






import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__a :    Dict								=				logging.get_logger(__name__)


__a :    str								=				{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all MVP models at https://huggingface.co/models?filter=mvp
__a :    Union[str, Any]								=				{
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
}

__a :    List[str]								=				{
    "RUCAIBox/mvp": 1024,
}



@lru_cache()
def      _SCREAMING_SNAKE_CASE  (	)  -> str:





    """simple docstring"""

    __A             =		(
        list(range(ord("""!"""      )     ,			ord("""~"""      ) + 1      )      ) + list(range(ord("""¡"""      )     ,			ord("""¬"""      ) + 1      )      ) + list(range(ord("""®"""      )     ,			ord("""ÿ"""      ) + 1      )      )
    )
    __A             =		bs[:]
    __A             =		0
    for b in range(2**8      ):
        if b not in bs:
            bs.append(__lowercase      )
            cs.append(2**8 + n      )
            n += 1
    __A             =		[chr(__lowercase      ) for n in cs]
    return dict(zip(__lowercase     ,			__lowercase      )      )



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     Optional[int]      )  -> Optional[Any]:





    """simple docstring"""

    __A             =		set()
    __A             =		word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)      )
        __A             =		char
    return pairs






class  __lowercase (		lowercase_					):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE				  =			VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE				  =			PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE				  =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE				  =			["input_ids", "attention_mask"]




     def __init__(			self    :     Union[str, Any]	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     Tuple="replace"	,		UpperCamelCase_    :     Optional[Any]="<s>"	,		UpperCamelCase_    :     Any="</s>"	,		UpperCamelCase_    :     Tuple="</s>"	,		UpperCamelCase_    :     Optional[Any]="<s>"	,		UpperCamelCase_    :     List[Any]="<unk>"	,		UpperCamelCase_    :     Union[str, Any]="<pad>"	,		UpperCamelCase_    :     str="<mask>"	,		UpperCamelCase_    :     Optional[int]=False	,		**UpperCamelCase_    :     Tuple	,		):


         """simple docstring"""



         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else bos_token
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else eos_token
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else sep_token
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else cls_token
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else unk_token
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         __A             =		AddedToken(UpperCamelCase_	,		lstrip=UpperCamelCase_	,		rstrip=UpperCamelCase_			) if isinstance(UpperCamelCase_	,		UpperCamelCase_			) else mask_token

         super().__init__(
             errors=UpperCamelCase_	,		bos_token=UpperCamelCase_	,		eos_token=UpperCamelCase_	,		unk_token=UpperCamelCase_	,		sep_token=UpperCamelCase_	,		cls_token=UpperCamelCase_	,		pad_token=UpperCamelCase_	,		mask_token=UpperCamelCase_	,		add_prefix_space=UpperCamelCase_	,		**UpperCamelCase_	,		)
         with open(UpperCamelCase_	,		encoding="""utf-8"""			) as vocab_handle:
             __A             =		json.load(UpperCamelCase_			)
         __A             =		{v: k for k, v in self.encoder.items()}
         __A             =		errors  # how to handle errors in decoding
         __A             =		bytes_to_unicode()
         __A             =		{v: k for k, v in self.byte_encoder.items()}
         with open(UpperCamelCase_	,		encoding="""utf-8"""			) as merges_handle:
             __A             =		merges_handle.read().split("""\n"""			)[1:-1]
         __A             =		[tuple(merge.split()			) for merge in bpe_merges]
         __A             =		dict(zip(UpperCamelCase_	,		range(len(UpperCamelCase_			)			)			)			)
         __A             =		{}
         __A             =		add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         __A             =		re.compile(R"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""			)




     @property
     def 						lowerCAmelCase_       (			self    :     List[Any]			):


         """simple docstring"""



         return len(self.encoder			)




     def 						lowerCAmelCase_       (			self    :     Union[str, Any]			):


         """simple docstring"""



         return dict(self.encoder	,		**self.added_tokens_encoder			)




     def 						lowerCAmelCase_       (			self    :     int	,		UpperCamelCase_    :     Optional[Any]			):


         """simple docstring"""



         if token in self.cache:
             return self.cache[token]
         __A             =		tuple(UpperCamelCase_			)
         __A             =		get_pairs(UpperCamelCase_			)

         if not pairs:
             return token

         while True:
             __A             =		min(UpperCamelCase_	,		key=lambda UpperCamelCase_			: self.bpe_ranks.get(UpperCamelCase_	,		float("""inf"""			)			)			)
             if bigram not in self.bpe_ranks:
                 break
             __A      ,		__A             =		bigram
             __A             =		[]
             __A             =		0
             while i < len(UpperCamelCase_			):
                 try:
                     __A             =		word.index(UpperCamelCase_	,		UpperCamelCase_			)
                 except ValueError:
                     new_word.extend(word[i:]			)
                     break
                 else:
                     new_word.extend(word[i:j]			)
                     __A             =		j

                 if word[i] == first and i < len(UpperCamelCase_			) - 1 and word[i + 1] == second:
                     new_word.append(first + second			)
                     i += 2
                 else:
                     new_word.append(word[i]			)
                     i += 1
             __A             =		tuple(UpperCamelCase_			)
             __A             =		new_word
             if len(UpperCamelCase_			) == 1:
                 break
             else:
                 __A             =		get_pairs(UpperCamelCase_			)
         __A             =		""" """.join(UpperCamelCase_			)
         __A             =		word
         return word




     def 						lowerCAmelCase_       (			self    :     Optional[Any]	,		UpperCamelCase_    :     List[Any]			):


         """simple docstring"""



         __A             =		[]
         for token in re.findall(self.pat	,		UpperCamelCase_			):
             __A             =		"""""".join(
                 self.byte_encoder[b] for b in token.encode("""utf-8"""			)			)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
             bpe_tokens.extend(bpe_token for bpe_token in self.bpe(UpperCamelCase_			).split(""" """			)			)
         return bpe_tokens




     def 						lowerCAmelCase_       (			self    :     Tuple	,		UpperCamelCase_    :     Tuple			):


         """simple docstring"""



         return self.encoder.get(UpperCamelCase_	,		self.encoder.get(self.unk_token			)			)




     def 						lowerCAmelCase_       (			self    :     Any	,		UpperCamelCase_    :     List[Any]			):


         """simple docstring"""



         return self.decoder.get(UpperCamelCase_			)




     def 						lowerCAmelCase_       (			self    :     List[str]	,		UpperCamelCase_    :     int			):


         """simple docstring"""



         __A             =		"""""".join(UpperCamelCase_			)
         __A             =		bytearray([self.byte_decoder[c] for c in text]			).decode("""utf-8"""	,		errors=self.errors			)
         return text




     def 						lowerCAmelCase_       (			self    :     Optional[int]	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     Optional[str] = None			):


         """simple docstring"""



         if not os.path.isdir(UpperCamelCase_			):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"			)
             return
         __A             =		os.path.join(
             UpperCamelCase_	,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]			)
         __A             =		os.path.join(
             UpperCamelCase_	,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]			)

         with open(UpperCamelCase_	,		"""w"""	,		encoding="""utf-8"""			) as f:
             f.write(json.dumps(self.encoder	,		indent=2	,		sort_keys=UpperCamelCase_	,		ensure_ascii=UpperCamelCase_			) + """\n"""			)

         __A             =		0
         with open(UpperCamelCase_	,		"""w"""	,		encoding="""utf-8"""			) as writer:
             writer.write("""#version: 0.2\n"""			)
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,		key=lambda UpperCamelCase_			: kv[1]			):
                 if index != token_index:
                     logger.warning(
                         F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                         """ Please check that the tokenizer is not corrupted!"""			)
                     __A             =		token_index
                 writer.write(""" """.join(UpperCamelCase_			) + """\n"""			)
                 index += 1

         return vocab_file, merge_file




     def 						lowerCAmelCase_       (			self    :     Optional[int]	,		UpperCamelCase_    :     List[int]	,		UpperCamelCase_    :     Optional[List[int]] = None			):


         """simple docstring"""



         if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         __A             =		[self.cls_token_id]
         __A             =		[self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep




     def 						lowerCAmelCase_       (			self    :     List[str]	,		UpperCamelCase_    :     List[int]	,		UpperCamelCase_    :     Optional[List[int]] = None	,		UpperCamelCase_    :     bool = False			):


         """simple docstring"""



         if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=UpperCamelCase_	,		token_ids_a=UpperCamelCase_	,		already_has_special_tokens=UpperCamelCase_			)

         if token_ids_a is None:
             return [1] + ([0] * len(UpperCamelCase_			)) + [1]
         return [1] + ([0] * len(UpperCamelCase_			)) + [1, 1] + ([0] * len(UpperCamelCase_			)) + [1]




     def 						lowerCAmelCase_       (			self    :     int	,		UpperCamelCase_    :     List[int]	,		UpperCamelCase_    :     Optional[List[int]] = None			):


         """simple docstring"""



         __A             =		[self.sep_token_id]
         __A             =		[self.cls_token_id]

         if token_ids_a is None:
             return len(cls + token_ids_a + sep			) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]





     def 						lowerCAmelCase_       (			self    :     Union[str, Any]	,		UpperCamelCase_    :     Dict	,		UpperCamelCase_    :     Tuple=False	,		**UpperCamelCase_    :     Tuple			):


         """simple docstring"""



         __A             =		kwargs.pop("""add_prefix_space"""	,		self.add_prefix_space			)
         if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase_			) > 0 and not text[0].isspace()):
             __A             =		""" """ + text
         return (text, kwargs)












# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     List[str]     ,			__lowercase				:     str      )  -> Optional[int]:





    """simple docstring"""

    if name != "training_function" and name != "main":
        raise ValueError(f"Incorrect function name passed: {name}, choose either 'main' or 'training_function'"      )
    __A      ,		__A             =		[], False
    for line in lines:
        if not found_start and f"def {name}" in line:
            __A             =		True
            good_lines.append(__lowercase      )
            continue
        if found_start:
            if name == "training_function" and "def main" in line:
                return good_lines
            if name == "main" and "if __name__" in line:
                return good_lines
            good_lines.append(__lowercase      )



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     List[str]      )  -> Optional[int]:





    """simple docstring"""

    return [line for line in lines if not line.lstrip().startswith("""#"""      ) and line != "\n"]






def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     str     ,			__lowercase				:     str     ,			__lowercase				:     bool     ,			__lowercase				:     str = None      )  -> List[Any]:





    """simple docstring"""

    with open(__lowercase     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    with open(os.path.abspath(os.path.join("""examples"""     ,			"""nlp_example.py"""      )      )     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    with open(__lowercase     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    if secondary_filename is not None:
        with open(__lowercase     ,			"""r"""      ) as f:
            __A             =		f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
    if parser_only:
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        if secondary_filename is not None:
            __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
    else:
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        if secondary_filename is not None:
            __A             =		clean_lines(
                get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )

    __A             =		"""train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n"""

    # Specific code in our script that differs from the full version, aka what is new
    __A             =		[]
    __A             =		[]  # We keep track of the idxs just in case it's a repeated statement
    __A             =		iter(__lowercase      )
    for i in range(len(__lowercase      ) - 1      ):
        if i not in passed_idxs:
            __A             =		next(__lowercase      )
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_feature_code.append(__lowercase      )
                    passed_idxs.append(__lowercase      )
                else:
                    # Skip over the `config['num_epochs'] = 2` statement
                    __A             =		next(__lowercase      )

    # Extract out just the new parts from the full_file_training_func
    __A             =		[]
    __A             =		[]  # We keep track of the idxs just in case it's a repeated statement
    for i, line in enumerate(__lowercase      ):
        if i not in passed_idxs:
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_full_example_parts.append(__lowercase      )
                    passed_idxs.append(__lowercase      )

    # Finally, get the overall diff
    __A             =		[line for line in new_feature_code if line not in new_full_example_parts]
    if secondary_filename is not None:
        __A             =		[line for line in full_file_contents if line not in secondary_file_func]
        __A             =		[line for line in diff_from_example if line not in diff_from_two]

    return diff_from_example




