





# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


A       :   List[str]					= '''Create a default config file for Accelerate with only a few flags set.'''







def   __lowerCamelCase   (				__a  :Any="no"       ,	__a  :str = default_json_config_file       ,	__a  :bool = False       )						->							List[str]:






		"""simple docstring"""

		A__     =  Path(__a       )
		path.parent.mkdir(parents=__a       ,	exist_ok=__a       )
		if path.exists():
				print(
				    F'Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'       )
				return False
		A__     =  mixed_precision.lower()
		if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
				raise ValueError(
				    F'`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'       )
		A__     =  {
		    """compute_environment""": """LOCAL_MACHINE""",
		    """mixed_precision""": mixed_precision,
		}
		if torch.cuda.is_available():
				A__     =  torch.cuda.device_count()
				A__     =  num_gpus
				A__     =  False
				if num_gpus > 1:
						A__     =  """MULTI_GPU"""
				else:
						A__     =  """NO"""
		elif is_xpu_available() and use_xpu:
				A__     =  torch.xpu.device_count()
				A__     =  num_xpus
				A__     =  False
				if num_xpus > 1:
						A__     =  """MULTI_XPU"""
				else:
						A__     =  """NO"""
		elif is_npu_available():
				A__     =  torch.npu.device_count()
				A__     =  num_npus
				A__     =  False
				if num_npus > 1:
						A__     =  """MULTI_NPU"""
				else:
						A__     =  """NO"""
		else:
				A__     =  0
				A__     =  True
				A__     =  1
				A__     =  """NO"""
		A__     =  ClusterConfig(**__a       )
		config.to_json_file(__a       )
		return path







def   __lowerCamelCase   (				__a  :Optional[Any]       ,	__a  :int       )						->							List[Any]:






		"""simple docstring"""

		A__     =  parser.add_parser("""default"""       ,	parents=__a       ,	help=__a       ,	formatter_class=__a       )
		parser.add_argument(
		    """--config_file"""       ,	default=__a       ,	help=(
		        """The path to use to store the config file. Will default to a file named default_config.yaml in the cache """
		        """location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have """
		        """such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed """
		        """with 'huggingface'."""
		    )       ,	dest="""save_location"""       ,	)

		parser.add_argument(
		    """--mixed_precision"""       ,	choices=["""no""", """fp16""", """bf16"""]       ,	type=__a       ,	help="""Whether or not to use mixed precision training. """
		    """Choose between FP16 and BF16 (bfloat16) training. """
		    """BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later."""       ,	default="""no"""       ,	)
		parser.set_defaults(func=__a       )
		return parser







def   __lowerCamelCase   (				__a  :Optional[int]       )						->							List[str]:






		"""simple docstring"""

		A__     =  write_basic_config(args.mixed_precision       ,	args.save_location       )
		if config_file:
				print(F'accelerate configuration saved at {config_file}'       )










def   __lowerCamelCase   (				__a  :Dict       )						->							Optional[int]:






		"""simple docstring"""

		A__     =  []
		A__     =  []
		A__     =  {
		    """^""": 3,
		    """*""": 2,
		    """/""": 2,
		    """%""": 2,
		    """+""": 1,
		    """-""": 1,
		}  # Priority of each operator
		A__     =  len(__a       ) if (len(__a       ) > 7) else 7

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

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

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

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

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







def   __lowerCamelCase   (				__a  :List[str]       )						->							Union[str, Any]:






		"""simple docstring"""

		A__     =  list(infix[::-1]       )  # reverse the infix equation

		for i in range(len(__a       )       ):
				if infix[i] == "(":
						A__     =  """)"""  # change "(" to ")"
				elif infix[i] == ")":
						A__     =  """("""  # change ")" to "("

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


if __name__ == "__main__":
					A       :   Union[str, Any]					= input('''\nEnter an Infix Equation = ''')  # Input an Infix equation
					A       :   Dict					= ''''''.join(Infix.split())  # Remove spaces from the input
					print('''\n\t''', Infix, '''(Infix) -> ''', infix_2_prefix(Infix), '''(Prefix)''')



