






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


SCREAMING_SNAKE_CASE__   :      Any				=		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   :      Union[str, Any]				=		{
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}
class     lowerCamelCase_					(   lowerCamelCase			):
				a__       							=	'''markuplm'''







				def __init__(    self							,       __lowerCAmelCase=3_0_5_2_2							,       __lowerCAmelCase=7_6_8							,       __lowerCAmelCase=1_2							,       __lowerCAmelCase=1_2							,       __lowerCAmelCase=3_0_7_2							,       __lowerCAmelCase="gelu"							,       __lowerCAmelCase=0.1							,       __lowerCAmelCase=0.1							,       __lowerCAmelCase=5_1_2							,       __lowerCAmelCase=2							,       __lowerCAmelCase=0.02							,       __lowerCAmelCase=1E-12							,       __lowerCAmelCase=0							,       __lowerCAmelCase=0							,       __lowerCAmelCase=2							,       __lowerCAmelCase=2_5_6							,       __lowerCAmelCase=1_0_2_4							,       __lowerCAmelCase=2_1_6							,       __lowerCAmelCase=1_0_0_1							,       __lowerCAmelCase=3_2							,       __lowerCAmelCase=5_0							,       __lowerCAmelCase="absolute"							,       __lowerCAmelCase=True							,       __lowerCAmelCase=None							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								super().__init__(
								    pad_token_id=__lowerCAmelCase							,       bos_token_id=__lowerCAmelCase							,       eos_token_id=__lowerCAmelCase							,       **__lowerCAmelCase							,       )
								__magic_name__		:Optional[Any]   =   vocab_size
								__magic_name__		:List[Any]   =   hidden_size
								__magic_name__		:Optional[Any]   =   num_hidden_layers
								__magic_name__		:int   =   num_attention_heads
								__magic_name__		:Optional[Any]   =   hidden_act
								__magic_name__		:Tuple   =   intermediate_size
								__magic_name__		:List[str]   =   hidden_dropout_prob
								__magic_name__		:int   =   attention_probs_dropout_prob
								__magic_name__		:Optional[Any]   =   max_position_embeddings
								__magic_name__		:Dict   =   type_vocab_size
								__magic_name__		:str   =   initializer_range
								__magic_name__		:Optional[int]   =   layer_norm_eps
								__magic_name__		:Optional[int]   =   position_embedding_type
								__magic_name__		:Dict   =   use_cache
								__magic_name__		:Union[str, Any]   =   classifier_dropout
								# additional properties
								__magic_name__		:str   =   max_depth
								__magic_name__		:List[Any]   =   max_xpath_tag_unit_embeddings
								__magic_name__		:Any   =   max_xpath_subs_unit_embeddings
								__magic_name__		:Any   =   tag_pad_id
								__magic_name__		:Dict   =   subs_pad_id
								__magic_name__		:int   =   xpath_unit_hidden_size












from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase







def      lowerCamelCase_						(			UpperCamelCase__							: str )	->			None:





				"""simple docstring"""


				__lowerCamelCase			,		__lowerCamelCase									=       analyze_text(UpperCamelCase__ )
				__lowerCamelCase									=       list(' ' + ascii_lowercase )
				# what is our total sum of probabilities.
				__lowerCamelCase									=       sum(single_char_strings.values() )

				# one length string
				__lowerCamelCase									=       0
				# for each alpha we go in our dict and if it is in it we calculate entropy
				for ch in my_alphas:
								if ch in single_char_strings:
												__lowerCamelCase									=       single_char_strings[ch]
												__lowerCamelCase									=       my_str / all_sum
												my_fir_sum += prob * math.loga(UpperCamelCase__ )  # entropy formula.

    # print entropy
				print(F"""{round(-1 * my_fir_sum ):.1f}""" )

				# two len string
				__lowerCamelCase									=       sum(two_char_strings.values() )
				__lowerCamelCase									=       0
				# for each alpha (two in size) calculate entropy.
				for cha in my_alphas:
								for cha in my_alphas:
												__lowerCamelCase									=       cha + cha
												if sequence in two_char_strings:
																__lowerCamelCase									=       two_char_strings[sequence]
																__lowerCamelCase									=       int(UpperCamelCase__ ) / all_sum
																my_sec_sum += prob * math.loga(UpperCamelCase__ )

    # print second entropy
				print(F"""{round(-1 * my_sec_sum ):.1f}""" )

				# print the difference between them
				print(F"""{round((-1 * my_sec_sum) - (-1 * my_fir_sum) ):.1f}""" )







def      lowerCamelCase_						(			UpperCamelCase__							: str )	->			tuple[dict, dict]:





				"""simple docstring"""


				__lowerCamelCase									=       Counter()  # type: ignore
				__lowerCamelCase									=       Counter()  # type: ignore
				single_char_strings[text[-1]] += 1

				# first case when we have space at start.
				two_char_strings[" " + text[0]] += 1
				for i in range(0					,	len(UpperCamelCase__ ) - 1 ):
								single_char_strings[text[i]] += 1
								two_char_strings[text[i : i + 2]] += 1
				return single_char_strings, two_char_strings







def      lowerCamelCase_						(			)	->			Dict:





				"""simple docstring"""


				import doctest

				doctest.testmod()
				# text = (
				#     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
				#     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
				#     "jointure saw horrible. He private he on be imagine suppose. Fertile "
				#     "beloved evident through no service elderly is. Blind there if every no so "
				#     "at. Own neglected you preferred way sincerity delivered his attempted. To "
				#     "of message cottage windows do besides against uncivil.  Delightful "
				#     "unreserved impossible few estimating men favourable see entreaties. She "
				#     "propriety immediate was improving. He or entrance humoured likewise "
				#     "moderate. Much nor game son say feel. Fat make met can must form into "
				#     "gate. Me we offending prevailed discovery. "
				# )

				# calculate_prob(text)


if __name__ == "__main__":
					main()


