"""simple docstring"""




import itertools
import string
from collections.abc import Generator, Iterable






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							iter(UpperCamelCase__ )
							while True:
														A__		   =							tuple(itertools.islice(UpperCamelCase__				,			UpperCamelCase__ ) )
														if not chunk:
																					return
														yield chunk






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							''.join([c.upper() for c in dirty if c in string.ascii_letters] )
							A__		   =							''

							if len(UpperCamelCase__ ) < 2:
														return dirty

							for i in range(len(UpperCamelCase__ ) - 1 ):
														clean += dirty[i]

														if dirty[i] == dirty[i + 1]:
																					clean += "X"

							clean += dirty[-1]

							if len(UpperCamelCase__ ) & 1:
														clean += "X"

							return clean






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							'ABCDEFGHIKLMNOPQRSTUVWXYZ'
							# we're using a list instead of a '2d' array because it makes the math
							# for setting up the table and doing the actual encoding/decoding simpler
							A__		   =							[]

							# copy key chars into the table if they are in `alphabet` ignoring duplicates
							for char in key.upper():
														if char not in table and char in alphabet:
																					table.append(UpperCamelCase__ )

    # fill the rest of the table in with the remaining alphabet chars
							for char in alphabet:
														if char not in table:
																					table.append(UpperCamelCase__ )

							return table






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							generate_table(UpperCamelCase__ )
							A__		   =							prepare_input(UpperCamelCase__ )
							A__		   =							''

							# https://en.wikipedia.org/wiki/Playfair_cipher#Description
							for chara, chara in chunker(UpperCamelCase__				,			2 ):
														A__   ,     A__		   =							divmod(table.index(UpperCamelCase__ )				,			5 )
														A__   ,     A__		   =							divmod(table.index(UpperCamelCase__ )				,			5 )

														if rowa == rowa:
																					ciphertext += table[rowa * 5 + (cola + 1) % 5]
																					ciphertext += table[rowa * 5 + (cola + 1) % 5]
														elif cola == cola:
																					ciphertext += table[((rowa + 1) % 5) * 5 + cola]
																					ciphertext += table[((rowa + 1) % 5) * 5 + cola]
														else:  # rectangle
																					ciphertext += table[rowa * 5 + cola]
																					ciphertext += table[rowa * 5 + cola]

							return ciphertext






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							generate_table(UpperCamelCase__ )
							A__		   =							''

							# https://en.wikipedia.org/wiki/Playfair_cipher#Description
							for chara, chara in chunker(UpperCamelCase__				,			2 ):
														A__   ,     A__		   =							divmod(table.index(UpperCamelCase__ )				,			5 )
														A__   ,     A__		   =							divmod(table.index(UpperCamelCase__ )				,			5 )

														if rowa == rowa:
																					plaintext += table[rowa * 5 + (cola - 1) % 5]
																					plaintext += table[rowa * 5 + (cola - 1) % 5]
														elif cola == cola:
																					plaintext += table[((rowa - 1) % 5) * 5 + cola]
																					plaintext += table[((rowa - 1) % 5) * 5 + cola]
														else:  # rectangle
																					plaintext += table[rowa * 5 + cola]
																					plaintext += table[rowa * 5 + cola]

							return plaintext






"""simple docstring"""




import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
				from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
				import torch_xla.core.xla_model as xm






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							if is_torch_version('<'				,			'2.0.0' ) or not hasattr(UpperCamelCase__				,			'_dynamo' ):
														return False
							return isinstance(UpperCamelCase__				,			torch._dynamo.eval_frame.OptimizedModule )






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ = True ):






							"""simple docstring"""





							A__		   =							(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

							A__		   =							is_compiled_module(UpperCamelCase__ )
							if is_compiled:
														A__		   =							model
														A__		   =							model._orig_mod

							if is_deepspeed_available():
														options += (DeepSpeedEngine,)

							while isinstance(UpperCamelCase__				,			UpperCamelCase__ ):
														A__		   =							model.module

							if not keep_fpaa_wrapper:
														A__		   =							getattr(UpperCamelCase__				,			'forward' )
														A__		   =							model.__dict__.pop('_original_forward'				,			UpperCamelCase__ )
														if original_forward is not None:
																					while hasattr(UpperCamelCase__				,			'__wrapped__' ):
																												A__		   =							forward.__wrapped__
																												if forward == original_forward:
																																			break
																					A__		   =							forward
														if getattr(UpperCamelCase__				,			'_converted_to_transformer_engine'				,			UpperCamelCase__ ):
																					convert_model(UpperCamelCase__				,			to_transformer_engine=UpperCamelCase__ )

							if is_compiled:
														A__		   =							model
														A__		   =							compiled_model

							return model






def      UpperCAmelCase    (		):






							"""simple docstring"""





							PartialState().wait_for_everyone()






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							if PartialState().distributed_type == DistributedType.TPU:
														xm.save(UpperCamelCase__				,			UpperCamelCase__ )
							elif PartialState().local_process_index == 0:
														torch.save(UpperCamelCase__				,			UpperCamelCase__ )






@contextmanager
def      UpperCAmelCase    (		**UpperCamelCase__ ):






							"""simple docstring"""





							for key, value in kwargs.items():
														A__		   =							str(UpperCamelCase__ )

							yield

							for key in kwargs:
														if key.upper() in os.environ:
																					del os.environ[key.upper()]






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							if not hasattr(UpperCamelCase__				,			'__qualname__' ) and not hasattr(UpperCamelCase__				,			'__name__' ):
														A__		   =							getattr(UpperCamelCase__				,			'__class__'				,			UpperCamelCase__ )
							if hasattr(UpperCamelCase__				,			'__qualname__' ):
														return obj.__qualname__
							if hasattr(UpperCamelCase__				,			'__name__' ):
														return obj.__name__
							return str(UpperCamelCase__ )






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							for key, value in source.items():
														if isinstance(UpperCamelCase__				,			UpperCamelCase__ ):
																					A__		   =							destination.setdefault(UpperCamelCase__				,			{} )
																					merge_dicts(UpperCamelCase__				,			UpperCamelCase__ )
														else:
																					A__		   =							value

							return destination






def      UpperCAmelCase    (		UpperCamelCase__ = None ):






							"""simple docstring"""





							if port is None:
														A__		   =							29_500
							with socket.socket(socket.AF_INET				,			socket.SOCK_STREAM ) as s:
														return s.connect_ex(('localhost', port) ) == 0





