#pragma once
#include "../elemwise/opr_impl.h"
#include "megdnn/oprs.h"
#include "src/cuda/cudnn_with_check.h"

namespace megdnn {
namespace cuda {

class ConvBiasForwardImpl : public ConvBiasForward {
public:
    using ConvBiasForward::ConvBiasForward;
    void exec(
            _megdnn_tensor_in src, _megdnn_tensor_in filter, _megdnn_tensor_in bias,
            _megdnn_tensor_in z, _megdnn_tensor_out dst,
            const PreprocessedFilter* preprocessed_filter,
            _megdnn_workspace workspace) override;
    size_t get_workspace_in_bytes(
            const TensorLayout&, const TensorLayout&, const TensorLayout&,
            const TensorLayout&, const TensorLayout&,
            const PreprocessedFilter*) override;

    size_t get_preprocess_workspace_in_bytes(
            const TensorLayout&, const TensorLayout&, const TensorLayout&,
            const TensorLayout&, const TensorLayout&) override;
    SmallVector<TensorLayout> deduce_preprocessed_filter_layout(
            const TensorLayout&, const TensorLayout&, const TensorLayout&,
            const TensorLayout&, const TensorLayout&) override;
    void exec_preprocess(
            const TensorLayout&, _megdnn_tensor_in, _megdnn_tensor_in,
            const TensorLayout&, const TensorLayout&, PreprocessedFilter*,
            _megdnn_workspace) override;
    const char* get_algorithm_set_name() const override;

    class AlgoBase;
    class AlgoChanwise;
    class AlgoChanwiseSmall;
    class AlgoDepthwiseLargeFilter;
    class AlgoChanwise8x8x32;
    class AlgoFallbackNCHWQS8;
    class AlgoInplaceMatmul;
    class AlgoMatmul;
    class AlgoMatmul8x8x32;
    class Algo1x1;
    class AlgoBatchedMatmul;
    class AlgoGroupConvGeneral;
    class AlgoQUInt4x4x32WMMA;
    class AlgoCutlassConvolutionBase;
    class AlgoInt8CHWN4DotProdImplicitGemm;
    class AlgoInt8NCHW4DotProdImplicitGemm;
    class AlgoInt8CHWN4IMMAImplicitGemm;
    class AlgoInt8NCHW4IMMAImplicitGemm;
    class AlgoInt8CHWN4IMMAImplicitGemmReorderFilter;
    class AlgoInt8CHWN4IMMAImplicitGemmUnrollWidth;
    class AlgoInt8NCHW32IMMAImplicitGemm;
    class AlgoInt8NHWCIMMAImplicitGemm;
    class AlgoInt4NCHW64IMMAImplicitGemmBase;
    class AlgoInt4Int4NCHW64IMMAImplicitGemm;
    class AlgoUInt4Int4NCHW64IMMAImplicitGemm;
    class AlgoInt4NHWCIMMAImplicitGemmBase;
    class AlgoInt4Int4NHWCIMMAImplicitGemm;
    class AlgoUInt4Int4NHWCIMMAImplicitGemm;
    class AlgoBFloat16;
    class AlgoSimpleInt1;
    // The following algorithms are suitable for channel wise convolution
    class AlgoFloat32NCHWFMAImplicitBatchedGemm;
    class AlgoFloat16NCHWHMMAImplicitBatchedGemm;
    class AlgoCUDNNConvBase;
    class AlgoCUDNNConv;
    class AlgoCUDNNConvBiasActivationBase;
    class AlgoCUDNNConvBiasActivation;
#if CUDNN_VERSION >= 8020
    class AlgoCUDNNConvV8;
    class AlgoCUDNNConvBiasActivationV8;
#endif

    class AlgoPack;

    static const AlgoPack& algo_pack() { return sm_algo_pack; }

    Algorithm* get_algorithm_from_desc(const AlgorithmDesc& desc) override;

    std::vector<Algorithm*> get_all_algorithms(
            const TensorLayout& src, const TensorLayout& filter,
            const TensorLayout& bias, const TensorLayout& z,
            const TensorLayout& dst) override;
    std::vector<Algorithm*> get_all_algorithms_safe(
            const TensorLayout& src, const TensorLayout& filter,
            const TensorLayout& bias, const TensorLayout& z,
            const TensorLayout& dst) override;
    Algorithm* get_algorithm_heuristic(
            const TensorLayout& src, const TensorLayout& filter,
            const TensorLayout& bias, const TensorLayout& z, const TensorLayout& dst,
            size_t workspace_limit_in_bytes, const AlgoAttribute& positive_attr,
            const AlgoAttribute& negative_attr) override;

private:
    static AlgoPack sm_algo_pack;
};

}  // namespace cuda
}  // namespace megdnn

// vim: syntax=cpp.doxygen