
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase	      = logging.get_logger(__name__)

UpperCAmelCase	      = "▁"

UpperCAmelCase	      = {"vocab_file": "vocab.txt", "sentencepiece_model_ckpt": "sentencepiece.bpe.model"}

UpperCAmelCase	      = {
    "sentencepiece_model_file": "sentencepiece.bpe.model",
    "vocab_file": "vocab.txt",
}

UpperCAmelCase	      = {
    "vocab_file": {
        "ernie-m-base": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt",
        "ernie-m-large": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt",
    },
    "sentencepiece_model_file": {
        "ernie-m-base": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model",
        "ernie-m-large": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model",
    },
}

UpperCAmelCase	      = {
    "ernie-m-base": 514,
    "ernie-m-large": 514,
}

UpperCAmelCase	      = {
    "ernie-m-base": {"do_lower_case": False},
    "ernie-m-large": {"do_lower_case": False},
}







class        A_   (			UpperCAmelCase__   ):




	'''simple docstring'''


	_UpperCamelCase     :     Tuple							 =       ["""input_ids"""]

	_UpperCamelCase     :     Any							 =       VOCAB_FILES_NAMES
	_UpperCamelCase     :     int							 =       PRETRAINED_INIT_CONFIGURATION
	_UpperCamelCase     :     Union[str, Any]							 =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_UpperCamelCase     :     str							 =       PRETRAINED_VOCAB_FILES_MAP
	_UpperCamelCase     :     Union[str, Any]							 =       RESOURCE_FILES_NAMES





	def __init__(       self		,    snake_case		,    snake_case=None		,    snake_case=False		,    snake_case="utf8"		,    snake_case="[UNK]"		,    snake_case="[SEP]"		,    snake_case="[PAD]"		,    snake_case="[CLS]"		,    snake_case="[MASK]"		,    snake_case = None		,    **snake_case		,    ):
		lowercase       =    {} if sp_model_kwargs is None else sp_model_kwargs
		super().__init__(
		    do_lower_case=__lowercase		,    unk_token=__lowercase		,    sep_token=__lowercase		,    pad_token=__lowercase		,    cls_token=__lowercase		,    mask_token=__lowercase		,    vocab_file=__lowercase		,    encoding=__lowercase		,    sp_model_kwargs=self.sp_model_kwargs		,    **__lowercase		,    )
		lowercase       =    do_lower_case
		lowercase       =    sentencepiece_model_ckpt
		lowercase       =    spm.SentencePieceProcessor(**self.sp_model_kwargs       )
		self.sp_model.Load(__lowercase       )

		# to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
		if vocab_file is not None:
			lowercase       =    self.load_vocab(filepath=__lowercase       )
		else:
			lowercase       =    {self.sp_model.id_to_piece(__lowercase       ): id for id in range(self.sp_model.get_piece_size()       )}
		lowercase       =    {v: k for k, v in self.vocab.items()}





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):






		if text is None:
			return None

		lowercase       =    self.tokenize(__lowercase       )
		lowercase  ,					lowercase       =    '', []

		for i, ch in enumerate(__lowercase       ):
			if ch in self.SP_CHAR_MAPPING:
				lowercase       =    self.SP_CHAR_MAPPING.get(__lowercase       )
			else:
				lowercase       =    unicodedata.normalize('NFKC'		,    __lowercase       )
			if self.is_whitespace(__lowercase       ):
				continue
			normalized_text += ch
			char_mapping.extend([i] * len(__lowercase       )       )

		lowercase  ,					lowercase  ,					lowercase       =    normalized_text, [], 0

		if self.do_lower_case:
			lowercase       =    text.lower()

		for token in split_tokens:
			if token[:1] == "▁":
				lowercase       =    token[1:]
			lowercase       =    text[offset:].index(__lowercase       ) + offset
			lowercase       =    start + len(__lowercase       )

			token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)       )
			lowercase       =    end
		return token_mapping





	@property
	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		return len(self.vocab       )





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		return dict(self.vocab		,    **self.added_tokens_encoder       )





	def __getstate__(       self       ):
		lowercase       =    self.__dict__.copy()
		lowercase       =    None
		return state





	def __setstate__(       self		,    snake_case       ):
		lowercase       =    d

		# for backward compatibility
		if not hasattr(self		,    'sp_model_kwargs'       ):
			lowercase       =    {}

		lowercase       =    spm.SentencePieceProcessor(**self.sp_model_kwargs       )
		self.sp_model.Load(self.sentencepiece_model_ckpt       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		return "".join((self.SP_CHAR_MAPPING.get(__lowercase		,    __lowercase       ) for c in text)       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case=False		,    snake_case=64		,    snake_case=0.1       ):






		if self.sp_model_kwargs.get('enable_sampling'       ) is True:
			lowercase       =    True
		if self.sp_model_kwargs.get('alpha'       ) is not None:
			lowercase       =    self.sp_model_kwargs.get('alpha'       )
		if self.sp_model_kwargs.get('nbest_size'       ) is not None:
			lowercase       =    self.sp_model_kwargs.get('nbest_size'       )

		if not enable_sampling:
			lowercase       =    self.sp_model.EncodeAsPieces(__lowercase       )
		else:
			lowercase       =    self.sp_model.SampleEncodeAsPieces(__lowercase		,    __lowercase		,    __lowercase       )
		lowercase       =    []
		for pi, piece in enumerate(__lowercase       ):
			if piece == SPIECE_UNDERLINE:
				if not pieces[pi + 1].startswith(__lowercase       ) and pi != 0:
					new_pieces.append(__lowercase       )
					continue
				else:
					continue
			lowercase       =    0
			for i, chunk in enumerate(__lowercase       ):
				if chunk == SPIECE_UNDERLINE:
					continue
				if self.is_ch_char(__lowercase       ) or self.is_punct(__lowercase       ):
					if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
						new_pieces.append(piece[lst_i:i]       )
					new_pieces.append(__lowercase       )
					lowercase       =    i + 1
				elif chunk.isdigit() and i > 0 and not piece[i - 1].isdigit():
					if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
						new_pieces.append(piece[lst_i:i]       )
					lowercase       =    i
				elif not chunk.isdigit() and i > 0 and piece[i - 1].isdigit():
					if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
						new_pieces.append(piece[lst_i:i]       )
					lowercase       =    i
			if len(__lowercase       ) > lst_i:
				new_pieces.append(piece[lst_i:]       )
		return new_pieces





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		lowercase       =    ''.join(__lowercase       ).replace(__lowercase		,    ' '       ).strip()
		return out_string





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		lowercase       =    self.convert_ids_to_tokens(__lowercase       )
		lowercase       =    ''.join(__lowercase       ).replace(__lowercase		,    ' '       ).strip()
		return out_string





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		return self.vocab.get(__lowercase		,    self.vocab.get(self.unk_token       )       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		return self.reverse_vocab.get(__lowercase		,    self.unk_token       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case=None       ):






		if token_ids_a is None:
			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
		lowercase       =    [self.cls_token_id]
		lowercase       =    [self.sep_token_id]
		return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case=None       ):






		if offset_mapping_a is None:
			return [(0, 0)] + offset_mapping_a + [(0, 0)]

		return [(0, 0)] + offset_mapping_a + [(0, 0), (0, 0)] + offset_mapping_a + [(0, 0)]





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case=None		,    snake_case=False       ):






		if already_has_special_tokens:
			if token_ids_a is not None:
				raise ValueError(
				    'You should not supply a second sequence if the provided sequence of '
				    'ids is already formatted with special tokens for the model.'       )
			return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

		if token_ids_a is not None:
			return [1] + ([0] * len(__lowercase       )) + [1, 1] + ([0] * len(__lowercase       )) + [1]
		return [1] + ([0] * len(__lowercase       )) + [1]





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case = None       ):






		if token_ids_a is None:
			# [CLS] X [SEP]
			return (len(__lowercase       ) + 2) * [0]

		# [CLS] A [SEP] [SEP] B [SEP]
		return [0] * (len(__lowercase       ) + 1) + [1] * (len(__lowercase       ) + 3)





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):






		if "\u4e00" <= char <= "\u9fff":
			return True
		return False





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):






		if ("a" <= char <= "z") or ("A" <= char <= "Z"):
			return True
		return False





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):






		if char in ",;:.?!~，；：。？！《》【】":
			return True
		return False





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):






		if char == " " or char == "\t" or char == "\n" or char == "\r":
			return True
		if len(__lowercase       ) == 1:
			lowercase       =    unicodedata.category(__lowercase       )
			if cat == "Zs":
				return True
		return False





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case       ):
		lowercase       =    {}
		with io.open(__lowercase		,    'r'		,    encoding='utf-8'       ) as f:
			for index, line in enumerate(__lowercase       ):
				lowercase       =    line.rstrip('\n'       )
				lowercase       =    int(__lowercase       )

		return token_to_idx





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case = None       ):
		lowercase       =    0
		if os.path.isdir(__lowercase       ):
			lowercase       =    os.path.join(
			    __lowercase		,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )
		else:
			lowercase       =    (filename_prefix + '-' if filename_prefix else '') + save_directory
		with open(__lowercase		,    'w'		,    encoding='utf-8'       ) as writer:
			for token, token_index in sorted(self.vocab.items()		,    key=lambda snake_case       : kv[1]       ):
				if index != token_index:
					logger.warning(
					    F'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
					    ' Please check that the vocabulary is not corrupted!'       )
					lowercase       =    token_index
				writer.write(token + '\n'       )
				index += 1

		lowercase       =    os.path.join(__lowercase		,    'sentencepiece.bpe.model'       )
		with open(__lowercase		,    'wb'       ) as fi:
			lowercase       =    self.sp_model.serialized_model_proto()
			fi.write(__lowercase       )

		return (vocab_file,)







def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	_enforce_args(_A     ,	_A							)
	if n == 0:
		return 0
	snake_case_		    =     float("-inf"							)
	for i in range(1     ,	n + 1							):
		snake_case_		    =     max(
		    _A     ,	prices[i - 1] + naive_cut_rod_recursive(n - i     ,	_A							)							)

	return max_revue


def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	_enforce_args(_A     ,	_A							)
	snake_case_		    =     [float("-inf"							) for _ in range(n + 1							)]
	return _top_down_cut_rod_recursive(_A     ,	_A     ,	_A							)


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A							):







	'''simple docstring'''





	if max_rev[n] >= 0:
		return max_rev[n]
	elif n == 0:
		return 0
	else:
		snake_case_		    =     float("-inf"							)
		for i in range(1     ,	n + 1							):
			snake_case_		    =     max(
			    _A     ,	prices[i - 1] + _top_down_cut_rod_recursive(n - i     ,	_A     ,	_A							)     ,	)

		snake_case_		    =     max_revenue

	return max_rev[n]


def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	_enforce_args(_A     ,	_A							)

	# length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
	# length 0.
	snake_case_		    =     [float("-inf"							) for _ in range(n + 1							)]
	snake_case_		    =     0

	for i in range(1     ,	n + 1							):
		snake_case_		    =     max_rev[i]
		for j in range(1     ,	i + 1							):
			snake_case_		    =     max(_A     ,	prices[j - 1] + max_rev[i - j]							)

		snake_case_		    =     max_revenue_i

	return max_rev[n]


def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	if n < 0:
		snake_case_		    =     f"n must be greater than or equal to 0. Got n = {n}"
		raise ValueError(_A							)

	if n > len(_A							):
		snake_case_		    =     (
		    "Each integral piece of rod must have a corresponding price. "
		    f"Got n = {n} but length of prices = {len(_A							)}"
		)
		raise ValueError(_A							)


def 						lowerCamelCase__    (		):







	'''simple docstring'''





	snake_case_		    =     [6, 10, 12, 15, 20, 23]
	snake_case_		    =     len(_A							)

	# the best revenue comes from cutting the rod into 6 pieces, each
	# of length 1 resulting in a revenue of 6 * 6 = 36.
	snake_case_		    =     36

	snake_case_		    =     top_down_cut_rod(_A     ,	_A							)
	snake_case_		    =     bottom_up_cut_rod(_A     ,	_A							)
	snake_case_		    =     naive_cut_rod_recursive(_A     ,	_A							)

	assert expected_max_revenue == max_rev_top_down
	assert max_rev_top_down == max_rev_bottom_up
	assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
		main()
