






'''simple docstring'''

# coding=utf-8
# Copyright 2020 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 sys

import transformers


UpperCamelCase      					='''3'''

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

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())
      print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
      print("Torch version:", None)

try:
      import deepspeed

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

try:
      import tensorflow as tf

      print("TensorFlow version:", tf.__version__)
      print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
      print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
      print("TensorFlow version:", None)







from __future__ import annotations

from random import choice






def _lowerCamelCase  (		snake_case  ):
							return choice(snake_case  )






def _lowerCamelCase  (		snake_case     , snake_case  ):
							_lowerCAmelCase							=							random_pivot(snake_case  )

							# partition based on pivot
							# linear time
							_lowerCAmelCase							=							[e for e in lst if e < pivot]
							_lowerCAmelCase							=							[e for e in lst if e > pivot]

							# if we get lucky, pivot might be the element we want.
							# we can easily see this:
							# small (elements smaller than k)
							# + pivot (kth element)
							# + big (elements larger than k)
							if len(snake_case  ) == k - 1:
														return pivot
							# pivot is in elements bigger than k
							elif len(snake_case  ) < k - 1:
														return kth_number(snake_case     , k - len(snake_case  ) - 1  )
							# pivot is in elements smaller than k
							else:
														return kth_number(snake_case     , snake_case  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()






