


import os
import shutil
import unittest
from unittest.mock import patch

from transformers.testing_utils import CaptureStd, is_pt_tf_cross_test, require_torch




class 					_UpperCamelCase (      unittest.TestCase	):







							'''simple docstring'''







							@patch('sys.argv'		,				['fakeprogrampath', 'env']		)
							def 		_UpperCAmelCase	(		self  :				Optional[Any]		):
													# test transformers-cli env
													import transformers.commands.transformers_cli

													with CaptureStd() as cs:
																			transformers.commands.transformers_cli.main()
													self.assertIn('Python version'		,				cs.out		)
													self.assertIn('Platform'		,				cs.out		)
													self.assertIn('Using distributed or parallel set-up in script?'		,				cs.out		)







							@is_pt_tf_cross_test
							@patch(
							    'sys.argv'		,				['fakeprogrampath', 'pt-to-tf', '--model-name', 'hf-internal-testing/tiny-random-gptj', '--no-pr']		)
							def 		_UpperCAmelCase	(		self  :				int		):
													import transformers.commands.transformers_cli

													shutil.rmtree('/tmp/hf-internal-testing/tiny-random-gptj'		,				ignore_errors=SCREAMING_SNAKE_CASE_		)  # cleans potential past runs
													transformers.commands.transformers_cli.main()

													# The original repo has no TF weights -- if they exist, they were created by the CLI
													self.assertTrue(os.path.exists('/tmp/hf-internal-testing/tiny-random-gptj/tf_model.h5'		)		)







							@require_torch
							@patch('sys.argv'		,				['fakeprogrampath', 'download', 'hf-internal-testing/tiny-random-gptj', '--cache-dir', '/tmp']		)
							def 		_UpperCAmelCase	(		self  :				str		):
													import transformers.commands.transformers_cli

													# # remove any previously downloaded model to start clean
													shutil.rmtree('/tmp/models--hf-internal-testing--tiny-random-gptj'		,				ignore_errors=SCREAMING_SNAKE_CASE_		)

													# run the command
													transformers.commands.transformers_cli.main()

													# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--tiny-random-gptj
													self.assertTrue(os.path.exists('/tmp/models--hf-internal-testing--tiny-random-gptj/blobs'		)		)
													self.assertTrue(os.path.exists('/tmp/models--hf-internal-testing--tiny-random-gptj/refs'		)		)
													self.assertTrue(os.path.exists('/tmp/models--hf-internal-testing--tiny-random-gptj/snapshots'		)		)







							@require_torch
							@patch(
							    'sys.argv'		,				[
							        'fakeprogrampath',
							        'download',
							        'hf-internal-testing/test_dynamic_model_with_tokenizer',
							        '--trust-remote-code',
							        '--cache-dir',
							        '/tmp',
							    ]		,				)
							def 		_UpperCAmelCase	(		self  :				Dict		):
													import transformers.commands.transformers_cli

													# # remove any previously downloaded model to start clean
													shutil.rmtree('/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer'		,				ignore_errors=SCREAMING_SNAKE_CASE_		)

													# run the command
													transformers.commands.transformers_cli.main()

													# check if the model files are downloaded correctly on /tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer
													self.assertTrue(os.path.exists('/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/blobs'		)		)
													self.assertTrue(os.path.exists('/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/refs'		)		)
													self.assertTrue(
													    os.path.exists('/tmp/models--hf-internal-testing--test_dynamic_model_with_tokenizer/snapshots'		)		)






def 							SCREAMING_SNAKE_CASE					(  _UpperCAmelCase				)    ->  bool:
						# must be
						_a     =			[list(_UpperCAmelCase				) for row in matrix]
						if matrix and isinstance(_UpperCAmelCase							,     _UpperCAmelCase				):
												if isinstance(matrix[0]							,     _UpperCAmelCase				):
																		_a     =			0
																		for row in matrix:
																								if prev_len == 0:
																														_a     =			len(_UpperCAmelCase				)
																														_a     =			True
																								else:
																														_a     =			prev_len == len(_UpperCAmelCase				)
												else:
																		_a     =			True
						else:
												_a     =			False

						return result


def 							SCREAMING_SNAKE_CASE					(  _UpperCAmelCase				)    ->  None:
						if check_matrix(_UpperCAmelCase				) and len(_UpperCAmelCase				) > 0:
												_a     =			[list(_UpperCAmelCase				) for row in a]
												_a     =			len(_UpperCAmelCase				)
												if isinstance(a[0]							,     _UpperCAmelCase				):
																		_a     =			len(a[0]				)
												else:
																		for dat in a:
																								print(_UpperCAmelCase				)
																		return

												# horizotal printing increasing
												for i in range(0							,     _UpperCAmelCase				):
																		print(a[0][i]				)
												# vertical printing down
												for i in range(1							,     _UpperCAmelCase				):
																		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]				)
												_a     =			[row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
												if len(_UpperCAmelCase				) > 0:
																		spiral_print_clockwise(_UpperCAmelCase				)
												else:
																		return
						else:
												print('Not a valid matrix'				)
												return


def 							SCREAMING_SNAKE_CASE					(  _UpperCAmelCase				)    ->  list[int]:
						if matrix:
												return list(matrix.pop(0				)				) + spiral_traversal(list(zip(*_UpperCAmelCase				)				)[::-1]				)
						else:
												return []


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

		doctest.testmod()

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


