// 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 "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 MulConverter(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();
    auto unique_op_name = lite::subgraph::bm::UniqueName(op_type);
    // only support y is const
    // input
    auto x_var_name = op_info->Input("X").front();
    auto x = scope->FindVar(x_var_name)->GetMutable<lite::Tensor>();
    auto x_dims = x->dims();
    const int64_t* x_shape_data =
             const_cast<const int64_t*>(&x_dims.data()[0]);
    std::vector<int> 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]);
    }
    // add reshape layer
    int i_x_reshape_shape_data[2];
    for (size_t i = 0; i < 2; i++) {
        i_x_reshape_shape_data[i] = static_cast<int>(x_shape_data[i]);
    }
    int reshape_param[] = {0, -1};
    auto unique_op_reshape_name =
            lite::subgraph::bm::UniqueName(op_type + "_reshape");
    add_reshape_layer(graph->GetCompilerHandle(),
                      const_cast<const int*>(&i_x_shape_data[0]),
                      x_dims.size(),
                      static_cast<const char*>(x_var_name.c_str()),
                      const_cast<const int*>(&i_x_reshape_shape_data[0]),
                      2,
                      static_cast<const char*>(unique_op_reshape_name.c_str()),
                      const_cast<const int*>(reshape_param));

    auto y_var_name = op_info->Input("Y").front();
    auto y = scope->FindVar(y_var_name)->GetMutable<lite::Tensor>();
    auto y_dims = y->dims();
    // 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]);
    }
    add_fc_layer(graph->GetCompilerHandle(),
        const_cast<const int*>(&i_x_reshape_shape_data[0]),
        2,
        static_cast<const char*>(unique_op_reshape_name.c_str()),
        const_cast<const int*>(&i_output_shape_data[0]),
        output_dims.size(),
        static_cast<const char*>(output_var_name.c_str()),
        static_cast<const char*>(unique_op_name.c_str()),
        i_x_reshape_shape_data[1],
        i_output_shape_data[1],
        static_cast<const float*>(y->mutable_data<float>()),
        nullptr,
        0,
        0);
    graph->AddNode(output_var_name);
    return SUCCESS;
}

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

REGISTER_SUBGRAPH_BRIDGE(mul,
   kBM, paddle::lite::subgraph::bm::MulConverter);
