/*
 * Copyright (c) 2019-2021, 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 "src/fastertransformer/kernels/layernorm_kernels.h"
#include "src/fastertransformer/models/glm/GlmDecoderLayerWeight.h"
#include "src/fastertransformer/utils/memory_utils.h"

namespace fastertransformer {

template<typename T>
struct GlmWeight {

    GlmWeight() = default;
    GlmWeight(const int hidden_units,
               const int inter_size,
               const int vocab_size,
               const int num_layer,
               const int max_seq_len,
               const int tensor_para_size = 1,
               const int tensor_para_rank = 0,
               const int layer_para_size = 1,
               const int layer_para_rank = 0);

    ~GlmWeight();
    GlmWeight(const GlmWeight& other);
    GlmWeight& operator=(const GlmWeight& other);

    void loadModel(std::string dir_path);
    void resizeLayer(const int num_layer);


    std::vector<GlmDecoderLayerWeight<T>*> decoder_layer_weights;
    const T* pre_decoder_embedding_table = nullptr;
    // GPT-J does not use embedding table, but we leave the ptr such that
    // Glm::forward and Gpt::forward become identical
    const T* position_encoding_table = nullptr;

    LayerNormWeight<T> post_decoder_layernorm;
    DenseWeight<T> post_decoder_embedding;


private:
    void setWeightPtr();
    void mallocWeights();
    bool isValidLayerParallelId(int l);

    int hidden_units_;
    int inter_size_;
    int vocab_size_;
    int num_layer_;
    int max_seq_len_;

    int tensor_para_size_;
    int tensor_para_rank_;
    int layer_para_size_;
    int layer_para_rank_;

    bool is_maintain_buffer = false;
    T* weights_ptr[4];
};

}  // namespace fastertransformer
