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.
  from typing import Optional
  
  from flash.core.data.utils import download_data
  from flash.core.utilities.flash_cli import FlashCLI
  from flash.pointcloud import PointCloudSegmentation, PointCloudSegmentationData
  
  __all__ = ["pointcloud_segmentation"]
  
  
  def from_kitti(
      batch_size: int = 4,
      num_workers: Optional[int] = None,
      **preprocess_kwargs,
  ) -> PointCloudSegmentationData:
      """Downloads and loads the semantic KITTI data set."""
      download_data("https://pl-flash-data.s3.amazonaws.com/SemanticKittiTiny.zip", "data/")
      return PointCloudSegmentationData.from_folders(
          train_folder="data/SemanticKittiTiny/train",
          val_folder="data/SemanticKittiTiny/val",
          batch_size=batch_size,
          num_workers=num_workers,
          **preprocess_kwargs,
      )
  
  
  def pointcloud_segmentation():
      """Segment objects in point clouds."""
      cli = FlashCLI(
          PointCloudSegmentation,
          PointCloudSegmentationData,
          default_datamodule_builder=from_kitti,
          default_arguments={
              "trainer.max_epochs": 3,
              "model.backbone": "randlanet_semantic_kitti",
          },
          finetune=False,
      )
  
      cli.trainer.save_checkpoint("pointcloud_segmentation_model.pt")
  
  
  if __name__ == "__main__":
      pointcloud_segmentation()
  