Source code for modelzoo.transformers.pytorch.gptj.utils

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[docs]def set_defaults(params): """ Update any missing parameters in the params dictionary with default values Args: params: The dictionary containing the params """ if params["train_input"]["data_processor"] == "Gpt2SyntheticDataProcessor": if "train_input" in params: params["train_input"]["vocab_size"] = params["train_input"].get( "vocab_size", params["model"]["vocab_size"] ) assert ( params["train_input"]["vocab_size"] == params["model"]["vocab_size"] ), f"Found different vocab_size in train_input ({params['train_input']['vocab_size']}) vs. model ({params['model']['vocab_size']})" params["train_input"]["max_sequence_length"] = params[ "train_input" ].get( "max_sequence_length", params["model"]["max_position_embeddings"], ) if "eval_input" in params: params["eval_input"]["vocab_size"] = params["eval_input"].get( "vocab_size", params["model"]["vocab_size"] ) assert ( params["eval_input"]["vocab_size"] == params["model"]["vocab_size"] ), f"Found different vocab_size in eval_input ({params['eval_input']['vocab_size']}) vs. model ({params['model']['vocab_size']})" params["eval_input"]["max_sequence_length"] = params[ "eval_input" ].get( "max_sequence_length", params["model"]["max_position_embeddings"], ) params["model"]["use_bfloat16"] = params["model"].get("use_bfloat16", True) params["optimizer"]["loss_scaling_factor"] = params["optimizer"].get( "loss_scaling_factor", 1.0 ) params["optimizer"]["log_summaries"] = params["optimizer"].get( "log_summaries", False ) params["runconfig"]["precision_opt_level"] = params["runconfig"].get( "precision_opt_level", 1 ) from modelzoo.transformers.pytorch.gpt2.utils import set_attention_kernel set_attention_kernel(params)