def _prepare_prompt_learning_config()

in src/peft/utils/other.py [0:0]

• 42 lines of code
• 18 McCabe index (conditional complexity)

def _prepare_prompt_learning_config(peft_config, model_config):
    # In case of VLM we focus on the language model portion of the model.
    if "text_config" in model_config:
        model_config = model_config["text_config"]

    if peft_config.num_layers is None:
        if "num_hidden_layers" in model_config:
            num_layers = model_config["num_hidden_layers"]
        elif "num_layers" in model_config:
            num_layers = model_config["num_layers"]
        elif "n_layer" in model_config:
            num_layers = model_config["n_layer"]
        else:
            raise ValueError("Please specify `num_layers` in `peft_config`")
        peft_config.num_layers = num_layers

    if peft_config.token_dim is None:
        if "hidden_size" in model_config:
            token_dim = model_config["hidden_size"]
        elif "n_embd" in model_config:
            token_dim = model_config["n_embd"]
        elif "d_model" in model_config:
            token_dim = model_config["d_model"]
        else:
            raise ValueError("Please specify `token_dim` in `peft_config`")
        peft_config.token_dim = token_dim

    if peft_config.num_attention_heads is None:
        if "num_attention_heads" in model_config:
            num_attention_heads = model_config["num_attention_heads"]
        elif "n_head" in model_config:
            num_attention_heads = model_config["n_head"]
        elif "num_heads" in model_config:
            num_attention_heads = model_config["num_heads"]
        elif "encoder_attention_heads" in model_config:
            num_attention_heads = model_config["encoder_attention_heads"]
        else:
            raise ValueError("Please specify `num_attention_heads` in `peft_config`")
        peft_config.num_attention_heads = num_attention_heads

    # For grouped-query attention, see #1901.
    if peft_config.peft_type == "PREFIX_TUNING" and "num_key_value_heads" in model_config:
        num_key_value_heads = model_config["num_key_value_heads"]
        peft_config.token_dim = peft_config.token_dim // peft_config.num_attention_heads * num_key_value_heads
        peft_config.num_attention_heads = num_key_value_heads

    if getattr(peft_config, "encoder_hidden_size", None) is None:
        setattr(peft_config, "encoder_hidden_size", peft_config.token_dim)

    return peft_config