

import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      DownBlockaD  # noqa F405
  a     =      "down"






  def    lowercase_	(							self		:	Union[str, Any]      )	->							List[str]:
       SCREAMING_SNAKE_CASE__					=					[-0.0232, -0.9869, 0.8054, -0.0637, -0.1688, -1.4264, 0.4470, -1.3394, 0.0904]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      ResnetDownsampleBlockaD  # noqa F405
  a     =      "down"






  def    lowercase_	(							self		:	Optional[int]      )	->							List[str]:
       SCREAMING_SNAKE_CASE__					=					[0.0710, 0.2410, -0.7320, -1.0757, -1.1343, 0.3540, -0.0133, -0.2576, 0.0948]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnDownBlockaD  # noqa F405
  a     =      "down"






  def    lowercase_	(							self		:	Dict      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					[0.0636, 0.8964, -0.6234, -1.0131, 0.0844, 0.4935, 0.3437, 0.0911, -0.2957]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      CrossAttnDownBlockaD  # noqa F405
  a     =      "down"






  def    lowercase_	(							self		:	Dict      )	->							int:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Tuple      )	->							int:
       SCREAMING_SNAKE_CASE__					=					[0.2238, -0.7396, -0.2255, -0.3829, 0.1925, 1.1665, 0.0603, -0.7295, 0.1983]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      SimpleCrossAttnDownBlockaD  # noqa F405
  a     =      "down"






  @property
  def    lowercase_	(							self		:	int      )	->							Union[str, Any]:
       return super().get_dummy_input(include_encoder_hidden_states=__lowerCamelCase      )






  def    lowercase_	(							self		:	int      )	->							List[str]:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  @unittest.skipIf(torch_device == '''mps'''			,     '''MPS result is not consistent'''      )
  def    lowercase_	(							self		:	Any      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					[0.7921, -0.0992, -0.1962, -0.7695, -0.4242, 0.7804, 0.4737, 0.2765, 0.3338]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      SkipDownBlockaD  # noqa F405
  a     =      "down"






  @property
  def    lowercase_	(							self		:	Any      )	->							Dict:
       return super().get_dummy_input(include_skip_sample=__lowerCamelCase      )







  def    lowercase_	(							self		:	List[Any]      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					[-0.0845, -0.2087, -0.2465, 0.0971, 0.1900, -0.0484, 0.2664, 0.4179, 0.5069]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnSkipDownBlockaD  # noqa F405
  a     =      "down"






  @property
  def    lowercase_	(							self		:	List[str]      )	->							int:
       return super().get_dummy_input(include_skip_sample=__lowerCamelCase      )







  def    lowercase_	(							self		:	Tuple      )	->							Dict:
       SCREAMING_SNAKE_CASE__					=					[0.5539, 0.1609, 0.4924, 0.0537, -0.1995, 0.4050, 0.0979, -0.2721, -0.0642]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      DownEncoderBlockaD  # noqa F405
  a     =      "down"






  @property
  def    lowercase_	(							self		:	Dict      )	->							Union[str, Any]:
       return super().get_dummy_input(include_temb=__lowerCamelCase      )






  def    lowercase_	(							self		:	List[Any]      )	->							str:
       SCREAMING_SNAKE_CASE__					=					{
           '''in_channels''': 32,
           '''out_channels''': 32,
       }
       SCREAMING_SNAKE_CASE__					=					self.dummy_input
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Tuple      )	->							Optional[Any]:
       SCREAMING_SNAKE_CASE__					=					[1.1102, 0.5302, 0.4872, -0.0023, -0.8042, 0.0483, -0.3489, -0.5632, 0.7626]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnDownEncoderBlockaD  # noqa F405
  a     =      "down"






  @property
  def    lowercase_	(							self		:	Dict      )	->							Optional[int]:
       return super().get_dummy_input(include_temb=__lowerCamelCase      )






  def    lowercase_	(							self		:	Any      )	->							Union[str, Any]:
       SCREAMING_SNAKE_CASE__					=					{
           '''in_channels''': 32,
           '''out_channels''': 32,
       }
       SCREAMING_SNAKE_CASE__					=					self.dummy_input
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Any      )	->							Any:
       SCREAMING_SNAKE_CASE__					=					[0.8966, -0.1486, 0.8568, 0.8141, -0.9046, -0.1342, -0.0972, -0.7417, 0.1538]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      UNetMidBlockaD  # noqa F405
  a     =      "mid"






  def    lowercase_	(							self		:	Optional[Any]      )	->							Any:
       SCREAMING_SNAKE_CASE__					=					{
           '''in_channels''': 32,
           '''temb_channels''': 128,
       }
       SCREAMING_SNAKE_CASE__					=					self.dummy_input
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Tuple      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					[-0.1062, 1.7248, 0.3494, 1.4569, -0.0910, -1.2421, -0.9984, 0.6736, 1.0028]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      UNetMidBlockaDCrossAttn  # noqa F405
  a     =      "mid"






  def    lowercase_	(							self		:	List[Any]      )	->							Union[str, Any]:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Any      )	->							Union[str, Any]:
       SCREAMING_SNAKE_CASE__					=					[0.0187, 2.4220, 0.4484, 1.1203, -0.6121, -1.5122, -0.8270, 0.7851, 1.8335]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      UNetMidBlockaDSimpleCrossAttn  # noqa F405
  a     =      "mid"






  @property
  def    lowercase_	(							self		:	Optional[int]      )	->							List[Any]:
       return super().get_dummy_input(include_encoder_hidden_states=__lowerCamelCase      )






  def    lowercase_	(							self		:	int      )	->							str:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	str      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					[0.7143, 1.9974, 0.5448, 1.3977, 0.1282, -1.1237, -1.4238, 0.5530, 0.8880]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      UpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Union[str, Any]      )	->							Tuple:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )







  def    lowercase_	(							self		:	int      )	->							Optional[Any]:
       SCREAMING_SNAKE_CASE__					=					[-0.2041, -0.4165, -0.3022, 0.0041, -0.6628, -0.7053, 0.1928, -0.0325, 0.0523]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      ResnetUpsampleBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Optional[Any]      )	->							Optional[Any]:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )







  def    lowercase_	(							self		:	Dict      )	->							Any:
       SCREAMING_SNAKE_CASE__					=					[0.2287, 0.3549, -0.1346, 0.4797, -0.1715, -0.9649, 0.7305, -0.5864, -0.6244]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      CrossAttnUpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	int      )	->							List[Any]:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )






  def    lowercase_	(							self		:	Union[str, Any]      )	->							Dict:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	int      )	->							Dict:
       SCREAMING_SNAKE_CASE__					=					[-0.1403, -0.3515, -0.0420, -0.1425, 0.3167, 0.5094, -0.2181, 0.5931, 0.5582]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      SimpleCrossAttnUpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Tuple      )	->							Optional[Any]:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase			,     include_encoder_hidden_states=__lowerCamelCase      )






  def    lowercase_	(							self		:	Tuple      )	->							Dict:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					32
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Any      )	->							Dict:
       SCREAMING_SNAKE_CASE__					=					[0.2645, 0.1480, 0.0909, 0.8044, -0.9758, -0.9083, 0.0994, -1.1453, -0.7402]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnUpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Optional[Any]      )	->							Optional[int]:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )







  @unittest.skipIf(torch_device == '''mps'''			,     '''MPS result is not consistent'''      )
  def    lowercase_	(							self		:	Any      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					[0.0979, 0.1326, 0.0021, 0.0659, 0.2249, 0.0059, 0.1132, 0.5952, 0.1033]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      SkipUpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Union[str, Any]      )	->							List[str]:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )







  def    lowercase_	(							self		:	Tuple      )	->							List[str]:
       SCREAMING_SNAKE_CASE__					=					[-0.0893, -0.1234, -0.1506, -0.0332, 0.0123, -0.0211, 0.0566, 0.0143, 0.0362]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnSkipUpBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	Union[str, Any]      )	->							Tuple:
       return super().get_dummy_input(include_res_hidden_states_tuple=__lowerCamelCase      )







  def    lowercase_	(							self		:	int      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					[0.0361, 0.0617, 0.2787, -0.0350, 0.0342, 0.3421, -0.0843, 0.0913, 0.3015]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      UpDecoderBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	List[str]      )	->							Union[str, Any]:
       return super().get_dummy_input(include_temb=__lowerCamelCase      )






  def    lowercase_	(							self		:	Tuple      )	->							Dict:
       SCREAMING_SNAKE_CASE__					=					{'''in_channels''': 32, '''out_channels''': 32}

       SCREAMING_SNAKE_CASE__					=					self.dummy_input
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	Union[str, Any]      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					[0.4404, 0.1998, -0.9886, -0.3320, -0.3128, -0.7034, -0.6955, -0.2338, -0.3137]
       super().test_output(__lowerCamelCase      )






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      AttnUpDecoderBlockaD  # noqa F405
  a     =      "up"






  @property
  def    lowercase_	(							self		:	List[Any]      )	->							Union[str, Any]:
       return super().get_dummy_input(include_temb=__lowerCamelCase      )






  def    lowercase_	(							self		:	int      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					{'''in_channels''': 32, '''out_channels''': 32}

       SCREAMING_SNAKE_CASE__					=					self.dummy_input
       return init_dict, inputs_dict







  def    lowercase_	(							self		:	List[str]      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					[0.6738, 0.4491, 0.1055, 1.0710, 0.7316, 0.3339, 0.3352, 0.1023, 0.3568]
       super().test_output(__lowerCamelCase      )





import inspect
import unittest

from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available

from ...test_backbone_common import BackboneTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
       import torch
       from torch import nn

       from transformers import BitBackbone, BitForImageClassification, BitImageProcessor, BitModel
       from transformers.models.bit.modeling_bit import BIT_PRETRAINED_MODEL_ARCHIVE_LIST


if is_vision_available():
       from PIL import Image






class  UpperCAmelCase__	:






  """simple docstring"""


  def __init__(							self		:	Optional[Any]			,     __lowerCamelCase		:	Union[str, Any]			,     __lowerCamelCase		:	Union[str, Any]=3			,     __lowerCamelCase		:	int=32			,     __lowerCamelCase		:	Tuple=3			,     __lowerCamelCase		:	Optional[int]=10			,     __lowerCamelCase		:	List[Any]=[8, 16, 32, 64]			,     __lowerCamelCase		:	Dict=[1, 1, 2, 1]			,     __lowerCamelCase		:	int=True			,     __lowerCamelCase		:	Dict=True			,     __lowerCamelCase		:	Optional[int]="relu"			,     __lowerCamelCase		:	Optional[Any]=3			,     __lowerCamelCase		:	Any=None			,     __lowerCamelCase		:	Optional[int]=["stage2", "stage3", "stage4"]			,     __lowerCamelCase		:	Tuple=[2, 3, 4]			,     __lowerCamelCase		:	List[Any]=1			,     )	->							List[str]:
       SCREAMING_SNAKE_CASE__					=					parent
       SCREAMING_SNAKE_CASE__					=					batch_size
       SCREAMING_SNAKE_CASE__					=					image_size
       SCREAMING_SNAKE_CASE__					=					num_channels
       SCREAMING_SNAKE_CASE__					=					embeddings_size
       SCREAMING_SNAKE_CASE__					=					hidden_sizes
       SCREAMING_SNAKE_CASE__					=					depths
       SCREAMING_SNAKE_CASE__					=					is_training
       SCREAMING_SNAKE_CASE__					=					use_labels
       SCREAMING_SNAKE_CASE__					=					hidden_act
       SCREAMING_SNAKE_CASE__					=					num_labels
       SCREAMING_SNAKE_CASE__					=					scope
       SCREAMING_SNAKE_CASE__					=					len(__lowerCamelCase      )
       SCREAMING_SNAKE_CASE__					=					out_features
       SCREAMING_SNAKE_CASE__					=					out_indices
       SCREAMING_SNAKE_CASE__					=					num_groups






  def    lowercase_	(							self		:	Optional[Any]      )	->							str:
       SCREAMING_SNAKE_CASE__					=					floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]      )

       SCREAMING_SNAKE_CASE__					=					None
       if self.use_labels:
            SCREAMING_SNAKE_CASE__					=					ids_tensor([self.batch_size]			,     self.num_labels      )

       SCREAMING_SNAKE_CASE__					=					self.get_config()

       return config, pixel_values, labels






  def    lowercase_	(							self		:	List[str]      )	->							Dict:
       return BitConfig(
           num_channels=self.num_channels			,     embeddings_size=self.embeddings_size			,     hidden_sizes=self.hidden_sizes			,     depths=self.depths			,     hidden_act=self.hidden_act			,     num_labels=self.num_labels			,     out_features=self.out_features			,     out_indices=self.out_indices			,     num_groups=self.num_groups			,     )






  def    lowercase_	(							self		:	Optional[Any]			,     __lowerCamelCase		:	List[str]			,     __lowerCamelCase		:	Dict			,     __lowerCamelCase		:	Union[str, Any]      )	->							int:
       SCREAMING_SNAKE_CASE__					=					BitModel(config=__lowerCamelCase      )
       model.to(__lowerCamelCase      )
       model.eval()
       SCREAMING_SNAKE_CASE__					=					model(__lowerCamelCase      )
       self.parent.assertEqual(
           result.last_hidden_state.shape			,     (self.batch_size, self.hidden_sizes[-1], self.image_size // 32, self.image_size // 32)			,     )






  def    lowercase_	(							self		:	str			,     __lowerCamelCase		:	List[str]			,     __lowerCamelCase		:	Union[str, Any]			,     __lowerCamelCase		:	Optional[int]      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					self.num_labels
       SCREAMING_SNAKE_CASE__					=					BitForImageClassification(__lowerCamelCase      )
       model.to(__lowerCamelCase      )
       model.eval()
       SCREAMING_SNAKE_CASE__					=					model(__lowerCamelCase			,     labels=__lowerCamelCase      )
       self.parent.assertEqual(result.logits.shape			,     (self.batch_size, self.num_labels)      )






  def    lowercase_	(							self		:	Optional[int]			,     __lowerCamelCase		:	Optional[int]			,     __lowerCamelCase		:	Optional[int]			,     __lowerCamelCase		:	Union[str, Any]      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					BitBackbone(config=__lowerCamelCase      )
       model.to(__lowerCamelCase      )
       model.eval()
       SCREAMING_SNAKE_CASE__					=					model(__lowerCamelCase      )

       # verify feature maps
       self.parent.assertEqual(len(result.feature_maps      )			,     len(config.out_features      )      )
       self.parent.assertListEqual(list(result.feature_maps[0].shape      )			,     [self.batch_size, self.hidden_sizes[1], 4, 4]      )

       # verify channels
       self.parent.assertEqual(len(model.channels      )			,     len(config.out_features      )      )
       self.parent.assertListEqual(model.channels			,     config.hidden_sizes[1:]      )

       # verify backbone works with out_features=None
       SCREAMING_SNAKE_CASE__					=					None
       SCREAMING_SNAKE_CASE__					=					BitBackbone(config=__lowerCamelCase      )
       model.to(__lowerCamelCase      )
       model.eval()
       SCREAMING_SNAKE_CASE__					=					model(__lowerCamelCase      )

       # verify feature maps
       self.parent.assertEqual(len(result.feature_maps      )			,     1      )
       self.parent.assertListEqual(list(result.feature_maps[0].shape      )			,     [self.batch_size, self.hidden_sizes[-1], 1, 1]      )

       # verify channels
       self.parent.assertEqual(len(model.channels      )			,     1      )
       self.parent.assertListEqual(model.channels			,     [config.hidden_sizes[-1]]      )







  def    lowercase_	(							self		:	Tuple      )	->							int:
       SCREAMING_SNAKE_CASE__					=					self.prepare_config_and_inputs()
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					config_and_inputs
       SCREAMING_SNAKE_CASE__					=					{'''pixel_values''': pixel_values}
       return config, inputs_dict






@require_torch
class  UpperCAmelCase__	( A__		,  A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      (BitModel, BitForImageClassification, BitBackbone) if is_torch_available() else ()
  a     =      (
      {"feature-extraction": BitModel, "image-classification": BitForImageClassification}
      if is_torch_available()
      else {}
  )

  a     =      False
  a     =      False
  a     =      False
  a     =      False
  a     =      False






  def    lowercase_	(							self		:	Optional[Any]      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					BitModelTester(self      )
       SCREAMING_SNAKE_CASE__					=					ConfigTester(self			,     config_class=__lowerCamelCase			,     has_text_modality=__lowerCamelCase      )






  def    lowercase_	(							self		:	Union[str, Any]      )	->							str:
       self.create_and_test_config_common_properties()
       self.config_tester.create_and_test_config_to_json_string()
       self.config_tester.create_and_test_config_to_json_file()
       self.config_tester.create_and_test_config_from_and_save_pretrained()
       self.config_tester.create_and_test_config_with_num_labels()
       self.config_tester.check_config_can_be_init_without_params()
       self.config_tester.check_config_arguments_init()






  def    lowercase_	(							self		:	str      )	->							Dict:
       return






  @unittest.skip(reason='''Bit does not output attentions'''      )
  def    lowercase_	(							self		:	Any      )	->							Dict:
       pass






  @unittest.skip(reason='''Bit does not use inputs_embeds'''      )
  def    lowercase_	(							self		:	Tuple      )	->							Optional[int]:
       pass






  @unittest.skip(reason='''Bit does not support input and output embeddings'''      )
  def    lowercase_	(							self		:	Optional[int]      )	->							str:
       pass






  def    lowercase_	(							self		:	str      )	->							str:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs_for_common()

       for model_class in self.all_model_classes:
            SCREAMING_SNAKE_CASE__					=					model_class(__lowerCamelCase      )
            SCREAMING_SNAKE_CASE__					=					inspect.signature(model.forward      )
            # signature.parameters is an OrderedDict => so arg_names order is deterministic
            SCREAMING_SNAKE_CASE__					=					[*signature.parameters.keys()]

            SCREAMING_SNAKE_CASE__					=					['''pixel_values''']
            self.assertListEqual(arg_names[:1]			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	Dict      )	->							Tuple:
       SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_model(*__lowerCamelCase      )






  def    lowercase_	(							self		:	Any      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_backbone(*__lowerCamelCase      )






  def    lowercase_	(							self		:	Any      )	->							str:
       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs_for_common()

       for model_class in self.all_model_classes:
            SCREAMING_SNAKE_CASE__					=					model_class(config=__lowerCamelCase      )
            for name, module in model.named_modules():
                 if isinstance(__lowerCamelCase			,     (nn.BatchNormad, nn.GroupNorm)      ):
                      self.assertTrue(
                          torch.all(module.weight == 1      )			,     msg=f'''Parameter {name} of model {model_class} seems not properly initialized'''			,     )
                      self.assertTrue(
                          torch.all(module.bias == 0      )			,     msg=f'''Parameter {name} of model {model_class} seems not properly initialized'''			,     )






  def    lowercase_	(							self		:	str      )	->							Optional[Any]:
       def check_hidden_states_output(__lowerCamelCase		:	List[Any]			,     __lowerCamelCase		:	Dict			,     __lowerCamelCase		:	Optional[Any]      ):
            SCREAMING_SNAKE_CASE__					=					model_class(__lowerCamelCase      )
            model.to(__lowerCamelCase      )
            model.eval()

            with torch.no_grad():
                 SCREAMING_SNAKE_CASE__					=					model(**self._prepare_for_class(__lowerCamelCase			,     __lowerCamelCase      )      )

            SCREAMING_SNAKE_CASE__					=					outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

            SCREAMING_SNAKE_CASE__					=					self.model_tester.num_stages
            self.assertEqual(len(__lowerCamelCase      )			,     expected_num_stages + 1      )

            # Bit's feature maps are of shape (batch_size, num_channels, height, width)
            self.assertListEqual(
                list(hidden_states[0].shape[-2:]      )			,     [self.model_tester.image_size // 4, self.model_tester.image_size // 4]			,     )

       SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs_for_common()
       SCREAMING_SNAKE_CASE__					=					['''preactivation''', '''bottleneck''']
       for model_class in self.all_model_classes:
            for layer_type in layers_type:
                 SCREAMING_SNAKE_CASE__					=					layer_type
                 SCREAMING_SNAKE_CASE__					=					True
                 check_hidden_states_output(__lowerCamelCase			,     __lowerCamelCase			,     __lowerCamelCase      )

                 # check that output_hidden_states also work using config
                 del inputs_dict["output_hidden_states"]
                 SCREAMING_SNAKE_CASE__					=					True

                 check_hidden_states_output(__lowerCamelCase			,     __lowerCamelCase			,     __lowerCamelCase      )






  @unittest.skip(reason='''Bit does not use feedforward chunking'''      )
  def    lowercase_	(							self		:	List[str]      )	->							Dict:
       pass






  def    lowercase_	(							self		:	List[Any]      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_image_classification(*__lowerCamelCase      )







  @slow
  def    lowercase_	(							self		:	Optional[Any]      )	->							Dict:
       for model_name in BIT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
            SCREAMING_SNAKE_CASE__					=					BitModel.from_pretrained(__lowerCamelCase      )
            self.assertIsNotNone(__lowerCamelCase      )



def        UpperCAmelCase_     (		):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''       )
     return image






@require_torch
@require_vision
class  UpperCAmelCase__	( unittest.TestCase ):






  """simple docstring"""


  @cached_property
  def    lowercase_	(							self		:	List[Any]      )	->							List[Any]:
       return (
           BitImageProcessor.from_pretrained(BIT_PRETRAINED_MODEL_ARCHIVE_LIST[0]      ) if is_vision_available() else None
       )







  @slow
  def    lowercase_	(							self		:	str      )	->							List[Any]:
       SCREAMING_SNAKE_CASE__					=					BitForImageClassification.from_pretrained(BIT_PRETRAINED_MODEL_ARCHIVE_LIST[0]      ).to(__lowerCamelCase      )

       SCREAMING_SNAKE_CASE__					=					self.default_image_processor
       SCREAMING_SNAKE_CASE__					=					prepare_img()
       SCREAMING_SNAKE_CASE__					=					image_processor(images=__lowerCamelCase			,     return_tensors='''pt'''      ).to(__lowerCamelCase      )

       # forward pass
       with torch.no_grad():
            SCREAMING_SNAKE_CASE__					=					model(**__lowerCamelCase      )

       # verify the logits
       SCREAMING_SNAKE_CASE__					=					torch.Size((1, 1000)      )
       self.assertEqual(outputs.logits.shape			,     __lowerCamelCase      )

       SCREAMING_SNAKE_CASE__					=					torch.tensor([[-0.6526, -0.5263, -1.4398]]      ).to(__lowerCamelCase      )

       self.assertTrue(torch.allclose(outputs.logits[0, :3]			,     __lowerCamelCase			,     atol=1e-4      )      )






@require_torch
class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      (BitBackbone,) if is_torch_available() else ()
  a     =      BitConfig

  a     =      False






  def    lowercase_	(							self		:	Optional[Any]      )	->							Dict:
       SCREAMING_SNAKE_CASE__					=					BitModelTester(self      )


