





'''simple docstring'''
import sys

from transformers import AutoTokenizer


a__							:							Dict			=sys.argv[1]
a__							:							Union[str, Any]			=sys.argv[2]
a__							:							int			=int(sys.argv[3])

a__							:							Dict			=0

a__							:							Any			=AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, '''rt''') as f_p:
    for line in f_p:
        a__							:							Union[str, Any]			=line.rstrip()

        if not line:
            print(line)
            a__							:							int			=0
            continue

        a__							:							Tuple			=line.split()[0]

        a__							:							Union[str, Any]			=len(tokenizer.tokenize(token))

        # Token contains strange control characters like \x96 or \x95
        # Just filter out the complete line
        if current_subwords_len == 0:
            continue

        if (subword_len_counter + current_subwords_len) > max_len:
            print('''''')
            print(line)
            a__							:							Optional[int]			=current_subwords_len
            continue

        subword_len_counter += current_subwords_len

        print(line)







'''simple docstring'''
a__							:							int			='''
# Transformers installation
! pip install transformers datasets evaluate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

a__							:							List[Any]			=[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
a__							:							Dict			={
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}
