/* Copyright 2025 The xLLM Authors. 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

    https://github.com/jd-opensource/xllm/blob/main/LICENSE

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 <torch/torch.h>

#include "core/framework/model_context.h"
#include "framework/state_dict/state_dict.h"
#include "framework/state_dict/utils.h"

namespace xllm {
namespace layer {

class RMSNormImpl : public torch::nn::Module {
 public:
  RMSNormImpl(int64_t dim, double eps, const torch::TensorOptions& options);
  RMSNormImpl(const ModelContext& context);

  // Standard forward: returns (normalized_output, updated_residual)
  std::tuple<torch::Tensor, std::optional<torch::Tensor>> forward(
      torch::Tensor& input,
      std::optional<torch::Tensor> residual = std::nullopt,
      std::optional<torch::Tensor> inplace_output = std::nullopt);

  // Fused forward with FP8 quantization output (for static quantization)
  // Returns: (fp8_quantized_output, updated_residual)
  // This combines RMSNorm + FP8 quantization to reduce memory bandwidth
  std::tuple<torch::Tensor, std::optional<torch::Tensor>> forward_fp8(
      torch::Tensor& input,
      const torch::Tensor& fp8_scale,
      std::optional<torch::Tensor> residual = std::nullopt);

  void set_layernorm_mode();

  void load_state_dict(const StateDict& state_dict);

  torch::Tensor weight() const { return weight_; }
  torch::Tensor bias() const { return bias_; }
  double eps() const { return eps_; }

 private:
  DEFINE_WEIGHT(weight);
  DEFINE_WEIGHT(bias);
  int64_t norm_dim_;
  double eps_;
  std::string mode_;
};
TORCH_MODULE(RMSNorm);

}  // namespace layer
}  // namespace xllm