"""simple docstring"""
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 					lowerCAmelCase_      (     lowerCAmelCase       ,      unittest.TestCase   ):



				"""simple docstring"""
				_lowerCAmelCase       :      Optional[Any]     					=  MgpstrTokenizer
				_lowerCAmelCase       :      int     					=  False
				_lowerCAmelCase       :      str     					=  {}
				_lowerCAmelCase       :      Tuple     					=  False

				def 						snake_case	(			self      ):






										"""simple docstring"""

										super().setUp()

										# fmt: off
										snake_case        =     ['[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        =     dict(zip(lowerCAmelCase						,      range(len(lowerCAmelCase      )      )      )      )

										snake_case        =     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(lowerCAmelCase      ) + '\n'      )

				def 						snake_case	(			self						,      **lowerCAmelCase      ):






										"""simple docstring"""

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

				def 						snake_case	(			self						,      lowerCAmelCase      ):






										"""simple docstring"""

										snake_case        =     'tester'
										snake_case        =     'tester'
										return input_text, output_text

				@unittest.skip('MGP-STR always lower cases letters.'      )
				def 						snake_case	(			self      ):






										"""simple docstring"""

										pass

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_tokenizers(do_lower_case=lowerCAmelCase      )
										for tokenizer in tokenizers:
																with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																						snake_case        =     '[SPECIAL_TOKEN]'

																						tokenizer.add_special_tokens({'cls_token': special_token}      )
																						snake_case        =     tokenizer.encode([special_token]						,      add_special_tokens=lowerCAmelCase      )
																						self.assertEqual(len(lowerCAmelCase      )						,      1      )

																						snake_case        =     tokenizer.decode(lowerCAmelCase						,      skip_special_tokens=lowerCAmelCase      )
																						self.assertTrue(special_token not in decoded      )

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     self.get_tokenizers()
										for tokenizer in tokenizers:
																with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																						snake_case   ,snake_case        =     self.get_input_output_texts(lowerCAmelCase      )

																						snake_case        =     tokenizer.tokenize(lowerCAmelCase      )
																						snake_case        =     tokenizer.convert_tokens_to_ids(lowerCAmelCase      )
																						snake_case        =     tokenizer.encode(lowerCAmelCase						,      add_special_tokens=lowerCAmelCase      )
																						self.assertListEqual(lowerCAmelCase						,      lowerCAmelCase      )

																						snake_case        =     tokenizer.convert_ids_to_tokens(lowerCAmelCase      )
																						self.assertNotEqual(len(lowerCAmelCase      )						,      0      )
																						snake_case        =     tokenizer.decode(lowerCAmelCase      )
																						self.assertIsInstance(lowerCAmelCase						,      lowerCAmelCase      )

																						self.assertEqual(text_a.replace(' '						,      ''      )						,      lowerCAmelCase      )

				@unittest.skip('MGP-STR tokenizer only handles one sequence.'      )
				def 						snake_case	(			self      ):






										"""simple docstring"""

										pass

				@unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer'      )
				def 						snake_case	(			self      ):






										"""simple docstring"""

										pass



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__   =					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =					{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}



class 					lowerCAmelCase_      (     lowerCAmelCase   ):



				"""simple docstring"""
				_lowerCAmelCase       :      Tuple     					=  """swinv2"""

				_lowerCAmelCase       :      Any     					=  {
				    """num_attention_heads""": """num_heads""",
				    """num_hidden_layers""": """num_layers""",
				}

				def __init__(			self						,      lowerCAmelCase=2_24						,      lowerCAmelCase=4						,      lowerCAmelCase=3						,      lowerCAmelCase=96						,      lowerCAmelCase=[2, 2, 6, 2]						,      lowerCAmelCase=[3, 6, 12, 24]						,      lowerCAmelCase=7						,      lowerCAmelCase=4.0						,      lowerCAmelCase=True						,      lowerCAmelCase=0.0						,      lowerCAmelCase=0.0						,      lowerCAmelCase=0.1						,      lowerCAmelCase="gelu"						,      lowerCAmelCase=False						,      lowerCAmelCase=0.02						,      lowerCAmelCase=1E-5						,      lowerCAmelCase=32						,      **lowerCAmelCase						,      ):






										"""simple docstring"""

										super().__init__(**lowerCAmelCase      )

										snake_case        =     image_size
										snake_case        =     patch_size
										snake_case        =     num_channels
										snake_case        =     embed_dim
										snake_case        =     depths
										snake_case        =     len(lowerCAmelCase      )
										snake_case        =     num_heads
										snake_case        =     window_size
										snake_case        =     mlp_ratio
										snake_case        =     qkv_bias
										snake_case        =     hidden_dropout_prob
										snake_case        =     attention_probs_dropout_prob
										snake_case        =     drop_path_rate
										snake_case        =     hidden_act
										snake_case        =     use_absolute_embeddings
										snake_case        =     layer_norm_eps
										snake_case        =     initializer_range
										snake_case        =     encoder_stride
										# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
										# this indicates the channel dimension after the last stage of the model
										snake_case        =     int(embed_dim * 2 ** (len(lowerCAmelCase      ) - 1)      )
										snake_case        =     (0, 0, 0, 0)


