



import torch

from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				return (torch.arange(state.num_processes						) + 1.0 + (state.num_processes * state.process_index)).to(state.device						)


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   List[Any]													=					create_tensor(__snake_case						)
				lowercase__					:   Tuple													=					gather(__snake_case						)
				assert gathered_tensor.tolist() == list(range(1					,			state.num_processes**2 + 1						)						)


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Tuple													=					[state.process_index]
				lowercase__					:   Union[str, Any]													=					gather_object(__snake_case						)
				assert len(__snake_case						) == state.num_processes, F"""{gathered_obj}, {len(__snake_case						)} != {state.num_processes}"""
				assert gathered_obj == list(range(state.num_processes						)						), F"""{gathered_obj} != {list(range(state.num_processes						)						)}"""


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Tuple													=					create_tensor(__snake_case						)
				lowercase__					:   Tuple													=					broadcast(__snake_case						)
				assert broadcasted_tensor.shape == torch.Size([state.num_processes]						)
				assert broadcasted_tensor.tolist() == list(range(1					,			state.num_processes + 1						)						)


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				if state.is_main_process:
								lowercase__					:   List[Any]													=					torch.arange(state.num_processes + 1						).to(state.device						)
				else:
								lowercase__					:   Any													=					torch.arange(state.num_processes						).to(state.device						)
				lowercase__					:   List[Any]													=					pad_across_processes(__snake_case						)
				assert padded_tensor.shape == torch.Size([state.num_processes + 1]						)
				if not state.is_main_process:
								assert padded_tensor.tolist() == list(range(0					,			state.num_processes						)						) + [0]


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				if state.num_processes != 2:
								return
				lowercase__					:   str													=					create_tensor(__snake_case						)
				lowercase__					:   str													=					reduce(__snake_case					,			"sum"						)
				lowercase__					:   List[str]													=					torch.tensor([4.0, 6]						).to(state.device						)
				assert torch.allclose(__snake_case					,			__snake_case						), F"""{reduced_tensor} != {truth_tensor}"""


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				if state.num_processes != 2:
								return
				lowercase__					:   List[str]													=					create_tensor(__snake_case						)
				lowercase__					:   Any													=					reduce(__snake_case					,			"mean"						)
				lowercase__					:   List[Any]													=					torch.tensor([2.0, 3]						).to(state.device						)
				assert torch.allclose(__snake_case					,			__snake_case						), F"""{reduced_tensor} != {truth_tensor}"""


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				main()


def  __lowerCamelCase (       ):

				"""simple docstring"""


				lowercase__					:   List[Any]													=					PartialState()
				state.print(F"""State: {state}"""						)
				state.print("testing gather"						)
				test_gather(__snake_case						)
				state.print("testing gather_object"						)
				test_gather_object(__snake_case						)
				state.print("testing broadcast"						)
				test_broadcast(__snake_case						)
				state.print("testing pad_across_processes"						)
				test_pad_across_processes(__snake_case						)
				state.print("testing reduce_sum"						)
				test_reduce_sum(__snake_case						)
				state.print("testing reduce_mean"						)
				test_reduce_mean(__snake_case						)


if __name__ == "__main__":
				main()









def  __lowerCamelCase (       lowerCamelCase__ = 1_000						):

				"""simple docstring"""


				lowercase__							,							lowercase__					:   int													=					1, 1
				lowercase__					:   List[Any]													=					[]
				for i in range(1					,			n + 1						):
								lowercase__					:   Dict													=					prev_numerator + 2 * prev_denominator
								lowercase__					:   Tuple													=					prev_numerator + prev_denominator
								if len(str(lowerCamelCase__						)						) > len(str(lowerCamelCase__						)						):
												result.append(lowerCamelCase__						)
								lowercase__					:   int													=					numerator
								lowercase__					:   int													=					denominator

				return len(lowerCamelCase__						)


if __name__ == "__main__":
				print(f'''{solution() = }''')




