




import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
     from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
     from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
     from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


UpperCamelCase								=					DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

UpperCamelCase								=					'main'
# Default branch name
UpperCamelCase								=					'f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'
# One particular commit (not the top of `main`)
UpperCamelCase								=					'aaaaaaa'
# This commit does not exist, so we should 404.

UpperCamelCase								=					'd9e9f15bc825e4b2c9249e9578f884bbcb5e3684'
# Sha-1 of config.json on the top of `main`, for checking purposes
UpperCamelCase								=					'4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'



@contextlib.contextmanager
def 							_A       (						):
     """simple docstring"""

     print("Welcome!"      )
     yield
     print("Bye!"      )



@contextlib.contextmanager
def 							_A       (						):
     """simple docstring"""

     print("Bonjour!"      )
     yield
     print("Au revoir!"      )





class 			__lowerCamelCase	(   unittest.TestCase   ):




    """simple docstring"""

    def        a				(	self					:					Optional[Any]       )				->	List[Any]:
         # If the spec is missing, importlib would not be able to import the module dynamically.
         assert transformers.__spec__ is not None
         assert importlib.util.find_spec("transformers"       ) is not None






class 			__lowerCamelCase	(   unittest.TestCase   ):




    """simple docstring"""

    @unittest.mock.patch("sys.stdout"       ,     new_callable=io.StringIO       )
    def        a				(	self					:					Optional[int]       ,     SCREAMING_SNAKE_CASE__					:					Dict       )				->	Union[str, Any]:
         with ContextManagers([]       ):
              print("Transformers are awesome!"       )
         # The print statement adds a new line at the end of the output
         self.assertEqual(mock_stdout.getvalue()       ,     "Transformers are awesome!\n"       )


    @unittest.mock.patch("sys.stdout"       ,     new_callable=io.StringIO       )
    def        a				(	self					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					Any       )				->	List[Any]:
         with ContextManagers([context_en()]       ):
              print("Transformers are awesome!"       )
         # The output should be wrapped with an English welcome and goodbye
         self.assertEqual(mock_stdout.getvalue()       ,     "Welcome!\nTransformers are awesome!\nBye!\n"       )


    @unittest.mock.patch("sys.stdout"       ,     new_callable=io.StringIO       )
    def        a				(	self					:					int       ,     SCREAMING_SNAKE_CASE__					:					Tuple       )				->	Union[str, Any]:
         with ContextManagers([context_fr(), context_en()]       ):
              print("Transformers are awesome!"       )
         # The output should be wrapped with an English and French welcome and goodbye
         self.assertEqual(mock_stdout.getvalue()       ,     "Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"       )


    @require_torch
    def        a				(	self					:					int       )				->	Dict:
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels"]       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels", "next_sentence_label"]       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["start_positions", "end_positions"]       )





         class 			__lowerCamelCase	(   UpperCamelCase__   ):




             """simple docstring"""

             pass






         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels"]       )


    @require_tf
    def        a				(	self					:					Any       )				->	Union[str, Any]:
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels"]       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels", "next_sentence_label"]       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["start_positions", "end_positions"]       )





         class 			__lowerCamelCase	(   UpperCamelCase__   ):




             """simple docstring"""

             pass






         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     ["labels"]       )


    @require_flax
    def        a				(	self					:					Any       )				->	Optional[Any]:
         # Flax models don't have labels
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     []       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     []       )
         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     []       )





         class 			__lowerCamelCase	(   UpperCamelCase__   ):




             """simple docstring"""

             pass






         self.assertEqual(find_labels(SCREAMING_SNAKE_CASE__       )       ,     []       )






import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer



def 							_A       (						lowerCAmelCase_					: str       ,    lowerCAmelCase_					: str       ,    **lowerCAmelCase_					: str      ):
     """simple docstring"""

     lowerCAmelCase__          =			AutoConfig.from_pretrained(lowerCAmelCase_       ,    **lowerCAmelCase_      )
     lowerCAmelCase__          =			AutoModelForSeqaSeqLM.from_config(lowerCAmelCase_      )
     model.save_pretrained(lowerCAmelCase_      )
     AutoTokenizer.from_pretrained(lowerCAmelCase_      ).save_pretrained(lowerCAmelCase_      )
     return model


if __name__ == "__main__":
     fire.Fire(save_randomly_initialized_version)
