text: # Copyright The PyTorch Lightning team.
  #
  # 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.
  import os
  
  import pytest
  import torch
  
  from flash import Trainer
  from flash.text import TextClassifier
  
  # ======== Mock functions ========
  
  
  class DummyDataset(torch.utils.data.Dataset):
  
      def __getitem__(self, index):
          return {
              "input_ids": torch.randint(1000, size=(100, )),
              "labels": torch.randint(2, size=(1, )).item(),
          }
  
      def __len__(self) -> int:
          return 100
  
  
  # ==============================
  
  TEST_BACKBONE = "prajjwal1/bert-tiny"  # super small model for testing
  
  
  @pytest.mark.skipif(os.name == "nt", reason="Huggingface timing out on Windows")
  def test_init_train(tmpdir):
      model = TextClassifier(2, TEST_BACKBONE)
      train_dl = torch.utils.data.DataLoader(DummyDataset())
      trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True)
      trainer.fit(model, train_dl)
  