/*
 * SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights
 * reserved. SPDX-License-Identifier: Apache-2.0
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#ifndef FLASHINFER_FP4_GEMM_CUTLASS_H_
#define FLASHINFER_FP4_GEMM_CUTLASS_H_

#include <cuda_runtime_api.h>

#include <vector>

#include "flashinfer/gemm/cutlass_gemm_configs.h"

namespace flashinfer {
namespace gemm {

/*
  This runner supports:
  FP4 inputs (A and B)
  float blockwise scaling factor
  float alpha scalings
  T output (D) where T = {float, half, __nv_bfloat16}

  Activations, biases and outputs are all assumed to be row-major.
  Weights are assumed to be column-major.
  Block scaling factor are interleaved.
*/

class CutlassFp4GemmRunnerInterface {
 public:
  CutlassFp4GemmRunnerInterface() {}

  virtual ~CutlassFp4GemmRunnerInterface() {}

  virtual void gemm(void* D, void const* A, void const* B, void const* input_sf,
                    void const* weight_sf, float const* global_sf, int m, int n, int k,
                    int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
                    const size_t workspaceBytes, cudaStream_t stream) = 0;

  // Returns desired workspace size in bytes.
  virtual size_t getWorkspaceSize(int const m, int const n, int const k, int batch_count) = 0;

  virtual std::vector<CutlassGemmConfig> getConfigs() const = 0;
};

enum class FP4GemmType {
  W4A4_NVFP4_NVFP4,
};

template <typename T, FP4GemmType gemmType = FP4GemmType::W4A4_NVFP4_NVFP4>
class CutlassFp4GemmRunner : public virtual CutlassFp4GemmRunnerInterface {
 public:
  CutlassFp4GemmRunner();
  ~CutlassFp4GemmRunner();

  void gemm(void* D, void const* A, void const* B, void const* input_sf, void const* weight_sf,
            float const* global_sf, int m, int n, int k, int batch_count,
            CutlassGemmConfig gemmConfig, char* workspace, const size_t workspaceBytes,
            cudaStream_t stream) override;

  // Returns desired workspace size in bytes.
  size_t getWorkspaceSize(int const m, int const n, int const k, int const batch_count) override;

  std::vector<CutlassGemmConfig> getConfigs() const override;

 private:
  size_t dispatchToArch(T* D, void const* A, void const* B, void const* input_sf,
                        void const* weight_sf, float const* global_sf, int m, int n, int k,
                        int batch_count, CutlassGemmConfig gemmConfig, char* workspace,
                        const size_t workspaceBytes, cudaStream_t stream, int* occupancy = nullptr);

  size_t getWorkspaceSizeImpl(int const m, int const n, int const k, int const batch_count);
};

}  // namespace gemm
}  // namespace flashinfer

#endif  // FLASHINFER_FP4_GEMM_CUTLASS_H_