def generate_random_data_sample(T, B=1, D=80):
    """Generate random data sample given the T, B, D values"""
    net_input = {
        "src_tokens": torch.tensor(random_number_generator.randn(B, T, D)).float(),
        "src_lengths": torch.tensor([T]),
    }
    return {"net_input": net_input}
Generate random data sample given the T, B, D values
understand_icl/fairseq/examples/speech_to_speech/benchmarking/data_utils.py