

import unittest

from diffusers import __version__
from diffusers.utils import deprecate


class   lowerCAmelCase     (      unittest.TestCase   ):
       lowerCAmelCase_		= ".".join([str(int(__version__.split("."   )[0]   ) + 1   )] + __version__.split("."   )[1:]   )
       lowerCAmelCase_		= "0.0.1"







       def 			snake_case   (							self			: List[str]      ):







            """simple docstring"""







            __lowercase					={'deprecated_arg': 4}

            with self.assertWarns(__lowercase      ) as warning:
                 __lowercase					=deprecate('deprecated_arg'						,      self.higher_version						,      'message'						,      take_from=__lowercase      )

            assert output == 4
            assert (
                str(warning.warning      )
                == f'''The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'''
                " message"
            )







       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            __lowercase					={'deprecated_arg': 4}

            with self.assertWarns(__lowercase      ) as warning:
                 __lowercase					=deprecate(('deprecated_arg', self.higher_version, 'message')						,      take_from=__lowercase      )

            assert output == 4
            assert (
                str(warning.warning      )
                == f'''The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'''
                " message"
            )







       def 			snake_case   (							self			: Dict      ):







            """simple docstring"""







            __lowercase					={'deprecated_arg_1': 4, 'deprecated_arg_2': 8}
            with self.assertWarns(__lowercase      ) as warning:
                 __lowercase		,     __lowercase					=deprecate(
                     ('deprecated_arg_1', self.higher_version, 'Hey')						,      ('deprecated_arg_2', self.higher_version, 'Hey')						,      take_from=__lowercase						,      )
            assert output_a == 4
            assert output_a == 8
            assert (
                str(warning.warnings[0].message      )
                == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
                f''' {self.higher_version}. Hey'''
            )
            assert (
                str(warning.warnings[1].message      )
                == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
                f''' {self.higher_version}. Hey'''
            )







       def 			snake_case   (							self			: int      ):







            """simple docstring"""







            __lowercase					={'deprecated_arg': 4}

            with self.assertRaises(__lowercase      ) as error:
                 deprecate(('wrong_arg', self.higher_version, 'message')						,      take_from=__lowercase      )

            assert "test_deprecate_function_incorrect_arg in" in str(error.exception      )
            assert "line" in str(error.exception      )
            assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception      )







       def 			snake_case   (							self			: Dict      ):







            """simple docstring"""







            with self.assertWarns(__lowercase      ) as warning:
                 deprecate(('deprecated_arg', self.higher_version, 'message')      )

            assert (
                str(warning.warning      )
                == f'''`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message'''
            )







       def 			snake_case   (							self			: Tuple      ):







            """simple docstring"""







            with self.assertWarns(__lowercase      ) as warning:
                 deprecate(
                     ('deprecated_arg_1', self.higher_version, 'Hey')						,      ('deprecated_arg_2', self.higher_version, 'Hey')						,      )
            assert (
                str(warning.warnings[0].message      )
                == f'''`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey'''
            )
            assert (
                str(warning.warnings[1].message      )
                == f'''`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey'''
            )







       def 			snake_case   (							self			: int      ):







            """simple docstring"""







            class   lowerCAmelCase     :
                   lowerCAmelCase_		= 5

            with self.assertWarns(__lowercase      ) as warning:
                 __lowercase					=deprecate(('arg', self.higher_version, 'message')						,      take_from=Args()      )

            assert arg == 5
            assert (
                str(warning.warning      )
                == f'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
            )







       def 			snake_case   (							self			: Any      ):







            """simple docstring"""







            class   lowerCAmelCase     :
                   lowerCAmelCase_		= 5
                   lowerCAmelCase_		= 7

            with self.assertWarns(__lowercase      ) as warning:
                 __lowercase		,     __lowercase					=deprecate(
                     ('arg', self.higher_version, 'message')						,      ('foo', self.higher_version, 'message')						,      ('does not exist', self.higher_version, 'message')						,      take_from=Args()						,      )

            assert arg_a == 5
            assert arg_a == 7
            assert (
                str(warning.warning      )
                == f'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
            )
            assert (
                str(warning.warnings[0].message      )
                == f'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
            )
            assert (
                str(warning.warnings[1].message      )
                == f'''The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message'''
            )







       def 			snake_case   (							self			: List[Any]      ):







            """simple docstring"""







            __lowercase					={'deprecated_arg': 4}

            with self.assertRaises(__lowercase      ) as error:
                 deprecate(('wrong_arg', self.lower_version, 'message')						,      take_from=__lowercase      )

            assert (
                str(error.exception      )
                == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
                f''' {__version__} is >= {self.lower_version}'''
            )







       def 			snake_case   (							self			: int      ):







            """simple docstring"""







            with self.assertWarns(__lowercase      ) as warning:
                 deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')						,      standard_warn=__lowercase      )

            assert str(warning.warning      ) == "This message is better!!!"







       def 			snake_case   (							self			: str      ):







            """simple docstring"""







            with self.assertWarns(__lowercase      ) as warning:
                 deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')						,      standard_warn=__lowercase      )
            assert str(warning.warning      ) == "This message is better!!!"
            assert "diffusers/tests/others/test_utils.py" in warning.filename





'''simple docstring'''

import collections
import inspect
import unittest

from transformers import SwinConfig
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, _config_zero_init, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
       import torch
       from torch import nn

       from transformers import SwinBackbone, SwinForImageClassification, SwinForMaskedImageModeling, SwinModel
       from transformers.models.swin.modeling_swin import SWIN_PRETRAINED_MODEL_ARCHIVE_LIST


if is_vision_available():
       from PIL import Image

       from transformers import AutoImageProcessor


class   lowerCAmelCase     :







       def __init__(							self			: List[str]						,      __lowercase			: Optional[int]						,      __lowercase			: Optional[int]=13						,      __lowercase			: Dict=32						,      __lowercase			: int=2						,      __lowercase			: Tuple=3						,      __lowercase			: Optional[int]=16						,      __lowercase			: Dict=[1, 2, 1]						,      __lowercase			: Dict=[2, 2, 4]						,      __lowercase			: int=2						,      __lowercase			: Optional[Any]=2.0						,      __lowercase			: int=True						,      __lowercase			: List[Any]=0.0						,      __lowercase			: int=0.0						,      __lowercase			: Optional[Any]=0.1						,      __lowercase			: List[str]="gelu"						,      __lowercase			: Any=False						,      __lowercase			: Dict=True						,      __lowercase			: Optional[Any]=0.0_2						,      __lowercase			: int=1E-5						,      __lowercase			: Dict=True						,      __lowercase			: Optional[int]=None						,      __lowercase			: List[Any]=True						,      __lowercase			: List[Any]=10						,      __lowercase			: Any=8						,      __lowercase			: Optional[int]=["stage1", "stage2"]						,      __lowercase			: str=[1, 2]						,      ):







            """simple docstring"""







            __lowercase					=parent
            __lowercase					=batch_size
            __lowercase					=image_size
            __lowercase					=patch_size
            __lowercase					=num_channels
            __lowercase					=embed_dim
            __lowercase					=depths
            __lowercase					=num_heads
            __lowercase					=window_size
            __lowercase					=mlp_ratio
            __lowercase					=qkv_bias
            __lowercase					=hidden_dropout_prob
            __lowercase					=attention_probs_dropout_prob
            __lowercase					=drop_path_rate
            __lowercase					=hidden_act
            __lowercase					=use_absolute_embeddings
            __lowercase					=patch_norm
            __lowercase					=layer_norm_eps
            __lowercase					=initializer_range
            __lowercase					=is_training
            __lowercase					=scope
            __lowercase					=use_labels
            __lowercase					=type_sequence_label_size
            __lowercase					=encoder_stride
            __lowercase					=out_features
            __lowercase					=out_indices







       def 			snake_case   (							self			: Tuple      ):







            """simple docstring"""







            __lowercase					=floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]      )

            __lowercase					=None
            if self.use_labels:
                 __lowercase					=ids_tensor([self.batch_size]						,      self.type_sequence_label_size      )

            __lowercase					=self.get_config()

            return config, pixel_values, labels







       def 			snake_case   (							self			: Dict      ):







            """simple docstring"""







            return SwinConfig(
                image_size=self.image_size						,      patch_size=self.patch_size						,      num_channels=self.num_channels						,      embed_dim=self.embed_dim						,      depths=self.depths						,      num_heads=self.num_heads						,      window_size=self.window_size						,      mlp_ratio=self.mlp_ratio						,      qkv_bias=self.qkv_bias						,      hidden_dropout_prob=self.hidden_dropout_prob						,      attention_probs_dropout_prob=self.attention_probs_dropout_prob						,      drop_path_rate=self.drop_path_rate						,      hidden_act=self.hidden_act						,      use_absolute_embeddings=self.use_absolute_embeddings						,      path_norm=self.patch_norm						,      layer_norm_eps=self.layer_norm_eps						,      initializer_range=self.initializer_range						,      encoder_stride=self.encoder_stride						,      out_features=self.out_features						,      out_indices=self.out_indices						,      )







       def 			snake_case   (							self			: Optional[Any]						,      __lowercase			: str						,      __lowercase			: Tuple						,      __lowercase			: int      ):







            """simple docstring"""







            __lowercase					=SwinModel(config=__lowercase      )
            model.to(__lowercase      )
            model.eval()
            __lowercase					=model(__lowercase      )

            __lowercase					=((config.image_size // config.patch_size) ** 2) // (4 ** (len(config.depths      ) - 1))
            __lowercase					=int(config.embed_dim * 2 ** (len(config.depths      ) - 1)      )

            self.parent.assertEqual(result.last_hidden_state.shape						,      (self.batch_size, expected_seq_len, expected_dim)      )







       def 			snake_case   (							self			: str						,      __lowercase			: str						,      __lowercase			: Dict						,      __lowercase			: List[Any]      ):







            """simple docstring"""







            __lowercase					=SwinBackbone(config=__lowercase      )
            model.to(__lowercase      )
            model.eval()
            __lowercase					=model(__lowercase      )

            # verify hidden states
            self.parent.assertEqual(len(result.feature_maps      )						,      len(config.out_features      )      )
            self.parent.assertListEqual(list(result.feature_maps[0].shape      )						,      [self.batch_size, model.channels[0], 16, 16]      )

            # verify channels
            self.parent.assertEqual(len(model.channels      )						,      len(config.out_features      )      )

            # verify backbone works with out_features=None
            __lowercase					=None
            __lowercase					=SwinBackbone(config=__lowercase      )
            model.to(__lowercase      )
            model.eval()
            __lowercase					=model(__lowercase      )

            # verify feature maps
            self.parent.assertEqual(len(result.feature_maps      )						,      1      )
            self.parent.assertListEqual(list(result.feature_maps[0].shape      )						,      [self.batch_size, model.channels[-1], 4, 4]      )

            # verify channels
            self.parent.assertEqual(len(model.channels      )						,      1      )







       def 			snake_case   (							self			: int						,      __lowercase			: int						,      __lowercase			: List[str]						,      __lowercase			: Dict      ):







            """simple docstring"""







            __lowercase					=SwinForMaskedImageModeling(config=__lowercase      )
            model.to(__lowercase      )
            model.eval()
            __lowercase					=model(__lowercase      )
            self.parent.assertEqual(
                result.logits.shape						,      (self.batch_size, self.num_channels, self.image_size, self.image_size)      )

            # test greyscale images
            __lowercase					=1
            __lowercase					=SwinForMaskedImageModeling(__lowercase      )
            model.to(__lowercase      )
            model.eval()

            __lowercase					=floats_tensor([self.batch_size, 1, self.image_size, self.image_size]      )
            __lowercase					=model(__lowercase      )
            self.parent.assertEqual(result.logits.shape						,      (self.batch_size, 1, self.image_size, self.image_size)      )







       def 			snake_case   (							self			: Any						,      __lowercase			: Optional[Any]						,      __lowercase			: List[str]						,      __lowercase			: Dict      ):







            """simple docstring"""







            __lowercase					=self.type_sequence_label_size
            __lowercase					=SwinForImageClassification(__lowercase      )
            model.to(__lowercase      )
            model.eval()
            __lowercase					=model(__lowercase						,      labels=__lowercase      )
            self.parent.assertEqual(result.logits.shape						,      (self.batch_size, self.type_sequence_label_size)      )

            # test greyscale images
            __lowercase					=1
            __lowercase					=SwinForImageClassification(__lowercase      )
            model.to(__lowercase      )
            model.eval()

            __lowercase					=floats_tensor([self.batch_size, 1, self.image_size, self.image_size]      )
            __lowercase					=model(__lowercase      )
            self.parent.assertEqual(result.logits.shape						,      (self.batch_size, self.type_sequence_label_size)      )







       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            __lowercase					=self.prepare_config_and_inputs()
            (
                (
                __lowercase
            )		,     (
                __lowercase
            )		,     (
                __lowercase
            )		,     
            )					=config_and_inputs
            __lowercase					={'pixel_values': pixel_values}
            return config, inputs_dict






@require_torch
class   lowerCAmelCase     (      A   ,			A   ,			unittest.TestCase   ):
       lowerCAmelCase_		= (
           (
               SwinModel,
               SwinBackbone,
               SwinForImageClassification,
               SwinForMaskedImageModeling,
           )
           if is_torch_available()
           else ()
       )
       lowerCAmelCase_		= (
           {"feature-extraction": SwinModel, "image-classification": SwinForImageClassification}
           if is_torch_available()
           else {}
       )
       lowerCAmelCase_		= True

       lowerCAmelCase_		= False
       lowerCAmelCase_		= False
       lowerCAmelCase_		= False







       def 			snake_case   (							self			: List[str]      ):







            """simple docstring"""







            __lowercase					=SwinModelTester(self      )
            __lowercase					=ConfigTester(self						,      config_class=__lowercase						,      embed_dim=37      )







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







            """simple docstring"""







            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 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            return







       def 			snake_case   (							self			: List[Any]      ):







            """simple docstring"""







            __lowercase					=self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_model(*__lowercase      )







       @unittest.skip(reason='Got `CUDA error: misaligned address` with PyTorch 2.0.0.'      )
       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            pass







       def 			snake_case   (							self			: Optional[int]      ):







            """simple docstring"""







            super().test_training_gradient_checkpointing()







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







            """simple docstring"""







            __lowercase					=self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_backbone(*__lowercase      )







       def 			snake_case   (							self			: List[str]      ):







            """simple docstring"""







            __lowercase					=self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_for_masked_image_modeling(*__lowercase      )







       def 			snake_case   (							self			: Dict      ):







            """simple docstring"""







            __lowercase					=self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_for_image_classification(*__lowercase      )







       @unittest.skip(reason='Swin does not use inputs_embeds'      )
       def 			snake_case   (							self			: List[Any]      ):







            """simple docstring"""







            pass







       @unittest.skip(reason='Swin Transformer does not use feedforward chunking'      )
       def 			snake_case   (							self			: int      ):







            """simple docstring"""







            pass







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







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()

            for model_class in self.all_model_classes:
                 __lowercase					=model_class(__lowercase      )
                 self.assertIsInstance(model.get_input_embeddings()						,      (nn.Module)      )
                 __lowercase					=model.get_output_embeddings()
                 self.assertTrue(x is None or isinstance(__lowercase						,      nn.Linear      )      )







       def 			snake_case   (							self			: Tuple      ):







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()

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

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







       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()
            __lowercase					=True

            for model_class in self.all_model_classes:
                 __lowercase					=True
                 __lowercase					=False
                 __lowercase					=True
                 __lowercase					=model_class(__lowercase      )
                 model.to(__lowercase      )
                 model.eval()
                 with torch.no_grad():
                      __lowercase					=model(**self._prepare_for_class(__lowercase						,      __lowercase      )      )
                 __lowercase					=outputs.attentions
                 __lowercase					=len(self.model_tester.depths      )
                 self.assertEqual(len(__lowercase      )						,      __lowercase      )

                 # check that output_attentions also work using config
                 del inputs_dict["output_attentions"]
                 __lowercase					=True
                 __lowercase					=config.window_size**2
                 __lowercase					=model_class(__lowercase      )
                 model.to(__lowercase      )
                 model.eval()
                 with torch.no_grad():
                      __lowercase					=model(**self._prepare_for_class(__lowercase						,      __lowercase      )      )
                 __lowercase					=outputs.attentions
                 self.assertEqual(len(__lowercase      )						,      __lowercase      )

                 self.assertListEqual(
                     list(attentions[0].shape[-3:]      )						,      [self.model_tester.num_heads[0], window_size_squared, window_size_squared]						,      )
                 __lowercase					=len(__lowercase      )

                 # Check attention is always last and order is fine
                 __lowercase					=True
                 __lowercase					=True
                 __lowercase					=model_class(__lowercase      )
                 model.to(__lowercase      )
                 model.eval()
                 with torch.no_grad():
                      __lowercase					=model(**self._prepare_for_class(__lowercase						,      __lowercase      )      )

                 # also another +1 for reshaped_hidden_states
                 __lowercase					=1 if model_class.__name__ == 'SwinBackbone' else 2
                 self.assertEqual(out_len + added_hidden_states						,      len(__lowercase      )      )

                 __lowercase					=outputs.attentions

                 self.assertEqual(len(__lowercase      )						,      __lowercase      )

                 self.assertListEqual(
                     list(self_attentions[0].shape[-3:]      )						,      [self.model_tester.num_heads[0], window_size_squared, window_size_squared]						,      )







       def 			snake_case   (							self			: List[str]						,      __lowercase			: Dict						,      __lowercase			: List[str]						,      __lowercase			: List[str]						,      __lowercase			: Any      ):







            """simple docstring"""







            __lowercase					=model_class(__lowercase      )
            model.to(__lowercase      )
            model.eval()

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

            __lowercase					=outputs.hidden_states

            __lowercase					=getattr(
                self.model_tester						,      'expected_num_hidden_layers'						,      len(self.model_tester.depths      ) + 1      )
            self.assertEqual(len(__lowercase      )						,      __lowercase      )

            # Swin has a different seq_length
            __lowercase					=(
                config.patch_size
                if isinstance(config.patch_size						,      collections.abc.Iterable      )
                else (config.patch_size, config.patch_size)
            )

            __lowercase					=(image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])

            self.assertListEqual(
                list(hidden_states[0].shape[-2:]      )						,      [num_patches, self.model_tester.embed_dim]						,      )

            if not model_class.__name__ == "SwinBackbone":
                 __lowercase					=outputs.reshaped_hidden_states
                 self.assertEqual(len(__lowercase      )						,      __lowercase      )

                 __lowercase		,     __lowercase		,     __lowercase		,     __lowercase					=reshaped_hidden_states[0].shape
                 __lowercase					=(
                     reshaped_hidden_states[0].view(__lowercase						,      __lowercase						,      height * width      ).permute(0						,      2						,      1      )
                 )
                 self.assertListEqual(
                     list(reshaped_hidden_states.shape[-2:]      )						,      [num_patches, self.model_tester.embed_dim]						,      )







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







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()

            __lowercase					=(
                self.model_tester.image_size
                if isinstance(self.model_tester.image_size						,      collections.abc.Iterable      )
                else (self.model_tester.image_size, self.model_tester.image_size)
            )

            for model_class in self.all_model_classes:
                 __lowercase					=True
                 self.check_hidden_states_output(__lowercase						,      __lowercase						,      __lowercase						,      __lowercase      )

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

                 self.check_hidden_states_output(__lowercase						,      __lowercase						,      __lowercase						,      __lowercase      )







       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()
            __lowercase					=3

            __lowercase					=(
                self.model_tester.image_size
                if isinstance(self.model_tester.image_size						,      collections.abc.Iterable      )
                else (self.model_tester.image_size, self.model_tester.image_size)
            )
            __lowercase					=(
                config.patch_size
                if isinstance(config.patch_size						,      collections.abc.Iterable      )
                else (config.patch_size, config.patch_size)
            )

            __lowercase					=image_size[0] + patch_size[0] - (image_size[0] % patch_size[0])
            __lowercase					=image_size[1] + patch_size[1] - (image_size[1] % patch_size[1])

            for model_class in self.all_model_classes:
                 __lowercase					=True
                 self.check_hidden_states_output(__lowercase						,      __lowercase						,      __lowercase						,      (padded_height, padded_width)      )

                 # check that output_hidden_states also work using config
                 del inputs_dict["output_hidden_states"]
                 __lowercase					=True
                 self.check_hidden_states_output(__lowercase						,      __lowercase						,      __lowercase						,      (padded_height, padded_width)      )







       @slow
       def 			snake_case   (							self			: Optional[Any]      ):







            """simple docstring"""







            for model_name in SWIN_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                 __lowercase					=SwinModel.from_pretrained(__lowercase      )
                 self.assertIsNotNone(__lowercase      )







       def 			snake_case   (							self			: List[Any]      ):







            """simple docstring"""







            __lowercase		,     __lowercase					=self.model_tester.prepare_config_and_inputs_for_common()

            __lowercase					=_config_zero_init(__lowercase      )
            for model_class in self.all_model_classes:
                 __lowercase					=model_class(config=__lowercase      )
                 for name, param in model.named_parameters():
                      if "embeddings" not in name and param.requires_grad:
                           self.assertIn(
                               ((param.data.mean() * 1E9).round() / 1E9).item()						,      [0.0, 1.0]						,      msg=f'''Parameter {name} of model {model_class} seems not properly initialized'''						,      )






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







       @cached_property
       def 			snake_case   (							self			: str      ):







            """simple docstring"""







            return (
                AutoImageProcessor.from_pretrained('microsoft/swin-tiny-patch4-window7-224'      )
                if is_vision_available()
                else None
            )







       @slow
       def 			snake_case   (							self			: Dict      ):







            """simple docstring"""







            __lowercase					=SwinForImageClassification.from_pretrained('microsoft/swin-tiny-patch4-window7-224'      ).to(__lowercase      )
            __lowercase					=self.default_image_processor

            __lowercase					=Image.open('./tests/fixtures/tests_samples/COCO/000000039769.png'      )
            __lowercase					=image_processor(images=__lowercase						,      return_tensors='pt'      ).to(__lowercase      )

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

            # verify the logits
            __lowercase					=torch.Size((1, 1000)      )
            self.assertEqual(outputs.logits.shape						,      __lowercase      )
            __lowercase					=torch.tensor([-0.0_9_4_8, -0.6_4_5_4, -0.0_9_2_1]      ).to(__lowercase      )
            self.assertTrue(torch.allclose(outputs.logits[0, :3]						,      __lowercase						,      atol=1E-4      )      )






@require_torch
class   lowerCAmelCase     (      unittest.TestCase   ,			A   ):
       lowerCAmelCase_		= (SwinBackbone,) if is_torch_available() else ()
       lowerCAmelCase_		= SwinConfig







       def 			snake_case   (							self			: List[Any]      ):







            """simple docstring"""







            __lowercase					=SwinModelTester(self      )


