code: def load_data(
      inputs,
      output_folder,
      input_directory=None,
      ground_truth=None,
      input_data=None,
      verbose=True,
  ):
      """A convenience function when building single-input pipelines. This function
      quickly builds DataCollections
      """
  
      if any(data is None for data in inputs):
          raise ValueError(
              "Cannot run pipeline; required inputs are missing. Please consult this module's documentation, and make sure all required parameters are input."
          )
  
      inputs = [
          os.path.abspath(input_filename) for input_filename in inputs
      ]
      output_folder = os.path.abspath(output_folder)
  
      input_data = {"input_data": inputs}
  
      if ground_truth is not None:
          input_data["ground_truth"] = [ground_truth]
  
      if input_directory is None:
          if any(data is None for data in input_data):
              raise ValueError(
                  "Cannot run pipeline; required inputs are missing. Please consult this module's documentation, and make sure all required parameters are input."
              )
  
          data_collection = DataCollection(verbose=verbose)
          data_collection.add_case(input_data, case_name=output_folder)
  
      else:
          data_collection = DataCollection(
              input_directory,
              data_group_dict=input_data,
              verbose=verbose,
          )
  
      if not os.path.exists(output_folder):
          os.makedirs(output_folder)
  
      if verbose:
          print("File loading completed.")
  
      return data_collection
  
file_path: DeepNeuro/deepneuro/pipelines/shared.py
imports: import os
  import sys
  import argparse
  from shutil import copy
  from deepneuro.data.data_collection import DataCollection
  from deepneuro.container.container_cli import nvidia_docker_wrapper
label_desc: Use image node_id 1 for calling a global function with example usage: load_data(inputs, output_folder, input_directory, ground_truth, input_data, verbose) and returns: data_collection