// Copyright (c) 2019 PaddlePaddle 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
//
//     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.
#include <bmcompiler_if.h>
#include <bmcompiler_if_lite.h>
#include <bmcompiler_defs.h>
#include "lite/kernels/npu/bridges/registry.h"
#include "lite/kernels/bm/bridges/graph.h"
#include "lite/kernels/bm/bridges/utility.h"

namespace paddle {
namespace lite {
namespace subgraph {
namespace bm {

int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
    CHECK(ctx != nullptr);
    CHECK(op != nullptr);
    auto graph = static_cast<Graph*>(ctx);
    auto scope = op->scope();
    auto op_info = op->op_info();
    auto op_type = op_info->Type();
    // input
    const int input_num = 2;
    int **shape = new int *[input_num];
    int *dim = new int[input_num];
    const char **name = new const char *[input_num];
    auto x_var_name = op_info->Input("X").front();
    auto x = scope->FindVar(x_var_name)->GetMutable<lite::Tensor>();
    auto x_dims = x->dims();
    name[0] = static_cast<const char*>(x_var_name.c_str());
    dim[0] = x_dims.size();
    const int64_t* x_shape_data =
        const_cast<const int64_t*>(&x_dims.data()[0]);
    std::vector<int32_t> i_x_shape_data(x_dims.size());
    for (size_t i = 0; i < x_dims.size(); i++) {
        i_x_shape_data[i] = static_cast<int>(x_shape_data[i]);
    }
    shape[0] = &i_x_shape_data[0];
    auto y_var_name = op_info->Input("Y").front();
    auto y = scope->FindVar(y_var_name)->GetMutable<lite::Tensor>();
    auto y_dims = y->dims();
    name[1] = static_cast<const char*>(y_var_name.c_str());
    dim[1] = y_dims.size();
    const int64_t* y_shape_data =
           const_cast<const int64_t*>(&y_dims.data()[0]);
    std::vector<int32_t> i_y_shape_data(y_dims.size());
    for (size_t i = 0; i < y_dims.size(); i++) {
        i_y_shape_data[i] = static_cast<int>(y_shape_data[i]);
    }
    shape[1] = &i_y_shape_data[0];
    bool y_is_const = !graph->HasNode(y_var_name);
    // output
    auto output_var_name = op_info->Output("Out").front();
    auto output =
         scope->FindVar(output_var_name)->GetMutable<lite::Tensor>();
    auto output_dims = output->dims();
    const int64_t* output_shape_data =
           const_cast<const int64_t*>(&output_dims.data()[0]);
    std::vector<int32_t> i_output_shape_data(output_dims.size());
    for (size_t i = 0; i < output_dims.size(); i++) {
        i_output_shape_data[i] = static_cast<int>(output_shape_data[i]);
    }
    if (y_is_const) {
        CHECK_EQ(op_type, "elementwise_add");
    }
    int op_code{-1};
    float coeff[2] = {1.f, 1.f};
    if (op_type == "elementwise_mul") {
        op_code = 0;
    } else if (op_type == "elementwise_add") {
        op_code = 1;
    } else if (op_type == "elementwise_sub") {
        op_code = 1;
        coeff[1] = -1.f;
    } else {
        LOG(FATAL) << "UNSUPPORTED ELTWISE OPERATION: " << op_type;
    }
    if (!y_is_const) {
        add_eltwise_layer(graph->GetCompilerHandle(),
           input_num,
           shape,
           dim,
           name,
           const_cast<const int*>(&i_output_shape_data[0]),
           output_dims.size(),
           static_cast<const char*>(output_var_name.c_str()),
           op_code,
           coeff);
    } else {
        const float* y_data =
               const_cast<const float*>(y->mutable_data<float>());
        const float* x_data =
               const_cast<const float*>(x->mutable_data<float>());
        bm_add_const_tensor(graph->GetCompilerHandle(),
                    name[1],
                    shape[0],
                    dim[0],
                    static_cast<bm_data_type_t>(DTYPE_FP32),
                    static_cast<const void*>(y_data));

        add_binary_layer_v2(graph->GetCompilerHandle(),
                    name[0],
                    shape[0],
                    dim[0],
                    0,
                    static_cast<const float*>(x_data),
                    name[1],
                    shape[0],
                    dim[0],
                    0,
                    static_cast<const float*>(y_data),
                    static_cast<const char*>(output_var_name.c_str()),
                    0);
    }
    delete [] shape;
    delete [] name;
    delete [] dim;
    graph->AddNode(output_var_name);
    return SUCCESS;
}

}  // namespace bm
}  // namespace subgraph
}  // namespace lite
}  // namespace paddle

REGISTER_SUBGRAPH_BRIDGE(elementwise_add, kBM,
     paddle::lite::subgraph::bm::ElementwiseConverter);
