From 0dc0d8eda87a01c11f9caabc0d2f2933737ba469 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Fri, 30 Apr 2021 03:18:37 +0100 Subject: Rename PixelwiseMultiplications to Mul for simplicity Changes the names of the following: - PixelWiseMultiplicationKernel to MulKernel for all backends - PixelWiseMultiplication to Mul for all backends Signed-off-by: Georgios Pinitas Change-Id: I88108c2d22c888fce37ea1028863026160b9da97 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5534 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Comments-Addressed: Arm Jenkins --- src/core/gpu/cl/kernels/ClMulKernel.cpp | 398 +++++++++++++++++++++ src/core/gpu/cl/kernels/ClMulKernel.h | 115 ++++++ .../cl/kernels/ClPixelWiseMultiplicationKernel.cpp | 398 --------------------- .../cl/kernels/ClPixelWiseMultiplicationKernel.h | 139 ------- 4 files changed, 513 insertions(+), 537 deletions(-) create mode 100644 src/core/gpu/cl/kernels/ClMulKernel.cpp create mode 100644 src/core/gpu/cl/kernels/ClMulKernel.h delete mode 100644 src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.cpp delete mode 100644 src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.h (limited to 'src/core/gpu/cl') diff --git a/src/core/gpu/cl/kernels/ClMulKernel.cpp b/src/core/gpu/cl/kernels/ClMulKernel.cpp new file mode 100644 index 0000000000..837324ede2 --- /dev/null +++ b/src/core/gpu/cl/kernels/ClMulKernel.cpp @@ -0,0 +1,398 @@ +/* + * Copyright (c) 2016-2021 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/gpu/cl/kernels/ClMulKernel.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 opencl +{ +namespace kernels +{ +namespace +{ +Status validate_arguments(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, 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(src1, src2, dst); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src1, + 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(src2, + 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(dst->data_type())); + + const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); + + // Validate in case of configured dst + if(dst->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, + 1, + DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, + DataType::S16, DataType::QSYMM16, DataType::F16, + DataType::S32, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::U8 && (src1->data_type() != DataType::U8 || src2->data_type() != DataType::U8), + "Dst can only be U8 if both src are U8"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QASYMM8 && (src1->data_type() != DataType::QASYMM8 || src2->data_type() != DataType::QASYMM8), + "Dst can only be QASYMM8 if both src are QASYMM8"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QASYMM8_SIGNED && (src1->data_type() != DataType::QASYMM8_SIGNED || src2->data_type() != DataType::QASYMM8_SIGNED), + "Dst can only be QASYMM8_SIGNED if both src are QASYMM8_SIGNED"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QSYMM16 && (src1->data_type() != DataType::QSYMM16 || src2->data_type() != DataType::QSYMM16), + "Dst can only be QSYMM16 if both src are QSYMM16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::S32 && (src1->data_type() != DataType::QSYMM16 || src2->data_type() != DataType::QSYMM16), + "Dst can only be S32 if both src are QSYMM16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst"); + } + + return Status{}; +} +} // namespace + +void ClMulKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src1, src2, dst, + scale, overflow_policy, rounding_policy, act_info)); + + auto padding_info = get_padding_info({ src1, src2, dst }); + + const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); + auto_init_if_empty(*dst, src1->clone()->set_tensor_shape(out_shape)); + + 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 src and dst + if(is_data_type_float(src1->data_type()) || is_data_type_float(src2->data_type())) + { + scale_int = -1; + acc_type = (src1->data_type() == DataType::F32 || src2->data_type() == DataType::F32) ? "float" : "half"; + } + else + { + if(src1->element_size() == 2 || src2->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(src1->data_type()); + const unsigned int vec_size = adjust_vec_size(16 / dst->element_size(), dst->dimension(0)); + const unsigned int vec_size_leftover = dst->dimension(0) % vec_size; + + // 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(src1->data_type())); + build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(src2->data_type())); + build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(dst->data_type())); + build_opts.add_option("-DVEC_SIZE_IN1=" + ((dst->dimension(0) != 1 && src1->dimension(0) == 1) ? "1" : support::cpp11::to_string(vec_size))); + build_opts.add_option("-DVEC_SIZE_IN2=" + ((dst->dimension(0) != 1 && src2->dimension(0) == 1) ? "1" : support::cpp11::to_string(vec_size))); + build_opts.add_option("-DVEC_SIZE_OUT=" + support::cpp11::to_string(vec_size)); + build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover)); + if(is_quantized && (dst->data_type() != DataType::S32)) + { + const UniformQuantizationInfo iq1_info = src1->quantization_info().uniform(); + const UniformQuantizationInfo iq2_info = src2->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); + + build_opts.add_option_if(is_data_type_quantized_asymmetric(src1->data_type()), + "-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset)); + build_opts.add_option_if(is_data_type_quantized_asymmetric(src2->data_type()), + "-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset)); + build_opts.add_option_if(is_data_type_quantized_asymmetric(dst->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(dst->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 src and dst parameters + + if(scale_int >= 0 && !is_quantized) + { + _kernel.setArg(idx++, scale_int); + } + else + { + _kernel.setArg(idx++, scale); + } + + Window win = calculate_max_window(*dst, Steps(vec_size)); + ICLKernel::configure_internal(win); + + ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); + + // Set config_id for enabling LWS tuning + _config_id = kernel_name; + _config_id += "_"; + _config_id += lower_string(string_from_data_type(dst->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(src1->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src1->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src1->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src2->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src2->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(src2->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(2)); +} + +Status ClMulKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src1, src2, dst, scale, overflow_policy, rounding_policy, act_info)); + + return Status{}; +} + +void ClMulKernel::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(tensors.get_const_tensor(TensorType::ACL_SRC_0)); + const auto src_1 = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_SRC_1)); + auto dst = utils::cast::polymorphic_downcast(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)); +} + +namespace +{ +constexpr unsigned int vec_size_complex = 1; + +Status validate_arguments_complex(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src1, 2, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src2, 2, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2); + + const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->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(dst->data_type())); + + // Validate in case of configured dst + if(dst->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 2, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, dst); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst"); + } + + return Status{}; +} +} // namespace + +void ClComplexMulKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(src1, src2, dst, act_info)); + + auto padding_info = get_padding_info({ src1, src2, dst }); + + const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); + auto_init_if_empty(*dst, src1->clone()->set_tensor_shape(out_shape)); + + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dst->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()); + + Window win = calculate_max_window(*dst, Steps(vec_size_complex)); + ICLKernel::configure_internal(win); + + ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); +} + +Status ClComplexMulKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_complex(src1, src2, dst, act_info)); + + return Status{}; +} + +void ClComplexMulKernel::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(tensors.get_const_tensor(TensorType::ACL_SRC_0)); + const auto src_1 = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_SRC_1)); + auto dst = utils::cast::polymorphic_downcast(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)); +} +} // namespace kernels +} // namespace opencl +} // namespace arm_compute diff --git a/src/core/gpu/cl/kernels/ClMulKernel.h b/src/core/gpu/cl/kernels/ClMulKernel.h new file mode 100644 index 0000000000..e2e54a836e --- /dev/null +++ b/src/core/gpu/cl/kernels/ClMulKernel.h @@ -0,0 +1,115 @@ +/* + * Copyright (c) 2016-2021 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. + */ +#ifndef ARM_COMPUTE_CL_MUL_KERNEL_H +#define ARM_COMPUTE_CL_MUL_KERNEL_H + +#include "src/core/common/Macros.h" +#include "src/core/gpu/cl/ClCompileContext.h" +#include "src/core/gpu/cl/IClKernel.h" + +namespace arm_compute +{ +namespace opencl +{ +namespace kernels +{ +/** Interface for the pixelwise multiplication kernel. */ +class ClMulKernel : public IClKernel +{ +public: + /** Default constructor */ + ClMulKernel() = default; + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClMulKernel); + /** Initialise the kernel's src and dst. + * + * Valid configurations (Input1,Input2) -> Output : + * + * - (U8,U8) -> U8 + * - (U8,U8) -> S16 + * - (U8,S16) -> S16 + * - (S16,U8) -> S16 + * - (S16,S16) -> S16 + * - (F16,F16) -> F16 + * - (F32,F32) -> F32 + * - (QASYMM8,QASYMM8) -> QASYMM8 + * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED + * - (QSYMM16,QSYMM16) -> QSYMM16 + * - (QSYMM16,QSYMM16) -> S32 + * + * @param[in] compile_context The compile context to be used. + * @param[in] src1 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. + * @param[in] src2 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. + * @param[out] dst The dst tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. + * @param[in] scale Scale to apply after multiplication. + * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. + * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate + * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + */ + void configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo()); + /** Static function to check if given info will lead to a valid configuration + * + * Similar to @ref ClMulKernel::configure() + * + * @return a status + */ + static Status validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float scale, + ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo()); + + // Inherited methods overridden: + void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; +}; + +/** Interface for the complex pixelwise multiplication kernel. */ +class ClComplexMulKernel : public ICLKernel +{ +public: + /** Default constructor */ + ClComplexMulKernel() = default; + ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClComplexMulKernel); + /** Initialise the kernel's src and dst. + * + * @param[in] compile_context The compile context to be used. + * @param[in] src1 An src tensor info. Data types supported: F32. Number of channels supported: 2. + * @param[in] src2 An src tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. + * @param[out] dst The dst tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + */ + void configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo()); + /** Static function to check if given info will lead to a valid configuration + * + * Similar to @ref ClComplexMulKernel::configure() + * + * @return a status + */ + static Status validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo()); + + // Inherited methods overridden: + void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; +}; +} // namespace kernels +} // namespace opencl +} // namespace arm_compute +#endif /* ARM_COMPUTE_CL_MUL_KERNEL_H */ diff --git a/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.cpp b/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.cpp deleted file mode 100644 index 5aed824d2c..0000000000 --- a/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.cpp +++ /dev/null @@ -1,398 +0,0 @@ -/* - * Copyright (c) 2016-2021 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/gpu/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 opencl -{ -namespace kernels -{ -namespace -{ -Status validate_arguments(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, 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(src1, src2, dst); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src1, - 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(src2, - 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(dst->data_type())); - - const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - // Validate in case of configured dst - if(dst->total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, - 1, - DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, - DataType::S16, DataType::QSYMM16, DataType::F16, - DataType::S32, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::U8 && (src1->data_type() != DataType::U8 || src2->data_type() != DataType::U8), - "Dst can only be U8 if both src are U8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QASYMM8 && (src1->data_type() != DataType::QASYMM8 || src2->data_type() != DataType::QASYMM8), - "Dst can only be QASYMM8 if both src are QASYMM8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QASYMM8_SIGNED && (src1->data_type() != DataType::QASYMM8_SIGNED || src2->data_type() != DataType::QASYMM8_SIGNED), - "Dst can only be QASYMM8_SIGNED if both src are QASYMM8_SIGNED"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::QSYMM16 && (src1->data_type() != DataType::QSYMM16 || src2->data_type() != DataType::QSYMM16), - "Dst can only be QSYMM16 if both src are QSYMM16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() == DataType::S32 && (src1->data_type() != DataType::QSYMM16 || src2->data_type() != DataType::QSYMM16), - "Dst can only be S32 if both src are QSYMM16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst"); - } - - return Status{}; -} -} // namespace - -void ClPixelWiseMultiplicationKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src1, src2, dst, - scale, overflow_policy, rounding_policy, act_info)); - - auto padding_info = get_padding_info({ src1, src2, dst }); - - const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); - auto_init_if_empty(*dst, src1->clone()->set_tensor_shape(out_shape)); - - 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 src and dst - if(is_data_type_float(src1->data_type()) || is_data_type_float(src2->data_type())) - { - scale_int = -1; - acc_type = (src1->data_type() == DataType::F32 || src2->data_type() == DataType::F32) ? "float" : "half"; - } - else - { - if(src1->element_size() == 2 || src2->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(src1->data_type()); - const unsigned int vec_size = adjust_vec_size(16 / dst->element_size(), dst->dimension(0)); - const unsigned int vec_size_leftover = dst->dimension(0) % vec_size; - - // 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(src1->data_type())); - build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(src2->data_type())); - build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(dst->data_type())); - build_opts.add_option("-DVEC_SIZE_IN1=" + ((dst->dimension(0) != 1 && src1->dimension(0) == 1) ? "1" : support::cpp11::to_string(vec_size))); - build_opts.add_option("-DVEC_SIZE_IN2=" + ((dst->dimension(0) != 1 && src2->dimension(0) == 1) ? "1" : support::cpp11::to_string(vec_size))); - build_opts.add_option("-DVEC_SIZE_OUT=" + support::cpp11::to_string(vec_size)); - build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover)); - if(is_quantized && (dst->data_type() != DataType::S32)) - { - const UniformQuantizationInfo iq1_info = src1->quantization_info().uniform(); - const UniformQuantizationInfo iq2_info = src2->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); - - build_opts.add_option_if(is_data_type_quantized_asymmetric(src1->data_type()), - "-DOFFSET_IN1=" + support::cpp11::to_string(iq1_info.offset)); - build_opts.add_option_if(is_data_type_quantized_asymmetric(src2->data_type()), - "-DOFFSET_IN2=" + support::cpp11::to_string(iq2_info.offset)); - build_opts.add_option_if(is_data_type_quantized_asymmetric(dst->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(dst->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 src and dst parameters - - if(scale_int >= 0 && !is_quantized) - { - _kernel.setArg(idx++, scale_int); - } - else - { - _kernel.setArg(idx++, scale); - } - - Window win = calculate_max_window(*dst, Steps(vec_size)); - ICLKernel::configure_internal(win); - - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); - - // Set config_id for enabling LWS tuning - _config_id = kernel_name; - _config_id += "_"; - _config_id += lower_string(string_from_data_type(dst->data_type())); - _config_id += "_"; - _config_id += support::cpp11::to_string(src1->dimension(0)); - _config_id += "_"; - _config_id += support::cpp11::to_string(src1->dimension(1)); - _config_id += "_"; - _config_id += support::cpp11::to_string(src1->dimension(2)); - _config_id += "_"; - _config_id += support::cpp11::to_string(src2->dimension(0)); - _config_id += "_"; - _config_id += support::cpp11::to_string(src2->dimension(1)); - _config_id += "_"; - _config_id += support::cpp11::to_string(src2->dimension(2)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(0)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(1)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(2)); -} - -Status ClPixelWiseMultiplicationKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src1, src2, dst, scale, overflow_policy, rounding_policy, act_info)); - - 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(tensors.get_const_tensor(TensorType::ACL_SRC_0)); - const auto src_1 = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_SRC_1)); - auto dst = utils::cast::polymorphic_downcast(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)); -} - -namespace -{ -constexpr unsigned int vec_size_complex = 1; - -Status validate_arguments_complex(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src1, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src2, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2); - - const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->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(dst->data_type())); - - // Validate in case of configured dst - if(dst->total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 2, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, dst); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst"); - } - - return Status{}; -} -} // namespace - -void ClComplexPixelWiseMultiplicationKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(src1, src2, dst, act_info)); - - auto padding_info = get_padding_info({ src1, src2, dst }); - - const TensorShape &out_shape = TensorShape::broadcast_shape(src1->tensor_shape(), src2->tensor_shape()); - auto_init_if_empty(*dst, src1->clone()->set_tensor_shape(out_shape)); - - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dst->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()); - - Window win = calculate_max_window(*dst, Steps(vec_size_complex)); - ICLKernel::configure_internal(win); - - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); -} - -Status ClComplexPixelWiseMultiplicationKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_complex(src1, src2, dst, act_info)); - - 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(tensors.get_const_tensor(TensorType::ACL_SRC_0)); - const auto src_1 = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_SRC_1)); - auto dst = utils::cast::polymorphic_downcast(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)); -} -} // namespace kernels -} // namespace opencl -} // namespace arm_compute diff --git a/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.h b/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.h deleted file mode 100644 index 5b827262a1..0000000000 --- a/src/core/gpu/cl/kernels/ClPixelWiseMultiplicationKernel.h +++ /dev/null @@ -1,139 +0,0 @@ -/* - * Copyright (c) 2016-2021 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. - */ -#ifndef ARM_COMPUTE_CLPIXELWISEMULTIPLICATIONKERNEL_H -#define ARM_COMPUTE_CLPIXELWISEMULTIPLICATIONKERNEL_H - -#include "src/core/common/Macros.h" -#include "src/core/gpu/cl/ClCompileContext.h" -#include "src/core/gpu/cl/IClKernel.h" - -namespace arm_compute -{ -namespace opencl -{ -namespace kernels -{ -/** Interface for the pixelwise multiplication kernel. */ -class ClPixelWiseMultiplicationKernel : public IClKernel -{ -public: - /** Default constructor */ - ClPixelWiseMultiplicationKernel() = default; - ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClPixelWiseMultiplicationKernel); - /** Initialise the kernel's src and dst. - * - * Valid configurations (Input1,Input2) -> Output : - * - * - (U8,U8) -> U8 - * - (U8,U8) -> S16 - * - (U8,S16) -> S16 - * - (S16,U8) -> S16 - * - (S16,S16) -> S16 - * - (F16,F16) -> F16 - * - (F32,F32) -> F32 - * - (QASYMM8,QASYMM8) -> QASYMM8 - * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED - * - (QSYMM16,QSYMM16) -> QSYMM16 - * - (QSYMM16,QSYMM16) -> S32 - * - * @param[in] compile_context The compile context to be used. - * @param[in] src1 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[in] src2 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[out] dst The dst tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[in] scale Scale to apply after multiplication. - * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. - * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate - * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - */ - void configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - /** Static function to check if given info will lead to a valid configuration of @ref ClPixelWiseMultiplicationKernel - * - * Valid configurations (Input1,Input2) -> Output : - * - * - (U8,U8) -> U8 - * - (U8,U8) -> S16 - * - (U8,S16) -> S16 - * - (S16,U8) -> S16 - * - (S16,S16) -> S16 - * - (F16,F16) -> F16 - * - (F32,F32) -> F32 - * - (QASYMM8,QASYMM8) -> QASYMM8 - * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED - * - (QSYMM16,QSYMM16) -> QSYMM16 - * - (QSYMM16,QSYMM16) -> S32 - * - * @param[in] src1 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[in] src2 An src tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[in] dst The dst tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32. - * @param[in] scale Scale to apply after multiplication. - * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. - * @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate - * @param[in] rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - * - * @return a status - */ - static Status validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, float scale, - ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - - // Inherited methods overridden: - void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; -}; - -/** Interface for the complex pixelwise multiplication kernel. */ -class ClComplexPixelWiseMultiplicationKernel : public ICLKernel -{ -public: - /** Default constructor */ - ClComplexPixelWiseMultiplicationKernel() = default; - ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClComplexPixelWiseMultiplicationKernel); - /** Initialise the kernel's src and dst. - * - * @param[in] compile_context The compile context to be used. - * @param[in] src1 An src tensor info. Data types supported: F32. Number of channels supported: 2. - * @param[in] src2 An src tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. - * @param[out] dst The dst tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - */ - void configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - /** Static function to check if given info will lead to a valid configuration of @ref ClComplexPixelWiseMultiplicationKernel - * - * @param[in] src1 An src tensor info. Data types supported: F32. Number of channels supported: 2. - * @param[in] src2 An src tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. - * @param[in] dst The dst tensor info. Data types supported: same as @p src1. Number of channels supported: same as @p src1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - * - * @return a status - */ - static Status validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - - // Inherited methods overridden: - void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override; -}; -} // namespace kernels -} // namespace opencl -} // namespace arm_compute -#endif /*ARM_COMPUTE_CLPIXELWISEMULTIPLICATIONKERNEL_H */ -- cgit v1.2.1