def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							_lowercase				=	[list(_A					) for row in matrix]
							if matrix and isinstance(_A ,_A					):
														if isinstance(matrix[0] ,_A					):
																					_lowercase				=	0
																					for row in matrix:
																												if prev_len == 0:
																																			_lowercase				=	len(_A					)
																																			_lowercase				=	True
																												else:
																																			_lowercase				=	prev_len == len(_A					)
														else:
																					_lowercase				=	True
							else:
														_lowercase				=	False

							return result


def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							if check_matrix(_A					) and len(_A					) > 0:
														_lowercase				=	[list(_A					) for row in a]
														_lowercase				=	len(_A					)
														if isinstance(a[0] ,_A					):
																					_lowercase				=	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]					)
														_lowercase				=	[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 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							if matrix:
														return list(matrix.pop(0					)					) + spiral_traversal(list(zip(*_A					)					)[::-1]					)
							else:
														return []


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

				doctest.testmod()

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



import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast


@require_vision
class _lowercase					(       unittest.TestCase						):





							"""simple docstring"""




							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	tempfile.mkdtemp()

														_lowercase				=	CLIPImageProcessor()
														_lowercase				=	BertTokenizer.from_pretrained(
														    """hf-internal-testing/tiny-random-BertModel"""     ,   model_input_names=["""input_ids""", """attention_mask"""]  )

														_lowercase				=	GitProcessor(UpperCAmelCase     ,   UpperCAmelCase  )

														processor.save_pretrained(self.tmpdirname  )



							def     _UpperCAmelCase       (    self     ,   **UpperCAmelCase  ):







														'''simple docstring'''






														return AutoProcessor.from_pretrained(self.tmpdirname     ,   **UpperCAmelCase  ).tokenizer



							def     _UpperCAmelCase       (    self     ,   **UpperCAmelCase  ):







														'''simple docstring'''






														return AutoProcessor.from_pretrained(self.tmpdirname     ,   **UpperCAmelCase  ).image_processor



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														shutil.rmtree(self.tmpdirname  )



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	[np.random.randint(255     ,   size=(3, 30, 400)     ,   dtype=np.uinta  )]

														_lowercase				=	[Image.fromarray(np.moveaxis(UpperCAmelCase     ,   0     ,   -1  )  ) for x in image_inputs]

														return image_inputs



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	GitProcessor(tokenizer=self.get_tokenizer()     ,   image_processor=self.get_image_processor()  )
														processor.save_pretrained(self.tmpdirname  )

														_lowercase				=	self.get_tokenizer(bos_token="""(BOS)"""     ,   eos_token="""(EOS)"""  )
														_lowercase				=	self.get_image_processor(do_normalize=UpperCAmelCase     ,   padding_value=1.0  )

														_lowercase				=	GitProcessor.from_pretrained(
														    self.tmpdirname     ,   bos_token="""(BOS)"""     ,   eos_token="""(EOS)"""     ,   do_normalize=UpperCAmelCase     ,   padding_value=1.0  )

														self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer_add_kwargs.get_vocab()  )
														self.assertIsInstance(processor.tokenizer     ,   UpperCAmelCase  )

														self.assertEqual(processor.image_processor.to_json_string()     ,   image_processor_add_kwargs.to_json_string()  )
														self.assertIsInstance(processor.image_processor     ,   UpperCAmelCase  )



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	self.get_image_processor()
														_lowercase				=	self.get_tokenizer()

														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )

														_lowercase				=	self.prepare_image_inputs()

														_lowercase				=	image_processor(UpperCAmelCase     ,   return_tensors="""np"""  )
														_lowercase				=	processor(images=UpperCAmelCase     ,   return_tensors="""np"""  )

														for key in input_feat_extract.keys():
																					self.assertAlmostEqual(input_feat_extract[key].sum()     ,   input_processor[key].sum()     ,   delta=1e-2  )



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	self.get_image_processor()
														_lowercase				=	self.get_tokenizer()

														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )

														_lowercase				=	"""lower newer"""

														_lowercase				=	processor(text=UpperCAmelCase  )

														_lowercase				=	tokenizer(UpperCAmelCase     ,   return_token_type_ids=UpperCAmelCase  )

														for key in encoded_tok.keys():
																					self.assertListEqual(encoded_tok[key]     ,   encoded_processor[key]  )



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	self.get_image_processor()
														_lowercase				=	self.get_tokenizer()

														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )

														_lowercase				=	"""lower newer"""
														_lowercase				=	self.prepare_image_inputs()

														_lowercase				=	processor(text=UpperCAmelCase     ,   images=UpperCAmelCase  )

														self.assertListEqual(list(inputs.keys()  )     ,   ["""input_ids""", """attention_mask""", """pixel_values"""]  )

														# test if it raises when no input is passed
														with pytest.raises(UpperCAmelCase  ):
																					processor()



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	self.get_image_processor()
														_lowercase				=	self.get_tokenizer()

														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )

														_lowercase				=	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

														_lowercase				=	processor.batch_decode(UpperCAmelCase  )
														_lowercase				=	tokenizer.batch_decode(UpperCAmelCase  )

														self.assertListEqual(UpperCAmelCase     ,   UpperCAmelCase  )



							def     _UpperCAmelCase       (    self  ):







														'''simple docstring'''






														_lowercase				=	self.get_image_processor()
														_lowercase				=	self.get_tokenizer()

														_lowercase				=	GitProcessor(tokenizer=UpperCAmelCase     ,   image_processor=UpperCAmelCase  )

														_lowercase				=	"""lower newer"""
														_lowercase				=	self.prepare_image_inputs()

														_lowercase				=	processor(text=UpperCAmelCase     ,   images=UpperCAmelCase  )

														# For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
														self.assertListEqual(list(inputs.keys()  )     ,   ["""input_ids""", """attention_mask""", """pixel_values"""]  )


