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/*
* Copyright (c) 2020-2021 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 "arm_compute/core/CL/CLCompileContext.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "support/StringSupport.h"
#include "src/core/CL/CLUtils.h"
#include "src/core/experimental/PostOpUtils.h"
namespace arm_compute
{
cl::Image2D create_image2d_from_buffer(const cl::Context &ctx, const cl::Buffer &buffer, const TensorShape &shape2d, DataType data_type, size_t image_row_pitch)
{
cl_channel_type cl_data_type;
switch(data_type)
{
case DataType::F32:
cl_data_type = CL_FLOAT;
break;
case DataType::F16:
cl_data_type = CL_HALF_FLOAT;
break;
default:
ARM_COMPUTE_ERROR("Data type not support with OpenCL image2d");
}
cl_mem cl_image;
cl_int err = CL_SUCCESS;
const cl_image_format format = { CL_RGBA, cl_data_type };
cl_image_desc desc;
memset(&desc, 0, sizeof(desc));
desc.image_type = CL_MEM_OBJECT_IMAGE2D;
desc.mem_object = buffer();
desc.image_row_pitch = image_row_pitch;
desc.image_width = shape2d[0];
desc.image_height = shape2d[1];
cl_image = clCreateImage(ctx(), CL_MEM_READ_ONLY, &format, &desc, nullptr, &err);
ARM_COMPUTE_UNUSED(err);
ARM_COMPUTE_ERROR_ON_MSG(err != CL_SUCCESS, "Error during the creation of CL image from buffer");
return cl::Image2D(cl_image);
}
namespace experimental
{
PostOpCLKernelUtils::PostOpCLKernelUtils(const Config &supported_config)
: _supported_config(supported_config)
{
ARM_COMPUTE_ERROR_ON_MSG(supported_config.empty(), "Empty PostOp CL kernel support configuration is not allowed");
for(auto it = _supported_config.begin(); it != _supported_config.end(); ++it)
{
auto post_op_sequence = it->first;
auto post_op_slots = std::get<1>(it->second);
ARM_COMPUTE_ERROR_ON_MSG(post_op_sequence.size() != post_op_slots.size(), "The number of PostOps must be the same as that of the assigned slots");
}
}
bool PostOpCLKernelUtils::are_post_op_shapes_compliant(const ITensorInfo *dst, const experimental::PostOpList<ITensorInfo *> &post_ops)
{
for(const auto &op : post_ops.get_list())
{
for(const auto &tensor : op->arguments())
{
const TensorShape &out_shape = TensorShape::broadcast_shape(dst->tensor_shape(), (*tensor)->tensor_shape());
// All post ops must be elementwise and must not alter the shape of the original dst tensor after broadcasting
if(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0))
{
return false;
}
// NOTE: Kernel limitation: currently only the following broadcasting types are supported:
// 1. Post op arg is scalar, broadcast in both first and second dims
// 2. Post op arg is of shape: second dim=1, first dim=N, broadcast only in second dim
// This means this case: Post op arg is of shape: second dim=M, first dim=1, broadcast only in first dim, is NOT supported
if(dst->dimension(0) > 1 && dst->dimension(1) > 1 && (*tensor)->dimension(0) == 1 && (*tensor)->dimension(1) > 1)
{
return false;
}
}
}
return true;
}
bool PostOpCLKernelUtils::is_post_op_sequence_supported(const PostOpList<ITensorInfo *> &post_ops) const
{
if(post_ops.size() == 0)
{
return true; // Always support cases where no post op is specified
}
const auto post_op_sequence = get_post_op_sequence(post_ops);
return _supported_config.find(post_op_sequence) != _supported_config.end();
}
void PostOpCLKernelUtils::set_post_ops_cl_build_options(CLBuildOptions &build_opts, const PostOpList<ITensorInfo *> &post_ops) const
{
const auto post_op_sequence = get_post_op_sequence(post_ops);
const auto slots = std::get<1>(_supported_config.at(post_op_sequence));
for(size_t post_op_id = 0; post_op_id < post_ops.size(); ++post_op_id)
{
const auto &post_op = post_ops.get_list().at(post_op_id);
const auto slot_prefix = "-DP" + support::cpp11::to_string(slots[post_op_id]);
if(post_op->type() == experimental::PostOpType::Activation)
{
const auto _post_op = utils::cast::polymorphic_downcast<const experimental::PostOpAct<ITensorInfo *> *>(post_op.get());
const auto act_type = slot_prefix + "_ACTIVATION_TYPE=" + lower_string(string_from_activation_func(_post_op->_act_info.activation()));
const auto act_a_val = slot_prefix + "_ACTIVATION_A_VAL=" + float_to_string_with_full_precision(_post_op->_act_info.a());
const auto act_b_val = slot_prefix + "_ACTIVATION_B_VAL=" + float_to_string_with_full_precision(_post_op->_act_info.b());
build_opts.add_option(act_type);
build_opts.add_option(act_a_val);
build_opts.add_option(act_b_val);
}
else if(post_op->type() == experimental::PostOpType::Eltwise_Add)
{
size_t arg_id = 1;
const auto eltwise_op = slot_prefix + "_ELTWISE_OP=ADD" + "_X_POS_" + support::cpp11::to_string(post_op->prev_dst_pos());
build_opts.add_option(eltwise_op);
for(const auto &tensor : post_op->arguments())
{
const auto height = slot_prefix + "_ELTWISE_ARG" + support::cpp11::to_string(arg_id) + "_HEIGHT=" + support::cpp11::to_string((*tensor)->dimension(1));
const auto width = slot_prefix + "_ELTWISE_ARG" + support::cpp11::to_string(arg_id) + "_WIDTH=" + support::cpp11::to_string((*tensor)->dimension(0));
build_opts.add_option(height);
build_opts.add_option(width);
++arg_id;
}
}
else if(post_op->type() == experimental::PostOpType::Eltwise_PRelu)
{
size_t arg_id = 1;
const auto eltwise_op = slot_prefix + "_ELTWISE_OP=PRELU" + "_X_POS_" + support::cpp11::to_string(post_op->prev_dst_pos());
build_opts.add_option(eltwise_op);
for(const auto &tensor : post_op->arguments())
{
const auto height = slot_prefix + "_ELTWISE_ARG" + support::cpp11::to_string(arg_id) + "_HEIGHT=" + support::cpp11::to_string((*tensor)->dimension(1));
const auto width = slot_prefix + "_ELTWISE_ARG" + support::cpp11::to_string(arg_id) + "_WIDTH=" + support::cpp11::to_string((*tensor)->dimension(0));
build_opts.add_option(height);
build_opts.add_option(width);
++arg_id;
}
}
}
}
void PostOpCLKernelUtils::set_post_ops_cl_kernel_name(std::string &kernel_name, const PostOpList<ITensorInfo *> &post_ops) const
{
const auto post_op_sequence = get_post_op_sequence(post_ops);
const auto postfix = std::get<0>(_supported_config.at(post_op_sequence));
kernel_name += postfix;
}
} // namespace experimental
} // namespace arm_compute
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