
from __future__ import annotations

from typing import Any






class        SCREAMING_SNAKE_CASE__    (							SCREAMING_SNAKE_CASE_    ):

							"""simple docstring"""






							pass






class        SCREAMING_SNAKE_CASE__    :

							"""simple docstring"""






							def __init__(  self     ,	SCREAMING_SNAKE_CASE_			)->   None:





													'''simple docstring'''






													__UpperCamelCase       =			data
													__UpperCamelCase       =			None



							def __iter__(  self			)->   Dict:





													'''simple docstring'''






													__UpperCamelCase       =			self
													__UpperCamelCase       =			[]
													while node:
																			if node in visited:
																									raise ContainsLoopError
																			visited.append(SCREAMING_SNAKE_CASE_			)
																			yield node.data
																			__UpperCamelCase       =			node.next_node



							@property
							def     A__		(  self			)->   bool:





													'''simple docstring'''






													try:
																			list(self			)
																			return False
													except ContainsLoopError:
																			return True


if __name__ == "__main__":
			lowercase__							:							str									=			Node(1)
			lowercase__							:							List[str]									=			Node(2)
			lowercase__							:							List[str]									=			Node(3)
			lowercase__							:							Optional[Any]									=			Node(4)
			print(root_node.has_loop)  # False
			lowercase__							:							List[Any]									=			root_node.next_node
			print(root_node.has_loop)  # True

			lowercase__							:							str									=			Node(5)
			lowercase__							:							Tuple									=			Node(6)
			lowercase__							:							Optional[int]									=			Node(5)
			lowercase__							:							Optional[int]									=			Node(6)
			print(root_node.has_loop)  # False

			lowercase__							:							Tuple									=			Node(1)
			print(root_node.has_loop)  # False






# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import platform
import sys


lowercase__							:							List[str]									=			"3"

print("Python version:", sys.version)

print("OS platform:", platform.platform())
print("OS architecture:", platform.machine())

try:
				import torch

				print("Torch version:", torch.__version__)
				print("Cuda available:", torch.cuda.is_available())
				print("Cuda version:", torch.version.cuda)
				print("CuDNN version:", torch.backends.cudnn.version())
				print("Number of GPUs available:", torch.cuda.device_count())
except ImportError:
				print("Torch version:", None)

try:
				import transformers

				print("transformers version:", transformers.__version__)
except ImportError:
				print("transformers version:", None)




