import builtins
import sys

from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP


_lowerCamelCase					:   Optional[int]							=		False
try:
							_lowerCamelCase					:   List[Any]							=		_is_package_available('''google.colab''')
except ModuleNotFoundError:
							pass


@input.register
class 						lowercase    :




							def __init__(						self   :					Optional[int]	,							_UpperCamelCase   :					str = None	,							_UpperCamelCase   :					list = []      )					->				Union[str, Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       0
												SCREAMING_SNAKE_CASE    			=       choices
												SCREAMING_SNAKE_CASE    			=       prompt
												if sys.platform == "win32":
																	SCREAMING_SNAKE_CASE    			=       "*"
												else:
																	SCREAMING_SNAKE_CASE    			=       "➔ "




							def 	__snake_case(						self   :					Optional[int]	,							_UpperCamelCase   :					str	,							_UpperCamelCase   :					str = ""      )					->				Union[str, Any]:



												'''simple docstring'''

												if sys.platform != "win32":
																	writeColor(self.choices[index]	,							32	,							_UpperCamelCase      )
												else:
																	forceWrite(self.choices[index]	,							_UpperCamelCase      )




							def 	__snake_case(						self   :					str	,							_UpperCamelCase   :					int      )					->				List[Any]:



												'''simple docstring'''

												if index == self.position:
																	forceWrite(F" {self.arrow_char} "      )
																	self.write_choice(_UpperCamelCase      )
												else:
																	forceWrite(F"    {self.choices[index]}"      )
												reset_cursor()




							def 	__snake_case(						self   :					Union[str, Any]	,							_UpperCamelCase   :					Direction	,							_UpperCamelCase   :					int = 1      )					->				Dict:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.position
												if direction == Direction.DOWN:
																	if self.position + 1 >= len(self.choices      ):
																						return
																	self.position += num_spaces
												else:
																	if self.position - 1 < 0:
																						return
																	self.position -= num_spaces
												clear_line()
												self.print_choice(_UpperCamelCase      )
												move_cursor(_UpperCamelCase	,							direction.name      )
												self.print_choice(self.position      )




							@input.mark(KEYMAP["up"]      )
							def 	__snake_case(						self   :					Union[str, Any]      )					->				Any:



												'''simple docstring'''

												self.move_direction(Direction.UP      )




							@input.mark(KEYMAP["down"]      )
							def 	__snake_case(						self   :					List[Any]      )					->				Any:



												'''simple docstring'''

												self.move_direction(Direction.DOWN      )




							@input.mark(KEYMAP["newline"]      )
							def 	__snake_case(						self   :					int      )					->				Dict:



												'''simple docstring'''

												move_cursor(len(self.choices      ) - self.position	,							"DOWN"      )
												return self.position




							@input.mark(KEYMAP["interrupt"]      )
							def 	__snake_case(						self   :					Any      )					->				Optional[int]:



												'''simple docstring'''

												move_cursor(len(self.choices      ) - self.position	,							"DOWN"      )
												raise KeyboardInterrupt




							@input.mark_multiple(*[KEYMAP[str(_UpperCamelCase      )] for number in range(10      )]      )
							def 	__snake_case(						self   :					Optional[int]      )					->				Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       int(chr(self.current_selection      )      )
												SCREAMING_SNAKE_CASE    			=       index - self.position
												if index == self.position:
																	return
												if index < len(self.choices      ):
																	if self.position > index:
																						self.move_direction(Direction.UP	,							-movement      )
																	elif self.position < index:
																						self.move_direction(Direction.DOWN	,							_UpperCamelCase      )
																	else:
																						return
												else:
																	return





							def 	__snake_case(						self   :					List[Any]	,							_UpperCamelCase   :					int = 0      )					->				List[str]:



												'''simple docstring'''

												if self.prompt:
																	linebreak()
																	forceWrite(self.prompt	,							"\n"      )
																	if in_colab:
																						forceWrite("Please input a choice index (starting from 0), and press enter"	,							"\n"      )
																	else:
																						forceWrite("Please select a choice using the arrow or number keys, and selecting with enter"	,							"\n"      )
												SCREAMING_SNAKE_CASE    			=       default_choice
												for i in range(len(self.choices      )      ):
																	self.print_choice(_UpperCamelCase      )
																	forceWrite("\n"      )
												move_cursor(len(self.choices      ) - self.position	,							"UP"      )
												with cursor.hide():
																	while True:
																						if in_colab:
																											try:
																																SCREAMING_SNAKE_CASE    			=       int(builtins.input()      )
																											except ValueError:
																																SCREAMING_SNAKE_CASE    			=       default_choice
																						else:
																											SCREAMING_SNAKE_CASE    			=       self.handle_input()
																						if choice is not None:
																											reset_cursor()
																											for _ in range(len(self.choices      ) + 1      ):
																																move_cursor(1	,							"UP"      )
																																clear_line()
																											self.write_choice(_UpperCamelCase	,							"\n"      )
																											return choice





import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment


class 						lowercase    (     unittest.TestCase     ):




							def 	__snake_case(						self   :					Union[str, Any]      )					->				List[str]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       inspect.getfile(accelerate.test_utils      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_script.py"]      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(
												    mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_distributed_data_loop.py"]      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_ops.py"]      )




							@require_multi_gpu
							def 	__snake_case(						self   :					Optional[int]      )					->				Any:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices."      )
												SCREAMING_SNAKE_CASE    			=       ["torchrun", F"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
												with patch_environment(omp_num_threads=1      ):
																	execute_subprocess_async(_UpperCamelCase	,							env=os.environ.copy()      )




							@require_multi_gpu
							def 	__snake_case(						self   :					List[Any]      )					->				int:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices."      )
												SCREAMING_SNAKE_CASE    			=       ["torchrun", F"--nproc_per_node={torch.cuda.device_count()}", self.operation_file_path]
												print(F"Command: {cmd}"      )
												with patch_environment(omp_num_threads=1      ):
																	execute_subprocess_async(_UpperCamelCase	,							env=os.environ.copy()      )




							@require_multi_gpu
							def 	__snake_case(						self   :					int      )					->				Optional[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       ["torchrun", F"--nproc_per_node={torch.cuda.device_count()}", inspect.getfile(self.__class__      )]
												with patch_environment(omp_num_threads=1      ):
																	execute_subprocess_async(_UpperCamelCase	,							env=os.environ.copy()      )





							@require_multi_gpu
							def 	__snake_case(						self   :					int      )					->				int:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices, using 2 devices only"      )
												SCREAMING_SNAKE_CASE    			=       ["torchrun", F"--nproc_per_node={torch.cuda.device_count()}", self.data_loop_file_path]
												with patch_environment(omp_num_threads=1	,							cuda_visible_devices="0,1"      ):
																	execute_subprocess_async(_UpperCamelCase	,							env=os.environ.copy()      )


if __name__ == "__main__":
							_lowerCamelCase					:   str							=		Accelerator()
							_lowerCamelCase					:   List[str]							=		(accelerator.state.process_index + 2, 10)
							_lowerCamelCase					:   str							=		torch.randint(0, 10, shape).to(accelerator.device)

							_lowerCamelCase					:   Optional[Any]							=		''''''

							_lowerCamelCase					:   str							=		accelerator.pad_across_processes(tensor)
							if tensora.shape[0] != accelerator.state.num_processes + 1:
														error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
							if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
														error_msg += "Tensors have different values."
							if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
														error_msg += "Padding was not done with the right value (0)."

							_lowerCamelCase					:   Any							=		accelerator.pad_across_processes(tensor, pad_first=True)
							if tensora.shape[0] != accelerator.state.num_processes + 1:
														error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
							_lowerCamelCase					:   int							=		accelerator.state.num_processes - accelerator.state.process_index - 1
							if not torch.equal(tensora[index:], tensor):
														error_msg += "Tensors have different values."
							if not torch.all(tensora[:index] == 0):
														error_msg += "Padding was not done with the right value (0)."

							# Raise error at the end to make sure we don't stop at the first failure.
							if len(error_msg) > 0:
														raise ValueError(error_msg)




