






import random
import unittest

import torch

from diffusers import IFSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin


@skip_mps
class 				snake_case__     (			__UpperCAmelCase      ,							__UpperCAmelCase      ,							unittest.TestCase):
					a_       =			IFSuperResolutionPipeline
					a_       =			TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"""width""", """height"""}
					a_       =			TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
					a_       =			PipelineTesterMixin.required_optional_params - {"""latents"""}




					def 						A     (       self       :						Tuple     )  ->    Any:
								return self._get_superresolution_dummy_components()




					def 						A     (       self       :						Any							,				_A       :						Union[str, Any]							,				_A       :						List[Any]=0     )  ->    List[str]:



								if str(lowerCamelCase__     ).startswith('''mps'''     ):
											UpperCAmelCase_     :   int       =   torch.manual_seed(lowerCamelCase__     )
								else:
											UpperCAmelCase_     :   List[Any]       =   torch.Generator(device=lowerCamelCase__     ).manual_seed(lowerCamelCase__     )

								UpperCAmelCase_     :   str       =   floats_tensor((1, 3, 32, 32)							,				rng=random.Random(lowerCamelCase__     )     ).to(lowerCamelCase__     )

								UpperCAmelCase_     :   Union[str, Any]       =   {
								    '''prompt''': '''A painting of a squirrel eating a burger''',
								    '''image''': image,
								    '''generator''': generator,
								    '''num_inference_steps''': 2,
								    '''output_type''': '''numpy''',
								}

								return inputs




					@unittest.skipIf(
					    torch_device != '''cuda''' or not is_xformers_available()							,				reason='''XFormers attention is only available with CUDA and `xformers` installed'''							,				)
					def 						A     (       self       :						List[Any]     )  ->    Tuple:
								self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3     )




					def 						A     (       self       :						str     )  ->    List[Any]:
								self._test_save_load_optional_components()




					@unittest.skipIf(torch_device != '''cuda'''							,				reason='''float16 requires CUDA'''     )
					def 						A     (       self       :						Any     )  ->    List[Any]:
								super().test_save_load_floataa(expected_max_diff=1e-1     )




					def 						A     (       self       :						Any     )  ->    Union[str, Any]:
								self._test_attention_slicing_forward_pass(expected_max_diff=1e-2     )




					def 						A     (       self       :						Union[str, Any]     )  ->    Dict:
								self._test_save_load_local()





					def 						A     (       self       :						Any     )  ->    List[str]:
								self._test_inference_batch_single_identical(
								    expected_max_diff=1e-2							,				)










'''simple docstring'''





def __UpperCAmelCase (			A			:	list[list[int]]						)  -> bool:
			# must be
			UpperCAmelCase_     :   int       =   [list(A						) for row in matrix]
			if matrix and isinstance(A	,   A						):
						if isinstance(matrix[0]	,   A						):
									UpperCAmelCase_     :   Optional[Any]       =   0
									for row in matrix:
												if prev_len == 0:
															UpperCAmelCase_     :   List[str]       =   len(A						)
															UpperCAmelCase_     :   Any       =   True
												else:
															UpperCAmelCase_     :   Tuple       =   prev_len == len(A						)
						else:
									UpperCAmelCase_     :   Any       =   True
			else:
						UpperCAmelCase_     :   Dict       =   False

			return result
def __UpperCAmelCase (			A			:	list[list[int]]						)  -> None:
			if check_matrix(A						) and len(A						) > 0:
						UpperCAmelCase_     :   Dict       =   [list(A						) for row in a]
						UpperCAmelCase_     :   List[Any]       =   len(A						)
						if isinstance(a[0]	,   A						):
									UpperCAmelCase_     :   Any       =   len(a[0]						)
						else:
									for dat in a:
												print(A						)
									return

						# horizotal printing increasing
						for i in range(0	,   A						):
									print(a[0][i]						)
						# vertical printing down
						for i in range(1	,   A						):
									print(a[i][mat_col - 1]						)
						# horizotal printing decreasing
						if mat_row > 1:
									for i in range(mat_col - 2	,   -1	,   -1						):
												print(a[mat_row - 1][i]						)
        # vertical printing up
						for i in range(mat_row - 2	,   0	,   -1						):
									print(a[i][0]						)
						UpperCAmelCase_     :   Union[str, Any]       =   [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
						if len(A						) > 0:
									spiral_print_clockwise(A						)
						else:
									return
			else:
						print('''Not a valid matrix'''						)
						return
def __UpperCAmelCase (			A			:	list[list]						)  -> list[int]:
			if matrix:
						return list(matrix.pop(0						)						) + spiral_traversal(list(zip(*A						)						)[::-1]						)
			else:
						return []


# driver code
if __name__ == "__main__":
						import doctest

						doctest.testmod()

						_UpperCamelCase		:		List[Any]								=			[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
						spiral_print_clockwise(a)


