
"""simple docstring"""

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 			_lowercase  (							unittest.TestCase						):




	@patch('sys.argv'						,					['fakeprogrampath', 'env']   )
	def      _UpperCamelCase       (					self   )						->				Dict:
			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   )						->				Dict:
			import transformers.commands.transformers_cli

			shutil.rmtree('/tmp/hf-internal-testing/tiny-random-gptj'						,					ignore_errors=_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=_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   )						->				int:
			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=_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'   )   )














from __future__ import annotations




def       _a   (							lowerCamelCase__				)  ->      list[int]:
 lowerCamelCase_							:    Any							=     [0] * max_one

 for i in range(0 ,			lowerCamelCase__				):
  lowerCamelCase_							:    Union[str, Any]							=     i

 for i in range(2 ,			lowerCamelCase__				):
  if totients[i] == i:
   for j in range(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				):
    totients[j] -= totients[j] // i

 return totients




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__				)  ->      bool:
 return sorted(str(lowerCamelCase__				)				) == sorted(str(lowerCamelCase__				)				)




def       _a   (							lowerCamelCase__ = 10_00_00_00				)  ->      int:
 lowerCamelCase_							:    Tuple							=     1  # i
 lowerCamelCase_							:    Union[str, Any]							=     0  # φ(i)
 lowerCamelCase_							:    List[Any]							=     get_totients(max_n + 1				)

 for i in range(2 ,			max_n + 1				):
  lowerCamelCase_							:    Tuple							=     totients[i]

  if i * min_denominator < min_numerator * t and has_same_digits(lowerCamelCase__ ,			lowerCamelCase__				):
   lowerCamelCase_							:    str							=     i
   lowerCamelCase_							:    List[Any]							=     t

 return min_numerator


if __name__ == "__main__":
       print(f'''{solution() = }''')
