





'''simple docstring'''






import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		UpperCAmelCase   (				lowercase_   ,     unittest.TestCase):


		"""simple docstring"""







		lowerCAmelCase_					=				RobertaTokenizer
		lowerCAmelCase_					=				RobertaTokenizerFast
		lowerCAmelCase_					=				True
		lowerCAmelCase_					=				{"""cls_token""": """<s>"""}


		def   UpperCamelCase__      (				self    :					Tuple  )     ->						List[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",
				    "\u0120",
				    "\u0120l",
				    "\u0120n",
				    "\u0120lo",
				    "\u0120low",
				    "er",
				    "\u0120lowest",
				    "\u0120newer",
				    "\u0120wider",
				    "<unk>",
				]
				_UpperCamelCase       			=dict(zip(__A							,	range(len(__A  )  )  )  )
				_UpperCamelCase       			=["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
				_UpperCamelCase       			={"unk_token": "<unk>"}

				_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'''							,	encoding='''utf-8'''  ) as fp:
						fp.write(json.dumps(__A  ) + '''\n'''  )
				with open(self.merges_file							,	'''w'''							,	encoding='''utf-8'''  ) as fp:
						fp.write('''\n'''.join(__A  )  )


		def   UpperCamelCase__      (				self    :					Dict							,	**UpperCamelCase__    :					Union[str, Any]  )     ->						Any:
				kwargs.update(self.special_tokens_map  )
				return self.tokenizer_class.from_pretrained(self.tmpdirname							,	**__A  )


		def   UpperCamelCase__      (				self    :					str							,	**UpperCamelCase__    :					Optional[int]  )     ->						Union[str, Any]:
				kwargs.update(self.special_tokens_map  )
				return RobertaTokenizerFast.from_pretrained(self.tmpdirname							,	**__A  )


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


		def   UpperCamelCase__      (				self    :					Optional[int]  )     ->						Tuple:
				_UpperCamelCase       			=self.tokenizer_class(self.vocab_file							,	self.merges_file							,	**self.special_tokens_map  )
				_UpperCamelCase       			="lower newer"
				_UpperCamelCase       			=["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
				_UpperCamelCase       			=tokenizer.tokenize(__A  )  # , add_prefix_space=True)
				self.assertListEqual(__A							,	__A  )

				_UpperCamelCase       			=tokens + [tokenizer.unk_token]
				_UpperCamelCase       			=[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(__A  )							,	__A  )


		def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						Dict:
				_UpperCamelCase       			=self.get_tokenizer()

				self.assertListEqual(tokenizer.encode('''Hello world!'''							,	add_special_tokens=__A  )							,	[0, 3_1414, 232, 328, 2]  )
				self.assertListEqual(
				    tokenizer.encode('''Hello world! cécé herlolip 418'''							,	add_special_tokens=__A  )							,	[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]							,	)


		@slow
		def   UpperCamelCase__      (				self    :					Any  )     ->						Optional[Any]:
				_UpperCamelCase       			=self.tokenizer_class.from_pretrained('''roberta-base'''  )

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

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

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

				assert encoded_sentence == encoded_text_from_decode
				assert encoded_pair == encoded_pair_from_decode


		def   UpperCamelCase__      (				self    :					List[Any]  )     ->						int:
				_UpperCamelCase       			=self.get_tokenizer()

				_UpperCamelCase       			="Encode this sequence."
				_UpperCamelCase       			=tokenizer.byte_encoder[" ".encode('''utf-8'''  )[0]]

				# Testing encoder arguments
				_UpperCamelCase       			=tokenizer.encode(__A							,	add_special_tokens=__A							,	add_prefix_space=__A  )
				_UpperCamelCase       			=tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
				self.assertNotEqual(__A							,	__A  )

				_UpperCamelCase       			=tokenizer.encode(__A							,	add_special_tokens=__A							,	add_prefix_space=__A  )
				_UpperCamelCase       			=tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
				self.assertEqual(__A							,	__A  )

				tokenizer.add_special_tokens({'''bos_token''': '''<s>'''}  )
				_UpperCamelCase       			=tokenizer.encode(__A							,	add_special_tokens=__A  )
				_UpperCamelCase       			=tokenizer.convert_ids_to_tokens(encoded[1]  )[0]
				self.assertNotEqual(__A							,	__A  )

				# Testing spaces after special tokens
				_UpperCamelCase       			="<mask>"
				tokenizer.add_special_tokens(
				    {'''mask_token''': AddedToken(__A							,	lstrip=__A							,	rstrip=__A  )}  )  # mask token has a left space
				_UpperCamelCase       			=tokenizer.convert_tokens_to_ids(__A  )

				_UpperCamelCase       			="Encode <mask> sequence"
				_UpperCamelCase       			="Encode <mask>sequence"

				_UpperCamelCase       			=tokenizer.encode(__A  )
				_UpperCamelCase       			=encoded.index(__A  )
				_UpperCamelCase       			=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
				self.assertEqual(__A							,	__A  )

				_UpperCamelCase       			=tokenizer.encode(__A  )
				_UpperCamelCase       			=encoded.index(__A  )
				_UpperCamelCase       			=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
				self.assertNotEqual(__A							,	__A  )


		def   UpperCamelCase__      (				self    :					int  )     ->						int:
				pass


		def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						List[Any]:
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(__A							,	**__A  )
								_UpperCamelCase       			=self.tokenizer_class.from_pretrained(__A							,	**__A  )
								_UpperCamelCase       			="A, <mask> AllenNLP sentence."
								_UpperCamelCase       			=tokenizer_r.encode_plus(__A							,	add_special_tokens=__A							,	return_token_type_ids=__A  )
								_UpperCamelCase       			=tokenizer_p.encode_plus(__A							,	add_special_tokens=__A							,	return_token_type_ids=__A  )

								# token_type_ids should put 0 everywhere
								self.assertEqual(sum(tokens_r['''token_type_ids''']  )							,	sum(tokens_p['''token_type_ids''']  )  )

								# attention_mask should put 1 everywhere, so sum over length should be 1
								self.assertEqual(
								    sum(tokens_r['''attention_mask''']  ) / len(tokens_r['''attention_mask''']  )							,	sum(tokens_p['''attention_mask''']  ) / len(tokens_p['''attention_mask''']  )							,	)

								_UpperCamelCase       			=tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']  )
								_UpperCamelCase       			=tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']  )

								# Rust correctly handles the space before the mask while python doesnt
								self.assertSequenceEqual(tokens_p['''input_ids''']							,	[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )
								self.assertSequenceEqual(tokens_r['''input_ids''']							,	[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )

								self.assertSequenceEqual(
								    __A							,	['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']  )
								self.assertSequenceEqual(
								    __A							,	['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']  )


		def   UpperCamelCase__      (				self    :					List[Any]  )     ->						List[str]:
				for trim_offsets, add_prefix_space in itertools.product([True, False]							,	repeat=2  ):
						_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
						    self.tmpdirname							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )

						_UpperCamelCase       			=json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()  )
						_UpperCamelCase       			=json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()  )

						self.assertEqual(pre_tokenizer_state['''add_prefix_space''']							,	__A  )

						self.assertEqual(post_processor_state['''add_prefix_space''']							,	__A  )
						self.assertEqual(post_processor_state['''trim_offsets''']							,	__A  )




		def   UpperCamelCase__      (				self    :					List[Any]  )     ->						Dict:
				# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
				# `trim_offsets`
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
								_UpperCamelCase       			="hello"  # `hello` is a token in the vocabulary of `pretrained_name`
								_UpperCamelCase       			=F'''{text_of_1_token} {text_of_1_token}'''

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(len(__A  ) + 1, len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(len(__A  ) + 1, len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(len(__A  ), len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(len(__A  ), len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=F''' {text}'''

								# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
								#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
								# )
								# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
								# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
								# self.assertEqual(
								#     encoding.offset_mapping[1],
								#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
								# )

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(1, 1 + len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(1 + len(__A  ) + 1, 1 + len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, 1 + len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(1 + len(__A  ), 1 + len(__A  ) + 1 + len(__A  ))							,	)

								_UpperCamelCase       			=self.rust_tokenizer_class.from_pretrained(
								    __A							,	use_fast=__A							,	add_prefix_space=__A							,	trim_offsets=__A  )
								_UpperCamelCase       			=tokenizer_r(__A							,	return_offsets_mapping=__A							,	add_special_tokens=__A  )
								self.assertEqual(encoding.offset_mapping[0]							,	(0, 1 + len(__A  ))  )
								self.assertEqual(
								    encoding.offset_mapping[1]							,	(1 + len(__A  ), 1 + len(__A  ) + 1 + len(__A  ))							,	)













'''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






