import os

import pytest

from transformers.dynamic_module_utils import get_imports


SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		"""
import os
"""

SCREAMING_SNAKE_CASE :	Optional[int]							     =		"""
def foo():
    import os
    return False
"""

SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		"""
def foo():
    def bar():
        if True:
            import os
        return False
    return bar()
"""

SCREAMING_SNAKE_CASE :	List[Any]							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	Tuple							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	List[Any]							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	str							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	int							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	Any							     =		"""
import os

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

SCREAMING_SNAKE_CASE :	Tuple							     =		[
    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"							,				_A					)
def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  os.path.join(_A							,				"test_file.py"					)
 with open(_A							,				"w"					) as _tmp_file:
  _tmp_file.write(_A					)

 __a       =  get_imports(_A					)
 assert parsed_imports == ["os"]



import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
  import jax.numpy as jnp

  from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_flax
class    A_ (       unittest.TestCase ):

  @slow
  def 		_UpperCAmelCase   (		self :      Dict       ):
   __a       =  FlaxXLMRobertaModel.from_pretrained("xlm-roberta-base"       )
   __a       =  AutoTokenizer.from_pretrained("xlm-roberta-base"       )
   __a       =  "The dog is cute and lives in the garden house"
   __a       =  jnp.array([tokenizer.encode(__SCREAMING_SNAKE_CASE       )]       )

   __a       =  (1, 12, 7_68)  # batch_size, sequence_length, embedding_vector_dim
   __a       =  jnp.array(
       [[-0.01_01, 0.12_18, -0.08_03, 0.08_01, 0.13_27, 0.07_76, -0.12_15, 0.23_83, 0.33_38, 0.31_06, 0.03_00, 0.02_52]]       )

   __a       =  model(__SCREAMING_SNAKE_CASE       )["last_hidden_state"]
   self.assertEqual(output.shape     ,							__SCREAMING_SNAKE_CASE       )
   # compare the actual values for a slice of last dim
   self.assertTrue(jnp.allclose(output[:, :, -1]     ,							__SCREAMING_SNAKE_CASE     ,							atol=1E-3       )       )


