

"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
_lowerCAmelCase         =							logging.getLogger(__name__)

if __name__ == "__main__":
							_lowerCAmelCase         =							argparse.ArgumentParser(
							    description="Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"
							)
							parser.add_argument(
							    "--data_file", type=str, default="data/dump.bert-base-uncased.pickle", help="The binarized dataset."
							)
							parser.add_argument(
							    "--token_counts_dump", type=str, default="data/token_counts.bert-base-uncased.pickle", help="The dump file."
							)
							parser.add_argument("--vocab_size", default=30_522, type=int)
							_lowerCAmelCase         =							parser.parse_args()

							logger.info(F'Loading data from {args.data_file}')
							with open(args.data_file, "rb") as fp:
														_lowerCAmelCase         =							pickle.load(fp)

							logger.info("Counting occurrences for MLM.")
							_lowerCAmelCase         =							Counter()
							for tk_ids in data:
														counter.update(tk_ids)
							_lowerCAmelCase         =							[0] * args.vocab_size
							for k, v in counter.items():
														_lowerCAmelCase         =							v

							logger.info(F'Dump to {args.token_counts_dump}')
							with open(args.token_counts_dump, "wb") as handle:
														pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)









"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase         =							{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCAmelCase         =							[
							    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "LukeForEntityClassification",
							    "LukeForEntityPairClassification",
							    "LukeForEntitySpanClassification",
							    "LukeForMultipleChoice",
							    "LukeForQuestionAnswering",
							    "LukeForSequenceClassification",
							    "LukeForTokenClassification",
							    "LukeForMaskedLM",
							    "LukeModel",
							    "LukePreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
							from .tokenization_luke import LukeTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_luke import (
														    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LukeForEntityClassification,
														    LukeForEntityPairClassification,
														    LukeForEntitySpanClassification,
														    LukeForMaskedLM,
														    LukeForMultipleChoice,
														    LukeForQuestionAnswering,
														    LukeForSequenceClassification,
														    LukeForTokenClassification,
														    LukeModel,
														    LukePreTrainedModel,
														)

else:
							import sys

							_lowerCAmelCase         =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

