'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_	:		List[str]			=     logging.get_logger(__name__)

lowerCAmelCase_	:		Tuple			=     {
    """alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}




class 		SCREAMING_SNAKE_CASE     (					SCREAMING_SNAKE_CASE	):







				'''simple docstring'''
				UpperCAmelCase__							=							'''mgp-str'''





				def __init__(						self					:						Tuple       ,		lowercase__					:						int=[32, 128]       ,		lowercase__					:						int=4       ,		lowercase__					:						str=3       ,		lowercase__					:						Dict=27       ,		lowercase__					:						str=38       ,		lowercase__					:						str=50_257       ,		lowercase__					:						Union[str, Any]=30_522       ,		lowercase__					:						List[Any]=768       ,		lowercase__					:						Any=12       ,		lowercase__					:						Any=12       ,		lowercase__					:						Dict=4.0       ,		lowercase__					:						int=True       ,		lowercase__					:						int=False       ,		lowercase__					:						Optional[int]=1e-5       ,		lowercase__					:						Union[str, Any]=0.0       ,		lowercase__					:						Optional[int]=0.0       ,		lowercase__					:						Optional[int]=0.0       ,		lowercase__					:						Dict=False       ,		lowercase__					:						Any=0.0_2       ,		**lowercase__					:						Optional[int]       ,		)							->List[str]:


										'''simple docstring'''




										super().__init__(**lowercase__					)

										_UpperCamelCase			:			Optional[Any]   			=						image_size
										_UpperCamelCase			:			List[Any]   			=						patch_size
										_UpperCamelCase			:			List[str]   			=						num_channels
										_UpperCamelCase			:			Dict   			=						max_token_length
										_UpperCamelCase			:			int   			=						num_character_labels
										_UpperCamelCase			:			Optional[Any]   			=						num_bpe_labels
										_UpperCamelCase			:			Dict   			=						num_wordpiece_labels
										_UpperCamelCase			:			Union[str, Any]   			=						hidden_size
										_UpperCamelCase			:			Optional[Any]   			=						num_hidden_layers
										_UpperCamelCase			:			Optional[Any]   			=						num_attention_heads
										_UpperCamelCase			:			Optional[int]   			=						mlp_ratio
										_UpperCamelCase			:			Optional[int]   			=						distilled
										_UpperCamelCase			:			List[Any]   			=						layer_norm_eps
										_UpperCamelCase			:			List[Any]   			=						drop_rate
										_UpperCamelCase			:			Union[str, Any]   			=						qkv_bias
										_UpperCamelCase			:			Union[str, Any]   			=						attn_drop_rate
										_UpperCamelCase			:			List[str]   			=						drop_path_rate
										_UpperCamelCase			:			Dict   			=						output_aa_attentions
										_UpperCamelCase			:			List[Any]   			=						initializer_range



'''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_	:		Optional[int]			=     logging.getLogger(__name__)

if __name__ == "__main__":
			lowerCAmelCase_	:		Optional[Any]			=     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=3_0522, type=int)
			lowerCAmelCase_	:		str			=     parser.parse_args()

			logger.info(f"""Loading data from {args.data_file}""")
			with open(args.data_file, """rb""") as fp:
						lowerCAmelCase_	:		Tuple			=     pickle.load(fp)

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


