




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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       DownBlockaD  # noqa F405
 lowercase_							       =       "down"



 def  lowerCAmelCase_    (				self    :						Tuple		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       ResnetDownsampleBlockaD  # noqa F405
 lowercase_							       =       "down"



 def  lowerCAmelCase_    (				self    :						List[Any]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnDownBlockaD  # noqa F405
 lowercase_							       =       "down"



 def  lowerCAmelCase_    (				self    :						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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       CrossAttnDownBlockaD  # noqa F405
 lowercase_							       =       "down"



 def  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     super().prepare_init_args_and_inputs_for_common()
       SCREAMING_SNAKE_CASE_      		=     32
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						Dict		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       SimpleCrossAttnDownBlockaD  # noqa F405
 lowercase_							       =       "down"



 @property
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       return super().get_dummy_input(include_encoder_hidden_states=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Any		):
       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  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       SkipDownBlockaD  # noqa F405
 lowercase_							       =       "down"



 @property
 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       return super().get_dummy_input(include_skip_sample=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Dict		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnSkipDownBlockaD  # noqa F405
 lowercase_							       =       "down"



 @property
 def  lowerCAmelCase_    (				self    :						int		):
       return super().get_dummy_input(include_skip_sample=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Any		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       DownEncoderBlockaD  # noqa F405
 lowercase_							       =       "down"



 @property
 def  lowerCAmelCase_    (				self    :						List[str]		):
       return super().get_dummy_input(include_temb=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       SCREAMING_SNAKE_CASE_      		=     {
           'in_channels': 32,
           'out_channels': 32,
       }
       SCREAMING_SNAKE_CASE_      		=     self.dummy_input
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnDownEncoderBlockaD  # noqa F405
 lowercase_							       =       "down"



 @property
 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       return super().get_dummy_input(include_temb=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_      		=     {
           'in_channels': 32,
           'out_channels': 32,
       }
       SCREAMING_SNAKE_CASE_      		=     self.dummy_input
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						Dict		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       UNetMidBlockaD  # noqa F405
 lowercase_							       =       "mid"



 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     {
           'in_channels': 32,
           'temb_channels': 128,
       }
       SCREAMING_SNAKE_CASE_      		=     self.dummy_input
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						Any		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       UNetMidBlockaDCrossAttn  # noqa F405
 lowercase_							       =       "mid"



 def  lowerCAmelCase_    (				self    :						Optional[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  lowerCAmelCase_    (				self    :						List[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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       UNetMidBlockaDSimpleCrossAttn  # noqa F405
 lowercase_							       =       "mid"



 @property
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       return super().get_dummy_input(include_encoder_hidden_states=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						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  lowerCAmelCase_    (				self    :						Optional[int]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       UpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						List[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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       ResnetUpsampleBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Optional[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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       CrossAttnUpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						int		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						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




 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       SimpleCrossAttnUpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Tuple		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase							,							include_encoder_hidden_states=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						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  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnUpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)




 @unittest.skipIf(torch_device == 'mps'							,							'MPS result is not consistent'		)
 def  lowerCAmelCase_    (				self    :						Any		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       SkipUpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Tuple		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnSkipUpBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Dict		):
       return super().get_dummy_input(include_res_hidden_states_tuple=_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Dict		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       UpDecoderBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						List[str]		):
       return super().get_dummy_input(include_temb=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     {'in_channels': 32, 'out_channels': 32}

       SCREAMING_SNAKE_CASE_      		=     self.dummy_input
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       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 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       AttnUpDecoderBlockaD  # noqa F405
 lowercase_							       =       "up"



 @property
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       return super().get_dummy_input(include_temb=_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Dict		):
       SCREAMING_SNAKE_CASE_      		=     {'in_channels': 32, 'out_channels': 32}

       SCREAMING_SNAKE_CASE_      		=     self.dummy_input
       return init_dict, inputs_dict




 def  lowerCAmelCase_    (				self    :						int		):
       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 numpy as np
import torch
from torch.utils.data import DataLoader

from accelerate.utils.dataclasses import DistributedType





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						Any							,							_lowerCAmelCase    :						Optional[int]=2							,							_lowerCAmelCase    :						Any=3							,							_lowerCAmelCase    :						Tuple=64							,							_lowerCAmelCase    :						List[str]=None		):
       SCREAMING_SNAKE_CASE_      		=     np.random.default_rng(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     length
       SCREAMING_SNAKE_CASE_      		=     rng.normal(size=(length,)		).astype(np.floataa		)
       SCREAMING_SNAKE_CASE_      		=     a * self.x + b + rng.normal(scale=0.1							,							size=(length,)		).astype(np.floataa		)



 def __len__(				self    :						Optional[int]		):
       return self.length




 def __getitem__(				self    :						str							,							_lowerCAmelCase    :						Union[str, Any]		):
       return {"x": self.x[i], "y": self.y[i]}





class 			lowerCamelCase_				( torch.nn.Module   ):


 '''simple docstring'''







 def __init__(				self    :						Tuple							,							_lowerCAmelCase    :						Dict=0							,							_lowerCAmelCase    :						List[str]=0							,							_lowerCAmelCase    :						str=False		):
       super().__init__()
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor([2, 3]		).float()		)
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor([2, 3]		).float()		)
       SCREAMING_SNAKE_CASE_      		=     True




 def  lowerCAmelCase_    (				self    :						Dict							,							_lowerCAmelCase    :						Union[str, Any]=None		):
       if self.first_batch:
             print(F"Model dtype: {self.a.dtype}, {self.b.dtype}. Input dtype: {x.dtype}"		)
             SCREAMING_SNAKE_CASE_      		=     False
       return x * self.a[0] + self.b[0]





class 			lowerCamelCase_				( torch.nn.Module   ):


 '''simple docstring'''







 def __init__(				self    :						Optional[int]							,							_lowerCAmelCase    :						Any=0							,							_lowerCAmelCase    :						Any=0							,							_lowerCAmelCase    :						Optional[Any]=False		):
       super().__init__()
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor(_lowerCAmelCase		).float()		)
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor(_lowerCAmelCase		).float()		)
       SCREAMING_SNAKE_CASE_      		=     True




 def  lowerCAmelCase_    (				self    :						Optional[Any]							,							_lowerCAmelCase    :						Optional[int]=None		):
       if self.first_batch:
             print(F"Model dtype: {self.a.dtype}, {self.b.dtype}. Input dtype: {x.dtype}"		)
             SCREAMING_SNAKE_CASE_      		=     False
       return x * self.a + self.b


def    UpperCAmelCase_				( __UpperCAmelCase		:      Dict     ,     __UpperCAmelCase		:      int = 16				)   ->					Union[str, Any]:
      from datasets import load_dataset
      from transformers import AutoTokenizer

      SCREAMING_SNAKE_CASE_      		=     AutoTokenizer.from_pretrained('bert-base-cased'				)
      SCREAMING_SNAKE_CASE_      		=     {'train': 'tests/test_samples/MRPC/train.csv', 'validation': 'tests/test_samples/MRPC/dev.csv'}
      SCREAMING_SNAKE_CASE_      		=     load_dataset('csv'     ,     data_files=__UpperCAmelCase				)
      SCREAMING_SNAKE_CASE_      		=     datasets['train'].unique('label'				)

      SCREAMING_SNAKE_CASE_      		=     {v: i for i, v in enumerate(__UpperCAmelCase				)}

      def tokenize_function(__UpperCAmelCase		:      Optional[int]				):
            # max_length=None => use the model max length (it's actually the default)
            SCREAMING_SNAKE_CASE_      		=     tokenizer(
                examples['sentence1']     ,     examples['sentence2']     ,     truncation=__UpperCAmelCase     ,     max_length=__UpperCAmelCase     ,     padding='max_length'				)
            if "label" in examples:
                  SCREAMING_SNAKE_CASE_      		=     [label_to_id[l] for l in examples['label']]
            return outputs

      # Apply the method we just defined to all the examples in all the splits of the dataset
      SCREAMING_SNAKE_CASE_      		=     datasets.map(
          __UpperCAmelCase     ,     batched=__UpperCAmelCase     ,     remove_columns=['sentence1', 'sentence2', 'label']     ,     )

      def collate_fn(__UpperCAmelCase		:      Dict				):
            # On TPU it's best to pad everything to the same length or training will be very slow.
            if accelerator.distributed_type == DistributedType.TPU:
                  return tokenizer.pad(__UpperCAmelCase     ,     padding='max_length'     ,     max_length=1_28     ,     return_tensors='pt'				)
            return tokenizer.pad(__UpperCAmelCase     ,     padding='longest'     ,     return_tensors='pt'				)

      # Instantiate dataloaders.
      SCREAMING_SNAKE_CASE_      		=     DataLoader(tokenized_datasets['train']     ,     shuffle=__UpperCAmelCase     ,     collate_fn=__UpperCAmelCase     ,     batch_size=2				)
      SCREAMING_SNAKE_CASE_      		=     DataLoader(tokenized_datasets['validation']     ,     shuffle=__UpperCAmelCase     ,     collate_fn=__UpperCAmelCase     ,     batch_size=1				)

      return train_dataloader, eval_dataloader