blink/common/params.py [64:144]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        parser = self.add_argument_group("Common Arguments")
        parser.add_argument(
            "--silent", action="store_true", help="Whether to print progress bars."
        )
        parser.add_argument(
            "--debug",
            action="store_true",
            help="Whether to run in debug mode with only 200 samples.",
        )
        parser.add_argument(
            "--data_parallel",
            action="store_true",
            help="Whether to distributed the candidate generation process.",
        )
        parser.add_argument(
            "--no_cuda", action="store_true", 
            help="Whether not to use CUDA when available",
        )
        parser.add_argument("--top_k", default=10, type=int) 
        parser.add_argument(
            "--seed", type=int, default=52313, help="random seed for initialization"
        )
        parser.add_argument(
            "--zeshel",
            default=True,
            type=bool,
            help="Whether the dataset is from zeroshot.",
        )

    def add_model_args(self, args=None):
        """
        Add model args.
        """
        parser = self.add_argument_group("Model Arguments")
        parser.add_argument(
            "--max_seq_length",
            default=256,
            type=int,
            help="The maximum total input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        )
        parser.add_argument(
            "--max_context_length",
            default=128,
            type=int,
            help="The maximum total context input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        )
        parser.add_argument(
            "--max_cand_length",
            default=128,
            type=int,
            help="The maximum total label input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        ) 
        parser.add_argument(
            "--path_to_model",
            default=None,
            type=str,
            required=False,
            help="The full path to the model to load.",
        )
        parser.add_argument(
            "--bert_model",
            default="bert-base-uncased",
            type=str,
            help="Bert pre-trained model selected in the list: bert-base-uncased, "
            "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.",
        )
        parser.add_argument(
            "--pull_from_layer", type=int, default=-1, help="Layers to pull from BERT",
        )
        parser.add_argument(
            "--lowercase",
            action="store_false",
            help="Whether to lower case the input text. True for uncased models, False for cased models.",
        )
        parser.add_argument("--context_key", default="context", type=str)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



elq/common/params.py [64:144]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        parser = self.add_argument_group("Common Arguments")
        parser.add_argument(
            "--silent", action="store_true", help="Whether to print progress bars."
        )
        parser.add_argument(
            "--debug",
            action="store_true",
            help="Whether to run in debug mode with only 200 samples.",
        )
        parser.add_argument(
            "--data_parallel",
            action="store_true",
            help="Whether to distributed the candidate generation process.",
        )
        parser.add_argument(
            "--no_cuda", action="store_true", 
            help="Whether not to use CUDA when available",
        )
        parser.add_argument("--top_k", default=10, type=int) 
        parser.add_argument(
            "--seed", type=int, default=52313, help="random seed for initialization"
        )
        parser.add_argument(
            "--zeshel",
            default=True,
            type=bool,
            help="Whether the dataset is from zeroshot.",
        )

    def add_model_args(self, args=None):
        """
        Add model args.
        """
        parser = self.add_argument_group("Model Arguments")
        parser.add_argument(
            "--max_seq_length",
            default=256,
            type=int,
            help="The maximum total input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        )
        parser.add_argument(
            "--max_context_length",
            default=128,
            type=int,
            help="The maximum total context input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        )
        parser.add_argument(
            "--max_cand_length",
            default=128,
            type=int,
            help="The maximum total label input sequence length after WordPiece tokenization. \n"
            "Sequences longer than this will be truncated, and sequences shorter \n"
            "than this will be padded.",
        ) 
        parser.add_argument(
            "--path_to_model",
            default=None,
            type=str,
            required=False,
            help="The full path to the model to load.",
        )
        parser.add_argument(
            "--bert_model",
            default="bert-base-uncased",
            type=str,
            help="Bert pre-trained model selected in the list: bert-base-uncased, "
            "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.",
        )
        parser.add_argument(
            "--pull_from_layer", type=int, default=-1, help="Layers to pull from BERT",
        )
        parser.add_argument(
            "--lowercase",
            action="store_false",
            help="Whether to lower case the input text. True for uncased models, False for cased models.",
        )
        parser.add_argument("--context_key", default="context", type=str)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -