





'''simple docstring'''






import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin







class 		UpperCAmelCase   (				lowercase_   ,     unittest.TestCase):


  """simple docstring"""







  lowerCAmelCase_					=				XLMTokenizer
  lowerCAmelCase_					=				False


  def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						Optional[Any]:
    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    _UpperCamelCase       			=[
        '''l''',
        '''o''',
        '''w''',
        '''e''',
        '''r''',
        '''s''',
        '''t''',
        '''i''',
        '''d''',
        '''n''',
        '''w</w>''',
        '''r</w>''',
        '''t</w>''',
        '''lo''',
        '''low''',
        '''er</w>''',
        '''low</w>''',
        '''lowest</w>''',
        '''newer</w>''',
        '''wider</w>''',
        '''<unk>''',
    ]
    _UpperCamelCase       			=dict(zip(UpperCamelCase__							,	range(len(UpperCamelCase__  )  )  )  )
    _UpperCamelCase       			=['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

    _UpperCamelCase       			=os.path.join(self.tmpdirname							,	VOCAB_FILES_NAMES['''vocab_file''']  )
    _UpperCamelCase       			=os.path.join(self.tmpdirname							,	VOCAB_FILES_NAMES['''merges_file''']  )
    with open(self.vocab_file							,	'''w'''  ) as fp:
      fp.write(json.dumps(UpperCamelCase__  )  )
    with open(self.merges_file							,	'''w'''  ) as fp:
      fp.write('''\n'''.join(UpperCamelCase__  )  )


  def   UpperCamelCase__      (				self    :					str							,	UpperCamelCase__    :					str  )     ->						Optional[Any]:
    _UpperCamelCase       			='''lower newer'''
    _UpperCamelCase       			='''lower newer'''
    return input_text, output_text


  def   UpperCamelCase__      (				self    :					List[str]  )     ->						int:
    _UpperCamelCase       			=XLMTokenizer(self.vocab_file							,	self.merges_file  )

    _UpperCamelCase       			='''lower'''
    _UpperCamelCase       			=['''low''', '''er</w>''']
    _UpperCamelCase       			=tokenizer.tokenize(UpperCamelCase__  )
    self.assertListEqual(UpperCamelCase__							,	UpperCamelCase__  )

    _UpperCamelCase       			=tokens + ['''<unk>''']
    _UpperCamelCase       			=[14, 15, 20]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__  )							,	UpperCamelCase__  )




  @slow
  def   UpperCamelCase__      (				self    :					Union[str, Any]  )     ->						int:
    _UpperCamelCase       			=XLMTokenizer.from_pretrained('''xlm-mlm-en-2048'''  )

    _UpperCamelCase       			=tokenizer.encode('''sequence builders'''							,	add_special_tokens=UpperCamelCase__  )
    _UpperCamelCase       			=tokenizer.encode('''multi-sequence build'''							,	add_special_tokens=UpperCamelCase__  )

    _UpperCamelCase       			=tokenizer.build_inputs_with_special_tokens(UpperCamelCase__  )
    _UpperCamelCase       			=tokenizer.build_inputs_with_special_tokens(UpperCamelCase__							,	UpperCamelCase__  )

    assert encoded_sentence == [0] + text + [1]
    assert encoded_pair == [0] + text + [1] + text_a + [1]













'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCamelCase						: Union[str, Any]		=   logging.get_logger(__name__)

__lowerCamelCase						: int		=   {
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				"""mobilenet_v2"""


  def __init__(				self    :					Tuple							,	UpperCamelCase__    :					Union[str, Any]=3							,	UpperCamelCase__    :					Dict=224							,	UpperCamelCase__    :					str=1.0							,	UpperCamelCase__    :					List[Any]=8							,	UpperCamelCase__    :					Union[str, Any]=8							,	UpperCamelCase__    :					str=6							,	UpperCamelCase__    :					str=32							,	UpperCamelCase__    :					str=True							,	UpperCamelCase__    :					int=True							,	UpperCamelCase__    :					str="relu6"							,	UpperCamelCase__    :					Tuple=True							,	UpperCamelCase__    :					List[str]=0.8							,	UpperCamelCase__    :					List[str]=0.02							,	UpperCamelCase__    :					str=0.001							,	UpperCamelCase__    :					Dict=255							,	**UpperCamelCase__    :					Tuple							,	)     ->						List[Any]:
    super().__init__(**UpperCamelCase__  )

    if depth_multiplier <= 0:
      raise ValueError('''depth_multiplier must be greater than zero.'''  )

    _UpperCamelCase       			=num_channels
    _UpperCamelCase       			=image_size
    _UpperCamelCase       			=depth_multiplier
    _UpperCamelCase       			=depth_divisible_by
    _UpperCamelCase       			=min_depth
    _UpperCamelCase       			=expand_ratio
    _UpperCamelCase       			=output_stride
    _UpperCamelCase       			=first_layer_is_expansion
    _UpperCamelCase       			=finegrained_output
    _UpperCamelCase       			=hidden_act
    _UpperCamelCase       			=tf_padding
    _UpperCamelCase       			=classifier_dropout_prob
    _UpperCamelCase       			=initializer_range
    _UpperCamelCase       			=layer_norm_eps
    _UpperCamelCase       			=semantic_loss_ignore_index







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				version.parse("""1.11""")


  @property
  def   UpperCamelCase__      (				self    :					str  )     ->						Mapping[str, Mapping[int, str]]:
    return OrderedDict([('''pixel_values''', {0: '''batch'''})]  )


  @property
  def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						Mapping[str, Mapping[int, str]]:
    if self.task == "image-classification":
      return OrderedDict([('''logits''', {0: '''batch'''})]  )
    else:
      return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]  )




  @property
  def   UpperCamelCase__      (				self    :					List[Any]  )     ->						float:
    return 1E-4






