






'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE							=						{
    'configuration_rembert': ['REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RemBertConfig', 'RemBertOnnxConfig']
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE							=						['RemBertTokenizer']

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE							=						['RemBertTokenizerFast']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE							=						[
          'REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'RemBertForCausalLM',
          'RemBertForMaskedLM',
          'RemBertForMultipleChoice',
          'RemBertForQuestionAnswering',
          'RemBertForSequenceClassification',
          'RemBertForTokenClassification',
          'RemBertLayer',
          'RemBertModel',
          'RemBertPreTrainedModel',
          'load_tf_weights_in_rembert',
      ]


try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE							=						[
          'TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFRemBertForCausalLM',
          'TFRemBertForMaskedLM',
          'TFRemBertForMultipleChoice',
          'TFRemBertForQuestionAnswering',
          'TFRemBertForSequenceClassification',
          'TFRemBertForTokenClassification',
          'TFRemBertLayer',
          'TFRemBertModel',
          'TFRemBertPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig, RemBertOnnxConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_rembert import RemBertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_rembert_fast import RemBertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_rembert import (
                REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                RemBertForCausalLM,
                RemBertForMaskedLM,
                RemBertForMultipleChoice,
                RemBertForQuestionAnswering,
                RemBertForSequenceClassification,
                RemBertForTokenClassification,
                RemBertLayer,
                RemBertModel,
                RemBertPreTrainedModel,
                load_tf_weights_in_rembert,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_rembert import (
                TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFRemBertForCausalLM,
                TFRemBertForMaskedLM,
                TFRemBertForMultipleChoice,
                TFRemBertForQuestionAnswering,
                TFRemBertForSequenceClassification,
                TFRemBertForTokenClassification,
                TFRemBertLayer,
                TFRemBertModel,
                TFRemBertPreTrainedModel,
            )


else:
      import sys

      SCREAMING_SNAKE_CASE							=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











'''simple docstring'''



import unittest

from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate


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



 """simple docstring"""




 return x + 2





class UpperCAmelCase_       (     unittest.TestCase					):




      """simple docstring"""




      def 					A__   (			self      :		Dict		)	->	List[Any]:


       '''simple docstring'''

       lowercase       : Optional[int]						='''x = 3'''
       lowercase       : Any						={}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3}		)

       lowercase       : str						='''x = y'''
       lowercase       : Optional[int]						={'''y''': 5}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 5, '''y''': 5}		)






      def 					A__   (			self      :		str		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : Optional[int]						='''y = add_two(x)'''
       lowercase       : str						={'''x''': 3}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)

       # Won't work without the tool
       with CaptureStdout() as out:
        lowercase       : Optional[Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result is None
       assert "tried to execute add_two" in out.out






      def 					A__   (			self      :		List[Any]		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : int						='''x = 3'''
       lowercase       : Dict						={}
       lowercase       : List[Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3}		)






      def 					A__   (			self      :		str		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Optional[Any]						='''test_dict = {\'x\': x, \'y\': add_two(x)}'''
       lowercase       : str						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_dict''': {'''x''': 3, '''y''': 5}}		)






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


       '''simple docstring'''

       lowercase       : Optional[Any]						='''x = 3\ny = 5'''
       lowercase       : int						={}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)






      def 					A__   (			self      :		Any		)	->	Tuple:


       '''simple docstring'''

       lowercase       : List[str]						='''text = f\'This is x: {x}.\''''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == "This is x: 3."
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''text''': '''This is x: 3.'''}		)






      def 					A__   (			self      :		Union[str, Any]		)	->	List[Any]:


       '''simple docstring'''

       lowercase       : Tuple						='''if x <= 3:\n    y = 2\nelse:\n    y = 5'''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Any						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 2
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 2}		)

       lowercase       : Optional[Any]						={'''x''': 8}
       lowercase       : str						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 8, '''y''': 5}		)






      def 					A__   (			self      :		str		)	->	Optional[Any]:


       '''simple docstring'''

       lowercase       : List[str]						='''test_list = [x, add_two(x)]'''
       lowercase       : Any						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       self.assertListEqual(UpperCAmelCase  ,   [3, 5]		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_list''': [3, 5]}		)






      def 					A__   (			self      :		Any		)	->	Tuple:


       '''simple docstring'''

       lowercase       : str						='''y = x'''
       lowercase       : Dict						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 3}		)






      def 					A__   (			self      :		str		)	->	List[str]:


       '''simple docstring'''

       lowercase       : Any						='''test_list = [x, add_two(x)]\ntest_list[1]'''
       lowercase       : Any						={'''x''': 3}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_list''': [3, 5]}		)

       lowercase       : int						='''test_dict = {\'x\': x, \'y\': add_two(x)}\ntest_dict[\'y\']'''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_dict''': {'''x''': 3, '''y''': 5}}		)






      def 					A__   (			self      :		List[str]		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Optional[int]						='''x = 0\nfor i in range(3):\n    x = i'''
       lowercase       : List[str]						={}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {'''range''': range}  ,   state=UpperCAmelCase		)
       assert result == 2
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 2, '''i''': 2}		)



