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 	__snake_case	( unittest.TestCase		):





      '''simple docstring'''






      @parameterized.expand([(None,), ("""foo.json""",)])
      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int]    ,  _UpperCamelCase     :				Union[str, Any])				->List[Any]:


          """simple docstring"""


          _lowerCamelCase     :		Tuple 						=						GenerationConfig(
              do_sample=_UpperCamelCase    ,  temperature=0.7    ,  length_penalty=1.0    ,  bad_words_ids=[[1, 2, 3], [4, 5]]    ,  )
          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(_UpperCamelCase    ,  config_name=_UpperCamelCase)
              _lowerCamelCase     :		Tuple 						=						GenerationConfig.from_pretrained(_UpperCamelCase    ,  config_name=_UpperCamelCase)

          # Checks parameters that were specified
          self.assertEqual(loaded_config.do_sample    ,  _UpperCamelCase)
          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    ,  _UpperCamelCase)



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Dict)				->List[str]:


          """simple docstring"""


          _lowerCamelCase     :		List[str] 						=						AutoConfig.from_pretrained("""gpt2""")
          _lowerCamelCase     :		Optional[Any] 						=						GenerationConfig.from_model_config(_UpperCamelCase)
          _lowerCamelCase     :		Any 						=						GenerationConfig()

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

          # 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 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple)				->Tuple:


          """simple docstring"""


          _lowerCamelCase     :		Optional[Any] 						=						GenerationConfig()
          _lowerCamelCase     :		str 						=						{
              """max_new_tokens""": 1024,
              """foo""": """bar""",
          }
          _lowerCamelCase     :		List[str] 						=						copy.deepcopy(_UpperCamelCase)
          _lowerCamelCase     :		Optional[int] 						=						generation_config.update(**_UpperCamelCase)

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

          # 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(_UpperCamelCase    ,  {"""foo""": """bar"""})



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Dict)				->List[Any]:


          """simple docstring"""


          _lowerCamelCase     :		List[Any] 						=						GenerationConfig()
          _lowerCamelCase     :		List[str] 						=						"""bar"""

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

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

          _lowerCamelCase     :		List[Any] 						=						GenerationConfig.from_model_config(_UpperCamelCase)
          assert not hasattr(_UpperCamelCase    ,  """foo""")  # no new kwargs should be initialized if from config




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->List[str]:


          """simple docstring"""


          _lowerCamelCase     :		Dict 						=						GenerationConfig()
          self.assertEqual(default_config.temperature    ,  1.0)
          self.assertEqual(default_config.do_sample    ,  _UpperCamelCase)
          self.assertEqual(default_config.num_beams    ,  1)

          _lowerCamelCase     :		List[Any] 						=						GenerationConfig(
              do_sample=_UpperCamelCase    ,  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    ,  _UpperCamelCase)
          self.assertEqual(config.num_beams    ,  1)

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

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





@is_staging_test
class 	__snake_case	( unittest.TestCase		):





      '''simple docstring'''






      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				Any)				->str:


          """simple docstring"""


          _lowerCamelCase     :		Optional[Any] 						=						TOKEN
          HfFolder.save_token(_UpperCamelCase)



      @classmethod
      def 	_SCREAMING_SNAKE_CASE    (					cls     :				int)				->Optional[Any]:


          """simple docstring"""


          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 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[Any])				->Dict:


          """simple docstring"""


          _lowerCamelCase     :		int 						=						GenerationConfig(
              do_sample=_UpperCamelCase    ,  temperature=0.7    ,  length_penalty=1.0    ,  )
          config.push_to_hub("""test-generation-config"""    ,  use_auth_token=self._token)

          _lowerCamelCase     :		Dict 						=						GenerationConfig.from_pretrained(F"""{USER}/test-generation-config""")
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(_UpperCamelCase    ,  getattr(_UpperCamelCase    ,  _UpperCamelCase))

        # 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(
                  _UpperCamelCase    ,  repo_id="""test-generation-config"""    ,  push_to_hub=_UpperCamelCase    ,  use_auth_token=self._token)

          _lowerCamelCase     :		Dict 						=						GenerationConfig.from_pretrained(F"""{USER}/test-generation-config""")
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(_UpperCamelCase    ,  getattr(_UpperCamelCase    ,  _UpperCamelCase))




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int])				->str:


          """simple docstring"""


          _lowerCamelCase     :		Optional[int] 						=						GenerationConfig(
              do_sample=_UpperCamelCase    ,  temperature=0.7    ,  length_penalty=1.0    ,  )
          config.push_to_hub("""valid_org/test-generation-config-org"""    ,  use_auth_token=self._token)

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

        # 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(
                  _UpperCamelCase    ,  repo_id="""valid_org/test-generation-config-org"""    ,  push_to_hub=_UpperCamelCase    ,  use_auth_token=self._token)

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





from math import log

from scipy.constants import Boltzmann, physical_constants

lowerCAmelCase			:							List[Any]     =300  # TEMPERATURE (unit = K)







def 						A__  (					__A   , __A   , __A   , ):







    '''simple docstring'''

    if donor_conc <= 0:
        raise ValueError("""Donor concentration should be positive"""	)
    elif acceptor_conc <= 0:
        raise ValueError("""Acceptor concentration should be positive"""	)
    elif intrinsic_conc <= 0:
        raise ValueError("""Intrinsic concentration should be positive"""	)
    elif donor_conc <= intrinsic_conc:
        raise ValueError(
            """Donor concentration should be greater than intrinsic concentration"""	)
    elif acceptor_conc <= intrinsic_conc:
        raise ValueError(
            """Acceptor concentration should be greater than intrinsic concentration"""	)
    else:
        return (
            Boltzmann
            * T
            * log((donor_conc * acceptor_conc) / intrinsic_conc**2	)
            / physical_constants["electron volt"][0]
        )


if __name__ == "__main__":
    import doctest

    doctest.testmod()




