





import unittest

from transformers import is_torch_available, load_tool

from .test_tools_common import ToolTesterMixin


if is_torch_available():
     import torch



class 				_UpperCamelCase       (						unittest.TestCase	,    lowerCAmelCase_  ):

       def lowercase			(		self:			Tuple		)							->			Optional[int]:




              """simple docstring"""


              UpperCamelCase_ 							=	load_tool("speech-to-text"		)
              self.tool.setup()

       def lowercase			(		self:			Optional[Any]		)							->			int:




              """simple docstring"""


              UpperCamelCase_ 							=	self.tool(torch.ones(3000		)		)
              self.assertEqual(_SCREAMING_SNAKE_CASE       , " you"		)



       def lowercase			(		self:			Optional[Any]		)							->			List[str]:




              """simple docstring"""


              UpperCamelCase_ 							=	self.tool(audio=torch.ones(3000		)		)
              self.assertEqual(_SCREAMING_SNAKE_CASE       , " you"		)



"""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  _snake_case	(    unittest.TestCase							):






							@patch("""sys.argv"""    ,			["""fakeprogrampath""", """env"""]     )
							def 				__lowercase	(       self    :      Tuple     ):






												"""simple docstring"""



												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 				__lowercase	(       self    :      List[str]     ):






												"""simple docstring"""



												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 				__lowercase	(       self    :      Optional[Any]     ):






												"""simple docstring"""



												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 				__lowercase	(       self    :      Union[str, Any]     ):






												"""simple docstring"""



												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"""     )     )
