
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 							A__	(			unittest.TestCase):
      @patch("""sys.argv"""					,						["""fakeprogrampath""", """env"""]   )
      def 		UpperCamelCase__							(   self   ):
       # 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   ):
       import transformers.commands.transformers_cli

       shutil.rmtree("""/tmp/hf-internal-testing/tiny-random-gptj"""					,						ignore_errors=__magic_name__   )  # 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   ):
       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=__magic_name__   )

       # 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   ):
       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=__magic_name__   )

       # 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 					_a      (		lowerCamelCase,			lowerCamelCase							):
 lowerCamelCase	:			Optional[Any]           =   float()
 try:
  lowerCamelCase	:			Tuple           =   mass * acceleration
 except Exception:
  return -0.0
 return force


if __name__ == "__main__":
      import doctest

      # run doctest
      doctest.testmod()

      # demo
      _lowerCamelCase           =12.5
      _lowerCamelCase           =1_0
      _lowerCamelCase           =newtons_second_law_of_motion(mass, acceleration)
      print("""The force is """, force, """N""")




