Random Selection of Fairseq Model and Dataset

This function randomly selects a model and dataset from the Fairseq library for model training.

Technology Stack : Fairseq, PyTorch

Code Type : Fairseq model and dataset random selection

Code Difficulty : Intermediate

                
                    
def random_fairseq_model_selection(args, dataset):
    """
    This function randomly selects a Fairseq model and dataset for training.
    """
    import random
    from fairseq.models import FairseqModel
    from fairseq.data import FairseqDataset

    # List of available Fairseq models
    models = ["transformer", "convolutional", "lstm", "gru", "transformer_xl"]

    # Randomly select a model
    selected_model = random.choice(models)

    # List of available Fairseq datasets
    datasets = ["wmt14_en_de", "opus15_en_de", "wmt16_en_de", "wmt17_en_de", "wmt18_en_de"]

    # Randomly select a dataset
    selected_dataset = random.choice(datasets)

    # Create model and dataset objects
    model = FairseqModel.from_pretrained(selected_model)
    data = FairseqDataset.from_pretrained(selected_dataset)

    # Return the selected model and dataset
    return model, data