

"""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


SCREAMING_SNAKE_CASE_					:	Optional[int]							  =						'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)









"""simple docstring"""



def  _snake_case     (    UpperCAmelCase_  :					List[str]			):
     A__										=  [0] * len(UpperCAmelCase_			)
     A__										=  []
     A__										=  [1] * len(UpperCAmelCase_			)

     for values in graph.values():
          for i in values:
               indegree[i] += 1

     for i in range(len(UpperCAmelCase_			)			):
          if indegree[i] == 0:
               queue.append(UpperCAmelCase_			)

     while queue:
          A__										=  queue.pop(0			)
          for x in graph[vertex]:
               indegree[x] -= 1

               if long_dist[vertex] + 1 > long_dist[x]:
                    A__										=  long_dist[vertex] + 1

               if indegree[x] == 0:
                    queue.append(UpperCAmelCase_			)

     print(max(UpperCAmelCase_			)			)


# Adjacency list of Graph
SCREAMING_SNAKE_CASE_					:	Any							  =						{0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}

longest_distance(graph)






