


'''simple docstring'''



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import torch

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


def 				lowerCamelCase__				(	A       :      List[str]					):




						'''simple docstring'''






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


def 				lowerCamelCase__				(	A       :      str					):




						'''simple docstring'''






						UpperCAmelCase					    =     create_tensor(A					)
						UpperCAmelCase					    =     gather(A					)
						assert gathered_tensor.tolist() == list(range(1				,       state.num_processes**2 + 1					)					)


def 				lowerCamelCase__				(	A       :      int					):




						'''simple docstring'''






						UpperCAmelCase					    =     [state.process_index]
						UpperCAmelCase					    =     gather_object(A					)
						assert len(A					) == state.num_processes, f"""{gathered_obj}, {len(A					)} != {state.num_processes}"""
						assert gathered_obj == list(range(state.num_processes					)					), f"""{gathered_obj} != {list(range(state.num_processes					)					)}"""


def 				lowerCamelCase__				(	A       :      List[str]					):




						'''simple docstring'''






						UpperCAmelCase					    =     create_tensor(A					)
						UpperCAmelCase					    =     broadcast(A					)
						assert broadcasted_tensor.shape == torch.Size([state.num_processes]					)
						assert broadcasted_tensor.tolist() == list(range(1				,       state.num_processes + 1					)					)


def 				lowerCamelCase__				(	A       :      Any					):




						'''simple docstring'''






						if state.is_main_process:
												UpperCAmelCase					    =     torch.arange(state.num_processes + 1					).to(state.device					)
						else:
												UpperCAmelCase					    =     torch.arange(state.num_processes					).to(state.device					)
						UpperCAmelCase					    =     pad_across_processes(A					)
						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__				(	A       :      Dict					):




						'''simple docstring'''






						if state.num_processes != 2:
												return
						UpperCAmelCase					    =     create_tensor(A					)
						UpperCAmelCase					    =     reduce(A				,       '''sum'''					)
						UpperCAmelCase					    =     torch.tensor([4.0, 6]					).to(state.device					)
						assert torch.allclose(A				,       A					), f"""{reduced_tensor} != {truth_tensor}"""


def 				lowerCamelCase__				(	A       :      Optional[int]					):




						'''simple docstring'''






						if state.num_processes != 2:
												return
						UpperCAmelCase					    =     create_tensor(A					)
						UpperCAmelCase					    =     reduce(A				,       '''mean'''					)
						UpperCAmelCase					    =     torch.tensor([2.0, 3]					).to(state.device					)
						assert torch.allclose(A				,       A					), f"""{reduced_tensor} != {truth_tensor}"""


def 				lowerCamelCase__				(	A       :      Optional[int]					):




						'''simple docstring'''






						main()


def 				lowerCamelCase__				(	):




						'''simple docstring'''






						UpperCAmelCase					    =     PartialState()
						state.print(f"""State: {state}"""					)
						state.print('''testing gather'''					)
						test_gather(A					)
						state.print('''testing gather_object'''					)
						test_gather_object(A					)
						state.print('''testing broadcast'''					)
						test_broadcast(A					)
						state.print('''testing pad_across_processes'''					)
						test_pad_across_processes(A					)
						state.print('''testing reduce_sum'''					)
						test_reduce_sum(A					)
						state.print('''testing reduce_mean'''					)
						test_reduce_mean(A					)


if __name__ == "__main__":
	main()









'''simple docstring'''



def 				lowerCamelCase__				(	A       :      int				,       A       :      int					):




						'''simple docstring'''






						return int(input_a == input_a == 0					)


def 				lowerCamelCase__				(	):




						'''simple docstring'''






						print('''Truth Table of NOR Gate:'''					)
						print('''|   Input 1   |  Input 2  | Output |'''					)
						print(f"""|      0      |    0      |  {nor_gate(0				,       0					)}     |"""					)
						print(f"""|      0      |    1      |  {nor_gate(0				,       1					)}     |"""					)
						print(f"""|      1      |    0      |  {nor_gate(1				,       0					)}     |"""					)
						print(f"""|      1      |    1      |  {nor_gate(1				,       1					)}     |"""					)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()





