


"""simple docstring"""


from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

_snake_case          =							TypeVar("KEY")
_snake_case          =							TypeVar("VAL")



@dataclass(frozen=SCREAMING_SNAKE_CASE_		,		slots=SCREAMING_SNAKE_CASE_ )
class   _a      (      Generic[KEY, VAL] ):
    a_    :				KEY
    a_    :				VAL





class   _a      (      _Item ):
    def __init__( self							:					List[str]				):
          super().__init__(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)


    def __bool__( self							:					str				):
          return False





_snake_case          =							_DeletedItem()



class   _a      (      MutableMapping[KEY, VAL] ):
    def __init__( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					int = 8							,					SCREAMING_SNAKE_CASE__							:					float = 0.75				):
          lowerCamelCase__           =		initial_block_size
          lowerCamelCase__           =		[None] * initial_block_size
          assert 0.0 < capacity_factor < 1.0
          lowerCamelCase__           =		capacity_factor
          lowerCamelCase__           =		0
    def      _UpperCamelCase       ( self							:					Optional[int]							,					SCREAMING_SNAKE_CASE__							:					KEY				):
          return hash(SCREAMING_SNAKE_CASE__				) % len(self._buckets				)
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					int				):
          return (ind + 1) % len(self._buckets				)
    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					KEY							,					SCREAMING_SNAKE_CASE__							:					VAL				):
          lowerCamelCase__           =		self._buckets[ind]
          if not stored:
                lowerCamelCase__           =		_Item(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)
                self._len += 1
                return True
          elif stored.key == key:
                lowerCamelCase__           =		_Item(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)
                return True
          else:
                return False
    def      _UpperCamelCase       ( self							:					Dict				):
          lowerCamelCase__           =		len(self._buckets				) * self._capacity_factor
          return len(self				) >= int(SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					int				):
          if len(self._buckets				) <= self._initial_block_size:
                return False
          lowerCamelCase__           =		len(self._buckets				) * self._capacity_factor / 2
          return len(self				) < limit
    def      _UpperCamelCase       ( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					int				):
          lowerCamelCase__           =		self._buckets
          lowerCamelCase__           =		[None] * new_size
          lowerCamelCase__           =		0
          for item in old_buckets:
                if item:
                      self._add_item(item.key							,					item.val				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          self._resize(len(self._buckets				) * 2				)
    def      _UpperCamelCase       ( self							:					Optional[int]				):
          self._resize(len(self._buckets				) // 2				)
    def      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					KEY				):
          lowerCamelCase__           =		self._get_bucket_index(SCREAMING_SNAKE_CASE__				)
          for _ in range(len(self._buckets				)				):
                yield ind
                lowerCamelCase__           =		self._get_next_ind(SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					KEY							,					SCREAMING_SNAKE_CASE__							:					VAL				):
          for ind in self._iterate_buckets(SCREAMING_SNAKE_CASE__				):
                if self._try_set(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				):
                      break
    def __setitem__( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					KEY							,					SCREAMING_SNAKE_CASE__							:					VAL				):
          if self._is_full():
                self._size_up()

          self._add_item(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)
    def __delitem__( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					KEY				):
          for ind in self._iterate_buckets(SCREAMING_SNAKE_CASE__				):
                lowerCamelCase__           =		self._buckets[ind]
                if item is None:
                      raise KeyError(SCREAMING_SNAKE_CASE__				)
                if item is _deleted:
                      continue
                if item.key == key:
                      lowerCamelCase__           =		_deleted
                      self._len -= 1
                      break
          if self._is_sparse():
                self._size_down()
    def __getitem__( self							:					str							,					SCREAMING_SNAKE_CASE__							:					KEY				):
          for ind in self._iterate_buckets(SCREAMING_SNAKE_CASE__				):
                lowerCamelCase__           =		self._buckets[ind]
                if item is None:
                      break
                if item is _deleted:
                      continue
                if item.key == key:
                      return item.val
          raise KeyError(SCREAMING_SNAKE_CASE__				)
    def __len__( self							:					List[Any]				):
          return self._len
    def __iter__( self							:					Optional[int]				):
          yield from (item.key for item in self._buckets if item)


    def __repr__( self							:					str				):
          lowerCamelCase__           =		' ,'.join(
              F'{item.key}: {item.val}' for item in self._buckets if item				)
          return F'HashMap({val_string})'







"""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   _a      :
    def __init__( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=12							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=7							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=True							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=True							,					SCREAMING_SNAKE_CASE__							:					str=True							,					SCREAMING_SNAKE_CASE__							:					Any=99							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=32							,					SCREAMING_SNAKE_CASE__							:					str=32							,					SCREAMING_SNAKE_CASE__							:					Tuple=2							,					SCREAMING_SNAKE_CASE__							:					str=4							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=37							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=0.1							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=0.1							,					SCREAMING_SNAKE_CASE__							:					str=5_12							,					SCREAMING_SNAKE_CASE__							:					str=0.02							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=0							,					SCREAMING_SNAKE_CASE__							:					Any=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      _UpperCamelCase       ( self							:					int				):
          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(SCREAMING_SNAKE_CASE__				):
                      lowerCamelCase__           =		1
                      lowerCamelCase__           =		0

          lowerCamelCase__           =		self.get_config()

          return config, input_ids, tf.convert_to_tensor(SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Any				):
          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							:					Any							,					SCREAMING_SNAKE_CASE__							:					Any							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					List[str]				):
          lowerCamelCase__           =		TFBlipTextModel(config=SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		model(SCREAMING_SNAKE_CASE__							,					attention_mask=SCREAMING_SNAKE_CASE__							,					training=SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		model(SCREAMING_SNAKE_CASE__							,					training=SCREAMING_SNAKE_CASE__				)
          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							:					Dict				):
          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      (      SCREAMING_SNAKE_CASE_		,		unittest.TestCase ):
    a_    :				str             =    (TFBlipTextModel,) if is_tf_available() else ()
    a_    :				List[str]             =    False
    a_    :				Optional[Any]             =    False
    a_    :				Union[str, Any]             =    False
    def      _UpperCamelCase       ( self							:					str				):
          lowerCamelCase__           =		BlipTextModelTester(self				)
          lowerCamelCase__           =		ConfigTester(self							,					config_class=SCREAMING_SNAKE_CASE__							,					hidden_size=37				)
    def      _UpperCamelCase       ( self							:					Tuple				):
          self.config_tester.run_common_tests()
    def      _UpperCamelCase       ( self							:					str				):
          lowerCamelCase__           =		self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_model(*SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Tuple				):
          pass
    def      _UpperCamelCase       ( self							:					Tuple				):
          pass
    @unittest.skip(reason='Blip does not use inputs_embeds'				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          pass
    @unittest.skip(reason='BlipTextModel has no base class and is not available in MODEL_MAPPING'				)
    def      _UpperCamelCase       ( self							:					Dict				):
          pass
    @unittest.skip(reason='BlipTextModel has no base class and is not available in MODEL_MAPPING'				)
    def      _UpperCamelCase       ( self							:					List[Any]				):
          pass
    @slow
    def      _UpperCamelCase       ( self							:					str				):
          for model_name in TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                lowerCamelCase__           =		TFBlipTextModel.from_pretrained(SCREAMING_SNAKE_CASE__				)
                self.assertIsNotNone(SCREAMING_SNAKE_CASE__				)


    def      _UpperCamelCase       ( self							:					Optional[int]							,					SCREAMING_SNAKE_CASE__							:					List[Any]=True				):
          super().test_pt_tf_model_equivalence(allow_missing_keys=SCREAMING_SNAKE_CASE__				)



