


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 			SCREAMING_SNAKE_CASE__  (    unittest.TestCase      ):
      @parameterized.expand([(None,), ('foo.json',)]					)
      def 	SCREAMING_SNAKE_CASE							(	self    :	str					,							SCREAMING_SNAKE_CASE__    :	Dict					)		->      Any:
             a_ :		Optional[Any]							=  GenerationConfig(
                 do_sample=SCREAMING_SNAKE_CASE__					,							temperature=0.7					,							length_penalty=1.0					,							bad_words_ids=[[1, 2, 3], [4, 5]]					,							)
             with tempfile.TemporaryDirectory() as tmp_dir:
                    config.save_pretrained(SCREAMING_SNAKE_CASE__					,							config_name=SCREAMING_SNAKE_CASE__					)
                    a_ :		List[Any]							=  GenerationConfig.from_pretrained(SCREAMING_SNAKE_CASE__					,							config_name=SCREAMING_SNAKE_CASE__					)

             # Checks parameters that were specified
             self.assertEqual(loaded_config.do_sample					,							SCREAMING_SNAKE_CASE__					)
             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					,							5_0					)
             self.assertEqual(loaded_config.max_length					,							2_0					)
             self.assertEqual(loaded_config.max_time					,							SCREAMING_SNAKE_CASE__					)
      def 	SCREAMING_SNAKE_CASE							(	self    :	int					)		->      List[Any]:
             a_ :		Union[str, Any]							=  AutoConfig.from_pretrained('gpt2'					)
             a_ :		int							=  GenerationConfig.from_model_config(SCREAMING_SNAKE_CASE__					)
             a_ :		Tuple							=  GenerationConfig()

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

             # 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    :	Optional[Any]					)		->      Optional[Any]:
             a_ :		Dict							=  GenerationConfig()
             a_ :		Union[str, Any]							=  {
                 'max_new_tokens': 1_0_2_4,
                 'foo': 'bar',
             }
             a_ :		Tuple							=  copy.deepcopy(SCREAMING_SNAKE_CASE__					)
             a_ :		Union[str, Any]							=  generation_config.update(**SCREAMING_SNAKE_CASE__					)

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

             # update_kwargs was used to update the config on valid attributes
             self.assertEqual(generation_config.max_new_tokens					,							1_0_2_4					)

             # `.update()` returns a dictionary of unused kwargs
             self.assertEqual(SCREAMING_SNAKE_CASE__					,							{'foo': 'bar'}					)
      def 	SCREAMING_SNAKE_CASE							(	self    :	Optional[Any]					)		->      int:
             a_ :		int							=  GenerationConfig()
             a_ :		List[Any]							=  'bar'

             with tempfile.TemporaryDirectory('test-generation-config'					) as tmp_dir:
                    generation_config.save_pretrained(SCREAMING_SNAKE_CASE__					)

                    a_ :		str							=  GenerationConfig.from_pretrained(SCREAMING_SNAKE_CASE__					)
             # update_kwargs was used to update the config on valid attributes
             self.assertEqual(new_config.foo					,							'bar'					)

             a_ :		Union[str, Any]							=  GenerationConfig.from_model_config(SCREAMING_SNAKE_CASE__					)
             assert not hasattr(SCREAMING_SNAKE_CASE__					,							'foo'					)  # no new kwargs should be initialized if from config

      def 	SCREAMING_SNAKE_CASE							(	self    :	Union[str, Any]					)		->      Optional[int]:
             a_ :		Tuple							=  GenerationConfig()
             self.assertEqual(default_config.temperature					,							1.0					)
             self.assertEqual(default_config.do_sample					,							SCREAMING_SNAKE_CASE__					)
             self.assertEqual(default_config.num_beams					,							1					)

             a_ :		int							=  GenerationConfig(
                 do_sample=SCREAMING_SNAKE_CASE__					,							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					,							SCREAMING_SNAKE_CASE__					)
             self.assertEqual(config.num_beams					,							1					)

             with tempfile.TemporaryDirectory() as tmp_dir:
                    config.save_pretrained(SCREAMING_SNAKE_CASE__					)
                    a_ :		int							=  GenerationConfig.from_pretrained(SCREAMING_SNAKE_CASE__					,							temperature=1.0					)

             self.assertEqual(loaded_config.temperature					,							1.0					)
             self.assertEqual(loaded_config.do_sample					,							SCREAMING_SNAKE_CASE__					)
             self.assertEqual(loaded_config.num_beams					,							1					)  # default value
@is_staging_test
class 			SCREAMING_SNAKE_CASE__  (    unittest.TestCase      ):
      @classmethod
      def 	SCREAMING_SNAKE_CASE							(	cls    :	Any					)		->      Optional[int]:
             a_ :		List[str]							=  TOKEN
             HfFolder.save_token(SCREAMING_SNAKE_CASE__					)
      @classmethod
      def 	SCREAMING_SNAKE_CASE							(	cls    :	str					)		->      List[Any]:
             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    :	Union[str, Any]					)		->      List[str]:
             a_ :		Union[str, Any]							=  GenerationConfig(
                 do_sample=SCREAMING_SNAKE_CASE__					,							temperature=0.7					,							length_penalty=1.0					,							)
             config.push_to_hub('test-generation-config'					,							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(SCREAMING_SNAKE_CASE__					,							getattr(SCREAMING_SNAKE_CASE__					,							SCREAMING_SNAKE_CASE__					)					)

        # 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(
                        SCREAMING_SNAKE_CASE__					,							repo_id='test-generation-config'					,							push_to_hub=SCREAMING_SNAKE_CASE__					,							use_auth_token=self._token					)

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

      def 	SCREAMING_SNAKE_CASE							(	self    :	Any					)		->      Optional[Any]:
             a_ :		Tuple							=  GenerationConfig(
                 do_sample=SCREAMING_SNAKE_CASE__					,							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(SCREAMING_SNAKE_CASE__					,							getattr(SCREAMING_SNAKE_CASE__					,							SCREAMING_SNAKE_CASE__					)					)

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

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






from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase_				:			str   =	1.054571817e-34  # unit of ℏ : J * s

UpperCAmelCase_				:			Dict   =	3e8  # unit of c : m * s^-1







def 	SCREAMING_SNAKE_CASE_						(      __A			:      float  ,   __A			:      float  ,   __A			:      float    )     ->		dict[str, float]:

       """simple docstring"""

       if (force, area, distance).count(0    ) != 1:
              raise ValueError('One and only one argument must be 0'    )
       if force < 0:
              raise ValueError('Magnitude of force can not be negative'    )
       if distance < 0:
              raise ValueError('Distance can not be negative'    )
       if area < 0:
              raise ValueError('Area can not be negative'    )
       if force == 0:
              a_ :		Optional[Any]							=  (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
                  2_40 * (distance) ** 4
              )
              return {"force": force}
       elif area == 0:
              a_ :		List[str]							=  (2_40 * force * (distance) ** 4) / (
                  REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
              )
              return {"area": area}
       elif distance == 0:
              a_ :		Tuple							=  (
                  (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (2_40 * force)
              ) ** (1 / 4)
              return {"distance": distance}
       raise ValueError('One and only one argument must be 0'    )


# Run doctest
if __name__ == "__main__":
   import doctest

   doctest.testmod()


