



'''simple docstring'''


import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowercase							       =			get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
@require_tokenizers
class 	UpperCAmelCase	(		__a					,	unittest.TestCase):


	'''simple docstring'''




	__magic_name__					: Optional[int]  =      XGLMTokenizer
	__magic_name__					: Dict  =      XGLMTokenizerFast
	__magic_name__					: List[Any]  =      True
	__magic_name__					: Tuple  =      True




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



						"""simple docstring"""







						super().setUp()

						# We have a SentencePiece fixture for testing
						a_       		=XGLMTokenizer(lowerCAmelCase_							,  keep_accents=lowerCAmelCase_)
						tokenizer.save_pretrained(self.tmpdirname)




	def       lowercase_  (   self) ->      Any:



						"""simple docstring"""







						a_       		="<pad>"
						a_       		=1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase_)							,  lowerCAmelCase_)
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase_)							,  lowerCAmelCase_)




	def       lowercase_  (   self) ->      Any:



						"""simple docstring"""







						a_       		=list(self.get_tokenizer().get_vocab().keys())

						self.assertEqual(vocab_keys[0]							,  "<s>")
						self.assertEqual(vocab_keys[1]							,  "<pad>")
						self.assertEqual(len(lowerCAmelCase_)							,  1_0_0_8)




	def       lowercase_  (   self) ->      Dict:



						"""simple docstring"""







						self.assertEqual(self.get_tokenizer().vocab_size							,  1_0_0_8)




	def       lowercase_  (   self) ->      Dict:



						"""simple docstring"""







						a_       		=XGLMTokenizer(lowerCAmelCase_							,  keep_accents=lowerCAmelCase_)

						a_       		=tokenizer.tokenize("This is a test")
						self.assertListEqual(lowerCAmelCase_							,  ["▁This", "▁is", "▁a", "▁t", "est"])

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(lowerCAmelCase_)							,  [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]							,  )

						a_       		=tokenizer.tokenize("I was born in 92000, and this is falsé.")
						self.assertListEqual(
						    lowerCAmelCase_							,  [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "9",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "é",
						        ".",
						    ]							,  )
						a_       		=tokenizer.convert_tokens_to_ids(lowerCAmelCase_)
						self.assertListEqual(
						    lowerCAmelCase_							,  [
						        value + tokenizer.fairseq_offset
						        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
						    ]							,  )

						a_       		=tokenizer.convert_ids_to_tokens(lowerCAmelCase_)
						self.assertListEqual(
						    lowerCAmelCase_							,  [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "<unk>",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "<unk>",
						        ".",
						    ]							,  )




	@cached_property
	def       lowercase_  (   self) ->      str:



						"""simple docstring"""







						return XGLMTokenizer.from_pretrained("facebook/xglm-564M")




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



						"""simple docstring"""







						with tempfile.NamedTemporaryFile() as f:
											shutil.copyfile(lowerCAmelCase_							,  f.name)
											a_       		=XGLMTokenizer(f.name							,  keep_accents=lowerCAmelCase_)
											a_       		=pickle.dumps(lowerCAmelCase_)
						pickle.loads(lowerCAmelCase_)




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



						"""simple docstring"""







						if not self.test_rust_tokenizer:
											return

						a_       		=self.get_tokenizer()
						a_       		=self.get_rust_tokenizer()

						a_       		="I was born in 92000, and this is falsé."

						a_       		=tokenizer.tokenize(lowerCAmelCase_)
						a_       		=rust_tokenizer.tokenize(lowerCAmelCase_)
						self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

						a_       		=tokenizer.encode(lowerCAmelCase_							,  add_special_tokens=lowerCAmelCase_)
						a_       		=rust_tokenizer.encode(lowerCAmelCase_							,  add_special_tokens=lowerCAmelCase_)
						self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)

						a_       		=self.get_rust_tokenizer()
						a_       		=tokenizer.encode(lowerCAmelCase_)
						a_       		=rust_tokenizer.encode(lowerCAmelCase_)
						self.assertListEqual(lowerCAmelCase_							,  lowerCAmelCase_)




	@slow
	def       lowercase_  (   self) ->      int:



						"""simple docstring"""







						a_       		="Hello World!"
						a_       		=[2, 3_1_2_2_7, 4_4_4_7, 3_5]

						self.assertListEqual(lowerCAmelCase_							,  self.big_tokenizer.encode(lowerCAmelCase_))




	@slow
	def       lowercase_  (   self) ->      Any:



						"""simple docstring"""







						a_       		=(
						    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
						    " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
						)
						# fmt: off
						a_       		=[2, 1_0_1_8, 6_7, 1_1, 1_9_8_8, 2_6_1_7, 5_6_3_1, 2_7_8, 1_1, 3_4_0_7, 4_8, 7_1_6_3_0, 2_8_0_8_5, 4, 3_2_3_4, 1_5_7, 1_3, 6, 5, 6, 4, 3_5_2_6, 7_6_8, 1_5, 6_5_9, 5_7, 2_9_8, 3_9_8_3, 8_6_4, 1_2_9, 2_1, 6, 5, 1_3_6_7_5, 3_7_7, 6_5_2, 7_5_8_0, 1_0_3_4_1, 1_5_5, 2_8_1_7, 4_2_2, 1_6_6_6, 7, 1_6_7_4, 5_3, 1_1_3, 2_0_2_2_7_7, 1_7_8_9_2, 3_3, 6_0, 8_7, 4, 3_2_3_4, 1_5_7, 6_1, 2_6_6_7, 5_2_3_7_6, 1_9, 8_8, 2_3, 7_3_5]
						# fmt: on

						self.assertListEqual(lowerCAmelCase_							,  self.big_tokenizer.encode(lowerCAmelCase_))




	@slow
	def       lowercase_  (   self) ->      Tuple:



						"""simple docstring"""







						a_       		={
						    "input_ids": [[2, 1_0_8_8_2_5, 1_1_6_3, 1_5, 8_8_0_1_0, 4_7_3, 1_5_8_9_8, 1_5_7, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 2_3_8_0_2_1, 1_1_6_3, 5_3, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 5_3_2_8_3, 1_8_2_3_9_6, 8, 1_8_5_6_6, 1_6, 3_6_7_3_3, 4_1_0_1, 8, 2_3_0, 2_4_4_0_1_7, 1_2_2_5_5_3, 7, 1_5, 1_3_2_5_9_7, 4, 2_9_3, 1_2_5_1_1, 7_6_1_0, 4, 3_4_1_4, 1_3_2_5_9_7, 9, 4, 3_2_3_6_1, 3_6_2, 4, 7_3_4, 2_8_5_1_2, 3_2_5_6_9, 1_8, 4, 3_2_3_6_1, 2_6_0_9_6, 1_4_9_8_2, 7_3, 1_8_7_1_5, 2_1_4_3_3, 2_3_5_2_6_1, 1_5, 4_9_2, 1_2_4_2_7, 1_6, 5_3, 1_8_7_1_5, 2_1_4_3_3, 6_5_4_5_4, 1_5, 2_3_6_5_9, 5_6_3, 1_6, 2_7_8, 5_9_7, 2_8_4_3, 5_9_5, 7_9_3_1, 1_8_2_3_9_6, 6_4_1_8_6, 2_2, 8_8_6, 5_9_5, 1_3_2_9_8_1, 5_3, 2_5_5_4_0, 3_4_4_9, 4_3_9_8_2, 3_9_9_0_1, 5_9_5_1, 8_7_8, 3_3_0, 4, 2_7_6_9_4, 8_0_2_6_9, 3_1_2, 5_3, 6_5_1_7, 1_1_7_8_0, 6_1_1, 2_0_4_0_8, 5], [2, 6, 1_3_2_5_9_7, 6_7, 4_2_8_9_7, 3_3, 5_9_2, 8, 1_6_3_7_2_9, 2_5_5_4_0, 3_6_1, 1_3_6_9_9_7, 1_0_9_5_1_4, 1_7_3_2_3_0, 7, 5_0_1, 6_0, 1_0_2_9_1_3, 1_9_6, 5_6_3_1, 2_3_5, 6_3_2_4_3, 4_7_3, 6, 2_3_1_7_5_7, 7_4, 5_2_7_7, 7_9_0_5, 5_3, 3_0_9_5, 3_7_3_1_7, 2_2, 4_5_4, 1_8_3_8_7_4, 5], [2, 2_6_8, 3_1_2_9_8, 4_6_5_3_0, 6, 1_3_2_9_3_5, 4_3_8_3_1, 7, 5_9_7, 3_2, 2_4, 3_6_8_8, 9_8_6_5, 5]],
						    "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
						}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=lowerCAmelCase_							,  model_name="facebook/xglm-564M"							,  padding=lowerCAmelCase_							,  )







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowercase							       =			{
    '''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''VisionEncoderDecoderOnnxConfig''']
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase							       =			['''VisionEncoderDecoderModel''']

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase							       =			['''TFVisionEncoderDecoderModel''']

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase							       =			['''FlaxVisionEncoderDecoderModel''']

if TYPE_CHECKING:
  from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
  import sys

  lowercase							       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


