/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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.
 */

/*
 * Copyright (c) 2021, Open AI Lab
 * Author: Shijie Chen
 */

#include "timvx_executor.hpp"

extern "C"
{
#include "operator/op.h"
#include "layernorm_param.h"
}


bool VXEngine::AddLayerNormNode(struct node* ir_node)
{
    struct graph* ir_graph = ir_node->graph;

    std::vector<std::shared_ptr<tim::vx::Tensor> > bn_in_tensor(ir_node->input_num);

    int in_set[3] = {0, 2, 1};
    for (int i = 0; i < ir_node->input_num; i++)
    {
        int idx = in_set[i];
        struct tensor* input_tensor = get_ir_graph_tensor(ir_graph, ir_node->input_tensors[idx]);
        bn_in_tensor[i] = this->vx_tensor_map[input_tensor->index];
    }
    struct tensor* output_tensor = get_ir_graph_tensor(ir_graph, ir_node->output_tensors[0]);

    struct layernorm_Param* param = (struct layernorm_Param*)ir_node->op.param_mem;

    auto layernorm = graph->CreateOperation<tim::vx::ops::LayerNormalization>(0, param->eps);
    (*layernorm)
            .BindInputs({ bn_in_tensor })
            .BindOutputs({ this->vx_tensor_map[output_tensor->index] });

    return true;
}