



import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing


class 	lowerCamelCase__	(       _a):



 """simple docstring"""

 def __init__(    self					:					Any			,						__lowerCAmelCase					:					str = "▁"			,						__lowerCAmelCase					:					bool = True			,						__lowerCAmelCase					:					Union[str, AddedToken] = "<unk>"			,						__lowerCAmelCase					:					Union[str, AddedToken] = "</s>"			,						__lowerCAmelCase					:					Union[str, AddedToken] = "<pad>"			,						)   ->	List[str]:
    _A      =       {
        """pad""": {"""id""": 0, """token""": pad_token},
        """eos""": {"""id""": 1, """token""": eos_token},
        """unk""": {"""id""": 2, """token""": unk_token},
    }

    _A      =       [None] * len(self.special_tokens      )
    for token_dict in self.special_tokens.values():
       _A      =       token_dict["""token"""]

    _A      =       Tokenizer(Unigram()      )

    _A      =       normalizers.Sequence(
        [
            normalizers.Nmt(),
            normalizers.NFKC(),
            normalizers.Replace(Regex(''' {2,}'''      )			,						''' '''      ),
            normalizers.Lowercase(),
        ]      )
    _A      =       pre_tokenizers.Sequence(
        [
            pre_tokenizers.Metaspace(replacement=snake_case_			,						add_prefix_space=snake_case_      ),
            pre_tokenizers.Digits(individual_digits=snake_case_      ),
            pre_tokenizers.Punctuation(),
        ]      )
    _A      =       decoders.Metaspace(replacement=snake_case_			,						add_prefix_space=snake_case_      )

    _A      =       TemplateProcessing(
        single=f'''$A {self.special_tokens['eos']['token']}'''			,						special_tokens=[(self.special_tokens['''eos''']['''token'''], self.special_tokens['''eos''']['''id'''])]			,						)

    _A      =       {
        """model""": """SentencePieceUnigram""",
        """replacement""": replacement,
        """add_prefix_space""": add_prefix_space,
    }

    super().__init__(snake_case_			,						snake_case_      )

 def     snake_case_      (    self					:					Dict			,						__lowerCAmelCase					:					Union[str, List[str]]			,						__lowerCAmelCase					:					int = 80_00			,						__lowerCAmelCase					:					bool = True			,						)   ->	int:
    _A      =       trainers.UnigramTrainer(
        vocab_size=snake_case_			,						special_tokens=self.special_tokens_list			,						show_progress=snake_case_			,						)

    if isinstance(snake_case_			,						snake_case_      ):
       _A      =       [files]
    self._tokenizer.train(snake_case_			,						trainer=snake_case_      )

    self.add_unk_id()

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					Union[Iterator[str], Iterator[Iterator[str]]]			,						__lowerCAmelCase					:					int = 80_00			,						__lowerCAmelCase					:					bool = True			,						)   ->	int:
    _A      =       trainers.UnigramTrainer(
        vocab_size=snake_case_			,						special_tokens=self.special_tokens_list			,						show_progress=snake_case_			,						)

    self._tokenizer.train_from_iterator(snake_case_			,						trainer=snake_case_      )

    self.add_unk_id()

 def     snake_case_      (    self					:					Any      )   ->	List[str]:
    _A      =       json.loads(self._tokenizer.to_str()      )

    _A      =       self.special_tokens["""unk"""]["""id"""]

    _A      =       Tokenizer.from_str(json.dumps(snake_case_      )      )








'''simple docstring'''





# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


__a  			=						"3"

print("Python version:", sys.version)
print("transformers version:", transformers.__version__)

try:
       import torch

       print("Torch version:", torch.__version__)
       print("Cuda available:", torch.cuda.is_available())
       print("Cuda version:", torch.version.cuda)
       print("CuDNN version:", torch.backends.cudnn.version())
       print("Number of GPUs available:", torch.cuda.device_count())
       print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
       print("Torch version:", None)

try:
       import deepspeed

       print("DeepSpeed version:", deepspeed.__version__)
except ImportError:
       print("DeepSpeed version:", None)

try:
       import tensorflow as tf

       print("TensorFlow version:", tf.__version__)
       print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
       print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
       print("TensorFlow version:", None)
