blob: c2bd01270395198341f94d267471ebba3620f149 [file] [log] [blame]
/*
* Copyright (c) 2022-2023 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/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h"
#include "arm_compute/core/CL/CLCompileContext.h"
#include "src/dynamic_fusion/sketch/gpu/GpuWorkloadContextImpl.h"
namespace arm_compute
{
namespace experimental
{
namespace dynamic_fusion
{
GpuWorkloadContext::GpuWorkloadContext(CLCompileContext *cl_compile_ctx)
: _impl{ std::make_unique<Impl>(GpuLanguage::OpenCL, cl_compile_ctx) }
{
}
GpuWorkloadContext::~GpuWorkloadContext() = default;
GpuWorkloadContext::GpuWorkloadContext(GpuWorkloadContext &&other) = default;
GpuWorkloadContext &GpuWorkloadContext::operator=(GpuWorkloadContext &&other) = default;
GpuTarget GpuWorkloadContext::gpu_target() const
{
return _impl->cl_compile_context()->get_gpu_target();
}
GpuLanguage GpuWorkloadContext::gpu_language() const
{
return _impl->gpu_language();
}
const CLCompileContext *GpuWorkloadContext::cl_compile_context() const
{
return _impl->cl_compile_context();
}
void GpuWorkloadContext::register_user_tensor(ITensorInfo &tensor_info)
{
_impl->register_user_tensor(tensor_info);
}
GpuWorkloadContext::Impl &GpuWorkloadContext::implementation()
{
return *_impl;
}
const GpuWorkloadContext::Impl &GpuWorkloadContext::implementation() const
{
return *_impl;
}
GpuWorkloadContext::Impl::Impl(GpuLanguage gpu_language, CLCompileContext *cl_compile_ctx)
: _gpu_language(gpu_language), _cl_compile_ctx(cl_compile_ctx), _next_tensor_id(1), _mem_map(), _managed_tensor_info()
{
}
GpuLanguage GpuWorkloadContext::Impl::gpu_language() const
{
return _gpu_language;
}
const CLCompileContext *GpuWorkloadContext::Impl::cl_compile_context() const
{
return _cl_compile_ctx;
}
const MemoryDescriptorMap &GpuWorkloadContext::Impl::mem_map() const
{
return _mem_map;
}
void GpuWorkloadContext::Impl::register_user_tensor(ITensorInfo &tensor_info)
{
ARM_COMPUTE_ERROR_ON(tensor_info.has_valid_id());
const auto tensor_id = next_tensor_id();
tensor_info.set_id(tensor_id);
_mem_map[tensor_id] = MemoryDescriptor{ MemoryType::User };
// Save a *copy* of the user tensor info in workload context for future reference
// Note that this means if the user modifies the @p tensor_info, the change will not be reflected in the context
_managed_tensor_info.emplace(tensor_info.id(), std::make_unique<TensorInfo>(tensor_info));
}
ITensorInfo *GpuWorkloadContext::Impl::create_virtual_tensor()
{
auto tensor_info = std::make_unique<TensorInfo>();
const auto tensor_id = -next_tensor_id();
tensor_info->set_id(tensor_id);
_mem_map[tensor_id] = MemoryDescriptor{ MemoryType::Virtual };
auto inserted = _managed_tensor_info.emplace(tensor_info->id(), std::move(tensor_info));
return inserted.first->second.get();
}
ITensorInfo *GpuWorkloadContext::Impl::create_auxiliary_tensor(const ITensorInfo &itensor_info)
{
auto tensor_info = std::make_unique<TensorInfo>(itensor_info);
const auto tensor_id = next_tensor_id();
tensor_info->set_id(tensor_id);
_mem_map[tensor_id] = MemoryDescriptor{ MemoryType::Auxiliary, AuxMemoryInfo{ tensor_info->total_size() } };
auto inserted = _managed_tensor_info.emplace(tensor_info->id(), std::move(tensor_info));
return inserted.first->second.get();
}
ITensorInfo *GpuWorkloadContext::Impl::get_tensor_info(ITensorInfo::Id id)
{
return _managed_tensor_info.at(id).get();
}
const ITensorInfo *GpuWorkloadContext::Impl::get_tensor_info(ITensorInfo::Id id) const
{
return _managed_tensor_info.at(id).get();
}
ITensorInfo::Id GpuWorkloadContext::Impl::next_tensor_id()
{
return _next_tensor_id++;
}
} // namespace dynamic_fusion
} // namespace experimental
} // namespace arm_compute