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"""
DatasetArgs Class
=================
"""
from dataclasses import dataclass
import textattack
from textattack.shared.utils import ARGS_SPLIT_TOKEN, load_module_from_file
HUGGINGFACE_DATASET_BY_MODEL = {
#
# bert-base-uncased
#
"bert-base-uncased-ag-news": ("ag_news", None, "test"),
"bert-base-uncased-cola": ("glue", "cola", "validation"),
"bert-base-uncased-imdb": ("imdb", None, "test"),
"bert-base-uncased-mnli": (
"glue",
"mnli",
"validation_matched",
None,
{0: 1, 1: 2, 2: 0},
),
"bert-base-uncased-mrpc": ("glue", "mrpc", "validation"),
"bert-base-uncased-qnli": ("glue", "qnli", "validation"),
"bert-base-uncased-qqp": ("glue", "qqp", "validation"),
"bert-base-uncased-rte": ("glue", "rte", "validation"),
"bert-base-uncased-sst2": ("glue", "sst2", "validation"),
"bert-base-uncased-stsb": (
"glue",
"stsb",
"validation",
None,
None,
None,
5.0,
),
"bert-base-uncased-wnli": ("glue", "wnli", "validation"),
"bert-base-uncased-mr": ("rotten_tomatoes", None, "test"),
"bert-base-uncased-snli": ("snli", None, "test", None, {0: 1, 1: 2, 2: 0}),
"bert-base-uncased-yelp": ("yelp_polarity", None, "test"),
#
# distilbert-base-cased
#
"distilbert-base-cased-cola": ("glue", "cola", "validation"),
"distilbert-base-cased-mrpc": ("glue", "mrpc", "validation"),
"distilbert-base-cased-qqp": ("glue", "qqp", "validation"),
"distilbert-base-cased-snli": ("snli", None, "test"),
"distilbert-base-cased-sst2": ("glue", "sst2", "validation"),
"distilbert-base-cased-stsb": (
"glue",
"stsb",
"validation",
None,
None,
None,
5.0,
),
"distilbert-base-uncased-ag-news": ("ag_news", None, "test"),
"distilbert-base-uncased-cola": ("glue", "cola", "validation"),
"distilbert-base-uncased-imdb": ("imdb", None, "test"),
"distilbert-base-uncased-mnli": (
"glue",
"mnli",
"validation_matched",
None,
{0: 1, 1: 2, 2: 0},
),
"distilbert-base-uncased-mr": ("rotten_tomatoes", None, "test"),
"distilbert-base-uncased-mrpc": ("glue", "mrpc", "validation"),
"distilbert-base-uncased-qnli": ("glue", "qnli", "validation"),
"distilbert-base-uncased-rte": ("glue", "rte", "validation"),
"distilbert-base-uncased-wnli": ("glue", "wnli", "validation"),
#
# roberta-base (RoBERTa is cased by default)
#
"roberta-base-ag-news": ("ag_news", None, "test"),
"roberta-base-cola": ("glue", "cola", "validation"),
"roberta-base-imdb": ("imdb", None, "test"),
"roberta-base-mr": ("rotten_tomatoes", None, "test"),
"roberta-base-mrpc": ("glue", "mrpc", "validation"),
"roberta-base-qnli": ("glue", "qnli", "validation"),
"roberta-base-rte": ("glue", "rte", "validation"),
"roberta-base-sst2": ("glue", "sst2", "validation"),
"roberta-base-stsb": ("glue", "stsb", "validation", None, None, None, 5.0),
"roberta-base-wnli": ("glue", "wnli", "validation"),
#
# albert-base-v2 (ALBERT is cased by default)
#
"albert-base-v2-ag-news": ("ag_news", None, "test"),
"albert-base-v2-cola": ("glue", "cola", "validation"),
"albert-base-v2-imdb": ("imdb", None, "test"),
"albert-base-v2-mr": ("rotten_tomatoes", None, "test"),
"albert-base-v2-rte": ("glue", "rte", "validation"),
"albert-base-v2-qqp": ("glue", "qqp", "validation"),
"albert-base-v2-snli": ("snli", None, "test"),
"albert-base-v2-sst2": ("glue", "sst2", "validation"),
"albert-base-v2-stsb": ("glue", "stsb", "validation", None, None, None, 5.0),
"albert-base-v2-wnli": ("glue", "wnli", "validation"),
"albert-base-v2-yelp": ("yelp_polarity", None, "test"),
#
# xlnet-base-cased
#
"xlnet-base-cased-cola": ("glue", "cola", "validation"),
"xlnet-base-cased-imdb": ("imdb", None, "test"),
"xlnet-base-cased-mr": ("rotten_tomatoes", None, "test"),
"xlnet-base-cased-mrpc": ("glue", "mrpc", "validation"),
"xlnet-base-cased-rte": ("glue", "rte", "validation"),
"xlnet-base-cased-stsb": (
"glue",
"stsb",
"validation",
None,
None,
None,
5.0,
),
"xlnet-base-cased-wnli": ("glue", "wnli", "validation"),
}
#
# Models hosted by textattack.
#
TEXTATTACK_DATASET_BY_MODEL = {
#
# LSTMs
#
"lstm-ag-news": ("ag_news", None, "test"),
"lstm-imdb": ("imdb", None, "test"),
"lstm-mr": ("rotten_tomatoes", None, "test"),
"lstm-sst2": ("glue", "sst2", "validation"),
"lstm-yelp": ("yelp_polarity", None, "test"),
#
# CNNs
#
"cnn-ag-news": ("ag_news", None, "test"),
"cnn-imdb": ("imdb", None, "test"),
"cnn-mr": ("rotten_tomatoes", None, "test"),
"cnn-sst2": ("glue", "sst2", "validation"),
"cnn-yelp": ("yelp_polarity", None, "test"),
#
# T5 for translation
#
"t5-en-de": (
"textattack.datasets.helpers.TedMultiTranslationDataset",
"en",
"de",
),
"t5-en-fr": (
"textattack.datasets.helpers.TedMultiTranslationDataset",
"en",
"fr",
),
"t5-en-ro": (
"textattack.datasets.helpers.TedMultiTranslationDataset",
"en",
"de",
),
#
# T5 for summarization
#
"t5-summarization": ("gigaword", None, "test"),
}
@dataclass
class DatasetArgs:
"""Arguments for loading dataset from command line input."""
dataset_by_model: str = None
dataset_from_huggingface: str = None
dataset_from_file: str = None
dataset_split: str = None
filter_by_labels: list = None
@classmethod
def _add_parser_args(cls, parser):
"""Adds dataset-related arguments to an argparser."""
dataset_group = parser.add_mutually_exclusive_group()
dataset_group.add_argument(
"--dataset-by-model",
type=str,
required=False,
default=None,
help="Dataset to load depending on the name of the model",
)
dataset_group.add_argument(
"--dataset-from-huggingface",
type=str,
required=False,
default=None,
help="Dataset to load from `datasets` repository.",
)
dataset_group.add_argument(
"--dataset-from-file",
type=str,
required=False,
default=None,
help="Dataset to load from a file.",
)
parser.add_argument(
"--dataset-split",
type=str,
required=False,
default=None,
help="Split of dataset to use when specifying --dataset-by-model or --dataset-from-huggingface.",
)
parser.add_argument(
"--filter-by-labels",
nargs="+",
type=int,
required=False,
default=None,
help="List of labels to keep in the dataset and discard all others.",
)
return parser
@classmethod
def _create_dataset_from_args(cls, args):
"""Given ``DatasetArgs``, return specified
``textattack.dataset.Dataset`` object."""
assert isinstance(
args, cls
), f"Expect args to be of type `{type(cls)}`, but got type `{type(args)}`."
# Automatically detect dataset for huggingface & textattack models.
# This allows us to use the --model shortcut without specifying a dataset.
if hasattr(args, "model"):
args.dataset_by_model = args.model
if args.dataset_by_model in HUGGINGFACE_DATASET_BY_MODEL:
args.dataset_from_huggingface = HUGGINGFACE_DATASET_BY_MODEL[
args.dataset_by_model
]
elif args.dataset_by_model in TEXTATTACK_DATASET_BY_MODEL:
dataset = TEXTATTACK_DATASET_BY_MODEL[args.dataset_by_model]
if dataset[0].startswith("textattack"):
# unsavory way to pass custom dataset classes
# ex: dataset = ('textattack.datasets.helpers.TedMultiTranslationDataset', 'en', 'de')
dataset = eval(f"{dataset[0]}")(*dataset[1:])
return dataset
else:
args.dataset_from_huggingface = dataset
# Get dataset from args.
if args.dataset_from_file:
textattack.shared.logger.info(
f"Loading model and tokenizer from file: {args.model_from_file}"
)
if ARGS_SPLIT_TOKEN in args.dataset_from_file:
dataset_file, dataset_name = args.dataset_from_file.split(
ARGS_SPLIT_TOKEN
)
else:
dataset_file, dataset_name = args.dataset_from_file, "dataset"
try:
dataset_module = load_module_from_file(dataset_file)
except Exception:
raise ValueError(f"Failed to import file {args.dataset_from_file}")
try:
dataset = getattr(dataset_module, dataset_name)
except AttributeError:
raise AttributeError(
f"Variable ``dataset`` not found in module {args.dataset_from_file}"
)
elif args.dataset_from_huggingface:
dataset_args = args.dataset_from_huggingface
if isinstance(dataset_args, str):
if ARGS_SPLIT_TOKEN in dataset_args:
dataset_args = dataset_args.split(ARGS_SPLIT_TOKEN)
else:
dataset_args = (dataset_args,)
if args.dataset_split:
if len(dataset_args) > 1:
dataset_args = (
dataset_args[:2] + (args.dataset_split,) + dataset_args[3:]
)
dataset = textattack.datasets.HuggingFaceDataset(
*dataset_args, shuffle=False
)
else:
dataset = textattack.datasets.HuggingFaceDataset(
*dataset_args, split=args.dataset_split, shuffle=False
)
else:
dataset = textattack.datasets.HuggingFaceDataset(
*dataset_args, shuffle=False
)
else:
raise ValueError("Must supply pretrained model or dataset")
assert isinstance(
dataset, textattack.datasets.Dataset
), "Loaded `dataset` must be of type `textattack.datasets.Dataset`."
if args.filter_by_labels:
dataset.filter_by_labels_(args.filter_by_labels)
return dataset
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