#pragma once
#include "megdnn/oprs.h"
#include "src/common/algo_base.h"
#include "src/common/metahelper.h"
#include "src/common/utils.h"
#include "src/cuda/handle.h"
#include "src/cuda/local_share/opr_impl.h"
#include <unordered_map>
namespace megdnn {
namespace cuda {
class LocalShareBackwardDataImpl::AlgoBase : public Algorithm {
protected:
~AlgoBase() = default;
public:
enum class AlgoType : uint32_t {
CUDA_IMPLICIT_GEMM,
CUDA_BATCHED_MATMUL,
};
using Mapper = std::unordered_map<AlgorithmDesc, AlgoBase*>;
AlgoBase() : Algorithm() { m_handle_type = Handle::HandleType::CUDA; }
struct SizeArgs {
LocalShareBackwardDataImpl* opr;
TensorLayout filter_layout, diff_layout, grad_layout;
std::string to_string() const;
SizeArgs(
LocalShareBackwardDataImpl* opr, const TensorLayout& filter,
const TensorLayout& diff, const TensorLayout& grad);
};
struct ExecArgs : public SizeArgs {
const TensorND *filter_tensor, *diff_tensor, *grad_tensor;
Workspace workspace;
ExecArgs(
LocalShareBackwardDataImpl* opr, _megdnn_tensor_in filter,
_megdnn_tensor_in diff, _megdnn_tensor_out grad,
_megdnn_workspace workspace);
};
virtual bool is_available(const SizeArgs& args) const = 0;
virtual size_t get_workspace_in_bytes(const SizeArgs& args) const = 0;
virtual void exec(const ExecArgs& args) const = 0;
bool is_available_wk(const SizeArgs& args, size_t limit) {
return is_available(args) && get_workspace_in_bytes(args) <= limit;
}
bool is_available_attribute(
const SizeArgs& args,
const AlgoAttribute& positive_attr = AlgoAttribute::REPRODUCIBLE,
const AlgoAttribute& negative_attr = AlgoAttribute::DEFAULT,
size_t limit = std::numeric_limits<size_t>::max()) {
return contain_attribute_all(positive_attr) &&
!contain_attribute_any(negative_attr) && is_available_wk(args, limit);
}
AlgoBase& check_workspace(const SizeArgs& args, const Workspace& workspace) {
auto req = get_workspace_in_bytes(args);
megdnn_assert(
req <= workspace.size,
"local share conv fwd algo %s: required workspace %zu "
"bytes, got %zu",
name(), req, workspace.size);
return *this;
}
};
class LocalShareBackwardDataImpl::AlgoImplicitGemm final : public AlgoBase {
public:
bool is_available(const SizeArgs& args) const override;
size_t get_workspace_in_bytes(const SizeArgs& args) const override;
void exec(const ExecArgs& args) const override;
AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
const char* name() const override { return "LOCAL_SHARE_IMPLICIT_GEMM"; }
MEGDNN_DECL_ALGO_TYPE(CUDA_IMPLICIT_GEMM)
};
class LocalShareBackwardDataImpl::AlgoBatchedMatMul final : public AlgoBase {
public:
bool is_available(const SizeArgs& args) const override;
size_t get_workspace_in_bytes(const SizeArgs& args) const override;
WorkspaceBundle get_workspace_bundle(dt_byte* raw_ptr, const SizeArgs& args) const;
void exec(const ExecArgs& args) const override;
AlgoAttribute attribute() const override { return AlgoAttribute::REPRODUCIBLE; }
const char* name() const override { return "LOCAL_SHARE_BATCHED_MATMUL"; }
MEGDNN_DECL_ALGO_TYPE(CUDA_BATCHED_MATMUL)
};
class LocalShareBackwardDataImpl::AlgoPack : NonCopyableObj {
AlgoBase::Mapper m_all_algos_map;
public:
AlgoPack();
AlgoImplicitGemm implicit_gemm;
AlgoBatchedMatMul batched_matmul;
std::vector<AlgoBase*> all_algos;
const AlgoBase::Mapper& all_algos_map() const { return m_all_algos_map; }
};
} }