diff options
Diffstat (limited to 'src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp | 481 |
1 files changed, 0 insertions, 481 deletions
diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp deleted file mode 100644 index c68c526ec9..0000000000 --- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp +++ /dev/null @@ -1,481 +0,0 @@ -/* - * Copyright (c) 2016-2020 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 "src/core/CL/kernels/CLPixelWiseMultiplicationKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/CL/OpenCL.h" -#include "arm_compute/core/TensorInfo.h" -#include "src/core/CL/CLValidate.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" -#include "support/Cast.h" -#include "support/StringSupport.h" - -namespace arm_compute -{ -namespace -{ -constexpr unsigned int num_elems_processed_per_iteration = 16; - -Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_UNUSED(overflow_policy); - ARM_COMPUTE_UNUSED(rounding_policy); - - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, - 1, - DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, - DataType::S16, DataType::QSYMM16, DataType::F16, - DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, - 1, - DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, - DataType::S16, DataType::QSYMM16, DataType::F16, - DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(scale < 0, "Scale cannot be negative."); - ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type())); - - const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - // Validate in case of configured output - if(output->total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, - 1, - DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, - DataType::S16, DataType::QSYMM16, DataType::F16, - DataType::S32, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), - "Output can only be U8 if both inputs are U8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QASYMM8 && (input1->data_type() != DataType::QASYMM8 || input2->data_type() != DataType::QASYMM8), - "Output can only be QASYMM8 if both inputs are QASYMM8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QASYMM8_SIGNED && (input1->data_type() != DataType::QASYMM8_SIGNED || input2->data_type() != DataType::QASYMM8_SIGNED), - "Output can only be QASYMM8_SIGNED if both inputs are QASYMM8_SIGNED"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QSYMM16 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16), - "Output can only be QSYMM16 if both inputs are QSYMM16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::S32 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16), - "Output can only be S32 if both inputs are QSYMM16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output"); - } - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - - // Auto initialize output if not initialized - { - set_shape_if_empty(*output, out_shape); - - if(input1->data_type() == DataType::S16 || input2->data_type() == DataType::S16) - { - set_format_if_unknown(*output, Format::S16); - } - else if(input1->data_type() == DataType::F32 || input2->data_type() == DataType::F32) - { - set_format_if_unknown(*output, Format::F32); - } - else if(input1->data_type() == DataType::QASYMM8) - { - set_data_type_if_unknown(*output, DataType::QASYMM8); - } - else if(input1->data_type() == DataType::QASYMM8_SIGNED) - { - set_data_type_if_unknown(*output, DataType::QASYMM8_SIGNED); - } - else if(input1->data_type() == DataType::QSYMM16) - { - set_data_type_if_unknown(*output, DataType::QSYMM16); - } - } - - Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration)); - Window win_input1 = win.broadcast_if_dimension_le_one(*input1); - Window win_input2 = win.broadcast_if_dimension_le_one(*input2); - - AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win_input1, input1_access) - || update_window_and_padding(win_input2, input2_access) - || update_window_and_padding(win, output_access); - - output_access.set_valid_region(win, valid_region); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -CLPixelWiseMultiplicationKernel::CLPixelWiseMultiplicationKernel() - : _input1(nullptr), _input2(nullptr), _output(nullptr) -{ -} - -void CLPixelWiseMultiplicationKernel::configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, scale, overflow_policy, rounding_policy, act_info); -} - -void CLPixelWiseMultiplicationKernel::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1, input2, output, - scale, overflow_policy, rounding_policy, act_info)); - - // Configure kernel window - auto win_config = validate_and_configure_window(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - _input1 = input1; - _input2 = input2; - _output = output; - - int scale_int = -1; - // Extract sign, exponent and mantissa - int exponent = 0; - float normalized_mantissa = std::frexp(scale, &exponent); - // Use int scaling if factor is equal to 1/2^n for 0 <= n <= 15 - // frexp returns 0.5 as mantissa which means that the exponent will be in the range of -1 <= e <= 14 - // Moreover, it will be negative as we deal with 1/2^n - if((normalized_mantissa == 0.5f) && (-14 <= exponent) && (exponent <= 1)) - { - // Store the positive exponent. We know that we compute 1/2^n - // Additionally we need to subtract 1 to compensate that frexp used a mantissa of 0.5 - scale_int = std::abs(exponent - 1); - } - - std::string acc_type; - // Check if it has float inputs and output - if(is_data_type_float(input1->data_type()) || is_data_type_float(input2->data_type())) - { - scale_int = -1; - acc_type = (input1->data_type() == DataType::F32 || input2->data_type() == DataType::F32) ? "float" : "half"; - } - else - { - if(input1->element_size() == 2 || input2->element_size() == 2) - { - // Use 32-bit accumulator for 16-bit input - acc_type = "int"; - } - else - { - // Use 16-bit accumulator for 8-bit input - acc_type = "ushort"; - } - } - - const bool is_quantized = is_data_type_quantized(input1->data_type()); - - // Set kernel build options - std::string kernel_name = "pixelwise_mul"; - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->data_type())); - build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->data_type())); - build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->data_type())); - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); - if(is_quantized && (output->data_type() != DataType::S32)) - { - const UniformQuantizationInfo iq1_info = input1->quantization_info().uniform(); - const UniformQuantizationInfo iq2_info = input2->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = output->quantization_info().uniform(); - - build_opts.add_option_if(is_data_type_quantized_asymmetric(input1->data_type()), - "-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset)); - build_opts.add_option_if(is_data_type_quantized_asymmetric(input2->data_type()), - "-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset)); - build_opts.add_option_if(is_data_type_quantized_asymmetric(output->data_type()), - "-DOFFSET_OUT=" + support::cpp11::to_string(oq_info.offset)); - build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale)); - build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale)); - build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale)); - kernel_name += "_quantized"; - } - else - { - kernel_name += (scale_int >= 0) ? "_int" : "_float"; - build_opts.add_option_if_else(overflow_policy == ConvertPolicy::WRAP || is_data_type_float(output->data_type()), "-DWRAP", "-DSATURATE"); - build_opts.add_option_if_else(rounding_policy == RoundingPolicy::TO_ZERO, "-DROUND=_rtz", "-DROUND=_rte"); - build_opts.add_option("-DACC_DATA_TYPE=" + acc_type); - if(act_info.enabled()) - { - build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); - build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - } - } - - // Create kernel - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - // Set scale argument - unsigned int idx = 3 * num_arguments_per_3D_tensor(); // Skip the inputs and output parameters - - if(scale_int >= 0 && !is_quantized) - { - _kernel.setArg(idx++, scale_int); - } - else - { - _kernel.setArg(idx++, scale); - } - - ICLKernel::configure_internal(win_config.second); -} - -Status CLPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, scale, overflow_policy, rounding_policy, act_info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first); - - return Status{}; -} - -void CLPixelWiseMultiplicationKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - const auto src_0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0)); - const auto src_1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1)); - auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); - - const TensorShape &in_shape1 = src_0->info()->tensor_shape(); - const TensorShape &in_shape2 = src_1->info()->tensor_shape(); - const TensorShape &out_shape = dst->info()->tensor_shape(); - - bool can_collapse = true; - if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1) - { - can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ); - for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); ++d) - { - can_collapse = (in_shape1[d] == in_shape2[d]); - } - } - - bool has_collapsed = false; - Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window; - - const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1; - const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2; - - Window slice = collapsed.first_slice_window_3D(); - Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed); - Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed); - - do - { - unsigned int idx = 0; - add_3D_tensor_argument(idx, src_0, slice_input1); - add_3D_tensor_argument(idx, src_1, slice_input2); - add_3D_tensor_argument(idx, dst, slice); - enqueue(queue, *this, slice, lws_hint()); - - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - } - while(collapsed.slide_window_slice_3D(slice)); -} - -BorderSize CLPixelWiseMultiplicationKernel::border_size() const -{ - const unsigned int replicateSize = _output->dimension(0) - std::min(_input1->dimension(0), _input2->dimension(0)); - const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize); - return BorderSize{ 0, border, 0, 0 }; -} - -namespace -{ -constexpr unsigned int num_elems_processed_per_iteration_complex = 1; - -Status validate_arguments_complex(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2); - - const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - ARM_COMPUTE_RETURN_ERROR_ON(act_info.enabled() && !is_data_type_float(output->data_type())); - - // Validate in case of configured output - if(output->total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, output); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output"); - } - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window_complex(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - - // Auto initialize output if not initialized - const TensorInfo out_info(out_shape, input1->num_channels(), input1->data_type()); - auto_init_if_empty(*output, out_info); - - Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration_complex)); - Window win_input1 = win.broadcast_if_dimension_le_one(*input1); - Window win_input2 = win.broadcast_if_dimension_le_one(*input2); - - AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration_complex); - AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration_complex); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration_complex); - - bool window_changed = update_window_and_padding(win_input1, input1_access) - || update_window_and_padding(win_input2, input2_access) - || update_window_and_padding(win, output_access); - - output_access.set_valid_region(win, valid_region); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -CLComplexPixelWiseMultiplicationKernel::CLComplexPixelWiseMultiplicationKernel() - : _input1(nullptr), _input2(nullptr), _output(nullptr) -{ -} - -void CLComplexPixelWiseMultiplicationKernel::configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); -} - -void CLComplexPixelWiseMultiplicationKernel::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(input1, input2, output, act_info)); - - // Configure kernel window - auto win_config = validate_and_configure_window_complex(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - _input1 = input1; - _input2 = input2; - _output = output; - - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_output->data_type())); - if(act_info.enabled()) - { - build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option("-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); - build_opts.add_option("-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - } - - // Create kernel - _kernel = create_kernel(compile_context, "pixelwise_mul_complex", build_opts.options()); - - ICLKernel::configure_internal(win_config.second); -} - -Status CLComplexPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_complex(input1, input2, output, act_info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_complex(input1->clone().get(), input2->clone().get(), output->clone().get()).first); - - return Status{}; -} - -void CLComplexPixelWiseMultiplicationKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - const auto src_0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0)); - const auto src_1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1)); - auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); - - const TensorShape &in_shape1 = src_0->info()->tensor_shape(); - const TensorShape &in_shape2 = src_1->info()->tensor_shape(); - const TensorShape &out_shape = dst->info()->tensor_shape(); - - bool can_collapse = true; - if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1) - { - can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ); - for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); ++d) - { - can_collapse = (in_shape1[d] == in_shape2[d]); - } - } - - bool has_collapsed = false; - Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window; - - const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1; - const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2; - - Window slice = collapsed.first_slice_window_3D(); - Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed); - Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed); - - do - { - unsigned int idx = 0; - add_3D_tensor_argument(idx, src_0, slice_input1); - add_3D_tensor_argument(idx, src_1, slice_input2); - add_3D_tensor_argument(idx, dst, slice); - enqueue(queue, *this, slice, lws_hint()); - - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - } - while(collapsed.slide_window_slice_3D(slice)); -} - -BorderSize CLComplexPixelWiseMultiplicationKernel::border_size() const -{ - const unsigned int replicateSize = _output->dimension(0) - std::min(_input1->dimension(0), _input2->dimension(0)); - const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration_complex - 1U, replicateSize); - return BorderSize{ 0, border, 0, 0 }; -} -} // namespace arm_compute |