
import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase					:			int			      =		get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model")


@require_sentencepiece
@require_tokenizers
class 						__lowerCAmelCase	(	lowerCAmelCase_ , unittest.TestCase      ):



      """simple docstring"""







      A__	:			List[Any]        =    GPTSwaTokenizer
      A__	:			str        =    False
      A__	:			List[Any]        =    True
      A__	:			List[str]        =    False




      def 		snake_case_			(      self		:       List[str]				):
          super().setUp()

          # We have a SentencePiece fixture for testing
          __lowercase		:			Tuple	    =       GPTSwaTokenizer(_snake_case				,       eos_token='''<unk>'''				,       bos_token='''<unk>'''				,       pad_token='''<unk>'''				)

          tokenizer.save_pretrained(self.tmpdirname				)




      def 		snake_case_			(      self		:       List[str]				,       _snake_case		:       Optional[Any]				):
          __lowercase		:			List[str]	    =       '''This is a test'''
          __lowercase		:			Any	    =       '''This is a test'''
          return input_text, output_text




      def 		snake_case_			(      self		:       Optional[Any]				):
          __lowercase		:			str	    =       '''<s>'''
          __lowercase		:			Tuple	    =       1

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




      def 		snake_case_			(      self		:       str				):
          __lowercase		:			Union[str, Any]	    =       list(self.get_tokenizer().get_vocab().keys()				)

          self.assertEqual(vocab_keys[0]				,       '''<unk>'''				)
          self.assertEqual(vocab_keys[1]				,       '''<s>'''				)
          self.assertEqual(vocab_keys[-1]				,       '''j'''				)
          self.assertEqual(len(_snake_case				)				,       2000				)




      def 		snake_case_			(      self		:       Tuple				):
          self.assertEqual(self.get_tokenizer().vocab_size				,       2000				)




      def 		snake_case_			(      self		:       List[str]				):
          __lowercase		:			Any	    =       GPTSwaTokenizer(_snake_case				)

          __lowercase		:			Any	    =       tokenizer.tokenize('''This is a test'''				)
          self.assertListEqual(_snake_case				,       ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']				)

          self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case				)				,       [465, 287, 265, 631, 842]				)

          __lowercase		:			Dict	    =       tokenizer.tokenize('''I was born in 92000, and this is falsé.'''				)
          # fmt: off
          self.assertListEqual(
              _snake_case				,       ['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.''']				,       )
          # fmt: on

          __lowercase		:			Dict	    =       tokenizer.convert_tokens_to_ids(_snake_case				)
          self.assertListEqual(
              _snake_case				,       [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]				,       )

          __lowercase		:			Union[str, Any]	    =       tokenizer.convert_ids_to_tokens(_snake_case				)
          # fmt: off
          self.assertListEqual(
              _snake_case				,       ['''▁I''', '''▁was''', '''▁bor''', '''n''', '''▁in''', '''▁''', '''<0x39>''', '''2''', '''0''', '''0''', '''0''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁f''', '''al''', '''s''', '''<0xC3>''', '''<0xA9>''', '''.''']				)
          # fmt: on




      def 		snake_case_			(      self		:       Union[str, Any]				):
          __lowercase		:			Tuple	    =       GPTSwaTokenizer(_snake_case				)
          __lowercase		:			Any	    =       ['''This is a test''', '''I was born in 92000, and this is falsé.''']
          __lowercase		:			Union[str, Any]	    =       [
              [465, 287, 265, 631, 842],
              [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
          ]

          # Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
          for text, expected_ids in zip(_snake_case				,       _snake_case				):
              self.assertListEqual(tokenizer.encode_fast(_snake_case				)				,       _snake_case				)

          # Test that decode_fast returns the input text
          for text, token_ids in zip(_snake_case				,       _snake_case				):
              self.assertEqual(tokenizer.decode_fast(_snake_case				)				,       _snake_case				)




      @slow
      def 		snake_case_			(      self		:       List[Any]				):
          __lowercase		:			str	    =       [
              '''<|python|>def fibonacci(n)\n    if n < 0:\n        print(\'Incorrect input\')''',
              '''Hey there, how are you doing this fine day?''',
              '''This is a text with a trailing spaces followed by a dot     .''',
              '''Häj sväjs lillebrör! =)''',
              '''Det är inget fel på Mr. Cool''',
          ]

          # fmt: off
          __lowercase		:			List[str]	    =       {'''input_ids''': [[6_3423, 5, 6811, 1_4954, 282, 816, 3821, 6_3466, 6_3425, 6_3462, 18, 6_3978, 678, 301, 1320, 6_3423, 6_3455, 6_3458, 18, 6_3982, 4246, 3940, 1901, 4_7789, 5547, 1_8994], [1_9630, 1100, 6_3446, 1342, 633, 544, 4488, 593, 5102, 2416, 6_3495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 5_8593, 2_2413, 9106, 546, 268, 3_3213, 6_3979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_5130, 6_3450, 924, 6_3449, 2249, 4062, 1558, 318, 6_3504, 2_1498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 6_3443, 2_6801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
          # fmt: on
          self.tokenizer_integration_test_util(
              expected_encoding=_snake_case				,       model_name='''AI-Sweden/gpt-sw3-126m'''				,       sequences=_snake_case				,       )




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


__lowerCAmelCase					:			Union[str, Any]			      =		logging.get_logger(__name__)

__lowerCAmelCase					:			Optional[int]			      =		{
    "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 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			Dict        =    '''segformer'''




      def __init__(      self		:       Optional[Any]				,       _snake_case		:       List[str]=3				,       _snake_case		:       Union[str, Any]=4				,       _snake_case		:       str=[2, 2, 2, 2]				,       _snake_case		:       Dict=[8, 4, 2, 1]				,       _snake_case		:       List[Any]=[32, 64, 160, 256]				,       _snake_case		:       Dict=[7, 3, 3, 3]				,       _snake_case		:       List[Any]=[4, 2, 2, 2]				,       _snake_case		:       Tuple=[1, 2, 5, 8]				,       _snake_case		:       Optional[Any]=[4, 4, 4, 4]				,       _snake_case		:       Optional[int]="gelu"				,       _snake_case		:       Optional[int]=0.0				,       _snake_case		:       Optional[int]=0.0				,       _snake_case		:       int=0.1				,       _snake_case		:       Any=0.02				,       _snake_case		:       Optional[int]=0.1				,       _snake_case		:       Union[str, Any]=1E-6				,       _snake_case		:       Tuple=256				,       _snake_case		:       str=255				,       **_snake_case		:       Any				,       ):
          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				,       )

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






class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			Union[str, Any]        =    version.parse('''1.11'''      )




      @property
      def 		snake_case_			(      self		:       Dict				):
          return OrderedDict(
              [
                  ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
              ]				)




      @property
      def 		snake_case_			(      self		:       int				):
          return 1E-4




      @property
      def 		snake_case_			(      self		:       List[Any]				):
          return 12


