



'''simple docstring'''



import unittest

from transformers import DonutProcessor


a__  :     Dict     							=     'naver-clova-ix/donut-base'
class     UpperCAmelCase__					(      unittest.TestCase):



 def 				__lowerCamelCase			(					self     )					->							Union[str, Any]:
  __UpperCamelCase			 =					DonutProcessor.from_pretrained(lowercase     )




 def 				__lowerCamelCase			(					self     )					->							Dict:
  __UpperCamelCase			 =					{
      """name""": """John Doe""",
      """age""": """99""",
      """city""": """Atlanta""",
      """state""": """GA""",
      """zip""": """30301""",
      """phone""": """123-4567""",
      """nicknames""": [{"""nickname""": """Johnny"""}, {"""nickname""": """JD"""}],
  }

  __UpperCamelCase			 =					(
      """<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"""
      """<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"""
      """<s_nicknames><s_nickname>Johnny</s_nickname>"""
      """<sep/><s_nickname>JD</s_nickname></s_nicknames>"""
  )
  __UpperCamelCase			 =					self.processor.tokenajson(lowercase     )

  self.assertDictEqual(lowercase						,		lowercase     )










'''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


a__  :     Tuple     							=     '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)





