






import unittest

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





def 						__UpperCAmelCase			(     a_):
							return x + 2




class  UpperCamelCase_      (			unittest.TestCase				):



	'''simple docstring'''




	def 							_UpperCamelCase			(       self					)       ->    Optional[int]:
								snake_case_				=							'x = 3'
								snake_case_				=							{}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								assert result == 3
								self.assertDictEqual(a       ,			{'x': 3}					)

								snake_case_				=							'x = y'
								snake_case_				=							{'y': 5}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								# evaluate returns the value of the last assignment.
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 5, 'y': 5}					)




	def 							_UpperCamelCase			(       self					)       ->    Union[str, Any]:
								snake_case_				=							'y = add_two(x)'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{'add_two': add_two}       ,			state=a					)
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 3, 'y': 5}					)

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




	def 							_UpperCamelCase			(       self					)       ->    List[str]:
								snake_case_				=							'x = 3'
								snake_case_				=							{}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								assert result == 3
								self.assertDictEqual(a       ,			{'x': 3}					)




	def 							_UpperCamelCase			(       self					)       ->    Any:
								snake_case_				=							'test_dict = {\'x\': x, \'y\': add_two(x)}'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{'add_two': add_two}       ,			state=a					)
								self.assertDictEqual(a       ,			{'x': 3, 'y': 5}					)
								self.assertDictEqual(a       ,			{'x': 3, 'test_dict': {'x': 3, 'y': 5}}					)




	def 							_UpperCamelCase			(       self					)       ->    Dict:
								snake_case_				=							'x = 3\ny = 5'
								snake_case_				=							{}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								# evaluate returns the value of the last assignment.
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 3, 'y': 5}					)




	def 							_UpperCamelCase			(       self					)       ->    int:
								snake_case_				=							'text = f\'This is x: {x}.\''
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								# evaluate returns the value of the last assignment.
								assert result == "This is x: 3."
								self.assertDictEqual(a       ,			{'x': 3, 'text': 'This is x: 3.'}					)




	def 							_UpperCamelCase			(       self					)       ->    Optional[int]:
								snake_case_				=							'if x <= 3:\n    y = 2\nelse:\n    y = 5'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								# evaluate returns the value of the last assignment.
								assert result == 2
								self.assertDictEqual(a       ,			{'x': 3, 'y': 2}					)

								snake_case_				=							{'x': 8}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								# evaluate returns the value of the last assignment.
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 8, 'y': 5}					)




	def 							_UpperCamelCase			(       self					)       ->    int:
								snake_case_				=							'test_list = [x, add_two(x)]'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{'add_two': add_two}       ,			state=a					)
								self.assertListEqual(a       ,			[3, 5]					)
								self.assertDictEqual(a       ,			{'x': 3, 'test_list': [3, 5]}					)




	def 							_UpperCamelCase			(       self					)       ->    Dict:
								snake_case_				=							'y = x'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{}       ,			state=a					)
								assert result == 3
								self.assertDictEqual(a       ,			{'x': 3, 'y': 3}					)




	def 							_UpperCamelCase			(       self					)       ->    int:
								snake_case_				=							'test_list = [x, add_two(x)]\ntest_list[1]'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{'add_two': add_two}       ,			state=a					)
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 3, 'test_list': [3, 5]}					)

								snake_case_				=							'test_dict = {\'x\': x, \'y\': add_two(x)}\ntest_dict[\'y\']'
								snake_case_				=							{'x': 3}
								snake_case_				=							evaluate(a       ,			{'add_two': add_two}       ,			state=a					)
								assert result == 5
								self.assertDictEqual(a       ,			{'x': 3, 'test_dict': {'x': 3, 'y': 5}}					)






	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								snake_case_				=							'x = 0\nfor i in range(3):\n    x = i'
								snake_case_				=							{}
								snake_case_				=							evaluate(a       ,			{'range': range}       ,			state=a					)
								assert result == 2
								self.assertDictEqual(a       ,			{'x': 2, 'i': 2}					)













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowercase  							=					{
    "configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
    "tokenization_tapas": ["TapasTokenizer"],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TapasForMaskedLM",
	    "TapasForQuestionAnswering",
	    "TapasForSequenceClassification",
	    "TapasModel",
	    "TapasPreTrainedModel",
	    "load_tf_weights_in_tapas",
	]
try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFTapasForMaskedLM",
	    "TFTapasForQuestionAnswering",
	    "TFTapasForSequenceClassification",
	    "TFTapasModel",
	    "TFTapasPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
	from .tokenization_tapas import TapasTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tapas import (
		    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TapasForMaskedLM,
		    TapasForQuestionAnswering,
		    TapasForSequenceClassification,
		    TapasModel,
		    TapasPreTrainedModel,
		    load_tf_weights_in_tapas,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_tapas import (
		    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTapasForMaskedLM,
		    TFTapasForQuestionAnswering,
		    TFTapasForSequenceClassification,
		    TFTapasModel,
		    TFTapasPreTrainedModel,
		)


else:
	import sys

	lowercase  							=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





