import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class        snake_case__							(					UpperCamelCase__       ,    unittest.TestCase				):
   _SCREAMING_SNAKE_CASE						:			Optional[Any]         =   MgpstrTokenizer
   _SCREAMING_SNAKE_CASE						:			Any         =   False
   _SCREAMING_SNAKE_CASE						:			Union[str, Any]         =   {}
   _SCREAMING_SNAKE_CASE						:			List[Any]         =   False



   def        UpperCAmelCase__							(					self : Tuple )				->  Optional[Any]:




         '''simple docstring'''




         super().setUp()

         # fmt: off
         snake_case_  :      int  	=							["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
         # fmt: on
         snake_case_  :      Union[str, Any]  	=							dict(zip(__snake_case      ,						range(len(__snake_case ) ) ) )

         snake_case_  :      Optional[int]  	=							os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES["vocab_file"] )
         with open(self.vocab_file      ,						"w"      ,						encoding="utf-8" ) as fp:
               fp.write(json.dumps(__snake_case ) + "\n" )



   def        UpperCAmelCase__							(					self : str      ,						**A__ : Tuple )				->  List[str]:




         '''simple docstring'''




         return MgpstrTokenizer.from_pretrained(self.tmpdirname      ,						**__snake_case )



   def        UpperCAmelCase__							(					self : List[str]      ,						A__ : List[str] )				->  Optional[Any]:




         '''simple docstring'''




         snake_case_  :      Optional[int]  	=							"""tester"""
         snake_case_  :      Any  	=							"""tester"""
         return input_text, output_text



   @unittest.skip("MGP-STR always lower cases letters." )
   def        UpperCAmelCase__							(					self : Dict )				->  Optional[Any]:




         '''simple docstring'''




         pass



   def        UpperCAmelCase__							(					self : Dict )				->  str:




         '''simple docstring'''




         snake_case_  :      Tuple  	=							self.get_tokenizers(do_lower_case=__snake_case )
         for tokenizer in tokenizers:
               with self.subTest(f"{tokenizer.__class__.__name__}" ):
                     snake_case_  :      Union[str, Any]  	=							"""[SPECIAL_TOKEN]"""

                     tokenizer.add_special_tokens({"cls_token": special_token} )
                     snake_case_  :      Optional[Any]  	=							tokenizer.encode([special_token]      ,						add_special_tokens=__snake_case )
                     self.assertEqual(len(__snake_case )      ,						1 )

                     snake_case_  :      int  	=							tokenizer.decode(__snake_case      ,						skip_special_tokens=__snake_case )
                     self.assertTrue(special_token not in decoded )



   def        UpperCAmelCase__							(					self : List[Any] )				->  Optional[int]:




         '''simple docstring'''




         snake_case_  :      int  	=							self.get_tokenizers()
         for tokenizer in tokenizers:
               with self.subTest(f"{tokenizer.__class__.__name__}" ):
                     snake_case_  :      List[str]  	=							self.get_input_output_texts(__snake_case )

                     snake_case_  :      Dict  	=							tokenizer.tokenize(__snake_case )
                     snake_case_  :      Union[str, Any]  	=							tokenizer.convert_tokens_to_ids(__snake_case )
                     snake_case_  :      Dict  	=							tokenizer.encode(__snake_case      ,						add_special_tokens=__snake_case )
                     self.assertListEqual(__snake_case      ,						__snake_case )

                     snake_case_  :      Tuple  	=							tokenizer.convert_ids_to_tokens(__snake_case )
                     self.assertNotEqual(len(__snake_case )      ,						0 )
                     snake_case_  :      Optional[Any]  	=							tokenizer.decode(__snake_case )
                     self.assertIsInstance(__snake_case      ,						__snake_case )

                     self.assertEqual(text_a.replace(" "      ,						"" )      ,						__snake_case )



   @unittest.skip("MGP-STR tokenizer only handles one sequence." )
   def        UpperCAmelCase__							(					self : Tuple )				->  List[str]:




         '''simple docstring'''




         pass



   @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer" )
   def        UpperCAmelCase__							(					self : Union[str, Any] )				->  Dict:




         '''simple docstring'''




         pass









import warnings
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


UpperCAmelCase_		:					Any          =  logging.get_logger(__name__)

UpperCAmelCase_		:					List[str]          =  {
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}




class 		__A   (      UpperCamelCase__      ):
						UpperCamelCase      =       """segformer"""

						def __init__(		self :List[str]     ,			__snake_case :str=3     ,			__snake_case :Optional[Any]=4     ,			__snake_case :List[Any]=[2, 2, 2, 2]     ,			__snake_case :Dict=[8, 4, 2, 1]     ,			__snake_case :Optional[int]=[32, 64, 1_60, 2_56]     ,			__snake_case :Union[str, Any]=[7, 3, 3, 3]     ,			__snake_case :Optional[Any]=[4, 2, 2, 2]     ,			__snake_case :Tuple=[1, 2, 5, 8]     ,			__snake_case :List[Any]=[4, 4, 4, 4]     ,			__snake_case :Optional[Any]="gelu"     ,			__snake_case :Tuple=0.0     ,			__snake_case :Dict=0.0     ,			__snake_case :Optional[int]=0.1     ,			__snake_case :Optional[int]=0.02     ,			__snake_case :Tuple=0.1     ,			__snake_case :Union[str, Any]=1E-6     ,			__snake_case :int=2_56     ,			__snake_case :Optional[int]=2_55     ,			**__snake_case :Dict     ,			):
										'''simple docstring'''

										super().__init__(**__snake_case			)

										if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
														warnings.warn(
														    """Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"""
														    """ removed, as the behaviour will default to that of reshape_last_stage = True."""     ,			__snake_case     ,			)

										__magic_name__						:						Dict										=num_channels
										__magic_name__						:						str										=num_encoder_blocks
										__magic_name__						:						List[Any]										=depths
										__magic_name__						:						Optional[Any]										=sr_ratios
										__magic_name__						:						List[str]										=hidden_sizes
										__magic_name__						:						List[str]										=patch_sizes
										__magic_name__						:						Any										=strides
										__magic_name__						:						Optional[Any]										=mlp_ratios
										__magic_name__						:						str										=num_attention_heads
										__magic_name__						:						int										=hidden_act
										__magic_name__						:						List[Any]										=hidden_dropout_prob
										__magic_name__						:						Optional[Any]										=attention_probs_dropout_prob
										__magic_name__						:						Optional[Any]										=classifier_dropout_prob
										__magic_name__						:						List[str]										=initializer_range
										__magic_name__						:						List[str]										=drop_path_rate
										__magic_name__						:						List[Any]										=layer_norm_eps
										__magic_name__						:						List[str]										=decoder_hidden_size
										__magic_name__						:						Union[str, Any]										=kwargs.get("""reshape_last_stage"""     ,			__snake_case			)
										__magic_name__						:						Dict										=semantic_loss_ignore_index




class 		__A   (      UpperCamelCase__      ):
						UpperCamelCase      =       version.parse("""1.11"""      )

						@property
						def      A__    (		self :List[str]			):
										'''simple docstring'''

										return OrderedDict(
										    [
										        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
										    ]			)

						@property
						def      A__    (		self :Any			):
										'''simple docstring'''

										return 1E-4


						@property
						def      A__    (		self :int			):
										'''simple docstring'''

										return 12




