Mask subset folder

operators.val.mask_subset_folder(client, folder_values1_in='/folder_values1_in', folder_mask_in='/folder_mask_in', folder_values_out='/folder_values_out', worker_instance_type='x2large', manager_instance_type='small', extension_file_values1_in='.npy', extension_file_mask_in='.npy', extension_file_values_out='.txt', skip_existing_files=False)

mask_subset_folder(client,
folder_values1_in=’/folder_values1_in’,
folder_mask_in=’/folder_mask_in’,
folder_values_out=’/folder_values_out’,
worker_instance_type=’x2large’,
manager_instance_type=”small”,
extension_folder_values1_in=”.npy”,
extension_folder_mask_in=”.npy”,
extension_folder_values_out=”.txt”,
skip_existing_files = False )
Parameters:
  • folder_values1_in – input folder [.txt or .npy]

  • folder_mask_in – input folder that contains [0,1] values

  • folder_values_out – output folder [.txt or .npy]

  • worker_instance_type – cloud instance type of worker nodes

  • manager_instance_type – cloud instance type of manager node

  • extension_folder_values1_in – File extension of files in folder for folder_values1_in

  • extension_folder_mask_in – File extension of files in folder for folder_mask_in

  • extension_folder_values_out – File extension of files in folder for folder_values_out

  • skip_existing_files – skip files that already exist in the output folder