"""simple docstring"""



import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)



def 					_lowerCamelCase(					a ,  a=False							):
       try:
              __a     				=  os.environ[key]
       except KeyError:
              # KEY isn't set, default to `default`.
              __a     				=  default
       else:
              # KEY is set, convert it to True or False.
              try:
                     __a     				=  strtobool(lowerCamelCase__							)
              except ValueError:
                     # More values are supported, but let's keep the message simple.
                     raise ValueError(F"If set, {key} must be yes or no."							)
       return _value


SCREAMING_SNAKE_CASE__:Tuple			=	parse_flag_from_env("""RUN_SLOW""", default=False)



def 					_lowerCamelCase(					a							):
       return unittest.skip("Test was skipped"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(_run_slow_tests ,  "test is slow"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(not torch.cuda.is_available() ,  "test requires only a CPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(torch.cuda.is_available() ,  "test requires a GPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_xpu_available() ,  "test requires a XPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_mps_available() ,  "test requires a `mps` backend support in `torch`"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(
           is_transformers_available() and is_datasets_available() ,  "test requires the Hugging Face suite"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_bnb_available() ,  "test requires the bitsandbytes library"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_tpu_available() ,  "test requires TPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(torch.cuda.device_count() == 1 ,  "test requires a GPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(torch.xpu.device_count() == 1 ,  "test requires a XPU"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(torch.cuda.device_count() > 1 ,  "test requires multiple GPUs"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(torch.xpu.device_count() > 1 ,  "test requires multiple XPUs"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_safetensors_available() ,  "test requires safetensors"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_deepspeed_available() ,  "test requires DeepSpeed"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_torch_version(">=" ,  "1.12.0"							) ,  "test requires torch version >= 1.12.0"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a=None ,  a=None							):
       if test_case is None:
              return partial(lowerCamelCase__ ,  version=lowerCamelCase__							)
       return unittest.skipUnless(is_torch_version(">=" ,  lowerCamelCase__							) ,  F"test requires torch version >= {version}"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_tensorboard_available() ,  "test requires Tensorboard"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_wandb_available() ,  "test requires wandb"							)(lowerCamelCase__							)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(is_comet_ml_available() ,  "test requires comet_ml"							)(lowerCamelCase__							)


SCREAMING_SNAKE_CASE__:Any			=	(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def 					_lowerCamelCase(					a							):
       return unittest.skipUnless(
           _atleast_one_tracker_available ,  "test requires at least one tracker to be available and for `comet_ml` to not be installed" ,  )(lowerCamelCase__							)






class 				snake_case__     (   unittest.TestCase   ):
 _snake_case   :			Optional[Any]           =		True


 @classmethod
 def 		a__ (				cls		):
        __a     				=  tempfile.mkdtemp()


 @classmethod
 def 		a__ (				cls		):
        if os.path.exists(cls.tmpdir		):
               shutil.rmtree(cls.tmpdir		)






 def 		a__ (				self		):
        if self.clear_on_setup:
               for path in Path(self.tmpdir		).glob("**/*"		):
                      if path.is_file():
                             path.unlink()
                      elif path.is_dir():
                             shutil.rmtree(lowerCamelCase		)






class 				snake_case__     (   unittest.TestCase   ):


 def 		a__ (				self		):
        super().tearDown()
        # Reset the state of the AcceleratorState singleton.
        AcceleratorState._reset_state()
        PartialState._reset_state()






class 				snake_case__     (   unittest.TestCase   ):


 def 		a__ (				self  ,						lowerCamelCase		):
        __a     				=  mocks if isinstance(lowerCamelCase  ,						(tuple, list)		) else [mocks]
        for m in self.mocks:
               m.start()
               self.addCleanup(m.stop		)



def 					_lowerCamelCase(					a							):
       __a     				=  AcceleratorState()
       __a     				=  tensor[None].clone().to(state.device							)
       __a     				=  gather(lowerCamelCase__							).cpu()
       __a     				=  tensor[0].cpu()
       for i in range(tensors.shape[0]							):
              if not torch.equal(tensors[i] ,  lowerCamelCase__							):
                     return False
       return True






class 				snake_case__     :


 def __init__(				self  ,						lowerCamelCase  ,						lowerCamelCase  ,						lowerCamelCase		):
        __a     				=  returncode
        __a     				=  stdout
        __a     				=  stderr



async def 					_lowerCamelCase(					a ,  a							):
       while True:
              __a     				=  await stream.readline()
              if line:
                     callback(lowerCamelCase__							)
              else:
                     break



async def 					_lowerCamelCase(					a ,  a=None ,  a=None ,  a=None ,  a=False ,  a=False							):
       if echo:
              print("\nRunning: " ,  " ".join(lowerCamelCase__							)							)

       __a     				=  await asyncio.create_subprocess_exec(
           cmd[0] ,  *cmd[1:] ,  stdin=lowerCamelCase__ ,  stdout=asyncio.subprocess.PIPE ,  stderr=asyncio.subprocess.PIPE ,  env=lowerCamelCase__ ,  )

       # note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
       # https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
       #
       # If it starts hanging, will need to switch to the following code. The problem is that no data
       # will be seen until it's done and if it hangs for example there will be no debug info.
       # out, err = await p.communicate()
       # return _RunOutput(p.returncode, out, err)

       __a     				=  []
       __a     				=  []

       def tee(a ,  a ,  a ,  a=""							):
              __a     				=  line.decode("utf-8"							).rstrip()
              sink.append(lowerCamelCase__							)
              if not quiet:
                     print(lowerCamelCase__ ,  lowerCamelCase__ ,  file=lowerCamelCase__							)

    # XXX: the timeout doesn't seem to make any difference here
       await asyncio.wait(
           [
               asyncio.create_task(_read_stream(p.stdout ,  lambda a							: tee(lowerCamelCase__ ,  lowerCamelCase__ ,  sys.stdout ,  label="stdout:"							)							)							),
               asyncio.create_task(_read_stream(p.stderr ,  lambda a							: tee(lowerCamelCase__ ,  lowerCamelCase__ ,  sys.stderr ,  label="stderr:"							)							)							),
           ] ,  timeout=lowerCamelCase__ ,  )
       return _RunOutput(await p.wait() ,  lowerCamelCase__ ,  lowerCamelCase__							)



def 					_lowerCamelCase(					a ,  a=None ,  a=None ,  a=1_8_0 ,  a=False ,  a=True							):
       __a     				=  asyncio.get_event_loop()
       __a     				=  loop.run_until_complete(
           _stream_subprocess(lowerCamelCase__ ,  env=lowerCamelCase__ ,  stdin=lowerCamelCase__ ,  timeout=lowerCamelCase__ ,  quiet=lowerCamelCase__ ,  echo=lowerCamelCase__							)							)

       __a     				=  " ".join(lowerCamelCase__							)
       if result.returncode > 0:
              __a     				=  "\n".join(result.stderr							)
              raise RuntimeError(
                  F"\'{cmd_str}\' failed with returncode {result.returncode}\n\n"
                  F"The combined stderr from workers follows:\n{stderr}"							)

       return result






class 				snake_case__     (   snake_case_   ):
 pass



def 					_lowerCamelCase(					a ,  a=False							):
       try:
              __a     				=  subprocess.check_output(lowerCamelCase__ ,  stderr=subprocess.STDOUT							)
              if return_stdout:
                     if hasattr(lowerCamelCase__ ,  "decode"							):
                            __a     				=  output.decode("utf-8"							)
                     return output
       except subprocess.CalledProcessError as e:
              raise SubprocessCallException(
                  F"Command `{' '.join(lowerCamelCase__							)}` failed with the following error:\n\n{e.output.decode()}"							) from e

"""simple docstring"""



from __future__ import annotations



def 					_lowerCamelCase(					a ,  a ,  a ,  a ,  a ,  ):
       __a     				=  len(a							)

       # If row is equal to the size of the board it means there are a queen in each row in
       # the current board (possible_board)
       if row == n:
              # We convert the variable possible_board that looks like this: [1, 3, 0, 2] to
              # this: ['. Q . . ', '. . . Q ', 'Q . . . ', '. . Q . ']
              boards.append([". " * i + "Q " + ". " * (n - 1 - i) for i in possible_board]							)
              return

       # We iterate each column in the row to find all possible results in each row
       for col in range(a							):
              # We apply that we learned previously. First we check that in the current board
              # (possible_board) there are not other same value because if there is it means
              # that there are a collision in vertical. Then we apply the two formulas we
              # learned before:
              #
              # 45º: y - x = b or 45: row - col = b
              # 135º: y + x = b or row + col = b.
              #
              # And we verify if the results of this two formulas not exist in their variables
              # respectively.  (diagonal_right_collisions, diagonal_left_collisions)
              #
              # If any or these are True it means there is a collision so we continue to the
              # next value in the for loop.
              if (
                  col in possible_board
                  or row - col in diagonal_right_collisions
                  or row + col in diagonal_left_collisions
              ):
                     continue

              # If it is False we call dfs function again and we update the inputs
              depth_first_search(
                  [*possible_board, col] ,  [*diagonal_right_collisions, row - col] ,  [*diagonal_left_collisions, row + col] ,  a ,  a ,  )



def 					_lowerCamelCase(					a							):
       __a     				=  []
       depth_first_search([] ,  [] ,  [] ,  a ,  a							)

       # Print all the boards
       for board in boards:
              for column in board:
                     print(a							)
              print(""							)

       print(len(a							) ,  "solutions were found."							)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   n_queens_solution(4)
