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FlameSky edited this page Jun 9, 2022 · 7 revisions

1. MMSA_run

The MMSA_run function is the main function of this project. It runs MSA experiments on datasets and models specified in the parameters.

Parameters:

  • model_name(required): Name of MSA model, see Supported Models for details.
  • dataset_name(required): Name of MSA dataset, see Supported Datasets for details.
  • config_file: Path to config file. Default config file will be used if not specified. See Config Files for details.
  • config: Config in the format of Python dict. Used to override arguments in config_file. Ignored in tune mode.
  • seeds: List of seeds. Default: [1111, 1112, 1113, 1114, 1115]
  • is_tune: Tuning mode switch. See Tuning Mode for details. Default: False
  • tune_times: # Sets of hyper parameters to tune. Default: 50
  • feature_T: Path to text feature file. Provide an empty string to use default BERT features. Default: ""
  • feature_A: Path to audio feature file. Provide an empty string to use default features provided by dataset creators. Default: ""
  • feature_V: Path to video feature file. Provide an empty string to use default features provided by dataset creators. Default: ""
  • model_save_dir: Path to save trained models. Default: ~/MMSA/saved_models
  • res_save_dir: Path to save csv results. Default: ~/MMSA/results
  • log_dir: Path to save log files. Default: ~/MMSA/logs
  • gpu_ids: GPUs to use. Will assign the most memory-free gpu if an empty list is provided. Default: [0]. Currently only supports single gpu.
  • num_workers: Number of workers used to load data. Default: 4
  • verbose_level: Verbose level of stdout. 0 for error, 1 for info, 2 for debug. Default: 1
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