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diff --git a/src/core/gpu/cl/kernels/ClMulKernel.cpp b/src/core/gpu/cl/kernels/ClMulKernel.cpp
deleted file mode 100644
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--- a/src/core/gpu/cl/kernels/ClMulKernel.cpp
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-/*
- * 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::S32,
- 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::S32,
- 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((src1->data_type() == DataType::S32 || src2->data_type() == DataType::S32) && (dst->data_type() != DataType::S32),
- "Dst must be S32 if source tensors are S32");
- 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() == 4 || src2->element_size() == 4)
- {
- // use 64 bit accumulator for 32-bit input
- acc_type = "long";
- }
- 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<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));
-}
-
-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<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));
-}
-} // namespace kernels
-} // namespace opencl
-} // namespace arm_compute