


'''simple docstring'''




import os

import pytest

from transformers.dynamic_module_utils import get_imports


__snake_case    						="""
import os
"""

__snake_case    						="""
def foo():
    import os
    return False
"""

__snake_case    						="""
def foo():
    def bar():
        if True:
            import os
        return False
    return bar()
"""

__snake_case    						="""
import os

try:
    import bar
except ImportError:
    raise ValueError()
"""

__snake_case    						="""
import os

def foo():
    try:
        import bar
    except ImportError:
        raise ValueError()
"""

__snake_case    						="""
import os

try:
    import bar
except (ImportError, AttributeError):
    raise ValueError()
"""

__snake_case    						="""
import os

try:
    import bar
except ImportError as e:
    raise ValueError()
"""

__snake_case    						="""
import os

try:
    import bar
except:
    raise ValueError()
"""

__snake_case    						="""
import os

try:
    import bar
    import baz
except ImportError:
    raise ValueError()
"""

__snake_case    						="""
import os

try:
    import bar
    import baz
except ImportError:
    x = 1
    raise ValueError()
"""

__snake_case    						=[
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]





@pytest.mark.parametrize('case'	, lowerCamelCase				)
def 	a_					( lowerCamelCase	:     List[str]	, lowerCamelCase	:     Tuple				):
   lowerCAmelCase     =			os.path.join(lowerCamelCase	, 'test_file.py'				)
   with open(lowerCamelCase	, 'w'				) as _tmp_file:
      _tmp_file.write(lowerCamelCase				)

   lowerCAmelCase     =			get_imports(lowerCamelCase				)
   assert parsed_imports == ["os"]









'''simple docstring'''




import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser





def 	a_					( lowerCamelCase	:     Dict				):
   lowerCAmelCase     =			{}
   lowerCAmelCase     =			tokenizer(example['content']	, truncation=lowerCamelCase				)['input_ids']
   lowerCAmelCase     =			len(example['content']				) / len(output['input_ids']				)
   return output


__snake_case    						=HfArgumentParser(PretokenizationArguments)
__snake_case    						=parser.parse_args()
if args.num_workers is None:
       __snake_case    						=multiprocessing.cpu_count()
__snake_case    						=AutoTokenizer.from_pretrained(args.tokenizer_dir)

__snake_case    						=time.time()
__snake_case    						=load_dataset(args.dataset_name, split="""train""")
print(F'''Dataset loaded in {time.time()-t_start:.2f}s''')

__snake_case    						=time.time()
__snake_case    						=ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        """repo_name""",
        """path""",
        """copies""",
        """size""",
        """content""",
        """license""",
        """hash""",
        """line_mean""",
        """line_max""",
        """alpha_frac""",
        """autogenerated""",
    ],
)
print(F'''Dataset tokenized in {time.time()-t_start:.2f}s''')

__snake_case    						=time.time()
ds.push_to_hub(args.tokenized_data_repo)




print(F'''Data pushed to the hub in {time.time()-t_start:.2f}s''')





