argmax_op.cc

// 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 "lite/kernels/npu/bridges/graph.h"
#include "lite/kernels/npu/bridges/registry.h"
#include "lite/kernels/npu/bridges/utility.h"

namespace paddle {
namespace lite {
namespace subgraph {
namespace npu {

int ArgmaxConverter(void* ctx, OpLite* op, KernelBase* kernel) {
  CHECK(ctx != nullptr);
  CHECK(op != nullptr);
  auto graph = static_cast<Graph*>(ctx);
  auto op_info = op->op_info();
  auto op_type = op_info->Type();
  auto scope = op->scope();
  VLOG(3) << "[NPU] Converting " + op_type + "...";

  // Get input and output vars and op attributes
  auto x_name = op_info->Input("X").front();
  auto x = scope->FindMutableTensor(x_name);
  auto x_dims = x->dims();
  auto out_name = op_info->Output("Out").front();
  int axis = op_info->GetAttr<int64_t>("axis");

  // X node
  std::shared_ptr<Node> x_node = nullptr;
  if (graph->Has(x_name)) {
    x_node = graph->Get(x_name);
  } else {
    x_node = graph->Add(x_name, *x);
  }

  // Axis node
  auto axis_node = graph->Add(out_name + "/axis", axis);

  // Argmax node
  auto argmax_node = graph->Add<ge::op::ArgMax>(out_name);
  auto argmax_op = argmax_node->data<ge::op::ArgMax>();
  argmax_op->set_input_x1(*x_node->data());
  argmax_op->set_input_x2(*axis_node->data());
  return SUCCESS;
}

}  // namespace npu
}  // namespace subgraph
}  // namespace lite
}  // namespace paddle

REGISTER_SUBGRAPH_BRIDGE(arg_max,
                         kNPU,
                         paddle::lite::subgraph::npu::ArgmaxConverter);