
'''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 		A_(     A						:		List[str]):
							if is_torch_version('<'		,     '2.0.0') or not hasattr(A		,     '_dynamo'):
														return False
							return isinstance(A		,     torch._dynamo.eval_frame.OptimizedModule)







def 		A_(     A						:		Union[str, Any]		,     A						:		bool = True):
							UpperCamelCase   			=     (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

							UpperCamelCase   			=     is_compiled_module(A)
							if is_compiled:
														UpperCamelCase   			=     model
														UpperCamelCase   			=     model._orig_mod

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

							while isinstance(A		,     A):
														UpperCamelCase   			=     model.module

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

							if is_compiled:
														UpperCamelCase   			=     model
														UpperCamelCase   			=     compiled_model

							return model







def 		A_(     ):
							PartialState().wait_for_everyone()







def 		A_(     A						:		Dict		,     A						:		int):
							if PartialState().distributed_type == DistributedType.TPU:
														xm.save(A		,     A)
							elif PartialState().local_process_index == 0:
														torch.save(A		,     A)







@contextmanager
def 		A_(     **A						:		Dict):
							for key, value in kwargs.items():
														UpperCamelCase   			=     str(A)

							yield

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







def 		A_(     A						:		int):
							if not hasattr(A		,     '__qualname__') and not hasattr(A		,     '__name__'):
														UpperCamelCase   			=     getattr(A		,     '__class__'		,     A)
							if hasattr(A		,     '__qualname__'):
														return obj.__qualname__
							if hasattr(A		,     '__name__'):
														return obj.__name__
							return str(A)







def 		A_(     A						:		Tuple		,     A						:		List[str]):
							for key, value in source.items():
														if isinstance(A		,     A):
																					UpperCamelCase   			=     destination.setdefault(A		,     {})
																					merge_dicts(A		,     A)
														else:
																					UpperCamelCase   			=     value

							return destination







def 		A_(     A						:		int = None):
							if port is None:
														UpperCamelCase   			=     2_9500
							with socket.socket(socket.AF_INET		,     socket.SOCK_STREAM) as s:
														return s.connect_ex(('localhost', port)) == 0








def 	_UpperCamelCase					(    )    ->list[list[int]]:
   return [list(range(1_0_0_0 - i	,    -1_0_0_0 - i	,    -1 ) ) for i in range(1_0_0_0 )]


__a	 =      generate_large_matrix()
__a	 =      (
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->None:
   assert all(row == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for row in grid )
   assert all(list(lowerCAmelCase_ ) == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for col in zip(*lowerCAmelCase_ ) )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(lowerCAmelCase_ ) - 1

   # Edge cases such as no values or all numbers are negative.
   if not array or array[0] < 0:
      return 0

   while right + 1 > left:
      UpperCAmelCase      					=  (left + right) // 2
      UpperCAmelCase      					=  array[mid]

      # Num must be negative and the index must be greater than or equal to 0.
      if num < 0 and array[mid - 1] >= 0:
         return mid

      if num >= 0:
         UpperCAmelCase      					=  mid + 1
      else:
         UpperCAmelCase      					=  mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
   return len(lowerCAmelCase_ )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(grid[0] )

   for i in range(len(lowerCAmelCase_ ) ):
      UpperCAmelCase      					=  find_negative_index(grid[i][:bound] )
      total += bound
   return (len(lowerCAmelCase_ ) * len(grid[0] )) - total
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   return len([number for row in grid for number in row if number < 0] )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   for row in grid:
      for i, number in enumerate(lowerCAmelCase_ ):
         if number < 0:
            total += len(lowerCAmelCase_ ) - i
            break
   return total
def 	_UpperCamelCase					(    )    ->None:
   from timeit import timeit

   print("""Running benchmarks""" )
   UpperCAmelCase      					=  (
       """from __main__ import count_negatives_binary_search, """
       """count_negatives_brute_force, count_negatives_brute_force_with_break, grid"""
   )
   for func in (
       "count_negatives_binary_search",  # took 0.7727 seconds
       "count_negatives_brute_force_with_break",  # took 4.6505 seconds
       "count_negatives_brute_force",  # took 12.8160 seconds
   ):
      UpperCAmelCase      					=  timeit(F"""{func}(grid=grid)"""	,    setup=lowerCAmelCase_	,    number=5_0_0 )
      print(F"""{func}() took {time:0.4f} seconds""" )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()



