


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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A      = logging.get_logger(__name__)

A      = {
    "microsoft/swin-tiny-patch4-window7-224": (
        "https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json"
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}


class     lowercase__  (					__SCREAMING_SNAKE_CASE					,							__SCREAMING_SNAKE_CASE		):
  A__=  'swin'

  A__=  {
      'num_attention_heads': 'num_heads',
      'num_hidden_layers': 'num_layers',
  }






  def __init__(					self      :					Optional[Any]		,						_lowercase      :					str=2_24		,						_lowercase      :					Optional[Any]=4		,						_lowercase      :					Optional[int]=3		,						_lowercase      :					str=96		,						_lowercase      :					Dict=[2, 2, 6, 2]		,						_lowercase      :					str=[3, 6, 12, 24]		,						_lowercase      :					Union[str, Any]=7		,						_lowercase      :					Tuple=4.0		,						_lowercase      :					Union[str, Any]=True		,						_lowercase      :					Dict=0.0		,						_lowercase      :					List[Any]=0.0		,						_lowercase      :					Union[str, Any]=0.1		,						_lowercase      :					Union[str, Any]="gelu"		,						_lowercase      :					Union[str, Any]=False		,						_lowercase      :					List[str]=0.0_2		,						_lowercase      :					List[str]=1E-5		,						_lowercase      :					str=32		,						_lowercase      :					Optional[int]=None		,						_lowercase      :					Union[str, Any]=None		,						**_lowercase      :					Dict		,						):




         """simple docstring"""







         super().__init__(**_lowercase )

         UpperCAmelCase__										=     image_size
         UpperCAmelCase__										=     patch_size
         UpperCAmelCase__										=     num_channels
         UpperCAmelCase__										=     embed_dim
         UpperCAmelCase__										=     depths
         UpperCAmelCase__										=     len(_lowercase )
         UpperCAmelCase__										=     num_heads
         UpperCAmelCase__										=     window_size
         UpperCAmelCase__										=     mlp_ratio
         UpperCAmelCase__										=     qkv_bias
         UpperCAmelCase__										=     hidden_dropout_prob
         UpperCAmelCase__										=     attention_probs_dropout_prob
         UpperCAmelCase__										=     drop_path_rate
         UpperCAmelCase__										=     hidden_act
         UpperCAmelCase__										=     use_absolute_embeddings
         UpperCAmelCase__										=     layer_norm_eps
         UpperCAmelCase__										=     initializer_range
         UpperCAmelCase__										=     encoder_stride
         # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         UpperCAmelCase__										=     int(embed_dim * 2 ** (len(_lowercase ) - 1) )
         UpperCAmelCase__										=     ["stem"] + [F"""stage{idx}""" for idx in range(1		,						len(_lowercase ) + 1 )]
         UpperCAmelCase__						,			UpperCAmelCase__										=     get_aligned_output_features_output_indices(
             out_features=_lowercase		,						out_indices=_lowercase		,						stage_names=self.stage_names )




class     lowercase__  (					__SCREAMING_SNAKE_CASE		):
  A__=  version.parse('1.11'		)






  @property
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







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






  @property
  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         return 1E-4









import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


A      = get_tests_dir("fixtures/test_sentencepiece_bpe.model")


class     lowercase__  (					__SCREAMING_SNAKE_CASE					,							unittest.TestCase		):
  A__=  BartphoTokenizer
  A__=  False
  A__=  True






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         super().setUp()

         UpperCAmelCase__										=     ["▁This", "▁is", "▁a", "▁t", "est"]
         UpperCAmelCase__										=     dict(zip(_lowercase		,						range(len(_lowercase ) ) ) )
         UpperCAmelCase__										=     {"unk_token": "<unk>"}

         UpperCAmelCase__										=     os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["monolingual_vocab_file"] )
         with open(self.monolingual_vocab_file		,						"w"		,						encoding="utf-8" ) as fp:
                for token in vocab_tokens:
                       fp.write(F"""{token} {vocab_tokens[token]}\n""" )

         UpperCAmelCase__										=     BartphoTokenizer(_lowercase		,						self.monolingual_vocab_file		,						**self.special_tokens_map )
         tokenizer.save_pretrained(self.tmpdirname )






  def 			_UpperCAmelCase  (					self      :					Dict		,						**_lowercase      :					Optional[Any] ):




         """simple docstring"""







         kwargs.update(self.special_tokens_map )
         return BartphoTokenizer.from_pretrained(self.tmpdirname		,						**_lowercase )






  def 			_UpperCAmelCase  (					self      :					List[Any]		,						_lowercase      :					Union[str, Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     "This is a là test"
         UpperCAmelCase__										=     "This is a<unk><unk> test"
         return input_text, output_text






  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     BartphoTokenizer(_lowercase		,						self.monolingual_vocab_file		,						**self.special_tokens_map )
         UpperCAmelCase__										=     "This is a là test"
         UpperCAmelCase__										=     "▁This ▁is ▁a ▁l à ▁t est".split()
         UpperCAmelCase__										=     tokenizer.tokenize(_lowercase )
         self.assertListEqual(_lowercase		,						_lowercase )

         UpperCAmelCase__										=     tokens + [tokenizer.unk_token]
         UpperCAmelCase__										=     [4, 5, 6, 3, 3, 7, 8, 3]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase )		,						_lowercase )





