

def 	snake_case_      (__A     :						list[int]     )			->	list[int]:
   if len(__A     ) > 1:
      __lowerCAmelCase  :			str					    =						len(__A     ) // 2  # Finds the middle of the array
      __lowerCAmelCase  :			Optional[Any]					    =						arr[
          :middle_length
      ]  # Creates an array of the elements in the first half.
      __lowerCAmelCase  :			List[Any]					    =						arr[
          middle_length:
      ]  # Creates an array of the elements in the second half.
      __lowerCAmelCase  :			Optional[Any]					    =						len(__A     )
      __lowerCAmelCase  :			Optional[Any]					    =						len(__A     )
      merge(__A     )  # Starts sorting the left.
      merge(__A     )  # Starts sorting the right
      __lowerCAmelCase  :			Dict					    =						0  # Left Counter
      __lowerCAmelCase  :			Union[str, Any]					    =						0  # Right Counter
      __lowerCAmelCase  :			List[str]					    =						0  # Position Counter
      while (
          left_index < left_size and right_index < right_size
      ):  # Runs until the lowers size of the left and right are sorted.
         if left_array[left_index] < right_array[right_index]:
            __lowerCAmelCase  :			Union[str, Any]					    =						left_array[left_index]
            left_index += 1
         else:
            __lowerCAmelCase  :			List[Any]					    =						right_array[right_index]
            right_index += 1
         index += 1
      while (
          left_index < left_size
      ):  # Adds the left over elements in the left half of the array
         __lowerCAmelCase  :			Dict					    =						left_array[left_index]
         left_index += 1
         index += 1
      while (
          right_index < right_size
      ):  # Adds the left over elements in the right half of the array
         __lowerCAmelCase  :			List[str]					    =						right_array[right_index]
         right_index += 1
         index += 1
   return arr


if __name__ == "__main__":
   import doctest

   doctest.testmod()




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      lowerCamelCase		(  unittest.TestCase  ):





     @patch("sys.argv"				,    ["fakeprogrampath", "env"]   )
     def 		UpperCAmelCase(self      :    Optional[Any]   )						->						Dict:
         # 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      :    Any   )						->						int:
         import transformers.commands.transformers_cli

         shutil.rmtree("/tmp/hf-internal-testing/tiny-random-gptj"				,    ignore_errors=_A   )  # 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      :    Dict   )						->						List[Any]:
         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=_A   )

         # 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      :    Any   )						->						List[str]:
         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=_A   )

         # 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"   )   )

