


import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class        __lowercase       (							a_			,							unittest.TestCase  ):



		"""simple docstring"""

		UpperCamelCase     :					Optional[Any]			       =		OpenAIGPTTokenizer
		UpperCamelCase     :					Tuple			       =		OpenAIGPTTokenizerFast
		UpperCamelCase     :					List[Any]			       =		True
		UpperCamelCase     :					Union[str, Any]			       =		False







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







					'''simple docstring'''







					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					lowerCamelCase    		=  [
					    """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>""",
					]
					lowerCamelCase    		=  dict(zip(A		,      range(len(A	)	)	)	)
					lowerCamelCase    		=  ["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

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







		def 					__A   ( self		,      A	)  -> Any:







					'''simple docstring'''







					return "lower newer", "lower newer"







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







					'''simple docstring'''







					lowerCamelCase    		=  OpenAIGPTTokenizer(self.vocab_file		,      self.merges_file	)

					lowerCamelCase    		=  """lower"""
					lowerCamelCase    		=  ["""low""", """er</w>"""]
					lowerCamelCase    		=  tokenizer.tokenize(A	)
					self.assertListEqual(A		,      A	)

					lowerCamelCase    		=  tokens + ["""<unk>"""]
					lowerCamelCase    		=  [14, 15, 20]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(A	)		,      A	)







		def 					__A   ( self		,      A=15	)  -> Tuple:







					'''simple docstring'''







					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'	):
											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(A		,      **A	)

											# Simple input
											lowerCamelCase    		=  """This is a simple input"""
											lowerCamelCase    		=  ["""This is a simple input 1""", """This is a simple input 2"""]
											lowerCamelCase    		=  ("""This is a simple input""", """This is a pair""")
											lowerCamelCase    		=  [
											    ("""This is a simple input 1""", """This is a simple input 2"""),
											    ("""This is a simple pair 1""", """This is a simple pair 2"""),
											]

											# Simple input tests
											self.assertRaises(A		,      tokenizer_r.encode		,      A		,      max_length=A		,      padding="""max_length"""	)

											# Simple input
											self.assertRaises(A		,      tokenizer_r.encode_plus		,      A		,      max_length=A		,      padding="""max_length"""	)

											# Simple input
											self.assertRaises(
											    A		,      tokenizer_r.batch_encode_plus		,      A		,      max_length=A		,      padding="""max_length"""		,      )

											# Pair input
											self.assertRaises(A		,      tokenizer_r.encode		,      A		,      max_length=A		,      padding="""max_length"""	)

											# Pair input
											self.assertRaises(A		,      tokenizer_r.encode_plus		,      A		,      max_length=A		,      padding="""max_length"""	)

											# Pair input
											self.assertRaises(
											    A		,      tokenizer_r.batch_encode_plus		,      A		,      max_length=A		,      padding="""max_length"""		,      )







		def 					__A   ( self	)  -> int:







					'''simple docstring'''







					pass







@require_ftfy
@require_spacy
@require_tokenizers
class        __lowercase       (							a_  ):



		"""simple docstring"""

		pass





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase   :    str     =		logging.get_logger(__name__)

UpperCAmelCase   :    List[Any]     =		{
    "facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}







class        __lowercase       (							a_  ):



		"""simple docstring"""

		UpperCamelCase     :					Optional[Any]			       =		"vit_mae"







		def __init__( self		,      A=7_68		,      A=12		,      A=12		,      A=30_72		,      A="gelu"		,      A=0.0		,      A=0.0		,      A=0.02		,      A=1e-1_2		,      A=2_24		,      A=16		,      A=3		,      A=True		,      A=16		,      A=5_12		,      A=8		,      A=20_48		,      A=0.75		,      A=False		,      **A		,      )  -> Dict:







					'''simple docstring'''







					super().__init__(**A	)

					lowerCamelCase    		=  hidden_size
					lowerCamelCase    		=  num_hidden_layers
					lowerCamelCase    		=  num_attention_heads
					lowerCamelCase    		=  intermediate_size
					lowerCamelCase    		=  hidden_act
					lowerCamelCase    		=  hidden_dropout_prob
					lowerCamelCase    		=  attention_probs_dropout_prob
					lowerCamelCase    		=  initializer_range
					lowerCamelCase    		=  layer_norm_eps
					lowerCamelCase    		=  image_size
					lowerCamelCase    		=  patch_size
					lowerCamelCase    		=  num_channels
					lowerCamelCase    		=  qkv_bias
					lowerCamelCase    		=  decoder_num_attention_heads
					lowerCamelCase    		=  decoder_hidden_size
					lowerCamelCase    		=  decoder_num_hidden_layers
					lowerCamelCase    		=  decoder_intermediate_size
					lowerCamelCase    		=  mask_ratio
					lowerCamelCase    		=  norm_pix_loss

