



"""simple docstring"""
from __future__ import annotations

import unittest

import numpy as np

from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask


if is_tf_available():
   import tensorflow as tf

   from transformers import TFBlipTextModel
   from transformers.models.blip.modeling_tf_blip import TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST


class    SCREAMING_SNAKE_CASE__ :

    def __init__(				self			:				List[Any] ,  lowerCAmelCase_			:				List[str] ,  lowerCAmelCase_			:				List[str]=1_2 ,  lowerCAmelCase_			:				Any=7 ,  lowerCAmelCase_			:				Any=True ,  lowerCAmelCase_			:				Tuple=True ,  lowerCAmelCase_			:				Any=True ,  lowerCAmelCase_			:				List[Any]=9_9 ,  lowerCAmelCase_			:				List[Any]=3_2 ,  lowerCAmelCase_			:				Any=3_2 ,  lowerCAmelCase_			:				Optional[Any]=2 ,  lowerCAmelCase_			:				Any=4 ,  lowerCAmelCase_			:				Dict=3_7 ,  lowerCAmelCase_			:				Optional[int]=0.1 ,  lowerCAmelCase_			:				List[str]=0.1 ,  lowerCAmelCase_			:				Union[str, Any]=5_1_2 ,  lowerCAmelCase_			:				Dict=0.02 ,  lowerCAmelCase_			:				int=0 ,  lowerCAmelCase_			:				Tuple=None ,  ):







      """simple docstring"""







      lowercase_								= parent
      lowercase_								= batch_size
      lowercase_								= seq_length
      lowercase_								= is_training
      lowercase_								= use_input_mask
      lowercase_								= use_labels
      lowercase_								= vocab_size
      lowercase_								= hidden_size
      lowercase_								= projection_dim
      lowercase_								= num_hidden_layers
      lowercase_								= num_attention_heads
      lowercase_								= intermediate_size
      lowercase_								= dropout
      lowercase_								= attention_dropout
      lowercase_								= max_position_embeddings
      lowercase_								= initializer_range
      lowercase_								= scope
      lowercase_								= bos_token_id

    def 					_UpperCAmelCase	(				self			:				List[Any]):







      """simple docstring"""







      lowercase_								= ids_tensor([self.batch_size, self.seq_length] ,  self.vocab_size)

      lowercase_								= None
      if self.use_input_mask:
        lowercase_								= random_attention_mask([self.batch_size, self.seq_length])

      if input_mask is not None:
        lowercase_								= input_mask.numpy()
        lowercase_					,    lowercase_								= input_mask.shape
        lowercase_								= np.random.randint(1 ,  seq_length - 1 ,  size=(batch_size,))
        for batch_idx, start_index in enumerate(_UpperCAmelCase):
          lowercase_								= 1
          lowercase_								= 0

      lowercase_								= self.get_config()

      return config, input_ids, tf.convert_to_tensor(_UpperCAmelCase)

    def 					_UpperCAmelCase	(				self			:				List[Any]):







      """simple docstring"""







      return BlipTextConfig(
          vocab_size=self.vocab_size ,  hidden_size=self.hidden_size ,  projection_dim=self.projection_dim ,  num_hidden_layers=self.num_hidden_layers ,  num_attention_heads=self.num_attention_heads ,  intermediate_size=self.intermediate_size ,  dropout=self.dropout ,  attention_dropout=self.attention_dropout ,  max_position_embeddings=self.max_position_embeddings ,  initializer_range=self.initializer_range ,  bos_token_id=self.bos_token_id ,  )

    def 					_UpperCAmelCase	(				self			:				Union[str, Any] ,  lowerCAmelCase_			:				List[Any] ,  lowerCAmelCase_			:				Optional[Any] ,  lowerCAmelCase_			:				Tuple):







      """simple docstring"""







      lowercase_								= TFBlipTextModel(config=_UpperCAmelCase)
      lowercase_								= model(_UpperCAmelCase ,  attention_mask=_UpperCAmelCase ,  training=_UpperCAmelCase)
      lowercase_								= model(_UpperCAmelCase ,  training=_UpperCAmelCase)
      self.parent.assertEqual(result.last_hidden_state.shape ,  (self.batch_size, self.seq_length, self.hidden_size))
      self.parent.assertEqual(result.pooler_output.shape ,  (self.batch_size, self.hidden_size))




    def 					_UpperCAmelCase	(				self			:				Tuple):







      """simple docstring"""







      lowercase_								= self.prepare_config_and_inputs()
      lowercase_					,    lowercase_					,    lowercase_								= config_and_inputs
      lowercase_								= {"""input_ids""": input_ids, """attention_mask""": input_mask}
      return config, inputs_dict







@require_tf
class    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase      ,  unittest.TestCase   ):
    lowercase__      =   (TFBlipTextModel,) if is_tf_available() else ()
    lowercase__      =   False
    lowercase__      =   False
    lowercase__      =   False

    def 					_UpperCAmelCase	(				self			:				List[str]):







      """simple docstring"""







      lowercase_								= BlipTextModelTester(self)
      lowercase_								= ConfigTester(self ,  config_class=_UpperCAmelCase ,  hidden_size=3_7)

    def 					_UpperCAmelCase	(				self			:				int):







      """simple docstring"""







      self.config_tester.run_common_tests()

    def 					_UpperCAmelCase	(				self			:				int):







      """simple docstring"""







      lowercase_								= self.model_tester.prepare_config_and_inputs()
      self.model_tester.create_and_check_model(*_UpperCAmelCase)

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







      """simple docstring"""







      pass

    def 					_UpperCAmelCase	(				self			:				List[Any]):







      """simple docstring"""







      pass

    @unittest.skip(reason="""Blip does not use inputs_embeds""")
    def 					_UpperCAmelCase	(				self			:				Any):







      """simple docstring"""







      pass

    @unittest.skip(reason="""BlipTextModel has no base class and is not available in MODEL_MAPPING""")
    def 					_UpperCAmelCase	(				self			:				Union[str, Any]):







      """simple docstring"""







      pass

    @unittest.skip(reason="""BlipTextModel has no base class and is not available in MODEL_MAPPING""")
    def 					_UpperCAmelCase	(				self			:				str):







      """simple docstring"""







      pass

    @slow
    def 					_UpperCAmelCase	(				self			:				Tuple):







      """simple docstring"""







      for model_name in TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
        lowercase_								= TFBlipTextModel.from_pretrained(_UpperCAmelCase)
        self.assertIsNotNone(_UpperCAmelCase)




    def 					_UpperCAmelCase	(				self			:				Tuple ,  lowerCAmelCase_			:				Union[str, Any]=True):







      """simple docstring"""







      super().test_pt_tf_model_equivalence(allow_missing_keys=_UpperCAmelCase)






"""simple docstring"""
import os
from collections.abc import Iterator


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase = "."							) ->						Iterator[str]:







  '''simple docstring'''


  for dir_path, dir_names, filenames in os.walk(__lowerCAmelCase							):
    lowercase_								= [d for d in dir_names if d != """scripts""" and d[0] not in """._"""]
    for filename in filenames:
      if filename == "__init__.py":
        continue
      if os.path.splitext(__lowerCAmelCase							)[1] in (".py", ".ipynb"):
        yield os.path.join(__lowerCAmelCase ,  __lowerCAmelCase							).lstrip("""./"""							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						Any:







  '''simple docstring'''


  return F'''{i * "  "}*''' if i else "\n##"


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						str:







  '''simple docstring'''


  lowercase_								= old_path.split(os.sep							)
  for i, new_part in enumerate(new_path.split(os.sep							)							):
    if (i + 1 > len(__lowerCAmelCase							) or old_parts[i] != new_part) and new_part:
      print(F'''{md_prefix(__lowerCAmelCase							)} {new_part.replace("_" ,  " "							).title()}'''							)
  return new_path


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase = "."							) ->						None:







  '''simple docstring'''


  lowercase_								= """"""
  for filepath in sorted(good_file_paths(__lowerCAmelCase							)							):
    lowercase_					,    lowercase_								= os.path.split(__lowerCAmelCase							)
    if filepath != old_path:
      lowercase_								= print_path(__lowerCAmelCase ,  __lowerCAmelCase							)
    lowercase_								= (filepath.count(os.sep							) + 1) if filepath else 0
    lowercase_								= F'''{filepath}/{filename}'''.replace(""" """ ,  """%20"""							)
    lowercase_								= os.path.splitext(filename.replace("""_""" ,  """ """							).title()							)[0]
    print(F'''{md_prefix(__lowerCAmelCase							)} [{filename}]({url})'''							)


if __name__ == "__main__":
       print_directory_md(".")

