



#
# Sort large text files in a minimum amount of memory
#
import argparse
import os


class 	a__       :


					"""simple docstring"""



					A__  :				List[Any]					 =				'''block_{0}.dat'''

					def __init__(		self     :List[str]      ,  lowercase__     :int    ):
										lowercase						   =       filename
										lowercase						   =       []

					def 				__UpperCAmelCase		(		self     :Union[str, Any]      ,  lowercase__     :List[str]      ,  lowercase__     :Optional[int]    ):
										lowercase						   =       self.BLOCK_FILENAME_FORMAT.format(lowercase__    )
										with open(lowercase__      ,  'w'    ) as file:
															file.write(lowercase__    )
										self.block_filenames.append(lowercase__    )

					def 				__UpperCAmelCase		(		self     :Union[str, Any]    ):
										return self.block_filenames

					def 				__UpperCAmelCase		(		self     :int      ,  lowercase__     :Optional[int]      ,  lowercase__     :Optional[int]=None    ):
										lowercase						   =       0
										with open(self.filename    ) as file:
															while True:
																				lowercase						   =       file.readlines(lowercase__    )

																				if lines == []:
																									break

																				if sort_key is None:
																									lines.sort()
																				else:
																									lines.sort(key=lowercase__    )

																				self.write_block(''.join(lowercase__    )      ,  lowercase__    )
																				i += 1



					def 				__UpperCAmelCase		(		self     :str    ):
										map(os.remove      ,  self.block_filenames    )




class 	a__       :


					"""simple docstring"""



					def 				__UpperCAmelCase		(		self     :Dict      ,  lowercase__     :str    ):
										lowercase						   =       -1
										lowercase						   =       None

										for i in range(len(lowercase__    )    ):
															if min_str is None or choices[i] < min_str:
																				lowercase						   =       i

										return min_index




class 	a__       :


					"""simple docstring"""



					def __init__(		self     :Any      ,  lowercase__     :List[str]    ):
										lowercase						   =       files
										lowercase						   =       set()
										lowercase						   =       len(lowercase__    )
										lowercase						   =       {i: None for i in range(self.num_buffers    )}

					def 				__UpperCAmelCase		(		self     :Any    ):
										return {
										    i: self.buffers[i] for i in range(self.num_buffers    ) if i not in self.empty
										}

					def 				__UpperCAmelCase		(		self     :int    ):
										for i in range(self.num_buffers    ):
															if self.buffers[i] is None and i not in self.empty:
																				lowercase						   =       self.files[i].readline()

																				if self.buffers[i] == "":
																									self.empty.add(lowercase__    )
																									self.files[i].close()

										if len(self.empty    ) == self.num_buffers:
															return False

										return True



					def 				__UpperCAmelCase		(		self     :Optional[Any]      ,  lowercase__     :Optional[int]    ):
										lowercase						   =       self.buffers[index]
										lowercase						   =       None

										return value




class 	a__       :


					"""simple docstring"""



					def __init__(		self     :Any      ,  lowercase__     :Dict    ):
										lowercase						   =       merge_strategy

					def 				__UpperCAmelCase		(		self     :str      ,  lowercase__     :int      ,  lowercase__     :List[Any]      ,  lowercase__     :Union[str, Any]    ):
										lowercase						   =       FilesArray(self.get_file_handles(lowercase__      ,  lowercase__    )    )
										with open(lowercase__      ,  'w'      ,  lowercase__    ) as outfile:
															while buffers.refresh():
																				lowercase						   =       self.merge_strategy.select(buffers.get_dict()    )
																				outfile.write(buffers.unshift(lowercase__    )    )



					def 				__UpperCAmelCase		(		self     :Optional[Any]      ,  lowercase__     :int      ,  lowercase__     :int    ):
										lowercase						   =       {}

										for i in range(len(lowercase__    )    ):
															lowercase						   =       open(filenames[i]      ,  'r'      ,  lowercase__    )  # noqa: UP015

										return files




class 	a__       :


					"""simple docstring"""



					def __init__(		self     :Optional[int]      ,  lowercase__     :List[Any]    ):
										lowercase						   =       block_size

					def 				__UpperCAmelCase		(		self     :Optional[int]      ,  lowercase__     :str      ,  lowercase__     :Union[str, Any]=None    ):
										lowercase						   =       self.get_number_blocks(lowercase__      ,  self.block_size    )
										lowercase						   =       FileSplitter(lowercase__    )
										splitter.split(self.block_size      ,  lowercase__    )

										lowercase						   =       FileMerger(NWayMerge()    )
										lowercase						   =       self.block_size / (num_blocks + 1)
										merger.merge(splitter.get_block_filenames()      ,  filename + '.out'      ,  lowercase__    )

										splitter.cleanup()



					def 				__UpperCAmelCase		(		self     :str      ,  lowercase__     :Optional[Any]      ,  lowercase__     :Optional[int]    ):
										return (os.stat(lowercase__    ).st_size / block_size) + 1





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					if string[-1].lower() == "k":
										return int(string[:-1]				) * 10_24
					elif string[-1].lower() == "m":
										return int(string[:-1]				) * 10_24 * 10_24
					elif string[-1].lower() == "g":
										return int(string[:-1]				) * 10_24 * 10_24 * 10_24
					else:
										return int(_UpperCAmelCase				)





def 		__snake_case						(    ):
					"""simple docstring"""






					lowercase						   =       argparse.ArgumentParser()
					parser.add_argument(
					    '-m'       ,			'--mem'       ,			help='amount of memory to use for sorting'       ,			default='100M'				)
					parser.add_argument(
					    'filename'       ,			metavar='<filename>'       ,			nargs=1       ,			help='name of file to sort'				)
					lowercase						   =       parser.parse_args()

					lowercase						   =       ExternalSort(parse_memory(args.mem				)				)
					sorter.sort(args.filename[0]				)


if __name__ == "__main__":
		main()











from typing import List, Optional, Tuple, Union

from . import logging
from .import_utils import is_torch_available, is_torch_version


if is_torch_available():
		import torch

__magic_name__       =     logging.get_logger(__name__)  # pylint: disable=invalid-name

try:
		from torch._dynamo import allow_in_graph as maybe_allow_in_graph
except (ImportError, ModuleNotFoundError):





		def 		__snake_case						(    cls				):
							"""simple docstring"""






							return cls





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase = None       ,			_UpperCAmelCase = None       ,			_UpperCAmelCase = None       ,			_UpperCAmelCase = None       ,			):
					"""simple docstring"""






					lowercase						   =       device
					lowercase						   =       shape[0]

					lowercase						   =       layout or torch.strided
					lowercase						   =       device or torch.device('cpu'				)

					if generator is not None:
										lowercase						   =       generator.device.type if not isinstance(_UpperCAmelCase       ,			_UpperCAmelCase				) else generator[0].device.type
										if gen_device_type != device.type and gen_device_type == "cpu":
															lowercase						   =       'cpu'
															if device != "mps":
																				logger.info(
																				    f"""The passed generator was created on 'cpu' even though a tensor on {device} was expected."""
																				    f""" Tensors will be created on 'cpu' and then moved to {device}. Note that one can probably"""
																				    f""" slighly speed up this function by passing a generator that was created on the {device} device."""				)
										elif gen_device_type != device.type and gen_device_type == "cuda":
															raise ValueError(f"""Cannot generate a {device} tensor from a generator of type {gen_device_type}."""				)

					if isinstance(_UpperCAmelCase       ,			_UpperCAmelCase				):
										lowercase						   =       (1,) + shape[1:]
										lowercase						   =       [
										    torch.randn(_UpperCAmelCase       ,			generator=generator[i]       ,			device=_UpperCAmelCase       ,			dtype=_UpperCAmelCase       ,			layout=_UpperCAmelCase				)
										    for i in range(_UpperCAmelCase				)
										]
										lowercase						   =       torch.cat(_UpperCAmelCase       ,			dim=0				).to(_UpperCAmelCase				)
					else:
										lowercase						   =       torch.randn(_UpperCAmelCase       ,			generator=_UpperCAmelCase       ,			device=_UpperCAmelCase       ,			dtype=_UpperCAmelCase       ,			layout=_UpperCAmelCase				).to(_UpperCAmelCase				)

					return latents





def 		__snake_case						(    _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				)






