/*
 * Copyright (c) 2019-2023, 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 <string>

#include "src/fastertransformer/kernels/layernorm_kernels.h"
#include "src/fastertransformer/layers/FfnWeight.h"
#include "src/fastertransformer/layers/attention_layers/AttentionWeight.h"
#include "src/fastertransformer/utils/cuda_utils.h"

namespace fastertransformer {

template<typename T>
struct LlamaDecoderLayerWeight {
public:
    LlamaDecoderLayerWeight() = default;
    LlamaDecoderLayerWeight(const int int8_mode);
    LlamaDecoderLayerWeight(const int  hidden_units,
                            const int  inter_size,
                            const int  tensor_para_size  = 1,
                            const int  tensor_para_rank  = 0,
                            const bool use_gptj_residual = true,
                            const int int8_mode = 0);
    ~LlamaDecoderLayerWeight();
    LlamaDecoderLayerWeight(const LlamaDecoderLayerWeight& other);
    LlamaDecoderLayerWeight& operator=(const LlamaDecoderLayerWeight& other);

    void loadModel(std::string dir_path, FtCudaDataType model_file_type);

    LayerNormWeight<T> pre_layernorm_weights;
    AttentionWeight<T> self_attention_weights;
    LayerNormWeight<T> post_attention_layernorm_weights;
    FfnWeight<T>       ffn_weights;

private:
    int       hidden_units_;
    int       inter_size_;
    int       tensor_para_size_;
    int       tensor_para_rank_;
    bool      use_gptj_residual_;
    const int attention_dense_bias_weight_id = 5;
    bool      is_maintain_buffer             = false;
    T*        weights_ptr[14];
    int       int8_mode_ = 0;

    std::vector<int8_t*> int8_weights_ptr = std::vector<int8_t*>(5, nullptr);
    std::vector<T*>      weight_only_scale_ptr = std::vector<T*>(5, nullptr);

    void setWeightPtr();
    void mallocWeights();
    void copyFrom(const LlamaDecoderLayerWeight& other);
};

}  // namespace fastertransformer
