/*
 * Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
 *
 * 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.
 */

#pragma once
#include <limits>

#include "cutlass/epilogue/thread/activation.h"
#include "tensorrt_llm/common/config.h"

TRTLLM_NAMESPACE_BEGIN

namespace kernels::cutlass_kernels {
// ============================== Activation Adaptors =================================

template <template <class> class ActFn>
struct IdentityAdaptor {
  constexpr static bool IS_GLU = false;
  float alpha = 1.0f;
  float beta = 0.0f;
  float limit = std::numeric_limits<float>::infinity();

  template <class T>
  __device__ T operator()(T const& x) const {
    ActFn<T> fn{};
    return fn(x);
  }
};

template <template <class> class ActFn>
struct GLUAdaptor {
  constexpr static bool IS_GLU = true;
  float alpha = 1.0f;
  float beta = 0.0f;
  float limit = std::numeric_limits<float>::infinity();

  template <class T>
  __device__ T operator()(T const& gate, T const& linear) const {
    ActFn<T> fn{};
    return fn(gate) * linear;
  }
};

struct SwigluBiasAdaptor {
  constexpr static bool IS_GLU = true;
  float alpha = 1.0f;
  float beta = 0.0f;
  float limit = std::numeric_limits<float>::infinity();

  template <class T>
  __device__ T operator()(T const& gate, T const& linear) const {
    cutlass::epilogue::thread::Sigmoid<T> fn{};
    T linear_clamped = cutlass::maximum<T>{}(cutlass::minimum<T>{}(linear, limit), -limit);
    T gate_clamped = cutlass::minimum<T>{}(gate, limit);
    return gate_clamped * fn(gate_clamped * alpha) * (linear_clamped + beta);
  }
};

}  // namespace kernels::cutlass_kernels

TRTLLM_NAMESPACE_END
