"""simple docstring"""




import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class 		__A							(				SCREAMING_SNAKE_CASE_	):






     @require_torch
     def 					__A						(	self						):
       # this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
       # `transformers` is loaded, and it's too late for inside pytest - so we are changing it
       # while running an external program

       # python one-liner segments

       # this must be loaded before socket.socket is monkey-patched
       _lowerCAmelCase		: int						    =  """
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        """

       _lowerCAmelCase		: str						    =  """
mname = \"hf-internal-testing/tiny-random-bert\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task=\"fill-mask\", model=mname)
print(\"success\")
        """

       _lowerCAmelCase		: int						    =  """
import socket
def offline_socket(*args, **kwargs): raise RuntimeError(\"Offline mode is enabled, we shouldn't access internet\")
socket.socket = offline_socket
        """

       # Force fetching the files so that we can use the cache
       _lowerCAmelCase		: Optional[Any]						    =  """hf-internal-testing/tiny-random-bert"""
       BertConfig.from_pretrained(a__						)
       BertModel.from_pretrained(a__						)
       BertTokenizer.from_pretrained(a__						)
       pipeline(task="""fill-mask"""       ,  model=a__						)

       # baseline - just load from_pretrained with normal network
       _lowerCAmelCase		: Any						    =  [sys.executable, """-c""", """\n""".join([load, run, mock]						)]

       # should succeed
       _lowerCAmelCase		: Union[str, Any]						    =  self.get_env()
       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       _lowerCAmelCase		: Dict						    =  """1"""
       _lowerCAmelCase		: Optional[int]						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)






     @require_torch
     def 					__A						(	self						):
       # python one-liner segments
       # this must be loaded before socket.socket is monkey-patched
       _lowerCAmelCase		: Dict						    =  """
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        """

       _lowerCAmelCase		: List[str]						    =  """
mname = \"hf-internal-testing/tiny-random-bert\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task=\"fill-mask\", model=mname)
print(\"success\")
        """

       _lowerCAmelCase		: List[Any]						    =  """
import socket
def offline_socket(*args, **kwargs): raise socket.error(\"Faking flaky internet\")
socket.socket = offline_socket
        """

       # Force fetching the files so that we can use the cache
       _lowerCAmelCase		: Dict						    =  """hf-internal-testing/tiny-random-bert"""
       BertConfig.from_pretrained(a__						)
       BertModel.from_pretrained(a__						)
       BertTokenizer.from_pretrained(a__						)
       pipeline(task="""fill-mask"""       ,  model=a__						)

       # baseline - just load from_pretrained with normal network
       _lowerCAmelCase		: int						    =  [sys.executable, """-c""", """\n""".join([load, run, mock]						)]

       # should succeed
       _lowerCAmelCase		: List[Any]						    =  self.get_env()
       _lowerCAmelCase		: List[str]						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)






     @require_torch
     def 					__A						(	self						):
       # this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
       # `transformers` is loaded, and it's too late for inside pytest - so we are changing it
       # while running an external program

       # python one-liner segments

       # this must be loaded before socket.socket is monkey-patched
       _lowerCAmelCase		: str						    =  """
from transformers import BertConfig, BertModel, BertTokenizer
        """

       _lowerCAmelCase		: int						    =  """
mname = \"hf-internal-testing/tiny-random-bert-sharded\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
print(\"success\")
        """

       _lowerCAmelCase		: Union[str, Any]						    =  """
import socket
def offline_socket(*args, **kwargs): raise ValueError(\"Offline mode is enabled\")
socket.socket = offline_socket
        """

       # baseline - just load from_pretrained with normal network
       _lowerCAmelCase		: int						    =  [sys.executable, """-c""", """\n""".join([load, run]						)]

       # should succeed
       _lowerCAmelCase		: Any						    =  self.get_env()
       _lowerCAmelCase		: int						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)

       # next emulate no network
       _lowerCAmelCase		: Optional[int]						    =  [sys.executable, """-c""", """\n""".join([load, mock, run]						)]

       # Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
       # env["TRANSFORMERS_OFFLINE"] = "0"
       # result = subprocess.run(cmd, env=env, check=False, capture_output=True)
       # self.assertEqual(result.returncode, 1, result.stderr)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       _lowerCAmelCase		: Any						    =  """1"""
       _lowerCAmelCase		: List[Any]						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)






     @require_torch
     def 					__A						(	self						):
       _lowerCAmelCase		: Optional[Any]						    =  """
from transformers import pipeline
        """
       _lowerCAmelCase		: List[Any]						    =  """
mname = \"hf-internal-testing/tiny-random-bert\"
pipe = pipeline(model=mname)
        """

       _lowerCAmelCase		: List[Any]						    =  """
import socket
def offline_socket(*args, **kwargs): raise socket.error(\"Offline mode is enabled\")
socket.socket = offline_socket
        """
       _lowerCAmelCase		: List[Any]						    =  self.get_env()
       _lowerCAmelCase		: Union[str, Any]						    =  """1"""
       _lowerCAmelCase		: Tuple						    =  [sys.executable, """-c""", """\n""".join([load, mock, run]						)]
       _lowerCAmelCase		: Tuple						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  1       ,  result.stderr						)
       self.assertIn(
           """You cannot infer task automatically within `pipeline` when using offline mode"""       ,  result.stderr.decode().replace("""\n"""       ,  """"""						)       ,  )






     @require_torch
     def 					__A						(	self						):
       _lowerCAmelCase		: List[str]						    =  """
from transformers import AutoModel
        """
       _lowerCAmelCase		: Optional[Any]						    =  """
mname = \"hf-internal-testing/test_dynamic_model\"
AutoModel.from_pretrained(mname, trust_remote_code=True)
print(\"success\")
        """

       # baseline - just load from_pretrained with normal network
       _lowerCAmelCase		: Tuple						    =  [sys.executable, """-c""", """\n""".join([load, run]						)]

       # should succeed
       _lowerCAmelCase		: Dict						    =  self.get_env()
       _lowerCAmelCase		: Tuple						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       _lowerCAmelCase		: Dict						    =  """1"""
       _lowerCAmelCase		: List[Any]						    =  subprocess.run(a__       ,  env=a__       ,  check=a__       ,  capture_output=a__						)
       self.assertEqual(result.returncode       ,  0       ,  result.stderr						)
       self.assertIn("""success"""       ,  result.stdout.decode()						)





"""simple docstring"""




import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)




