





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  __A       :


				def __init__(						self				,	UpperCAmelCase_				,	UpperCAmelCase_=12				,	UpperCAmelCase_=7				,	UpperCAmelCase_=True				,	UpperCAmelCase_=True				,	UpperCAmelCase_=True				,	UpperCAmelCase_=99				,	UpperCAmelCase_=32				,	UpperCAmelCase_=32				,	UpperCAmelCase_=2				,	UpperCAmelCase_=4				,	UpperCAmelCase_=37				,	UpperCAmelCase_=0.1				,	UpperCAmelCase_=0.1				,	UpperCAmelCase_=512				,	UpperCAmelCase_=0.0_2				,	UpperCAmelCase_=0				,	UpperCAmelCase_=None				,	):
								lowerCamelCase			=parent
								lowerCamelCase			=batch_size
								lowerCamelCase			=seq_length
								lowerCamelCase			=is_training
								lowerCamelCase			=use_input_mask
								lowerCamelCase			=use_labels
								lowerCamelCase			=vocab_size
								lowerCamelCase			=hidden_size
								lowerCamelCase			=projection_dim
								lowerCamelCase			=num_hidden_layers
								lowerCamelCase			=num_attention_heads
								lowerCamelCase			=intermediate_size
								lowerCamelCase			=dropout
								lowerCamelCase			=attention_dropout
								lowerCamelCase			=max_position_embeddings
								lowerCamelCase			=initializer_range
								lowerCamelCase			=scope
								lowerCamelCase			=bos_token_id


				def _snake_case    (						self							):
								lowerCamelCase			=ids_tensor([self.batch_size, self.seq_length]				,	self.vocab_size							)

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

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

								lowerCamelCase			=self.get_config()

								return config, input_ids, tf.convert_to_tensor(UpperCAmelCase_							)


				def _snake_case    (						self							):
								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 _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=TFBlipTextModel(config=UpperCAmelCase_							)
								lowerCamelCase			=model(UpperCAmelCase_				,	attention_mask=UpperCAmelCase_				,	training=UpperCAmelCase_							)
								lowerCamelCase			=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 _snake_case    (						self							):
								lowerCamelCase			=self.prepare_config_and_inputs()
								lowerCamelCase	,					lowerCamelCase	,					lowerCamelCase			=config_and_inputs
								lowerCamelCase			={"""input_ids""": input_ids, """attention_mask""": input_mask}
								return config, inputs_dict




@require_tf
class  __A       (  a      ,   unittest.TestCase      ):
				__A								=			(TFBlipTextModel,) if is_tf_available() else ()
				__A								=			False
				__A								=			False
				__A								=			False


				def _snake_case    (						self							):
								lowerCamelCase			=BlipTextModelTester(self							)
								lowerCamelCase			=ConfigTester(self				,	config_class=UpperCAmelCase_				,	hidden_size=37							)


				def _snake_case    (						self							):
								self.config_tester.run_common_tests()


				def _snake_case    (						self							):
								lowerCamelCase			=self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_model(*UpperCAmelCase_							)


				def _snake_case    (						self							):
								pass


				def _snake_case    (						self							):
								pass


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


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


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


				@slow
				def _snake_case    (						self							):
								for model_name in TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
												lowerCamelCase			=TFBlipTextModel.from_pretrained(UpperCAmelCase_							)
												self.assertIsNotNone(UpperCAmelCase_							)


				def _snake_case    (						self				,	UpperCAmelCase_=True							):
								super().test_pt_tf_model_equivalence(allow_missing_keys=UpperCAmelCase_							)













import argparse
import os
import re

import packaging.version


UpperCAmelCase__  :     List[Any]   			='''examples/'''
UpperCAmelCase__  :     List[str]   			={
    '''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
    '''init''': (re.compile(r'''^__version__\s+=\s+"([^"]+)"\s*$''', re.MULTILINE), '''__version__ = "VERSION"\n'''),
    '''setup''': (re.compile(r'''^(\s*)version\s*=\s*"[^"]+",''', re.MULTILINE), r'''\1version="VERSION",'''),
    '''doc''': (re.compile(r'''^(\s*)release\s*=\s*"[^"]+"$''', re.MULTILINE), '''release = "VERSION"\n'''),
}
UpperCAmelCase__  :     List[Any]   			={
    '''init''': '''src/transformers/__init__.py''',
    '''setup''': '''setup.py''',
}
UpperCAmelCase__  :     Union[str, Any]   			='''README.md'''





def        _lowercase   (  _UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase			)  ->					str:
				with open(_UpperCAmelCase     , """r"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								lowerCamelCase			=f.read()
				lowerCamelCase	,					lowerCamelCase			=REPLACE_PATTERNS[pattern]
				lowerCamelCase			=replace.replace("""VERSION"""     , _UpperCAmelCase			)
				lowerCamelCase			=re_pattern.sub(_UpperCAmelCase     , _UpperCAmelCase			)
				with open(_UpperCAmelCase     , """w"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								f.write(_UpperCAmelCase			)





def        _lowercase   (  _UpperCAmelCase			)  ->					int:
				for folder, directories, fnames in os.walk(_UpperCAmelCase			):
								# Removing some of the folders with non-actively maintained examples from the walk
								if "research_projects" in directories:
												directories.remove("""research_projects"""			)
								if "legacy" in directories:
												directories.remove("""legacy"""			)
								for fname in fnames:
												if fname.endswith(""".py"""			):
																update_version_in_file(os.path.join(_UpperCAmelCase     , _UpperCAmelCase			)     , _UpperCAmelCase     , pattern="""examples"""			)





def        _lowercase   (  _UpperCAmelCase     , _UpperCAmelCase=False			)  ->					Any:
				for pattern, fname in REPLACE_FILES.items():
								update_version_in_file(_UpperCAmelCase     , _UpperCAmelCase     , _UpperCAmelCase			)
				if not patch:
								update_version_in_examples(_UpperCAmelCase			)





def        _lowercase   (  )  ->					Dict:
				lowerCamelCase			="""🤗 Transformers currently provides the following architectures"""
				lowerCamelCase			="""1. Want to contribute a new model?"""
				with open(_UpperCAmelCase     , """r"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								lowerCamelCase			=f.readlines()

				# Find the start of the list.
				lowerCamelCase			=0
				while not lines[start_index].startswith(_start_prompt			):
								start_index += 1
				start_index += 1

				lowerCamelCase			=start_index
				# Update the lines in the model list.
				while not lines[index].startswith(_end_prompt			):
								if lines[index].startswith("""1."""			):
												lowerCamelCase			=lines[index].replace(
												    """https://huggingface.co/docs/transformers/main/model_doc"""     , """https://huggingface.co/docs/transformers/model_doc"""     , )
								index += 1

				with open(_UpperCAmelCase     , """w"""     , encoding="""utf-8"""     , newline="""\n"""			) as f:
								f.writelines(_UpperCAmelCase			)





def        _lowercase   (  )  ->					Optional[int]:
				with open(REPLACE_FILES["""init"""]     , """r"""			) as f:
								lowerCamelCase			=f.read()
				lowerCamelCase			=REPLACE_PATTERNS["""init"""][0].search(_UpperCAmelCase			).groups()[0]
				return packaging.version.parse(_UpperCAmelCase			)





def        _lowercase   (  _UpperCAmelCase=False			)  ->					List[str]:
				lowerCamelCase			=get_version()
				if patch and default_version.is_devrelease:
								raise ValueError("""Can't create a patch version from the dev branch, checkout a released version!"""			)
				if default_version.is_devrelease:
								lowerCamelCase			=default_version.base_version
				elif patch:
								lowerCamelCase			=F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
				else:
								lowerCamelCase			=F"""{default_version.major}.{default_version.minor + 1}.0"""

				# Now let's ask nicely if that's the right one.
				lowerCamelCase			=input(F"""Which version are you releasing? [{default_version}]"""			)
				if len(_UpperCAmelCase			) == 0:
								lowerCamelCase			=default_version

				print(F"""Updating version to {version}."""			)
				global_version_update(_UpperCAmelCase     , patch=_UpperCAmelCase			)
				if not patch:
								print("""Cleaning main README, don't forget to run `make fix-copies`."""			)
								clean_main_ref_in_model_list()





def        _lowercase   (  )  ->					str:
				lowerCamelCase			=get_version()
				lowerCamelCase			=F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
				lowerCamelCase			=current_version.base_version

				# Check with the user we got that right.
				lowerCamelCase			=input(F"""Which version are we developing now? [{dev_version}]"""			)
				if len(_UpperCAmelCase			) == 0:
								lowerCamelCase			=dev_version

				print(F"""Updating version to {version}."""			)
				global_version_update(_UpperCAmelCase			)
				print("""Cleaning main README, don't forget to run `make fix-copies`."""			)
				clean_main_ref_in_model_list()


if __name__ == "__main__":
							UpperCAmelCase__  :     Optional[Any]   			=argparse.ArgumentParser()
							parser.add_argument('''--post_release''', action='''store_true''', help='''Whether this is pre or post release.''')
							parser.add_argument('''--patch''', action='''store_true''', help='''Whether or not this is a patch release.''')
							UpperCAmelCase__  :     str   			=parser.parse_args()
							if not args.post_release:
														pre_release_work(patch=args.patch)
							elif args.patch:
														print('''Nothing to do after a patch :-)''')
							else:
														post_release_work()





