

import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand





def a(lowercase__	):





	'''simple docstring'''
	return EnvironmentCommand()





def a(lowercase__	):





	'''simple docstring'''
	return EnvironmentCommand(args.accelerate_config_file	)






class SCREAMING_SNAKE_CASE  (		__UpperCAmelCase							):






			"""simple docstring"""




			@staticmethod
			def 			__lowerCAmelCase (    __UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= parser.add_parser('env'							)
				download_parser.set_defaults(func=lowerCAmelCase_							)
				download_parser.add_argument(
				    '--accelerate-config_file' ,				default=lowerCAmelCase_ ,				help='The accelerate config file to use for the default values in the launching script.' ,				)
				download_parser.set_defaults(func=lowerCAmelCase_							)


			def __init__(    self ,				__UpperCamelCase ,				*__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= accelerate_config_file


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= 'not installed'
				if is_safetensors_available():
					import safetensors

					snake_case_      		= safetensors.__version__
				elif importlib.util.find_spec('safetensors'							) is not None:
					import safetensors

					snake_case_      		= f"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

				snake_case_      		= 'not installed'
				snake_case_      		= snake_case_      		= 'not found'
				if is_accelerate_available():
					import accelerate
					from accelerate.commands.config import default_config_file, load_config_from_file

					snake_case_      		= accelerate.__version__
					# Get the default from the config file.
					if self._accelerate_config_file is not None or os.path.isfile(lowerCAmelCase_							):
						snake_case_      		= load_config_from_file(self._accelerate_config_file							).to_dict()

					snake_case_      		= (
					    '\n'.join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]							)
					    if isinstance(lowerCAmelCase_ ,				lowerCAmelCase_							)
					    else f"""\t{accelerate_config}"""
					)

				snake_case_      		= 'not installed'
				snake_case_      		= 'NA'
				if is_torch_available():
					import torch

					snake_case_      		= torch.__version__
					snake_case_      		= torch.cuda.is_available()

				snake_case_      		= 'not installed'
				snake_case_      		= 'NA'
				if is_tf_available():
					import tensorflow as tf

					snake_case_      		= tf.__version__
					try:
						# deprecated in v2.1
						snake_case_      		= tf.test.is_gpu_available()
					except AttributeError:
						# returns list of devices, convert to bool
						snake_case_      		= bool(tf.config.list_physical_devices('GPU'							)							)

				snake_case_      		= 'not installed'
				snake_case_      		= 'not installed'
				snake_case_      		= 'not installed'
				snake_case_      		= 'NA'
				if is_flax_available():
					import flax
					import jax
					import jaxlib

					snake_case_      		= flax.__version__
					snake_case_      		= jax.__version__
					snake_case_      		= jaxlib.__version__
					snake_case_      		= jax.lib.xla_bridge.get_backend().platform

				snake_case_      		= {
				    '`transformers` version': version,
				    'Platform': platform.platform(),
				    'Python version': platform.python_version(),
				    'Huggingface_hub version': huggingface_hub.__version__,
				    'Safetensors version': f"""{safetensors_version}""",
				    'Accelerate version': f"""{accelerate_version}""",
				    'Accelerate config': f"""{accelerate_config_str}""",
				    'PyTorch version (GPU?)': f"""{pt_version} ({pt_cuda_available})""",
				    'Tensorflow version (GPU?)': f"""{tf_version} ({tf_cuda_available})""",
				    'Flax version (CPU?/GPU?/TPU?)': f"""{flax_version} ({jax_backend})""",
				    'Jax version': f"""{jax_version}""",
				    'JaxLib version': f"""{jaxlib_version}""",
				    'Using GPU in script?': '<fill in>',
				    'Using distributed or parallel set-up in script?': '<fill in>',
				}

				print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'							)
				print(self.format_dict(lowerCAmelCase_							)							)

				return info







			@staticmethod
			def 			__lowerCAmelCase (    __UpperCamelCase							):

				"""simple docstring"""


				return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()]							) + "\n"



import operator as op





def a(lowercase__	):





	'''simple docstring'''
	snake_case_      		= []
	snake_case_      		= lambda lowercase__			, lowercase__	: int(x / y	)  # noqa: E731 integer division operation
	snake_case_      		= {
	    '^': op.pow,
	    '*': op.mul,
	    '/': div,
	    '+': op.add,
	    '-': op.sub,
	}  # operators & their respective operation

	# print table header
	print('Symbol'.center(8	)			, 'Action'.center(12	)			, 'Stack'			, sep=' | '	)
	print('-' * (30 + len(lowercase__	))	)

	for x in post_fix:
		if x.isdigit():  # if x in digit
			stack.append(lowercase__	)  # append x to stack
			# output in tabular format
			print(x.rjust(8	)			, ('push(' + x + ')').ljust(12	)			, ','.join(lowercase__	)			, sep=' | '	)
		else:
			snake_case_      		= stack.pop()  # pop stack
			# output in tabular format
			print(''.rjust(8	)			, ('pop(' + b + ')').ljust(12	)			, ','.join(lowercase__	)			, sep=' | '	)

			snake_case_      		= stack.pop()  # pop stack
			# output in tabular format
			print(''.rjust(8	)			, ('pop(' + a + ')').ljust(12	)			, ','.join(lowercase__	)			, sep=' | '	)

			stack.append(
			    str(opr[x](int(lowercase__	)			, int(lowercase__	)	)	)	)  # evaluate the 2 values popped from stack & push result to stack
			# output in tabular format
			print(
			    x.rjust(8	)			, ('push(' + a + x + b + ')').ljust(12	)			, ','.join(lowercase__	)			, sep=' | '			, )

	return int(stack[0]	)


if __name__ == "__main__":
		A											=     input('\n\nEnter a Postfix Equation (space separated) = ').split(' ')
		print('\n\tResult = ', solve(Postfix))
