






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



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = True				):
				A__							 =       (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

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

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

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

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

				if is_compiled:
								A__							 =       model
								A__							 =       compiled_model

				return model



def  __lowerCamelCase					(					):
				PartialState().wait_for_everyone()



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



@contextmanager
def  __lowerCamelCase					(					**lowerCAmelCase__				):
				for key, value in kwargs.items():
								A__							 =       str(lowerCAmelCase__				)

				yield

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



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



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

				return destination







def  __lowerCamelCase					(					lowerCAmelCase__ = None				):
				if port is None:
								A__							 =       2_9500
				with socket.socket(socket.AF_INET       ,socket.SOCK_STREAM				) as s:
								return s.connect_ex(('localhost', port)				) == 0










"""simple docstring"""






from __future__ import annotations



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = None				):
				A__							 =       word_bank or []
				# create a table
				A__							 =       len(lowerCAmelCase__				) + 1

				A__							 =       []
				for _ in range(lowerCAmelCase__				):
								table.append([]				)
				# seed value
				A__							 =       [[]]  # because empty string has empty combination

				# iterate through the indices
				for i in range(lowerCAmelCase__				):
								# condition
								if table[i] != []:
												for word in word_bank:
																# slice condition
																if target[i : i + len(lowerCAmelCase__				)] == word:
																				A__							 =       [
																				    [word, *way] for way in table[i]
																				]
																				# adds the word to every combination the current position holds
																				# now,push that combination to the table[i+len(word)]
																				table[i + len(lowerCAmelCase__				)] += new_combinations

    # combinations are in reverse order so reverse for better output
				for combination in table[len(lowerCAmelCase__				)]:
								combination.reverse()

				return table[len(lowerCAmelCase__				)]


if __name__ == "__main__":
					print(all_construct('''jwajalapa''', ['''jwa''', '''j''', '''w''', '''a''', '''la''', '''lapa''']))
					print(all_construct('''rajamati''', ['''s''', '''raj''', '''amat''', '''raja''', '''ma''', '''i''', '''t''']))
					print(
					    all_construct(
					        '''hexagonosaurus''',
					        ['''h''', '''ex''', '''hex''', '''ag''', '''ago''', '''ru''', '''auru''', '''rus''', '''go''', '''no''', '''o''', '''s'''],
					    )
					)


