






"""simple docstring"""





import inspect
import unittest

from transformers import SwinaSRConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
  import torch
  from torch import nn

  from transformers import SwinaSRForImageSuperResolution, SwinaSRModel
  from transformers.models.swinasr.modeling_swinasr import SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST

if is_vision_available():
  from PIL import Image

  from transformers import SwinaSRImageProcessor







class 		_a       :





   '''simple docstring'''






   def __init__(   self			,				UpperCAmelCase_			,				UpperCAmelCase_=13			,				UpperCAmelCase_=32			,				UpperCAmelCase_=1			,				UpperCAmelCase_=3			,				UpperCAmelCase_=16			,				UpperCAmelCase_=[1, 2, 1]			,				UpperCAmelCase_=[2, 2, 4]			,				UpperCAmelCase_=2			,				UpperCAmelCase_=2.0			,				UpperCAmelCase_=True			,				UpperCAmelCase_=0.0			,				UpperCAmelCase_=0.0			,				UpperCAmelCase_=0.1			,				UpperCAmelCase_="gelu"			,				UpperCAmelCase_=False			,				UpperCAmelCase_=True			,				UpperCAmelCase_=0.02			,				UpperCAmelCase_=1E-5			,				UpperCAmelCase_=True			,				UpperCAmelCase_=None			,				UpperCAmelCase_=False			,				UpperCAmelCase_=2			,				)	-> Optional[Any]:




          '''simple docstring'''




          lowercase__:    Any        =      parent
          lowercase__:    List[str]        =      batch_size
          lowercase__:    Optional[int]        =      image_size
          lowercase__:    Dict        =      patch_size
          lowercase__:    Tuple        =      num_channels
          lowercase__:    Optional[int]        =      embed_dim
          lowercase__:    int        =      depths
          lowercase__:    List[str]        =      num_heads
          lowercase__:    List[str]        =      window_size
          lowercase__:    List[str]        =      mlp_ratio
          lowercase__:    Optional[Any]        =      qkv_bias
          lowercase__:    Any        =      hidden_dropout_prob
          lowercase__:    str        =      attention_probs_dropout_prob
          lowercase__:    Union[str, Any]        =      drop_path_rate
          lowercase__:    Dict        =      hidden_act
          lowercase__:    List[str]        =      use_absolute_embeddings
          lowercase__:    Optional[int]        =      patch_norm
          lowercase__:    Dict        =      layer_norm_eps
          lowercase__:    Union[str, Any]        =      initializer_range
          lowercase__:    Dict        =      is_training
          lowercase__:    List[Any]        =      scope
          lowercase__:    Tuple        =      use_labels
          lowercase__:    Any        =      upscale

          # here we set some attributes to make tests pass
          lowercase__:    List[str]        =      len(UpperCAmelCase_)
          lowercase__:    Union[str, Any]        =      embed_dim
          lowercase__:    List[Any]        =      (image_size // patch_size) ** 2





   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          lowercase__:    Optional[Any]        =      floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])

          lowercase__:    List[Any]        =      None
          if self.use_labels:
                 lowercase__:    List[Any]        =      ids_tensor([self.batch_size]			,				self.type_sequence_label_size)

          lowercase__:    List[Any]        =      self.get_config()

          return config, pixel_values, labels





   def __lowercase    (   self)	-> Any:




          '''simple docstring'''




          return SwinaSRConfig(
              image_size=self.image_size			,				patch_size=self.patch_size			,				num_channels=self.num_channels			,				embed_dim=self.embed_dim			,				depths=self.depths			,				num_heads=self.num_heads			,				window_size=self.window_size			,				mlp_ratio=self.mlp_ratio			,				qkv_bias=self.qkv_bias			,				hidden_dropout_prob=self.hidden_dropout_prob			,				attention_probs_dropout_prob=self.attention_probs_dropout_prob			,				drop_path_rate=self.drop_path_rate			,				hidden_act=self.hidden_act			,				use_absolute_embeddings=self.use_absolute_embeddings			,				path_norm=self.patch_norm			,				layer_norm_eps=self.layer_norm_eps			,				initializer_range=self.initializer_range			,				upscale=self.upscale			,				)





   def __lowercase    (   self			,				UpperCAmelCase_			,				UpperCAmelCase_			,				UpperCAmelCase_)	-> Any:




          '''simple docstring'''




          lowercase__:    str        =      SwinaSRModel(config=UpperCAmelCase_)
          model.to(UpperCAmelCase_)
          model.eval()
          lowercase__:    int        =      model(UpperCAmelCase_)

          self.parent.assertEqual(
              result.last_hidden_state.shape			,				(self.batch_size, self.embed_dim, self.image_size, self.image_size))





   def __lowercase    (   self			,				UpperCAmelCase_			,				UpperCAmelCase_			,				UpperCAmelCase_)	-> int:




          '''simple docstring'''




          lowercase__:    List[str]        =      SwinaSRForImageSuperResolution(UpperCAmelCase_)
          model.to(UpperCAmelCase_)
          model.eval()
          lowercase__:    str        =      model(UpperCAmelCase_)

          lowercase__:    Union[str, Any]        =      self.image_size * self.upscale
          self.parent.assertEqual(
              result.reconstruction.shape			,				(self.batch_size, self.num_channels, expected_image_size, expected_image_size))





   def __lowercase    (   self)	-> Optional[Any]:




          '''simple docstring'''




          lowercase__:    Optional[Any]        =      self.prepare_config_and_inputs()
          lowercase__  ,     lowercase__  ,     lowercase__:    Union[str, Any]        =      config_and_inputs
          lowercase__:    str        =      {"pixel_values": pixel_values}
          return config, inputs_dict







@require_torch
class 		_a       (						lowercase_    ,					lowercase_    ,					unittest.TestCase   ):





   '''simple docstring'''






   UpperCamelCase__      					=    (SwinaSRModel, SwinaSRForImageSuperResolution) if is_torch_available() else ()
   UpperCamelCase__      					=    {"""feature-extraction""": SwinaSRModel} if is_torch_available() else {}

   UpperCamelCase__      					=    False
   UpperCamelCase__      					=    False
   UpperCamelCase__      					=    False
   UpperCamelCase__      					=    False
   UpperCamelCase__      					=    False





   def __lowercase    (   self)	-> List[str]:




          '''simple docstring'''




          lowercase__:    Dict        =      SwinaSRModelTester(self)
          lowercase__:    List[str]        =      ConfigTester(self			,				config_class=UpperCAmelCase_			,				embed_dim=37)





   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          self.config_tester.create_and_test_config_to_json_string()
          self.config_tester.create_and_test_config_to_json_file()
          self.config_tester.create_and_test_config_from_and_save_pretrained()
          self.config_tester.create_and_test_config_with_num_labels()
          self.config_tester.check_config_can_be_init_without_params()
          self.config_tester.check_config_arguments_init()





   def __lowercase    (   self)	-> Optional[int]:




          '''simple docstring'''




          lowercase__:    List[Any]        =      self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_model(*UpperCAmelCase_)





   def __lowercase    (   self)	-> List[str]:




          '''simple docstring'''




          lowercase__:    List[str]        =      self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_for_image_super_resolution(*UpperCAmelCase_)





   @unittest.skip(reason="Got `CUDA error: misaligned address` with PyTorch 2.0.0.")
   def __lowercase    (   self)	-> Any:




          '''simple docstring'''




          pass





   @unittest.skip(reason="Swin2SR does not use inputs_embeds")
   def __lowercase    (   self)	-> List[str]:




          '''simple docstring'''




          pass





   @unittest.skip(reason="Swin2SR does not support training yet")
   def __lowercase    (   self)	-> Dict:




          '''simple docstring'''




          pass





   @unittest.skip(reason="Swin2SR does not support training yet")
   def __lowercase    (   self)	-> Dict:




          '''simple docstring'''




          pass





   def __lowercase    (   self)	-> str:




          '''simple docstring'''




          lowercase__  ,     lowercase__:    List[str]        =      self.model_tester.prepare_config_and_inputs_for_common()

          for model_class in self.all_model_classes:
                 lowercase__:    Any        =      model_class(UpperCAmelCase_)
                 self.assertIsInstance(model.get_input_embeddings()			,				(nn.Module))
                 lowercase__:    Union[str, Any]        =      model.get_output_embeddings()
                 self.assertTrue(x is None or isinstance(UpperCAmelCase_			,				nn.Linear))





   def __lowercase    (   self)	-> Tuple:




          '''simple docstring'''




          lowercase__  ,     lowercase__:    Union[str, Any]        =      self.model_tester.prepare_config_and_inputs_for_common()

          for model_class in self.all_model_classes:
                 lowercase__:    Any        =      model_class(UpperCAmelCase_)
                 lowercase__:    int        =      inspect.signature(model.forward)
                 # signature.parameters is an OrderedDict => so arg_names order is deterministic
                 lowercase__:    str        =      [*signature.parameters.keys()]

                 lowercase__:    str        =      ["pixel_values"]
                 self.assertListEqual(arg_names[:1]			,				UpperCAmelCase_)





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




          '''simple docstring'''




          for model_name in SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                 lowercase__:    List[Any]        =      SwinaSRModel.from_pretrained(UpperCAmelCase_)
                 self.assertIsNotNone(UpperCAmelCase_)





   def __lowercase    (   self)	-> List[str]:




          '''simple docstring'''




          lowercase__  ,     lowercase__:    Optional[Any]        =      self.model_tester.prepare_config_and_inputs_for_common()

          lowercase__:    Tuple        =      _config_zero_init(UpperCAmelCase_)
          for model_class in self.all_model_classes:
                 lowercase__:    Dict        =      model_class(config=UpperCAmelCase_)
                 for name, param in model.named_parameters():
                        if "logit_scale" in name:
                               continue
                        if param.requires_grad:
                               self.assertIn(
                                   ((param.data.mean() * 1E9).round() / 1E9).item()			,				[0.0, 1.0]			,				msg=F"""Parameter {name} of model {model_class} seems not properly initialized"""			,				)





   def __lowercase    (   self)	-> List[str]:




          '''simple docstring'''




          lowercase__  ,     lowercase__:    int        =      self.model_tester.prepare_config_and_inputs_for_common()
          lowercase__:    Optional[int]        =      True

          for model_class in self.all_model_classes:
                 lowercase__:    Union[str, Any]        =      True
                 lowercase__:    str        =      False
                 lowercase__:    str        =      True
                 lowercase__:    Any        =      model_class(UpperCAmelCase_)
                 model.to(UpperCAmelCase_)
                 model.eval()
                 with torch.no_grad():
                        lowercase__:    Tuple        =      model(**self._prepare_for_class(UpperCAmelCase_			,				UpperCAmelCase_))
                 lowercase__:    List[Any]        =      outputs.attentions
                 lowercase__:    Tuple        =      len(self.model_tester.depths)
                 self.assertEqual(len(UpperCAmelCase_)			,				UpperCAmelCase_)

                 # check that output_attentions also work using config
                 del inputs_dict["output_attentions"]
                 lowercase__:    Optional[int]        =      True
                 lowercase__:    Union[str, Any]        =      config.window_size**2
                 lowercase__:    List[str]        =      model_class(UpperCAmelCase_)
                 model.to(UpperCAmelCase_)
                 model.eval()
                 with torch.no_grad():
                        lowercase__:    int        =      model(**self._prepare_for_class(UpperCAmelCase_			,				UpperCAmelCase_))
                 lowercase__:    Dict        =      outputs.attentions
                 self.assertEqual(len(UpperCAmelCase_)			,				UpperCAmelCase_)

                 self.assertListEqual(
                     list(attentions[0].shape[-3:])			,				[self.model_tester.num_heads[0], window_size_squared, window_size_squared]			,				)
                 lowercase__:    int        =      len(UpperCAmelCase_)

                 # Check attention is always last and order is fine
                 lowercase__:    Optional[Any]        =      True
                 lowercase__:    List[str]        =      True
                 lowercase__:    int        =      model_class(UpperCAmelCase_)
                 model.to(UpperCAmelCase_)
                 model.eval()
                 with torch.no_grad():
                        lowercase__:    Optional[Any]        =      model(**self._prepare_for_class(UpperCAmelCase_			,				UpperCAmelCase_))

                 self.assertEqual(out_len + 1			,				len(UpperCAmelCase_))

                 lowercase__:    List[Any]        =      outputs.attentions

                 self.assertEqual(len(UpperCAmelCase_)			,				UpperCAmelCase_)

                 self.assertListEqual(
                     list(self_attentions[0].shape[-3:])			,				[self.model_tester.num_heads[0], window_size_squared, window_size_squared]			,				)







@require_vision
@require_torch
@slow
class 		_a       (						unittest.TestCase   ):





   '''simple docstring'''






   def __lowercase    (   self)	-> str:




          '''simple docstring'''




          lowercase__:    Union[str, Any]        =      SwinaSRImageProcessor()
          lowercase__:    Union[str, Any]        =      SwinaSRForImageSuperResolution.from_pretrained("caidas/swin2SR-classical-sr-x2-64").to(UpperCAmelCase_)

          lowercase__:    Dict        =      Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png")
          lowercase__:    Dict        =      processor(images=UpperCAmelCase_			,				return_tensors="pt").to(UpperCAmelCase_)

          # forward pass
          with torch.no_grad():
                 lowercase__:    Optional[int]        =      model(**UpperCAmelCase_)

          # verify the logits
          lowercase__:    Union[str, Any]        =      torch.Size([1, 3, 976, 1_296])
          self.assertEqual(outputs.reconstruction.shape			,				UpperCAmelCase_)
          lowercase__:    Union[str, Any]        =      torch.tensor(
              [[0.54_58, 0.55_46, 0.56_38], [0.55_26, 0.55_65, 0.56_51], [0.53_96, 0.54_26, 0.56_21]]).to(UpperCAmelCase_)
          self.assertTrue(torch.allclose(outputs.reconstruction[0, 0, :3, :3]			,				UpperCAmelCase_			,				atol=1E-4))














"""simple docstring"""





import os
import unittest

from transformers import ElectraTokenizerFast
from transformers.models.electra.tokenization_electra import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    ElectraTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english







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





   '''simple docstring'''






   UpperCamelCase__      					=    ElectraTokenizer
   UpperCamelCase__      					=    ElectraTokenizerFast
   UpperCamelCase__      					=    True
   UpperCamelCase__      					=    True
   UpperCamelCase__      					=    filter_non_english





   def __lowercase    (   self)	-> str:




          '''simple docstring'''




          super().setUp()

          lowercase__:    List[str]        =      [
              "[UNK]",
              "[CLS]",
              "[SEP]",
              "[PAD]",
              "[MASK]",
              "want",
              "##want",
              "##ed",
              "wa",
              "un",
              "runn",
              "##ing",
              ",",
              "low",
              "lowest",
          ]
          lowercase__:    int        =      os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["vocab_file"])
          with open(self.vocab_file			,				"w"			,				encoding="utf-8") as vocab_writer:
                 vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))





   def __lowercase    (   self			,				UpperCAmelCase_)	-> Dict:




          '''simple docstring'''




          lowercase__:    str        =      "UNwant\u00E9d,running"
          lowercase__:    List[Any]        =      "unwanted, running"
          return input_text, output_text





   def __lowercase    (   self)	-> Union[str, Any]:




          '''simple docstring'''




          lowercase__:    str        =      self.tokenizer_class(self.vocab_file)

          lowercase__:    Tuple        =      tokenizer.tokenize("UNwant\u00E9d,running")
          self.assertListEqual(UpperCAmelCase_			,				["un", "##want", "##ed", ",", "runn", "##ing"])
          self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_)			,				[9, 6, 7, 12, 10, 11])





   def __lowercase    (   self)	-> Optional[int]:




          '''simple docstring'''




          if not self.test_rust_tokenizer:
                 return

          lowercase__:    Dict        =      self.get_tokenizer()
          lowercase__:    List[Any]        =      self.get_rust_tokenizer()

          lowercase__:    Optional[Any]        =      "UNwant\u00E9d,running"

          lowercase__:    Tuple        =      tokenizer.tokenize(UpperCAmelCase_)
          lowercase__:    Tuple        =      rust_tokenizer.tokenize(UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

          lowercase__:    List[str]        =      tokenizer.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
          lowercase__:    Optional[Any]        =      rust_tokenizer.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

          lowercase__:    List[Any]        =      self.get_rust_tokenizer()
          lowercase__:    int        =      tokenizer.encode(UpperCAmelCase_)
          lowercase__:    str        =      rust_tokenizer.encode(UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

          # With lower casing
          lowercase__:    Optional[Any]        =      self.get_tokenizer(do_lower_case=UpperCAmelCase_)
          lowercase__:    List[Any]        =      self.get_rust_tokenizer(do_lower_case=UpperCAmelCase_)

          lowercase__:    str        =      "UNwant\u00E9d,running"

          lowercase__:    str        =      tokenizer.tokenize(UpperCAmelCase_)
          lowercase__:    Tuple        =      rust_tokenizer.tokenize(UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

          lowercase__:    List[Any]        =      tokenizer.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
          lowercase__:    List[str]        =      rust_tokenizer.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

          lowercase__:    Any        =      self.get_rust_tokenizer()
          lowercase__:    Dict        =      tokenizer.encode(UpperCAmelCase_)
          lowercase__:    List[Any]        =      rust_tokenizer.encode(UpperCAmelCase_)
          self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)





   def __lowercase    (   self)	-> Dict:




          '''simple docstring'''




          lowercase__:    Optional[int]        =      BasicTokenizer()

          self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz")			,				["ah", "\u535A", "\u63A8", "zz"])





   def __lowercase    (   self)	-> Optional[int]:




          '''simple docstring'''




          lowercase__:    str        =      BasicTokenizer(do_lower_case=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")			,				["hello", "!", "how", "are", "you", "?"])
          self.assertListEqual(tokenizer.tokenize("H\u00E9llo")			,				["hello"])





   def __lowercase    (   self)	-> Union[str, Any]:




          '''simple docstring'''




          lowercase__:    Any        =      BasicTokenizer(do_lower_case=UpperCAmelCase_			,				strip_accents=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")			,				["hällo", "!", "how", "are", "you", "?"])
          self.assertListEqual(tokenizer.tokenize("H\u00E9llo")			,				["h\u00E9llo"])





   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          lowercase__:    Tuple        =      BasicTokenizer(do_lower_case=UpperCAmelCase_			,				strip_accents=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")			,				["hallo", "!", "how", "are", "you", "?"])
          self.assertListEqual(tokenizer.tokenize("H\u00E9llo")			,				["hello"])





   def __lowercase    (   self)	-> Union[str, Any]:




          '''simple docstring'''




          lowercase__:    int        =      BasicTokenizer(do_lower_case=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")			,				["hallo", "!", "how", "are", "you", "?"])
          self.assertListEqual(tokenizer.tokenize("H\u00E9llo")			,				["hello"])





   def __lowercase    (   self)	-> Optional[Any]:




          '''simple docstring'''




          lowercase__:    Optional[int]        =      BasicTokenizer(do_lower_case=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")			,				["HeLLo", "!", "how", "Are", "yoU", "?"])





   def __lowercase    (   self)	-> Optional[Any]:




          '''simple docstring'''




          lowercase__:    Optional[Any]        =      BasicTokenizer(do_lower_case=UpperCAmelCase_			,				strip_accents=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")			,				["HäLLo", "!", "how", "Are", "yoU", "?"])





   def __lowercase    (   self)	-> Union[str, Any]:




          '''simple docstring'''




          lowercase__:    Any        =      BasicTokenizer(do_lower_case=UpperCAmelCase_			,				strip_accents=UpperCAmelCase_)

          self.assertListEqual(
              tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")			,				["HaLLo", "!", "how", "Are", "yoU", "?"])





   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          lowercase__:    List[Any]        =      BasicTokenizer(do_lower_case=UpperCAmelCase_			,				never_split=["[UNK]"])

          self.assertListEqual(
              tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]")			,				["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"])





   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          lowercase__:    List[str]        =      ["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

          lowercase__:    Dict        =      {}
          for i, token in enumerate(UpperCAmelCase_):
                 lowercase__:    Optional[int]        =      i
          lowercase__:    str        =      WordpieceTokenizer(vocab=UpperCAmelCase_			,				unk_token="[UNK]")

          self.assertListEqual(tokenizer.tokenize("")			,				[])

          self.assertListEqual(tokenizer.tokenize("unwanted running")			,				["un", "##want", "##ed", "runn", "##ing"])

          self.assertListEqual(tokenizer.tokenize("unwantedX running")			,				["[UNK]", "runn", "##ing"])





   def __lowercase    (   self)	-> Dict:




          '''simple docstring'''




          self.assertTrue(_is_whitespace(" "))
          self.assertTrue(_is_whitespace("\t"))
          self.assertTrue(_is_whitespace("\r"))
          self.assertTrue(_is_whitespace("\n"))
          self.assertTrue(_is_whitespace("\u00A0"))

          self.assertFalse(_is_whitespace("A"))
          self.assertFalse(_is_whitespace("-"))





   def __lowercase    (   self)	-> List[Any]:




          '''simple docstring'''




          self.assertTrue(_is_control("\u0005"))

          self.assertFalse(_is_control("A"))
          self.assertFalse(_is_control(" "))
          self.assertFalse(_is_control("\t"))
          self.assertFalse(_is_control("\r"))





   def __lowercase    (   self)	-> List[Any]:




          '''simple docstring'''




          self.assertTrue(_is_punctuation("-"))
          self.assertTrue(_is_punctuation("$"))
          self.assertTrue(_is_punctuation("`"))
          self.assertTrue(_is_punctuation("."))

          self.assertFalse(_is_punctuation("A"))
          self.assertFalse(_is_punctuation(" "))





   def __lowercase    (   self)	-> Tuple:




          '''simple docstring'''




          lowercase__:    Optional[Any]        =      self.get_tokenizer()
          lowercase__:    str        =      self.get_rust_tokenizer()

          # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
          self.assertListEqual([tokenizer.tokenize(UpperCAmelCase_) for t in ["Test", "\xad", "test"]]			,				[["[UNK]"], [], ["[UNK]"]])

          self.assertListEqual(
              [rust_tokenizer.tokenize(UpperCAmelCase_) for t in ["Test", "\xad", "test"]]			,				[["[UNK]"], [], ["[UNK]"]])





   @slow
   def __lowercase    (   self)	-> int:




          '''simple docstring'''




          lowercase__:    Dict        =      self.tokenizer_class.from_pretrained("google/electra-base-discriminator")

          lowercase__:    Optional[int]        =      tokenizer.encode("sequence builders"			,				add_special_tokens=UpperCAmelCase_)
          lowercase__:    List[str]        =      tokenizer.encode("multi-sequence build"			,				add_special_tokens=UpperCAmelCase_)

          lowercase__:    Dict        =      tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_)
          lowercase__:    Union[str, Any]        =      tokenizer.build_inputs_with_special_tokens(UpperCAmelCase_			,				UpperCAmelCase_)

          assert encoded_sentence == [101] + text + [102]
          assert encoded_pair == [101] + text + [102] + text_a + [102]





   def __lowercase    (   self)	-> List[Any]:




          '''simple docstring'''




          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                        lowercase__:    Any        =      self.rust_tokenizer_class.from_pretrained(UpperCAmelCase_			,				**UpperCAmelCase_)

                        lowercase__:    int        =      F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
                        lowercase__:    Tuple        =      tokenizer_r.encode_plus(
                            UpperCAmelCase_			,				return_attention_mask=UpperCAmelCase_			,				return_token_type_ids=UpperCAmelCase_			,				return_offsets_mapping=UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_			,				)

                        lowercase__:    str        =      tokenizer_r.do_lower_case if hasattr(UpperCAmelCase_			,				"do_lower_case") else False
                        lowercase__:    List[Any]        =      (
                            [
                                ((0, 0), tokenizer_r.cls_token),
                                ((0, 1), "A"),
                                ((1, 2), ","),
                                ((3, 5), "na"),
                                ((5, 6), "##ï"),
                                ((6, 8), "##ve"),
                                ((9, 15), tokenizer_r.mask_token),
                                ((16, 21), "Allen"),
                                ((21, 23), "##NL"),
                                ((23, 24), "##P"),
                                ((25, 33), "sentence"),
                                ((33, 34), "."),
                                ((0, 0), tokenizer_r.sep_token),
                            ]
                            if not do_lower_case
                            else [
                                ((0, 0), tokenizer_r.cls_token),
                                ((0, 1), "a"),
                                ((1, 2), ","),
                                ((3, 8), "naive"),
                                ((9, 15), tokenizer_r.mask_token),
                                ((16, 21), "allen"),
                                ((21, 23), "##nl"),
                                ((23, 24), "##p"),
                                ((25, 33), "sentence"),
                                ((33, 34), "."),
                                ((0, 0), tokenizer_r.sep_token),
                            ]
                        )

                        self.assertEqual(
                            [e[1] for e in expected_results]			,				tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]))
                        self.assertEqual([e[0] for e in expected_results]			,				tokens["offset_mapping"])





   def __lowercase    (   self)	-> List[Any]:




          '''simple docstring'''




          lowercase__:    Union[str, Any]        =      ["的", "人", "有"]
          lowercase__:    Any        =      "".join(UpperCAmelCase_)
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                        lowercase__:    Optional[Any]        =      True
                        lowercase__:    List[str]        =      self.tokenizer_class.from_pretrained(UpperCAmelCase_			,				**UpperCAmelCase_)
                        lowercase__:    Dict        =      self.rust_tokenizer_class.from_pretrained(UpperCAmelCase_			,				**UpperCAmelCase_)

                        lowercase__:    str        =      tokenizer_p.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
                        lowercase__:    Optional[int]        =      tokenizer_r.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)

                        lowercase__:    Union[str, Any]        =      tokenizer_r.convert_ids_to_tokens(UpperCAmelCase_)
                        lowercase__:    List[str]        =      tokenizer_p.convert_ids_to_tokens(UpperCAmelCase_)

                        # it is expected that each Chinese character is not preceded by "##"
                        self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)
                        self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)

                        lowercase__:    Dict        =      False
                        lowercase__:    Optional[int]        =      self.rust_tokenizer_class.from_pretrained(UpperCAmelCase_			,				**UpperCAmelCase_)
                        lowercase__:    int        =      self.tokenizer_class.from_pretrained(UpperCAmelCase_			,				**UpperCAmelCase_)

                        lowercase__:    str        =      tokenizer_r.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)
                        lowercase__:    Tuple        =      tokenizer_p.encode(UpperCAmelCase_			,				add_special_tokens=UpperCAmelCase_)

                        lowercase__:    Union[str, Any]        =      tokenizer_r.convert_ids_to_tokens(UpperCAmelCase_)
                        lowercase__:    List[str]        =      tokenizer_p.convert_ids_to_tokens(UpperCAmelCase_)

                        # it is expected that only the first Chinese character is not preceded by "##".
                        lowercase__:    List[str]        =      [
                            F"""##{token}""" if idx != 0 else token for idx, token in enumerate(UpperCAmelCase_)
                        ]
                        self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)
                        self.assertListEqual(UpperCAmelCase_			,				UpperCAmelCase_)






