

'''simple docstring'''




import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def 						UpperCamelCase	(			a		,						a			)				->     List[str]:






     '''simple docstring'''
     assert isinstance(a		,						a			)
     assert dataset.num_rows == 4
     assert dataset.num_columns == 1
     assert dataset.column_names == ["text"]
     for feature, expected_dtype in expected_features.items():
          assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('''keep_in_memory'''		,						[False, True]			)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     Optional[Any]:






     '''simple docstring'''
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          __magic_name__						       =    TextDatasetReader(a		,						cache_dir=a		,						keep_in_memory=a			).read()
     _check_text_dataset(a		,						a			)




@pytest.mark.parametrize(
    '''features'''		,						[
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]		,						)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     Optional[Any]:






     '''simple docstring'''
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     __magic_name__						       =    features.copy() if features else default_expected_features
     __magic_name__						       =    (
         Features({feature: Value(a			) for feature, dtype in features.items()}			) if features is not None else None
     )
     __magic_name__						       =    TextDatasetReader(a		,						features=a		,						cache_dir=a			).read()
     _check_text_dataset(a		,						a			)




@pytest.mark.parametrize('''split'''		,						[None, NamedSplit('''train'''			), '''train''', '''test''']			)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     Tuple:






     '''simple docstring'''
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     __magic_name__						       =    TextDatasetReader(a		,						cache_dir=a		,						split=a			).read()
     _check_text_dataset(a		,						a			)
     assert dataset.split == split if split else "train"




@pytest.mark.parametrize('''path_type'''		,						[str, list]			)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     List[Any]:






     '''simple docstring'''
     if issubclass(a		,						a			):
          __magic_name__						       =    text_path
     elif issubclass(a		,						a			):
          __magic_name__						       =    [text_path]
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     __magic_name__						       =    TextDatasetReader(a		,						cache_dir=a			).read()
     _check_text_dataset(a		,						a			)




def 						UpperCamelCase	(			a		,						a		,						a=("train",)			)				->     Dict:






     '''simple docstring'''
     assert isinstance(a		,						a			)
     for split in splits:
          __magic_name__						       =    dataset_dict[split]
          assert dataset.num_rows == 4
          assert dataset.num_columns == 1
          assert dataset.column_names == ["text"]
          for feature, expected_dtype in expected_features.items():
               assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('''keep_in_memory'''		,						[False, True]			)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     Dict:






     '''simple docstring'''
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          __magic_name__						       =    TextDatasetReader({'''train''': text_path}		,						cache_dir=a		,						keep_in_memory=a			).read()
     _check_text_datasetdict(a		,						a			)




@pytest.mark.parametrize(
    '''features'''		,						[
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]		,						)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     Union[str, Any]:






     '''simple docstring'''
     __magic_name__						       =    tmp_path / '''cache'''
     # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
     __magic_name__						       =    {'''text''': '''string'''}
     __magic_name__						       =    features.copy() if features else default_expected_features
     __magic_name__						       =    (
         Features({feature: Value(a			) for feature, dtype in features.items()}			) if features is not None else None
     )
     __magic_name__						       =    TextDatasetReader({'''train''': text_path}		,						features=a		,						cache_dir=a			).read()
     _check_text_datasetdict(a		,						a			)




@pytest.mark.parametrize('''split'''		,						[None, NamedSplit('''train'''			), '''train''', '''test''']			)
def 						UpperCamelCase	(			a		,						a		,						a			)				->     List[str]:






     '''simple docstring'''
     if split:
          __magic_name__						       =    {split: text_path}
     else:
          __magic_name__						       =    '''train'''
          __magic_name__						       =    {'''train''': text_path, '''test''': text_path}
     __magic_name__						       =    tmp_path / '''cache'''
     __magic_name__						       =    {'''text''': '''string'''}
     __magic_name__						       =    TextDatasetReader(a		,						cache_dir=a			).read()
     _check_text_datasetdict(a		,						a		,						splits=list(path.keys()			)			)
     assert all(dataset[split].split == split for split in path.keys()			)









'''simple docstring'''




import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
_lowerCAmelCase         =						object()

# For specifying empty leaf dict `{}`
_lowerCAmelCase         =						object()




def 						UpperCamelCase	(			a		,						a			)				->     Union[str, Any]:






     '''simple docstring'''
     __magic_name__						       =    tuple((re.compile(x + '''$'''			) for x in qs)			)
     for i in range(len(a			) - len(a			) + 1			):
          __magic_name__						       =    [x.match(a			) for x, y in zip(a		,						ks[i:]			)]
          if matches and all(a			):
               return True
     return False




def 						UpperCamelCase	(			a			)				->     Tuple:






     '''simple docstring'''
     def replace(a		,						a			):
          for rule, replacement in rules:
               if _match(a		,						a			):
                    return replacement
          return val

     return replace




def 						UpperCamelCase	(			)				->     Union[str, Any]:






     '''simple docstring'''
     return [
         # embeddings
         (("transformer", "wpe", "embedding"), P('''mp'''		,						a			)),
         (("transformer", "wte", "embedding"), P('''mp'''		,						a			)),
         # atention
         (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(a		,						'''mp'''			)),
         (("attention", "out_proj", "kernel"), P('''mp'''		,						a			)),
         (("attention", "out_proj", "bias"), None),
         # mlp
         (("mlp", "c_fc", "kernel"), P(a		,						'''mp'''			)),
         (("mlp", "c_fc", "bias"), P('''mp'''			)),
         (("mlp", "c_proj", "kernel"), P('''mp'''		,						a			)),
         (("mlp", "c_proj", "bias"), None),
         # layer norms
         ((r"ln_\d+", "bias"), None),
         ((r"\d+", r"ln_\d+", "scale"), None),
         (("ln_f", "bias"), None),
         (("ln_f", "scale"), None),
     ]




def 						UpperCamelCase	(			a			)				->     str:






     '''simple docstring'''
     __magic_name__						       =    _get_partition_rules()
     __magic_name__						       =    _replacement_rules(a			)
     __magic_name__						       =    {k: _unmatched for k in flatten_dict(a			)}
     __magic_name__						       =    {k: replace(a		,						a			) for k, v in initd.items()}
     assert _unmatched not in result.values(), "Incomplete partition spec."
     return freeze(unflatten_dict(a			)			)






