




import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 @require_torch
 def  lowerCAmelCase_    (				self    :						int		):
       # this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
       # `transformers` is loaded, and it's too late for inside pytest - so we are changing it
       # while running an external program

       # python one-liner segments

       # this must be loaded before socket.socket is monkey-patched
       SCREAMING_SNAKE_CASE_      		=     '\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nmname = "hf-internal-testing/tiny-random-bert"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task="fill-mask", model=mname)\nprint("success")\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nimport socket\ndef offline_socket(*args, **kwargs): raise RuntimeError("Offline mode is enabled, we shouldn\'t access internet")\nsocket.socket = offline_socket\n        '

       # Force fetching the files so that we can use the cache
       SCREAMING_SNAKE_CASE_      		=     'hf-internal-testing/tiny-random-bert'
       BertConfig.from_pretrained(_lowerCAmelCase		)
       BertModel.from_pretrained(_lowerCAmelCase		)
       BertTokenizer.from_pretrained(_lowerCAmelCase		)
       pipeline(task='fill-mask'							,							model=_lowerCAmelCase		)

       # baseline - just load from_pretrained with normal network
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, run, mock]		)]

       # should succeed
       SCREAMING_SNAKE_CASE_      		=     self.get_env()
       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       SCREAMING_SNAKE_CASE_      		=     '1'
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)



 @require_torch
 def  lowerCAmelCase_    (				self    :						Tuple		):
       # python one-liner segments
       # this must be loaded before socket.socket is monkey-patched
       SCREAMING_SNAKE_CASE_      		=     '\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nmname = "hf-internal-testing/tiny-random-bert"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nBertTokenizer.from_pretrained(mname)\npipe = pipeline(task="fill-mask", model=mname)\nprint("success")\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error("Faking flaky internet")\nsocket.socket = offline_socket\n        '

       # Force fetching the files so that we can use the cache
       SCREAMING_SNAKE_CASE_      		=     'hf-internal-testing/tiny-random-bert'
       BertConfig.from_pretrained(_lowerCAmelCase		)
       BertModel.from_pretrained(_lowerCAmelCase		)
       BertTokenizer.from_pretrained(_lowerCAmelCase		)
       pipeline(task='fill-mask'							,							model=_lowerCAmelCase		)

       # baseline - just load from_pretrained with normal network
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, run, mock]		)]

       # should succeed
       SCREAMING_SNAKE_CASE_      		=     self.get_env()
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)



 @require_torch
 def  lowerCAmelCase_    (				self    :						List[str]		):
       # this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
       # `transformers` is loaded, and it's too late for inside pytest - so we are changing it
       # while running an external program

       # python one-liner segments

       # this must be loaded before socket.socket is monkey-patched
       SCREAMING_SNAKE_CASE_      		=     '\nfrom transformers import BertConfig, BertModel, BertTokenizer\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nmname = "hf-internal-testing/tiny-random-bert-sharded"\nBertConfig.from_pretrained(mname)\nBertModel.from_pretrained(mname)\nprint("success")\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nimport socket\ndef offline_socket(*args, **kwargs): raise ValueError("Offline mode is enabled")\nsocket.socket = offline_socket\n        '

       # baseline - just load from_pretrained with normal network
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, run]		)]

       # should succeed
       SCREAMING_SNAKE_CASE_      		=     self.get_env()
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)

       # next emulate no network
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, mock, run]		)]

       # Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
       # env["TRANSFORMERS_OFFLINE"] = "0"
       # result = subprocess.run(cmd, env=env, check=False, capture_output=True)
       # self.assertEqual(result.returncode, 1, result.stderr)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       SCREAMING_SNAKE_CASE_      		=     '1'
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)



 @require_torch
 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     '\nfrom transformers import pipeline\n        '
       SCREAMING_SNAKE_CASE_      		=     '\nmname = "hf-internal-testing/tiny-random-bert"\npipe = pipeline(model=mname)\n        '

       SCREAMING_SNAKE_CASE_      		=     '\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error("Offline mode is enabled")\nsocket.socket = offline_socket\n        '
       SCREAMING_SNAKE_CASE_      		=     self.get_env()
       SCREAMING_SNAKE_CASE_      		=     '1'
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, mock, run]		)]
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							1							,							result.stderr		)
       self.assertIn(
           'You cannot infer task automatically within `pipeline` when using offline mode'							,							result.stderr.decode().replace('\n'							,							''		)							,							)




 @require_torch
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     '\nfrom transformers import AutoModel\n        '
       SCREAMING_SNAKE_CASE_      		=     '\nmname = "hf-internal-testing/test_dynamic_model"\nAutoModel.from_pretrained(mname, trust_remote_code=True)\nprint("success")\n        '

       # baseline - just load from_pretrained with normal network
       SCREAMING_SNAKE_CASE_      		=     [sys.executable, '-c', '\n'.join([load, run]		)]

       # should succeed
       SCREAMING_SNAKE_CASE_      		=     self.get_env()
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       SCREAMING_SNAKE_CASE_      		=     '1'
       SCREAMING_SNAKE_CASE_      		=     subprocess.run(_lowerCAmelCase							,							env=_lowerCAmelCase							,							check=_lowerCAmelCase							,							capture_output=_lowerCAmelCase		)
       self.assertEqual(result.returncode							,							0							,							result.stderr		)
       self.assertIn('success'							,							result.stdout.decode()		)

'''simple docstring'''





import unittest

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







def snake_case_     (					lowercase__		):
  return x + 2






class 							UpperCAmelCase_							(    unittest.TestCase				):

 '''simple docstring'''







 def 							UpperCamelCase  (					self		:  Optional[int] ):



   '''simple docstring'''




   UpperCAmelCase__      :					List[str]				       =							"x = 3"
   UpperCAmelCase__      :					List[str]				       =							{}
   UpperCAmelCase__      :					Tuple				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   assert result == 3
   self.assertDictEqual(snake_case__			,				{"x": 3} )

   UpperCAmelCase__      :					Any				       =							"x = y"
   UpperCAmelCase__      :					List[str]				       =							{"y": 5}
   UpperCAmelCase__      :					Dict				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   # evaluate returns the value of the last assignment.
   assert result == 5
   self.assertDictEqual(snake_case__			,				{"x": 5, "y": 5} )







 def 							UpperCamelCase  (					self		:  Union[str, Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					int				       =							"y = add_two(x)"
   UpperCAmelCase__      :					Tuple				       =							{"x": 3}
   UpperCAmelCase__      :					Union[str, Any]				       =							evaluate(snake_case__			,				{"add_two": add_two}			,				state=snake_case__ )
   assert result == 5
   self.assertDictEqual(snake_case__			,				{"x": 3, "y": 5} )

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







 def 							UpperCamelCase  (					self		:  List[str] ):



   '''simple docstring'''




   UpperCAmelCase__      :					Tuple				       =							"x = 3"
   UpperCAmelCase__      :					List[Any]				       =							{}
   UpperCAmelCase__      :					Tuple				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   assert result == 3
   self.assertDictEqual(snake_case__			,				{"x": 3} )







 def 							UpperCamelCase  (					self		:  Dict ):



   '''simple docstring'''




   UpperCAmelCase__      :					int				       =							"test_dict = {'x': x, 'y': add_two(x)}"
   UpperCAmelCase__      :					List[Any]				       =							{"x": 3}
   UpperCAmelCase__      :					int				       =							evaluate(snake_case__			,				{"add_two": add_two}			,				state=snake_case__ )
   self.assertDictEqual(snake_case__			,				{"x": 3, "y": 5} )
   self.assertDictEqual(snake_case__			,				{"x": 3, "test_dict": {"x": 3, "y": 5}} )







 def 							UpperCamelCase  (					self		:  List[str] ):



   '''simple docstring'''




   UpperCAmelCase__      :					int				       =							"x = 3\ny = 5"
   UpperCAmelCase__      :					Dict				       =							{}
   UpperCAmelCase__      :					Union[str, Any]				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   # evaluate returns the value of the last assignment.
   assert result == 5
   self.assertDictEqual(snake_case__			,				{"x": 3, "y": 5} )







 def 							UpperCamelCase  (					self		:  Union[str, Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					Dict				       =							"text = f'This is x: {x}.'"
   UpperCAmelCase__      :					Dict				       =							{"x": 3}
   UpperCAmelCase__      :					Dict				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   # evaluate returns the value of the last assignment.
   assert result == "This is x: 3."
   self.assertDictEqual(snake_case__			,				{"x": 3, "text": "This is x: 3."} )







 def 							UpperCamelCase  (					self		:  List[Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					List[str]				       =							"if x <= 3:\n    y = 2\nelse:\n    y = 5"
   UpperCAmelCase__      :					Dict				       =							{"x": 3}
   UpperCAmelCase__      :					Dict				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   # evaluate returns the value of the last assignment.
   assert result == 2
   self.assertDictEqual(snake_case__			,				{"x": 3, "y": 2} )

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







 def 							UpperCamelCase  (					self		:  str ):



   '''simple docstring'''




   UpperCAmelCase__      :					Optional[int]				       =							"test_list = [x, add_two(x)]"
   UpperCAmelCase__      :					Any				       =							{"x": 3}
   UpperCAmelCase__      :					Any				       =							evaluate(snake_case__			,				{"add_two": add_two}			,				state=snake_case__ )
   self.assertListEqual(snake_case__			,				[3, 5] )
   self.assertDictEqual(snake_case__			,				{"x": 3, "test_list": [3, 5]} )







 def 							UpperCamelCase  (					self		:  str ):



   '''simple docstring'''




   UpperCAmelCase__      :					str				       =							"y = x"
   UpperCAmelCase__      :					str				       =							{"x": 3}
   UpperCAmelCase__      :					Any				       =							evaluate(snake_case__			,				{}			,				state=snake_case__ )
   assert result == 3
   self.assertDictEqual(snake_case__			,				{"x": 3, "y": 3} )







 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					Optional[int]				       =							"test_list = [x, add_two(x)]\ntest_list[1]"
   UpperCAmelCase__      :					List[Any]				       =							{"x": 3}
   UpperCAmelCase__      :					List[Any]				       =							evaluate(snake_case__			,				{"add_two": add_two}			,				state=snake_case__ )
   assert result == 5
   self.assertDictEqual(snake_case__			,				{"x": 3, "test_list": [3, 5]} )

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







 def 							UpperCamelCase  (					self		:  Union[str, Any] ):



   '''simple docstring'''




   UpperCAmelCase__      :					List[Any]				       =							"x = 0\nfor i in range(3):\n    x = i"
   UpperCAmelCase__      :					List[Any]				       =							{}
   UpperCAmelCase__      :					Any				       =							evaluate(snake_case__			,				{"range": range}			,				state=snake_case__ )
   assert result == 2
   self.assertDictEqual(snake_case__			,				{"x": 2, "i": 2} )



