





"""simple docstring"""
from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
  import numpy as np
  import tensorflow as tf

  from transformers import TFXLMRobertaModel






@require_tf
@require_sentencepiece
@require_tokenizers
class 					_SCREAMING_SNAKE_CASE(   unittest.TestCase  ):




       @slow
       def     _UpperCamelCase     (						self							)			->      Union[str, Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE   :Optional[int]						=  TFXLMRobertaModel.from_pretrained('''jplu/tf-xlm-roberta-base'''							)

             __SCREAMING_SNAKE_CASE   :str						=  {
                 '''input_ids''': tf.convert_to_tensor([[0, 26_46, 1_02_69, 83, 9_99_42, 2]]		,dtype=tf.intaa							),  # "My dog is cute"
                 '''attention_mask''': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]		,dtype=tf.intaa							),
             }

             __SCREAMING_SNAKE_CASE   :Optional[Any]						=  model(SCREAMING_SNAKE_CASE__							)['''last_hidden_state''']
             __SCREAMING_SNAKE_CASE   :int						=  tf.TensorShape((1, 6, 7_68)							)
             self.assertEqual(output.shape		,SCREAMING_SNAKE_CASE__							)
             # compare the actual values for a slice.
             __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  tf.convert_to_tensor(
                 [
                     [
                         [0.0_6_8_1_7_6_2, 0.1_0_8_9_4_4_5_1, 0.0_6_7_7_2_5_0_4],
                         [-0.0_6_4_2_3_6_6_8, 0.0_2_3_6_6_6_1_5, 0.0_4_3_2_9_3_4_4],
                         [-0.0_6_0_5_7_2_9_5, 0.0_9_9_7_4_1_3_5, -0.0_0_0_7_0_5_8_4],
                     ]
                 ]		,dtype=tf.floataa		,)

             self.assertTrue(np.allclose(output[:, :3, :3].numpy()		,expected_slice.numpy()		,atol=1E-4							)							)






"""simple docstring"""
# Copyright 2021 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.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def      __lowerCamelCase   (							)			->      Any:
      __SCREAMING_SNAKE_CASE   :Tuple						=  ArgumentParser('''Accelerate CLI tool''' ,   usage='''accelerate <command> [<args>]''' ,   allow_abbrev=a_							)
      __SCREAMING_SNAKE_CASE   :str						=  parser.add_subparsers(help='''accelerate command helpers'''							)

      # Register commands
      get_config_parser(subparsers=a_							)
      env_command_parser(subparsers=a_							)
      launch_command_parser(subparsers=a_							)
      tpu_command_parser(subparsers=a_							)
      test_command_parser(subparsers=a_							)

      # Let's go
      __SCREAMING_SNAKE_CASE   :int						=  parser.parse_args()

      if not hasattr(a_ ,   '''func'''							):
            parser.print_help()
            exit(1							)

      # Run
      args.func(a_							)


if __name__ == "__main__":
  main()