/*
 * Copyright (c) 2019 Samsung Electronics Co., Ltd. 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 "TestHelper.h"

#include "Importer.h"

#include <loco.h>
#include <loco/IR/TensorShape.h>
#include <loco/IR/FeatureShape.h>
#include <nncc/core/ADT/tensor/Shape.h>
#include <plier/tf/TestHelper.h>

#include <gtest/gtest.h>

#include <memory>

using namespace moco::tf::test;

namespace
{
// clang-format off
const char *known_batch_pbtxt = STRING_CONTENT(
node {
  name: "placeholder"
  op: "Placeholder"
  attr {
    key: "dtype" value { type: DT_FLOAT }
  }
  attr {
    key: "shape"
    value {
      shape {
        dim { size: 1024 }
        dim { size: 2 }
        dim { size: 3 }
        dim { size: 4 }
      }
    }
  }
}
node {
  name: "output"
  op: "Identity"
  input: "placeholder"
  attr {
    key: "T" value { type: DT_FLOAT }
  }
}
);
// clang-format on

} // namespace

TEST(TensorFlowImport, placeholder_knwon_batch)
{
  // load graph
  moco::tf::Importer importer;
  moco::tf::ModelSignature signature;
  signature.add_output(moco::tf::TensorName("output", 0));

  tensorflow::GraphDef graph_def;
  EXPECT_TRUE(plier::tf::parse_graphdef(known_batch_pbtxt, graph_def));
  std::unique_ptr<loco::Graph> graph = importer.import(signature, graph_def);

  // get loco::Pull
  loco::Graph::NodeContext *loco_nodes = graph->nodes();
  loco::Pull *pull_node = dynamic_cast<loco::Pull *>(loco_nodes->at(0));

  // Check dim
  ASSERT_TRUE(pull_node->dim(0).known() && pull_node->dim(0).value() == 1024);
  ASSERT_TRUE(pull_node->dim(1).known() && pull_node->dim(1).value() == 2);
  ASSERT_TRUE(pull_node->dim(2).known() && pull_node->dim(2).value() == 3);
  ASSERT_TRUE(pull_node->dim(3).known() && pull_node->dim(3).value() == 4);
}