth_multiplier, dilation,
- (output_multipliers != nullptr) ? output_multipliers->clone().get() : nullptr,
- (output_shifts != nullptr) ? output_shifts->clone().get() : nullptr)
- .first);
-
- return Status{};
-}
-
-void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::CommandQueue &queue)
-{
- ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
-
- // Collapse window
- Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
- const size_t total_batches = _input->info()->tensor_shape().total_size_upper(3);
-
- Window win = window_collapsed;
- win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration)) * total_batches, 1));
-
- // Create input window and adjust
- Window win_in = win;
- win_in.set_dimension_step(Window::DimY, _num_rows_processed_per_iteration);
- win_in.set_dimension_step(Window::DimZ, _conv_stride_y);
-
- ARM_COMPUTE_ERROR_ON((win_in.y().step() < window.y().step()) || (win_in.z().step() < window.z().step()));
-
- Window slice_in = win_in.first_slice_window_4D();
- Window slice_out = win.first_slice_window_4D();
-
- unsigned int idx = 2 * num_arguments_per_4D_tensor() + (_is_quantized ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor());
-
- if(_is_quantized)
- {
- Window slice;
- slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape());
- slice.set_dimension_step(Window::DimX, window.x().step());
- add_1D_tensor_argument(idx, _output_multipliers, slice);
- add_1D_tensor_argument(idx, _output_shifts, slice);
- }
-
- if(_biases != nullptr)
- {
- Window win_biases;
- win_biases.use_tensor_dimensions(_biases->info()->tensor_shape());
- win_biases.set_dimension_step(Window::DimX, window.x().step());
- add_1D_tensor_argument(idx, _biases, win_biases);
- }
-
- // Calculate the max_offset.
- // max_offset is the offset for the last NOT valid value in the Z dimension (spatial dimension Y for NHWC)
- // |******************|
- // | pad_top |
- // |******************|
- // | |
- // | plane0 |
- // | batch0 |
- // |__________________|
- // |******************| Batch 0
- // | pad_bottom |
- // | pad_top |
- // |******************|
- // | |
- // | plane1 |
- // | batch0 |
- // |__________________|-----> max_offset
- // |******************|
- // | pad_bottom |
- // | pad_top |
- // |******************|
- // | |
- // | plane0 |
- // | batch1 |
- // |__________________|
- // |******************| Batch 1
- // | pad_bottom |
- // | pad_top |
- // |******************|
- // | |
- // | plane1 |
- // | batch1 |
- // |__________________|
- // | pad_bottom |
- // |******************|
- const int max_offset = _input->info()->strides_in_bytes().z() * _input->info()->dimension(2) - (_input->info()->padding().bottom + _input->info()->padding().top) *
- _input->info()->strides_in_bytes().y();
- _kernel.setArg(idx, max_offset);
-
- do
- {
- unsigned int idx = 0;
- add_4D_tensor_argument(idx, _input, slice_in);
- add_4D_tensor_argument(idx, _output, slice_out);
- if(_is_quantized)
- {
- add_2D_tensor_argument(idx, _weights, slice_out);
- }
- else
- {
- add_3D_tensor_argument(idx, _weights, slice_out);
- }
- enqueue(queue, *this, slice_out, lws_hint());
- }
- while(win.slide_window_slice_4D(slice_out) && win_in.slide_window_slice_4D(slice_in));
-}
-} // namespace arm_compute