/*
 * 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 <vector>

#include "src/fastertransformer/kernels/add_residual_kernels.h"
#include "src/fastertransformer/kernels/layernorm_kernels.h"
#include "src/fastertransformer/layers/BaseLayer.h"
#include "src/fastertransformer/layers/TensorParallelGeluFfnLayer.h"
#include "src/fastertransformer/layers/TensorParallelReluFfnLayer.h"
#include "src/fastertransformer/layers/TensorParallelSiluFfnLayer.h"
#include "src/fastertransformer/layers/attention_layers/TensorParallelDecoderCrossAttentionLayer.h"
#include "src/fastertransformer/layers/attention_layers/TensorParallelDecoderSelfAttentionLayer.h"
#include "src/fastertransformer/models/bart/BartDecoderLayerWeight.h"
#include "src/fastertransformer/utils/Tensor.h"
#include "src/fastertransformer/utils/allocator.h"
#include "src/fastertransformer/utils/cublasMMWrapper.h"
#include "src/fastertransformer/utils/custom_ar_comm.h"

namespace fastertransformer {

template<typename T>
class BartDecoder: public BaseLayer {
private:
    // buffer handling
    size_t max_batch_size_ = 0;
    // meta data
    const size_t         head_num_;
    const size_t         size_per_head_;
    const size_t         inter_size_;
    const size_t         d_model_;
    const size_t         num_layer_;
    const size_t         hidden_units_;
    const ActivationType activation_type_;
    const LayerNormType  layernorm_type_;  // still need to distinguish pre-/post- LayerNorm of
    const float          layernorm_eps_;
    float                q_scaling_;

    BaseAttentionLayer<T>* self_attention_layer_;
    BaseAttentionLayer<T>* cross_attention_layer_;
    FfnLayer<T>*           ffn_layer_;

    void allocateBuffer() override;
    void freeBuffer() override;
    bool isValidBatchSize(size_t batch_size);
    void allocateBuffer(size_t batch_size);

    void initialize();

    NcclParam tensor_para_;
    NcclParam pipeline_para_;

    std::shared_ptr<AbstractCustomComm> custom_all_reduce_comm_;
    int                                 enable_custom_all_reduce_;

    bool isValidLayerParallelId(uint l);
    bool isFirstLayerParallelId(uint l);
    bool isLastLayerParallelId(uint l);
    int  getFirstLayerParallelId();

protected:
    T* decoder_normed_input_     = nullptr;
    T* self_attn_output_         = nullptr;
    T* normed_self_attn_output_  = nullptr;
    T* cross_attn_output_        = nullptr;
    T* normed_cross_attn_output_ = nullptr;
    T* decoder_layer_output_     = nullptr;

public:
    BartDecoder(size_t                              max_batch_size,
                size_t                              head_num,
                size_t                              size_per_head,
                size_t                              inter_size,
                size_t                              d_model,
                size_t                              num_layer,
                float                               layernorm_eps_,
                cudaStream_t                        stream,
                cublasMMWrapper*                    cublas_wrapper,
                IAllocator*                         allocator,
                bool                                is_free_buffer_after_forward,
                NcclParam                           tensor_para,
                NcclParam                           pipeline_para,
                ActivationType                      activation_type,
                LayerNormType                       layernorm_type,
                float                               q_scaling                = 1.0f,
                std::shared_ptr<AbstractCustomComm> custom_all_reduce_comm   = nullptr,
                int                                 enable_custom_all_reduce = 0);

    BartDecoder(BartDecoder<T> const& decoder);

    ~BartDecoder();

    void forward(std::vector<Tensor>*                           output_tensors,
                 const std::vector<Tensor>*                     input_tensors,
                 const std::vector<BartDecoderLayerWeight<T>*>* decoder_layer_weights);
    void setStream(cudaStream_t stream) override;
};

}  // namespace fastertransformer
