import os
import re
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


_SCREAMING_SNAKE_CASE:						Any    	=       logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE:						int    	=       {'''vocab_file''': '''spiece.model'''}

_SCREAMING_SNAKE_CASE:						Union[str, Any]    	=       {
    '''vocab_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/spiece.model''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/spiece.model''',
    },
}

_SCREAMING_SNAKE_CASE:						int    	=       {
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

_SCREAMING_SNAKE_CASE:						Optional[int]    	=       '''▁'''

class 	_SCREAMING_SNAKE_CASE							(     lowerCamelCase_							):






		"""simple docstring"""







		A_						 =      VOCAB_FILES_NAMES
		A_						 =      PRETRAINED_VOCAB_FILES_MAP
		A_						 =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		A_						 =      ["""input_ids""", """token_type_ids"""]



		def __init__(			self    :				Dict  ,					__SCREAMING_SNAKE_CASE    :				Tuple  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]=False  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]=True  ,					__SCREAMING_SNAKE_CASE    :				Optional[int]=True  ,					__SCREAMING_SNAKE_CASE    :				str="<unk>"  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]="[SEP]"  ,					__SCREAMING_SNAKE_CASE    :				int="<pad>"  ,					__SCREAMING_SNAKE_CASE    :				int="[CLS]"  ,					__SCREAMING_SNAKE_CASE    :				Any="[MASK]"  ,					__SCREAMING_SNAKE_CASE    :				Tuple = None  ,					**__SCREAMING_SNAKE_CASE    :				int  ,					):






					"""simple docstring"""
					_snake_case              =      (
					    AddedToken(__SCREAMING_SNAKE_CASE  ,					lstrip=__SCREAMING_SNAKE_CASE  ,					rstrip=__SCREAMING_SNAKE_CASE  ,					normalized=__SCREAMING_SNAKE_CASE   )
					    if isinstance(__SCREAMING_SNAKE_CASE  ,					__SCREAMING_SNAKE_CASE   )
					    else mask_token
					)

					_snake_case              =      {} if sp_model_kwargs is None else sp_model_kwargs

					super().__init__(
					    do_lower_case=__SCREAMING_SNAKE_CASE  ,					remove_space=__SCREAMING_SNAKE_CASE  ,					keep_accents=__SCREAMING_SNAKE_CASE  ,					unk_token=__SCREAMING_SNAKE_CASE  ,					sep_token=__SCREAMING_SNAKE_CASE  ,					pad_token=__SCREAMING_SNAKE_CASE  ,					cls_token=__SCREAMING_SNAKE_CASE  ,					mask_token=__SCREAMING_SNAKE_CASE  ,					sp_model_kwargs=self.sp_model_kwargs  ,					**__SCREAMING_SNAKE_CASE  ,					)

					_snake_case              =      do_lower_case
					_snake_case              =      remove_space
					_snake_case              =      keep_accents
					_snake_case              =      vocab_file

					_snake_case              =      spm.SentencePieceProcessor(**self.sp_model_kwargs   )
					self.sp_model.Load(__SCREAMING_SNAKE_CASE   )



		@property
		def 				_a				(			self    :				Union[str, Any]   ):






					"""simple docstring"""
					return len(self.sp_model   )



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






					"""simple docstring"""
					_snake_case              =      {self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE   ): i for i in range(self.vocab_size   )}
					vocab.update(self.added_tokens_encoder   )
					return vocab



		def __getstate__(			self    :				Any   ):






					"""simple docstring"""
					_snake_case              =      self.__dict__.copy()
					_snake_case              =      None
					return state



		def __setstate__(			self    :				Optional[int]  ,					__SCREAMING_SNAKE_CASE    :				str   ):






					"""simple docstring"""
					_snake_case              =      d

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

					_snake_case              =      spm.SentencePieceProcessor(**self.sp_model_kwargs   )
					self.sp_model.Load(self.vocab_file   )



		def 				_a				(			self    :				Optional[int]  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]   ):






					"""simple docstring"""







					if self.remove_space:
								_snake_case              =      " ".join(inputs.strip().split()   )
					else:
								_snake_case              =      inputs
					_snake_case              =      outputs.replace("``"  ,					"\""   ).replace("''"  ,					"\""   )

					if not self.keep_accents:
								_snake_case              =      unicodedata.normalize("NFKD"  ,					__SCREAMING_SNAKE_CASE   )
								_snake_case              =      "".join([c for c in outputs if not unicodedata.combining(__SCREAMING_SNAKE_CASE   )]   )
					if self.do_lower_case:
								_snake_case              =      outputs.lower()

					return outputs



		def 				_a				(			self    :				List[str]  ,					__SCREAMING_SNAKE_CASE    :				Any   ):






					"""simple docstring"""
					_snake_case              =      self.preprocess_text(__SCREAMING_SNAKE_CASE   )
					_snake_case              =      self.sp_model.encode(__SCREAMING_SNAKE_CASE  ,					out_type=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      []
					for piece in pieces:
								if len(__SCREAMING_SNAKE_CASE   ) > 1 and piece[-1] == str(","   ) and piece[-2].isdigit():
											_snake_case              =      self.sp_model.EncodeAsPieces(piece[:-1].replace(__SCREAMING_SNAKE_CASE  ,					""   )   )
											if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
														if len(cur_pieces[0]   ) == 1:
																	_snake_case              =      cur_pieces[1:]
														else:
																	_snake_case              =      cur_pieces[0][1:]
											cur_pieces.append(piece[-1]   )
											new_pieces.extend(__SCREAMING_SNAKE_CASE   )
								else:
											new_pieces.append(__SCREAMING_SNAKE_CASE   )

					return new_pieces



		def 				_a				(			self    :				Optional[int]  ,					__SCREAMING_SNAKE_CASE    :				int   ):






					"""simple docstring"""
					return self.sp_model.PieceToId(__SCREAMING_SNAKE_CASE   )



		def 				_a				(			self    :				Optional[int]  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]   ):






					"""simple docstring"""
					return self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE   )



		def 				_a				(			self    :				Any  ,					__SCREAMING_SNAKE_CASE    :				List[Any]   ):






					"""simple docstring"""
					_snake_case              =      []
					_snake_case              =      ""
					_snake_case              =      False
					for token in tokens:
								# make sure that special tokens are not decoded using sentencepiece model
								if token in self.all_special_tokens:
											if not prev_is_special:
														out_string += " "
											out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE   ) + token
											_snake_case              =      True
											_snake_case              =      []
								else:
											current_sub_tokens.append(__SCREAMING_SNAKE_CASE   )
											_snake_case              =      False
					out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE   )
					return out_string.strip()



		def 				_a				(			self    :				List[Any]  ,					__SCREAMING_SNAKE_CASE    :				int  ,					__SCREAMING_SNAKE_CASE    :				Optional[int] = False  ,					__SCREAMING_SNAKE_CASE    :				Dict = None  ,					__SCREAMING_SNAKE_CASE    :				Tuple = True  ,					**__SCREAMING_SNAKE_CASE    :				str  ,					):






					"""simple docstring"""
					_snake_case              =      kwargs.pop("use_source_tokenizer"  ,					__SCREAMING_SNAKE_CASE   )

					_snake_case              =      self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE  ,					skip_special_tokens=__SCREAMING_SNAKE_CASE   )

					# To avoid mixing byte-level and unicode for byte-level BPT
					# we need to build string separately for added tokens and byte-level tokens
					# cf. https://github.com/huggingface/transformers/issues/1133
					_snake_case              =      []
					_snake_case              =      []
					for token in filtered_tokens:
								if skip_special_tokens and token in self.all_special_ids:
											continue
								if token in self.added_tokens_encoder:
											if current_sub_text:
														sub_texts.append(self.convert_tokens_to_string(__SCREAMING_SNAKE_CASE   )   )
														_snake_case              =      []
											sub_texts.append(__SCREAMING_SNAKE_CASE   )
								else:
											current_sub_text.append(__SCREAMING_SNAKE_CASE   )
					if current_sub_text:
								sub_texts.append(self.convert_tokens_to_string(__SCREAMING_SNAKE_CASE   )   )

					# Mimic the behavior of the Rust tokenizer:
					# No space after <unk>
					if spaces_between_special_tokens:
								_snake_case              =      re.sub(R"(<unk>) "  ,					R"\1"  ,					" ".join(__SCREAMING_SNAKE_CASE   )   )
					else:
								_snake_case              =      "".join(__SCREAMING_SNAKE_CASE   )

					_snake_case              =      (
					    clean_up_tokenization_spaces
					    if clean_up_tokenization_spaces is not None
					    else self.clean_up_tokenization_spaces
					)
					if clean_up_tokenization_spaces:
								_snake_case              =      self.clean_up_tokenization(__SCREAMING_SNAKE_CASE   )
								return clean_text
					else:
								return text



		def 				_a				(			self    :				int  ,					__SCREAMING_SNAKE_CASE    :				Union[str, Any]  ,					__SCREAMING_SNAKE_CASE    :				Union[str, Any] = None   ):






					"""simple docstring"""
					_snake_case              =      [self.sep_token_id]
					_snake_case              =      [self.cls_token_id]
					if token_ids_a is None:
								return cls + token_ids_a + sep
					return cls + token_ids_a + sep + token_ids_a + sep



		def 				_a				(			self    :				List[str]  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]  ,					__SCREAMING_SNAKE_CASE    :				List[str] = None  ,					__SCREAMING_SNAKE_CASE    :				Dict = False   ):






					"""simple docstring"""







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

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



		def 				_a				(			self    :				int  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any] = None   ):






					"""simple docstring"""
					_snake_case              =      [self.sep_token_id]
					_snake_case              =      [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   ) * [0] + len(token_ids_a + sep   ) * [1]







		def 				_a				(			self    :				List[Any]  ,					__SCREAMING_SNAKE_CASE    :				int  ,					__SCREAMING_SNAKE_CASE    :				Optional[int] = None   ):






					"""simple docstring"""







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

					if os.path.abspath(self.vocab_file   ) != os.path.abspath(__SCREAMING_SNAKE_CASE   ) and os.path.isfile(self.vocab_file   ):
								copyfile(self.vocab_file  ,					__SCREAMING_SNAKE_CASE   )
					elif not os.path.isfile(self.vocab_file   ):
								with open(__SCREAMING_SNAKE_CASE  ,					"wb"   ) as fi:
											_snake_case              =      self.sp_model.serialized_model_proto()
											fi.write(__SCREAMING_SNAKE_CASE   )

					return (out_vocab_file,)


import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


_SCREAMING_SNAKE_CASE:						List[str]    	=       logging.get_logger(__name__)  # pylint: disable=invalid-name


_SCREAMING_SNAKE_CASE:						Dict    	=       '''lfs-multipart-upload'''

class 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		@staticmethod
		def 				_a				(			__SCREAMING_SNAKE_CASE    :				ArgumentParser   ):






					"""simple docstring"""
					_snake_case              =      parser.add_parser(
					    "lfs-enable-largefiles"  ,					help=(
					        "Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB."
					    )  ,					)
					enable_parser.add_argument("path"  ,					type=__SCREAMING_SNAKE_CASE  ,					help="Local path to repository you want to configure."   )
					enable_parser.set_defaults(func=lambda __SCREAMING_SNAKE_CASE   : LfsEnableCommand(__SCREAMING_SNAKE_CASE   )   )

					_snake_case              =      parser.add_parser(
					    __SCREAMING_SNAKE_CASE  ,					help=(
					        "Deprecated: use `huggingface-cli` instead. "
					        "Command will get called by git-lfs, do not call it directly."
					    )  ,					)
					upload_parser.set_defaults(func=lambda __SCREAMING_SNAKE_CASE   : LfsUploadCommand(__SCREAMING_SNAKE_CASE   )   )

class 	_SCREAMING_SNAKE_CASE							:






		"""simple docstring"""







		def __init__(			self    :				Union[str, Any]  ,					__SCREAMING_SNAKE_CASE    :				List[str]   ):






					"""simple docstring"""
					_snake_case              =      args







		def 				_a				(			self    :				Optional[int]   ):






					"""simple docstring"""
					warnings.warn(
					    "Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead."   )
					_snake_case              =      os.path.abspath(self.args.path   )
					if not os.path.isdir(__SCREAMING_SNAKE_CASE   ):
								print("This does not look like a valid git repo."   )
								exit(1   )
					subprocess.run(
					    "git config lfs.customtransfer.multipart.path transformers-cli".split()  ,					check=__SCREAMING_SNAKE_CASE  ,					cwd=__SCREAMING_SNAKE_CASE   )
					subprocess.run(
					    F'git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'.split()  ,					check=__SCREAMING_SNAKE_CASE  ,					cwd=__SCREAMING_SNAKE_CASE  ,					)
					print("Local repo set up for largefiles"   )






def    UpperCAmelCase__(						lowerCamelCase_  ):



			"""simple docstring"""





			_snake_case              =      json.dumps(lowerCamelCase_  ) + "\n"
			sys.stdout.write(lowerCamelCase_  )
			sys.stdout.flush()






def    UpperCAmelCase__(						):



			"""simple docstring"""





			_snake_case              =      json.loads(sys.stdin.readline().strip()  )

			if "terminate" in (msg.get("type"  ), msg.get("event"  )):
						# terminate message received
						return None

			if msg.get("event"  ) not in ("download", "upload"):
						logger.critical("Received unexpected message"  )
						sys.exit(1  )

			return msg

class 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		def __init__(			self    :				Optional[int]  ,					__SCREAMING_SNAKE_CASE    :				str  ,					__SCREAMING_SNAKE_CASE    :				int  ,					__SCREAMING_SNAKE_CASE    :				int   ):






					"""simple docstring"""
					_snake_case              =      filepath
					_snake_case              =      seek_from
					_snake_case              =      read_limit
					_snake_case              =      0



		def __enter__(			self    :				Optional[int]   ):






					"""simple docstring"""
					_snake_case              =      open(self.filepath  ,					"rb"   )
					self.f.seek(self.seek_from   )
					return self



		def __len__(			self    :				List[str]   ):






					"""simple docstring"""
					_snake_case              =      os.fstat(self.f.fileno()   ).st_size
					return min(self.read_limit  ,					total_length - self.seek_from   )



		def 				_a				(			self    :				Dict  ,					__SCREAMING_SNAKE_CASE    :				Any=-1   ):






					"""simple docstring"""
					if self.n_seen >= self.read_limit:
								return b""
					_snake_case              =      self.read_limit - self.n_seen
					_snake_case              =      self.f.read(remaining_amount if n < 0 else min(__SCREAMING_SNAKE_CASE  ,					__SCREAMING_SNAKE_CASE   )   )
					self.n_seen += len(__SCREAMING_SNAKE_CASE   )
					return data



		def __iter__(			self    :				str   ):






					"""simple docstring"""
					yield self.read(n=4 * 1_024 * 1_024   )







		def __exit__(			self    :				Dict  ,					*__SCREAMING_SNAKE_CASE    :				int   ):






					"""simple docstring"""
					self.f.close()

class 	_SCREAMING_SNAKE_CASE							:






		"""simple docstring"""







		def __init__(			self    :				str  ,					__SCREAMING_SNAKE_CASE    :				str   ):






					"""simple docstring"""
					_snake_case              =      args







		def 				_a				(			self    :				Optional[int]   ):






					"""simple docstring"""
					# Immediately after invoking a custom transfer process, git-lfs
					# sends initiation data to the process over stdin.
					# This tells the process useful information about the configuration.
					_snake_case              =      json.loads(sys.stdin.readline().strip()   )
					if not (init_msg.get("event"   ) == "init" and init_msg.get("operation"   ) == "upload"):
								write_msg({"error": {"code": 32, "message": "Wrong lfs init operation"}}   )
								sys.exit(1   )

					# The transfer process should use the information it needs from the
					# initiation structure, and also perform any one-off setup tasks it
					# needs to do. It should then respond on stdout with a simple empty
					# confirmation structure, as follows:
					write_msg({}   )

					# After the initiation exchange, git-lfs will send any number of
					# transfer requests to the stdin of the transfer process, in a serial sequence.
					while True:
								_snake_case              =      read_msg()
								if msg is None:
											# When all transfers have been processed, git-lfs will send
											# a terminate event to the stdin of the transfer process.
											# On receiving this message the transfer process should
											# clean up and terminate. No response is expected.
											sys.exit(0   )

								_snake_case              =      msg["oid"]
								_snake_case              =      msg["path"]
								_snake_case              =      msg["action"]["href"]
								_snake_case              =      msg["action"]["header"]
								_snake_case              =      int(header.pop("chunk_size"   )   )
								_snake_case              =      list(header.values()   )

								_snake_case              =      []
								for i, presigned_url in enumerate(__SCREAMING_SNAKE_CASE   ):
											with FileSlice(__SCREAMING_SNAKE_CASE  ,					seek_from=i * chunk_size  ,					read_limit=__SCREAMING_SNAKE_CASE   ) as data:
														_snake_case              =      requests.put(__SCREAMING_SNAKE_CASE  ,					data=__SCREAMING_SNAKE_CASE   )
														r.raise_for_status()
														parts.append(
														    {
														        "etag": r.headers.get("etag"   ),
														        "partNumber": i + 1,
														    }   )
														# In order to support progress reporting while data is uploading / downloading,
														# the transfer process should post messages to stdout
														write_msg(
														    {
														        "event": "progress",
														        "oid": oid,
														        "bytesSoFar": (i + 1) * chunk_size,
														        "bytesSinceLast": chunk_size,
														    }   )
														# Not precise but that's ok.

								_snake_case              =      requests.post(
								    __SCREAMING_SNAKE_CASE  ,					json={
								        "oid": oid,
								        "parts": parts,
								    }  ,					)
								r.raise_for_status()

								write_msg({"event": "complete", "oid": oid}   )

