generators.py - cmikke97/Automatic-Malware-Signature-Generation GitHub Wiki

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Imported Modules



  • from .dataset import Dataset

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Classes and functions

GeneratorFactory (class) - Generator factory class.

  • __init__(self, ds_root, batch_size, mode, num_workers, n_samples, use_malicious_labels, use_count_labels, use_tag_labels, return_shas, shuffle) (member function) - Initialize generator factory class.
    • ds_root (arg) - Path of the directory where to find the pre-processed dataset (containing .dat files)
    • batch_size (arg) - How many samples per batch to load (default: None -> 1024)
    • mode (arg) - Mode of use of the dataset object (may be 'train', 'validation' or 'test') (default: 'train')
    • num_workers (arg) - How many subprocesses to use for data loading by the Dataloader (default: max_workers)
    • n_samples (arg) - Number of samples to consider (used just to access the right pre-processed files) (default: None -> all)
    • use_malicious_labels (arg) - Whether to return the malicious label for the data points or not (default: False)
    • use_count_labels (arg) - Whether to return the counts for the data points or not (default: False)
    • use_tag_labels (arg) - Whether to return the tags for the data points or not (default: False)
    • return_shas (arg) - Whether to return the sha256 of the data points or not (default: False)
    • shuffle (arg) - Set to True to have the data reshuffled at every epoch (default: None -> if mode is 'train' then shuffle is set to True, otherwise it is set to False)
  • __call__(self) (member function) - Generator-factory call method.

get_generator(ds_root, batch_size, mode, num_workers, n_samples, use_malicious_labels, use_count_labels, use_count_labels, use_tag_labels, return_shas, shuffle) (function) - Get generator based on the provided arguments.

  • ds_root (arg) - Path of the directory where to find the pre-processed dataset (containing .dat files)
  • batch_size (arg) - How many samples per batch to load (default: 8192)
  • mode (arg) - Mode of use of the dataset object (may be 'train', 'validation' or 'test') (default: 'train')
  • num_workers (arg) - How many subprocesses to use for data loading by the Dataloader (if None -> set to current system cpu count) (default: None)
  • n_samples (arg) - Number of samples to consider (used just to access the right pre-processed files) (default: None -> all)
  • use_malicious_labels (arg) - Whether to return the malicious label for the data points or not (default: False)
  • use_count_labels (arg) - Whether to return the counts for the data points or not (default: False)
  • use_tag_labels (arg) - Whether to return the tags for the data points or not (default: False)
  • return_shas (arg) - Whether to return the sha256 of the data points or not (default: False)
  • shuffle (arg) - Set to True to have the data reshuffled at every epoch (default: None -> if mode is 'train' then shuffle is set to True, otherwise it is set to False)

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