


def        UpperCamelCase_(   lowerCamelCase_				)					->		Union[str, Any]:
    _lowercase :							Any   	=	[]
    _lowercase :							Optional[Any]   	=	[]
    _lowercase :							Optional[Any]   	=	{
        '^': 3,
        '*': 2,
        '/': 2,
        '%': 2,
        '+': 1,
        '-': 1,
    }  # Priority of each operator
    _lowercase :							List[str]   	=	len(lowerCamelCase_				) if (len(lowerCamelCase_				) > 7) else 7

    # Print table header for output
    print(
        'Symbol'.center(8				)							,				'Stack'.center(lowerCamelCase_				)							,				'Postfix'.center(lowerCamelCase_				)							,				sep=' | '							,				)
    print('-' * (print_width * 3 + 7)				)

    for x in infix:
        if x.isalpha() or x.isdigit():
            post_fix.append(lowerCamelCase_				)  # if x is Alphabet / Digit, add it to Postfix
        elif x == "(":
            stack.append(lowerCamelCase_				)  # if x is "(" push to Stack
        elif x == ")":  # if x is ")" pop stack until "(" is encountered
            while stack[-1] != "(":
                post_fix.append(stack.pop()				)  # Pop stack & add the content to Postfix
            stack.pop()
        else:
            if len(lowerCamelCase_				) == 0:
                stack.append(lowerCamelCase_				)  # If stack is empty, push x to stack
            else:  # while priority of x is not > priority of element in the stack
                while len(lowerCamelCase_				) > 0 and priority[x] <= priority[stack[-1]]:
                    post_fix.append(stack.pop()				)  # pop stack & add to Postfix
                stack.append(lowerCamelCase_				)  # push x to stack

        print(
            x.center(8				)							,				(''.join(lowerCamelCase_				)).ljust(lowerCamelCase_				)							,				(''.join(lowerCamelCase_				)).ljust(lowerCamelCase_				)							,				sep=' | '							,				)  # Output in tabular format

    while len(lowerCamelCase_				) > 0:  # while stack is not empty
        post_fix.append(stack.pop()				)  # pop stack & add to Postfix
        print(
            ' '.center(8				)							,				(''.join(lowerCamelCase_				)).ljust(lowerCamelCase_				)							,				(''.join(lowerCamelCase_				)).ljust(lowerCamelCase_				)							,				sep=' | '							,				)  # Output in tabular format

    return "".join(lowerCamelCase_				)  # return Postfix as str



def        UpperCamelCase_(   lowerCamelCase_				)					->		Tuple:
    _lowercase :							Optional[int]   	=	list(infix[::-1]				)  # reverse the infix equation

    for i in range(len(lowerCamelCase_				)				):
        if infix[i] == "(":
            _lowercase :							List[Any]   	=	')'  # change "(" to ")"
        elif infix[i] == ")":
            _lowercase :							Any   	=	'('  # change ")" to "("

    return (infix_2_postfix(''.join(lowerCamelCase_				)				))[
        ::-1
    ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE :   Dict							      =				input("\nEnter an Infix Equation = ")  # Input an Infix equation
 SCREAMING_SNAKE_CASE :   Any							      =				"".join(Infix.split())  # Remove spaces from the input
 print("\n\t", Infix, "(Infix) -> ", infix_2_prefix(Infix), "(Prefix)")






import subprocess
import sys

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






class _lowerCamelCase(		_a     ):
       @require_torch
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	'\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        '

           _lowercase :							Union[str, Any]   	=	'\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        '

           _lowercase :							List[str]   	=	'\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
           _lowercase :							Union[str, Any]   	=	'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
           _lowercase :							Any   	=	[sys.executable, '-c', '\n'.join([load, run, mock])]

           # should succeed
           _lowercase :							List[str]   	=	self.get_env()
           # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
           _lowercase :							Any   	=	'1'
           _lowercase :							List[Any]   	=	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     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							int   	=	'\nfrom transformers import BertConfig, BertModel, BertTokenizer, pipeline\n        '

           _lowercase :							Union[str, Any]   	=	'\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        '

           _lowercase :							List[Any]   	=	'\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
           _lowercase :							Any   	=	'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
           _lowercase :							List[str]   	=	[sys.executable, '-c', '\n'.join([load, run, mock])]

           # should succeed
           _lowercase :							Any   	=	self.get_env()
           _lowercase :							str   	=	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     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Tuple   	=	'\nfrom transformers import BertConfig, BertModel, BertTokenizer\n        '

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

           _lowercase :							List[Any]   	=	'\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
           _lowercase :							int   	=	[sys.executable, '-c', '\n'.join([load, run])]

           # should succeed
           _lowercase :							List[str]   	=	self.get_env()
           _lowercase :							Dict   	=	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
           _lowercase :							Union[str, Any]   	=	[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
           _lowercase :							Optional[Any]   	=	'1'
           _lowercase :							Optional[Any]   	=	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     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	'\nfrom transformers import pipeline\n        '
           _lowercase :							Dict   	=	'\nmname = "hf-internal-testing/tiny-random-bert"\npipe = pipeline(model=mname)\n        '

           _lowercase :							Optional[Any]   	=	'\nimport socket\ndef offline_socket(*args, **kwargs): raise socket.error("Offline mode is enabled")\nsocket.socket = offline_socket\n        '
           _lowercase :							Tuple   	=	self.get_env()
           _lowercase :							Tuple   	=	'1'
           _lowercase :							Union[str, Any]   	=	[sys.executable, '-c', '\n'.join([load, mock, run])]
           _lowercase :							Tuple   	=	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     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							Dict   	=	'\nfrom transformers import AutoModel\n        '
           _lowercase :							int   	=	'\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
           _lowercase :							Optional[int]   	=	[sys.executable, '-c', '\n'.join([load, run])]

           # should succeed
           _lowercase :							int   	=	self.get_env()
           _lowercase :							List[str]   	=	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
           _lowercase :							Tuple   	=	'1'
           _lowercase :							Dict   	=	subprocess.run(lowerCamelCase,   env=lowerCamelCase,   check=lowerCamelCase,   capture_output=lowerCamelCase)
           self.assertEqual(result.returncode,   0,   result.stderr)
           self.assertIn('success',   result.stdout.decode())


