




"""simple docstring"""

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


_lowerCamelCase	:      Tuple   =							logging.get_logger(__name__)  # pylint: disable=invalid-name


_lowerCamelCase	:      Optional[int]   =							'lfs-multipart-upload'

class 							lowercase   (     __UpperCAmelCase):







				@staticmethod
				def        a_	(				_lowerCamelCase :       ArgumentParser							):



					"""simple docstring"""

					A_	:					Optional[Any]						 =		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=_lowerCamelCase   ,  help='''Local path to repository you want to configure.'''							)
					enable_parser.set_defaults(func=lambda _lowerCamelCase							: LfsEnableCommand(_lowerCamelCase							)							)

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

class 							lowercase   :







				def __init__(				self :       Optional[int]   ,  _lowerCamelCase :       Dict							):



					"""simple docstring"""

					A_	:					List[str]						 =		args







				def        a_	(				self :       str							):



					"""simple docstring"""

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

def 		lowercase_   (		_UpperCAmelCase						):




	"""simple docstring"""






	A_	:					Optional[Any]						 =		json.dumps(_UpperCAmelCase						) + '''\n'''
	sys.stdout.write(_UpperCAmelCase						)
	sys.stdout.flush()

def 		lowercase_   (		):




	"""simple docstring"""






	A_	:					List[str]						 =		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 							lowercase   (     __UpperCAmelCase):







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



					"""simple docstring"""

					A_	:					Dict						 =		filepath
					A_	:					Any						 =		seek_from
					A_	:					Dict						 =		read_limit
					A_	:					Any						 =		0







				def __enter__(				self :       Any							):



					"""simple docstring"""

					A_	:					int						 =		open(self.filepath   ,  '''rb'''							)
					self.f.seek(self.seek_from							)
					return self







				def __len__(				self :       Tuple							):



					"""simple docstring"""

					A_	:					str						 =		os.fstat(self.f.fileno()							).st_size
					return min(self.read_limit   ,  total_length - self.seek_from							)







				def        a_	(				self :       Optional[int]   ,  _lowerCamelCase :       List[Any]=-1							):



					"""simple docstring"""

					if self.n_seen >= self.read_limit:
						return b""
					A_	:					Optional[Any]						 =		self.read_limit - self.n_seen
					A_	:					List[Any]						 =		self.f.read(remaining_amount if n < 0 else min(_lowerCamelCase   ,  _lowerCamelCase							)							)
					self.n_seen += len(_lowerCamelCase							)
					return data







				def __iter__(				self :       Dict							):



					"""simple docstring"""

					yield self.read(n=4 * 10_24 * 10_24							)







				def __exit__(				self :       List[Any]   ,  *_lowerCamelCase :       Any							):



					"""simple docstring"""

					self.f.close()

class 							lowercase   :







				def __init__(				self :       Dict   ,  _lowerCamelCase :       Any							):



					"""simple docstring"""

					A_	:					Dict						 =		args







				def        a_	(				self :       Any							):



					"""simple docstring"""

					A_	:					Dict						 =		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:
						A_	:					Any						 =		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							)

						A_	:					Tuple						 =		msg['''oid''']
						A_	:					Tuple						 =		msg['''path''']
						A_	:					Tuple						 =		msg['''action''']['''href''']
						A_	:					Optional[int]						 =		msg['''action''']['''header''']
						A_	:					Union[str, Any]						 =		int(header.pop('''chunk_size'''							)							)
						A_	:					List[str]						 =		list(header.values()							)

						A_	:					int						 =		[]
						for i, presigned_url in enumerate(_lowerCamelCase							):
							with FileSlice(_lowerCamelCase   ,  seek_from=i * chunk_size   ,  read_limit=_lowerCamelCase							) as data:
								A_	:					Tuple						 =		requests.put(_lowerCamelCase   ,  data=_lowerCamelCase							)
								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.

						A_	:					Any						 =		requests.post(
						    _lowerCamelCase   ,  json={
						        '''oid''': oid,
						        '''parts''': parts,
						    }   ,  )
						r.raise_for_status()

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











"""simple docstring"""

import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_xglm import XGLMTokenizer
else:
		_lowerCamelCase	:      Union[str, Any]   =							None


_lowerCamelCase	:      Optional[Any]   =							logging.get_logger(__name__)

_lowerCamelCase	:      Tuple   =							{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

_lowerCamelCase	:      Union[str, Any]   =							{
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json',
    },
}

_lowerCamelCase	:      Dict   =							{
    'facebook/xglm-564M': 2048,
}

class 							lowercase   (     __UpperCAmelCase):
				__lowerCAmelCase     :     Optional[int]								= VOCAB_FILES_NAMES
				__lowerCAmelCase     :     Tuple								= PRETRAINED_VOCAB_FILES_MAP
				__lowerCAmelCase     :     List[Any]								= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__lowerCAmelCase     :     Union[str, Any]								= ["""input_ids""", """attention_mask"""]
				__lowerCAmelCase     :     List[str]								= XGLMTokenizer







				def __init__(				self :       str   ,  _lowerCamelCase :       int=None   ,  _lowerCamelCase :       Any=None   ,  _lowerCamelCase :       List[str]="<s>"   ,  _lowerCamelCase :       int="</s>"   ,  _lowerCamelCase :       Any="</s>"   ,  _lowerCamelCase :       Optional[int]="<s>"   ,  _lowerCamelCase :       List[Any]="<unk>"   ,  _lowerCamelCase :       Optional[int]="<pad>"   ,  **_lowerCamelCase :       List[Any]   ,  ):



					"""simple docstring"""

					A_	:					Tuple						 =		7
					A_	:					Dict						 =		[F"""<madeupword{i}>""" for i in range(self.num_madeup_words							)]

					A_	:					str						 =		kwargs.get('''additional_special_tokens'''   ,  []							)
					kwargs["additional_special_tokens"] += [
					    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
					]

					super().__init__(
					    _lowerCamelCase   ,  tokenizer_file=_lowerCamelCase   ,  bos_token=_lowerCamelCase   ,  eos_token=_lowerCamelCase   ,  sep_token=_lowerCamelCase   ,  cls_token=_lowerCamelCase   ,  unk_token=_lowerCamelCase   ,  pad_token=_lowerCamelCase   ,  **_lowerCamelCase   ,  )

					A_	:					Tuple						 =		vocab_file
					A_	:					str						 =		False if not self.vocab_file else True







				def        a_	(				self :       List[Any]   ,  _lowerCamelCase :       List[int]   ,  _lowerCamelCase :       Optional[List[int]] = None							):



					"""simple docstring"""

					if token_ids_a is None:
						return [self.sep_token_id] + token_ids_a
					A_	:					List[Any]						 =		[self.sep_token_id]
					return sep + token_ids_a + sep + sep + token_ids_a







				def        a_	(				self :       List[str]   ,  _lowerCamelCase :       List[int]   ,  _lowerCamelCase :       Optional[List[int]] = None							):



					"""simple docstring"""

					A_	:					Dict						 =		[self.sep_token_id]

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







				def        a_	(				self :       List[str]   ,  _lowerCamelCase :       str   ,  _lowerCamelCase :       Optional[str] = None							):



					"""simple docstring"""

					if not self.can_save_slow_tokenizer:
						raise ValueError(
						    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
						    '''tokenizer.'''							)

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

					if os.path.abspath(self.vocab_file							) != os.path.abspath(_lowerCamelCase							):
						copyfile(self.vocab_file   ,  _lowerCamelCase							)

					return (out_vocab_file,)





