

import copy
import tempfile
import unittest

from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError

from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test



class    _a						(unittest.TestCase    ):


     '''simple docstring'''






     @parameterized.expand([(None,), ("""foo.json""",)]      )
     def   __A      (			self   ,	A__      ):
      A__							:   Optional[int]					       =		GenerationConfig(
          do_sample=A__   ,	temperature=0.7   ,	length_penalty=1.0   ,	bad_words_ids=[[1, 2, 3], [4, 5]]   ,	)
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(A__   ,	config_name=A__      )
       A__							:   str					       =		GenerationConfig.from_pretrained(A__   ,	config_name=A__      )

      # Checks parameters that were specified
      self.assertEqual(loaded_config.do_sample   ,	A__      )
      self.assertEqual(loaded_config.temperature   ,	0.7      )
      self.assertEqual(loaded_config.length_penalty   ,	1.0      )
      self.assertEqual(loaded_config.bad_words_ids   ,	[[1, 2, 3], [4, 5]]      )

      # Checks parameters that were not specified (defaults)
      self.assertEqual(loaded_config.top_k   ,	50      )
      self.assertEqual(loaded_config.max_length   ,	20      )
      self.assertEqual(loaded_config.max_time   ,	A__      )






     def   __A      (			self      ):
      A__							:   List[str]					       =		AutoConfig.from_pretrained("""gpt2"""      )
      A__							:   Optional[int]					       =		GenerationConfig.from_model_config(A__      )
      A__							:   List[Any]					       =		GenerationConfig()

      # The generation config has loaded a few non-default parameters from the model config
      self.assertNotEqual(A__   ,	A__      )

      # One of those parameters is eos_token_id -- check if it matches
      self.assertNotEqual(generation_config_from_model.eos_token_id   ,	default_generation_config.eos_token_id      )
      self.assertEqual(generation_config_from_model.eos_token_id   ,	model_config.eos_token_id      )






     def   __A      (			self      ):
      A__							:   Union[str, Any]					       =		GenerationConfig()
      A__							:   Any					       =		{
          """max_new_tokens""": 1024,
          """foo""": """bar""",
      }
      A__							:   Optional[Any]					       =		copy.deepcopy(A__      )
      A__							:   Union[str, Any]					       =		generation_config.update(**A__      )

      # update_kwargs was not modified (no side effects)
      self.assertEqual(A__   ,	A__      )

      # update_kwargs was used to update the config on valid attributes
      self.assertEqual(generation_config.max_new_tokens   ,	1024      )

      # `.update()` returns a dictionary of unused kwargs
      self.assertEqual(A__   ,	{"""foo""": """bar"""}      )






     def   __A      (			self      ):
      A__							:   Optional[int]					       =		GenerationConfig()
      A__							:   Any					       =		"""bar"""

      with tempfile.TemporaryDirectory("""test-generation-config"""      ) as tmp_dir:
       generation_config.save_pretrained(A__      )

       A__							:   List[Any]					       =		GenerationConfig.from_pretrained(A__      )
      # update_kwargs was used to update the config on valid attributes
      self.assertEqual(new_config.foo   ,	"""bar"""      )

      A__							:   str					       =		GenerationConfig.from_model_config(A__      )
      assert not hasattr(A__   ,	"""foo"""      )  # no new kwargs should be initialized if from config






     def   __A      (			self      ):
      A__							:   List[str]					       =		GenerationConfig()
      self.assertEqual(default_config.temperature   ,	1.0      )
      self.assertEqual(default_config.do_sample   ,	A__      )
      self.assertEqual(default_config.num_beams   ,	1      )

      A__							:   List[str]					       =		GenerationConfig(
          do_sample=A__   ,	temperature=0.7   ,	length_penalty=1.0   ,	bad_words_ids=[[1, 2, 3], [4, 5]]   ,	)
      self.assertEqual(config.temperature   ,	0.7      )
      self.assertEqual(config.do_sample   ,	A__      )
      self.assertEqual(config.num_beams   ,	1      )

      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(A__      )
       A__							:   Optional[Any]					       =		GenerationConfig.from_pretrained(A__   ,	temperature=1.0      )

      self.assertEqual(loaded_config.temperature   ,	1.0      )
      self.assertEqual(loaded_config.do_sample   ,	A__      )
      self.assertEqual(loaded_config.num_beams   ,	1      )  # default value



@is_staging_test
class    _a						(unittest.TestCase    ):


     '''simple docstring'''






     @classmethod
     def   __A      (			cls      ):
      A__							:   Optional[Any]					       =		TOKEN
      HfFolder.save_token(A__      )






     @classmethod
     def   __A      (			cls      ):
      try:
       delete_repo(token=cls._token   ,	repo_id="""test-generation-config"""      )
      except HTTPError:
       pass

      try:
       delete_repo(token=cls._token   ,	repo_id="""valid_org/test-generation-config-org"""      )
      except HTTPError:
       pass






     def   __A      (			self      ):
      A__							:   Optional[int]					       =		GenerationConfig(
          do_sample=A__   ,	temperature=0.7   ,	length_penalty=1.0   ,	)
      config.push_to_hub("""test-generation-config"""   ,	use_auth_token=self._token      )

      A__							:   List[str]					       =		GenerationConfig.from_pretrained(F"""{USER}/test-generation-config"""      )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(A__   ,	getattr(A__   ,	A__      )      )

        # Reset repo
      delete_repo(token=self._token   ,	repo_id="""test-generation-config"""      )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(
           A__   ,	repo_id="""test-generation-config"""   ,	push_to_hub=A__   ,	use_auth_token=self._token      )

      A__							:   Optional[Any]					       =		GenerationConfig.from_pretrained(F"""{USER}/test-generation-config"""      )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(A__   ,	getattr(A__   ,	A__      )      )






     def   __A      (			self      ):
      A__							:   str					       =		GenerationConfig(
          do_sample=A__   ,	temperature=0.7   ,	length_penalty=1.0   ,	)
      config.push_to_hub("""valid_org/test-generation-config-org"""   ,	use_auth_token=self._token      )

      A__							:   Optional[Any]					       =		GenerationConfig.from_pretrained("""valid_org/test-generation-config-org"""      )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(A__   ,	getattr(A__   ,	A__      )      )

        # Reset repo
      delete_repo(token=self._token   ,	repo_id="""valid_org/test-generation-config-org"""      )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(
           A__   ,	repo_id="""valid_org/test-generation-config-org"""   ,	push_to_hub=A__   ,	use_auth_token=self._token      )

      A__							:   str					       =		GenerationConfig.from_pretrained("""valid_org/test-generation-config-org"""      )
      for k, v in config.to_dict().items():
       if k != "transformers_version":
        self.assertEqual(A__   ,	getattr(A__   ,	A__      )      )






from argparse import ArgumentParser

from . import BaseTransformersCLICommand

def 						UpperCamelCase (lowercase_:			int )					->				str:
	return DownloadCommand(args.model   ,				args.cache_dir   ,				args.force   ,				args.trust_remote_code )



class    _a						(__magic_name__    ):


					'''simple docstring'''






					@staticmethod
					def   __A      (			A__      ):
						A__							:   Any					       =		parser.add_parser("""download"""      )
						download_parser.add_argument(
						    """--cache-dir"""   ,	type=A__   ,	default=A__   ,	help="""Path to location to store the models"""      )
						download_parser.add_argument(
						    """--force"""   ,	action="""store_true"""   ,	help="""Force the model to be download even if already in cache-dir"""      )
						download_parser.add_argument(
						    """--trust-remote-code"""   ,	action="""store_true"""   ,	help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""   ,	)
						download_parser.add_argument("""model"""   ,	type=A__   ,	help="""Name of the model to download"""      )
						download_parser.set_defaults(func=A__      )






					def __init__(			self   ,	A__   ,	A__   ,	A__   ,	A__      ):
						A__							:   Union[str, Any]					       =		model
						A__							:   Dict					       =		cache
						A__							:   str					       =		force
						A__							:   Tuple					       =		trust_remote_code






					def   __A      (			self      ):
						from ..models.auto import AutoModel, AutoTokenizer

						AutoModel.from_pretrained(
						    self._model   ,	cache_dir=self._cache   ,	force_download=self._force   ,	trust_remote_code=self._trust_remote_code      )
						AutoTokenizer.from_pretrained(
						    self._model   ,	cache_dir=self._cache   ,	force_download=self._force   ,	trust_remote_code=self._trust_remote_code      )



