



"""simple docstring"""
import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE=None   ,  _SCREAMING_SNAKE_CASE=True   ,  _SCREAMING_SNAKE_CASE=None   ,  **_SCREAMING_SNAKE_CASE		)						->   Union[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[int]			=			parent
    UpperCAmelCase			:      Any			=			config_class
    UpperCAmelCase			:      Union[str, Any]			=			has_text_modality
    UpperCAmelCase			:      int			=			kwargs
    UpperCAmelCase			:      Dict			=			common_properties

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[int]			=			self.config_class(**self.inputs_dict		)
    UpperCAmelCase			:      List[str]			=			(
        ["""hidden_size""", """num_attention_heads""", """num_hidden_layers"""]
        if self.common_properties is None
        else self.common_properties
    )

    # Add common fields for text models
    if self.has_text_modality:
     common_properties.extend(["""vocab_size"""]		)

    # Test that config has the common properties as getters
    for prop in common_properties:
     self.parent.assertTrue(hasattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)   ,  msg=F"`{prop}` does not exist"		)

    # Test that config has the common properties as setter
    for idx, name in enumerate(_SCREAMING_SNAKE_CASE		):
     try:
      setattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)
      self.parent.assertEqual(
          getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE   ,  msg=F"`{name} value {idx} expected, but was {getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)}"		)
     except NotImplementedError:
      # Some models might not be able to implement setters for common_properties
      # In that case, a NotImplementedError is raised
      pass

        # Test if config class can be called with Config(prop_name=..)
    for idx, name in enumerate(_SCREAMING_SNAKE_CASE		):
     try:
      UpperCAmelCase			:      Union[str, Any]			=			self.config_class(**{name: idx}		)
      self.parent.assertEqual(
          getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE   ,  msg=F"`{name} value {idx} expected, but was {getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)}"		)
     except NotImplementedError:
      # Some models might not be able to implement setters for common_properties
      # In that case, a NotImplementedError is raised
      pass

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





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			self.config_class(**self.inputs_dict		)
    UpperCAmelCase			:      str			=			json.loads(config.to_json_string()		)
    for key, value in self.inputs_dict.items():
     self.parent.assertEqual(obj[key]   ,  _SCREAMING_SNAKE_CASE		)

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





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			self.config_class(**self.inputs_dict		)

    with tempfile.TemporaryDirectory() as tmpdirname:
     UpperCAmelCase			:      Tuple			=			os.path.join(_SCREAMING_SNAKE_CASE   ,  """config.json"""		)
     config_first.to_json_file(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      Any			=			self.config_class.from_json_file(_SCREAMING_SNAKE_CASE		)

    self.parent.assertEqual(config_second.to_dict()   ,  config_first.to_dict()		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[int]			=			self.config_class(**self.inputs_dict		)

    with tempfile.TemporaryDirectory() as tmpdirname:
     config_first.save_pretrained(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      Tuple			=			self.config_class.from_pretrained(_SCREAMING_SNAKE_CASE		)

    self.parent.assertEqual(config_second.to_dict()   ,  config_first.to_dict()		)

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





    '''simple docstring'''




    UpperCAmelCase			:      Dict			=			self.config_class(**self.inputs_dict		)

    UpperCAmelCase			:      Optional[int]			=			"""test"""
    with tempfile.TemporaryDirectory() as tmpdirname:
     UpperCAmelCase			:      Tuple			=			os.path.join(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)
     config_first.save_pretrained(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      Tuple			=			self.config_class.from_pretrained(_SCREAMING_SNAKE_CASE   ,  subfolder=_SCREAMING_SNAKE_CASE		)

    self.parent.assertEqual(config_second.to_dict()   ,  config_first.to_dict()		)

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





    '''simple docstring'''




    UpperCAmelCase			:      Optional[Any]			=			self.config_class(**self.inputs_dict   ,  num_labels=5		)
    self.parent.assertEqual(len(config.idalabel		)   ,  5		)
    self.parent.assertEqual(len(config.labelaid		)   ,  5		)

    UpperCAmelCase			:      Any			=			3
    self.parent.assertEqual(len(config.idalabel		)   ,  3		)
    self.parent.assertEqual(len(config.labelaid		)   ,  3		)

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





    '''simple docstring'''




    if self.config_class.is_composition:
     return
    UpperCAmelCase			:      Tuple			=			self.config_class()
    self.parent.assertIsNotNone(_SCREAMING_SNAKE_CASE		)

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





    '''simple docstring'''




    UpperCAmelCase			:      Optional[int]			=			copy.deepcopy(_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Any			=			self.config_class(**_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Optional[int]			=			[]
    for key, value in config_common_kwargs.items():
     if key == "torch_dtype":
      if not is_torch_available():
       continue
      else:
       import torch

       if config.torch_dtype != torch.floataa:
        wrong_values.append(("""torch_dtype""", config.torch_dtype, torch.floataa)		)
     elif getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		) != value:
      wrong_values.append((key, getattr(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		), value)		)

    if len(_SCREAMING_SNAKE_CASE		) > 0:
     UpperCAmelCase			:      Dict			=			"""\n""".join([F"- {v[0]}: got {v[1]} instead of {v[2]}" for v in wrong_values]		)
     raise ValueError(F"The following keys were not properly set in the config:\n{errors}"		)




   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    self.create_and_test_config_common_properties()
    self.create_and_test_config_to_json_string()
    self.create_and_test_config_to_json_file()
    self.create_and_test_config_from_and_save_pretrained()
    self.create_and_test_config_from_and_save_pretrained_subfolder()
    self.create_and_test_config_with_num_labels()
    self.check_config_can_be_init_without_params()
    self.check_config_arguments_init()





"""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    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__   ,    unittest.TestCase				):
   __lowerCAmelCase						:     Any		=		XLMTokenizer
   __lowerCAmelCase						:     List[Any]		=		False

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





    '''simple docstring'''




    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    UpperCAmelCase			:      Optional[int]			=			[
        """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			:      str			=			dict(zip(_SCREAMING_SNAKE_CASE   ,  range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
    UpperCAmelCase			:      List[Any]			=			["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

    UpperCAmelCase			:      Optional[Any]			=			os.path.join(self.tmpdirname   ,  VOCAB_FILES_NAMES["""vocab_file"""]		)
    UpperCAmelCase			:      Optional[Any]			=			os.path.join(self.tmpdirname   ,  VOCAB_FILES_NAMES["""merges_file"""]		)
    with open(self.vocab_file   ,  """w"""		) as fp:
     fp.write(json.dumps(_SCREAMING_SNAKE_CASE		)		)
    with open(self.merges_file   ,  """w"""		) as fp:
     fp.write("""\n""".join(_SCREAMING_SNAKE_CASE		)		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   Any:





    '''simple docstring'''




    UpperCAmelCase			:      Optional[int]			=			"""lower newer"""
    UpperCAmelCase			:      Dict			=			"""lower newer"""
    return input_text, output_text

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





    '''simple docstring'''




    UpperCAmelCase			:      Union[str, Any]			=			XLMTokenizer(self.vocab_file   ,  self.merges_file		)

    UpperCAmelCase			:      Optional[int]			=			"""lower"""
    UpperCAmelCase			:      Optional[int]			=			["""low""", """er</w>"""]
    UpperCAmelCase			:      List[Any]			=			tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
    self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Optional[int]			=			tokens + ["""<unk>"""]
    UpperCAmelCase			:      List[Any]			=			[14, 15, 20]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)




   @slow
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Any:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			XLMTokenizer.from_pretrained("""xlm-mlm-en-2048"""		)

    UpperCAmelCase			:      int			=			tokenizer.encode("""sequence builders"""   ,  add_special_tokens=_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      List[Any]			=			tokenizer.encode("""multi-sequence build"""   ,  add_special_tokens=_SCREAMING_SNAKE_CASE		)

    UpperCAmelCase			:      Tuple			=			tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      str			=			tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)

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