SuperposPrompt_Thesis/_utils.py

def prefix_dict_keys(prefix, input_dict):
    return {f'{prefix}_{key}': val for key, val in input_dict.items()}

def print_system_info():
    from platform import python_version
    print(f"Python version is: {python_version()}")
    
    try:
        import sklearn
        print(f"Scikit-learn version is: {sklearn.__version__}")
    except:
        print("Scikit-learn not found!!!")
    
    try:
        import torch
        print(f"Torch version is: {torch.__version__}")
        if torch.cuda.is_available() and torch.cuda.device_count() >= 0:
            print(f"Nvidia device is: {torch.cuda.get_device_name(0)}")
        else:
            print("Torch is using CPU")
    except:
        print("Torch not found!!!")
        return

    try:
        import transformers
        print(f"Transformers version is: {transformers.__version__}")
        try:
            print(f"Adapterhub version is: {transformers.adapters.__version__}")
        except:
            print("Adapterhub not found!!!")
    except:
        print("Transformers not found!!!")

def silent_logs():
    import os
    os.environ["WANDB_SILENT"] = "true"
    # os.environ["TRANSFORMERS_VERBOSITY"] = "fatal"
    os.environ["TRANSFORMERS_NO_ADVISORY_WARNINGS"] = "1"
    os.environ["ACCELERATE_LOG_LEVEL"] = "CRITICAL"
    import transformers
    from transformers.utils import logging
    logging.set_verbosity(transformers.logging.FATAL)
    from datasets.utils.logging import disable_progress_bar, set_verbosity_error
    disable_progress_bar()
    set_verbosity_error()
    
    import accelerate.utils.other as accelerate_other
    accelerate_other.logger.setLevel(50)

def sp_encode(data):
    import json
    import base64
    return base64.b32encode(json.dumps(data).encode())

def sp_decode(encoded_data):
    import json
    import base64
    return json.loads(base64.b32decode(encoded_data).decode())