



"""simple docstring"""
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       ):



  @parameterized.expand([(None,), ("""foo.json""",)]		)
  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					List[Any]		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=GenerationConfig(
         do_sample=__lowerCAmelCase       ,		temperature=0.7       ,		length_penalty=1.0       ,		bad_words_ids=[[1, 2, 3], [4, 5]]       ,		)
     with tempfile.TemporaryDirectory() as tmp_dir:
        config.save_pretrained(__lowerCAmelCase       ,		config_name=__lowerCAmelCase		)
        SCREAMING_SNAKE_CASE_: List[Any]     			=GenerationConfig.from_pretrained(__lowerCAmelCase       ,		config_name=__lowerCAmelCase		)

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



  def 	lowerCamelCase__       (						self :					Optional[int]		)     ->					Any:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=AutoConfig.from_pretrained("""gpt2"""		)
     SCREAMING_SNAKE_CASE_: str     			=GenerationConfig.from_model_config(__lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: str     			=GenerationConfig()

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

     # 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 	lowerCamelCase__       (						self :					Tuple		)     ->					Tuple:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=GenerationConfig()
     SCREAMING_SNAKE_CASE_: str     			={
         """max_new_tokens""": 1024,
         """foo""": """bar""",
     }
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=copy.deepcopy(__lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Dict     			=generation_config.update(**__lowerCAmelCase		)

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

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



  def 	lowerCamelCase__       (						self :					Any		)     ->					Any:


     '''simple docstring'''




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

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

        SCREAMING_SNAKE_CASE_: Tuple     			=GenerationConfig.from_pretrained(__lowerCAmelCase		)
     # update_kwargs was used to update the config on valid attributes
     self.assertEqual(new_config.foo       ,		"""bar"""		)

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





  def 	lowerCamelCase__       (						self :					List[str]		)     ->					int:


     '''simple docstring'''




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

     SCREAMING_SNAKE_CASE_: Optional[Any]     			=GenerationConfig(
         do_sample=__lowerCAmelCase       ,		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       ,		__lowerCAmelCase		)
     self.assertEqual(config.num_beams       ,		1		)

     with tempfile.TemporaryDirectory() as tmp_dir:
        config.save_pretrained(__lowerCAmelCase		)
        SCREAMING_SNAKE_CASE_: Any     			=GenerationConfig.from_pretrained(__lowerCAmelCase       ,		temperature=1.0		)

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







@is_staging_test
class 					a	(  unittest.TestCase       ):



  @classmethod
  def 	lowerCamelCase__       (						cls :					str		)     ->					Dict:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=TOKEN
     HfFolder.save_token(__lowerCAmelCase		)



  @classmethod
  def 	lowerCamelCase__       (						cls :					Union[str, Any]		)     ->					Optional[int]:


     '''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 	lowerCamelCase__       (						self :					int		)     ->					Union[str, Any]:


     '''simple docstring'''




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

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=GenerationConfig.from_pretrained(f'''{USER}/test-generation-config'''		)
     for k, v in config.to_dict().items():
        if k != "transformers_version":
           self.assertEqual(__lowerCAmelCase       ,		getattr(__lowerCAmelCase       ,		__lowerCAmelCase		)		)

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

     SCREAMING_SNAKE_CASE_: Tuple     			=GenerationConfig.from_pretrained(f'''{USER}/test-generation-config'''		)
     for k, v in config.to_dict().items():
        if k != "transformers_version":
           self.assertEqual(__lowerCAmelCase       ,		getattr(__lowerCAmelCase       ,		__lowerCAmelCase		)		)





  def 	lowerCamelCase__       (						self :					Dict		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[str]     			=GenerationConfig(
         do_sample=__lowerCAmelCase       ,		temperature=0.7       ,		length_penalty=1.0       ,		)
     config.push_to_hub("""valid_org/test-generation-config-org"""       ,		use_auth_token=self._token		)

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

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

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








"""simple docstring"""
import gc
import unittest

from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
   import jax
   import jax.numpy as jnp
   from flax.jax_utils import replicate
   from flax.training.common_utils import shard
@slow
@require_flax
class 					a	(  unittest.TestCase       ):



  def 	lowerCamelCase__       (						self :					Dict		)     ->					str:


     '''simple docstring'''




     super().tearDown()
     gc.collect()



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: Dict     			=FlaxStableDiffusionPipeline.from_pretrained(
         """stabilityai/stable-diffusion-2"""       ,		revision="""bf16"""       ,		dtype=jnp.bfloataa       ,		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			="""A painting of a squirrel eating a burger"""
     SCREAMING_SNAKE_CASE_: Any     			=jax.device_count()
     SCREAMING_SNAKE_CASE_: Dict     			=num_samples * [prompt]
     SCREAMING_SNAKE_CASE_: List[Any]     			=sd_pipe.prepare_inputs(lowerCAmelCase		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=replicate(lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			=shard(lowerCAmelCase		)

     SCREAMING_SNAKE_CASE_: Dict     			=jax.random.PRNGKey(0		)
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=jax.random.split(lowerCAmelCase       ,		jax.device_count()		)

     SCREAMING_SNAKE_CASE_: Tuple     			=sd_pipe(lowerCAmelCase       ,		lowerCAmelCase       ,		lowerCAmelCase       ,		num_inference_steps=25       ,		jit=lowerCAmelCase		)[0]
     assert images.shape == (jax.device_count(), 1, 768, 768, 3)

     SCREAMING_SNAKE_CASE_: Dict     			=images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
     SCREAMING_SNAKE_CASE_: Dict     			=images[0, 253:256, 253:256, -1]

     SCREAMING_SNAKE_CASE_: Optional[int]     			=jnp.asarray(jax.device_get(image_slice.flatten()		)		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			=jnp.array([0.4_2_3_8, 0.4_4_1_4, 0.4_3_9_5, 0.4_4_5_3, 0.4_6_2_9, 0.4_5_9_0, 0.4_5_3_1, 0.4_5_5_0_8, 0.4_5_1_2]		)
     print(f'''output_slice: {output_slice}'''		)
     assert jnp.abs(output_slice - expected_slice		).max() < 1E-2





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


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			="""stabilityai/stable-diffusion-2"""
     SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: Optional[int]     			=FlaxDPMSolverMultistepScheduler.from_pretrained(lowerCAmelCase       ,		subfolder="""scheduler"""		)
     SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: Optional[int]     			=FlaxStableDiffusionPipeline.from_pretrained(
         lowerCAmelCase       ,		scheduler=lowerCAmelCase       ,		revision="""bf16"""       ,		dtype=jnp.bfloataa       ,		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			=scheduler_params

     SCREAMING_SNAKE_CASE_: Tuple     			="""A painting of a squirrel eating a burger"""
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=jax.device_count()
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=num_samples * [prompt]
     SCREAMING_SNAKE_CASE_: List[Any]     			=sd_pipe.prepare_inputs(lowerCAmelCase		)

     SCREAMING_SNAKE_CASE_: Tuple     			=replicate(lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			=shard(lowerCAmelCase		)

     SCREAMING_SNAKE_CASE_: Any     			=jax.random.PRNGKey(0		)
     SCREAMING_SNAKE_CASE_: Any     			=jax.random.split(lowerCAmelCase       ,		jax.device_count()		)

     SCREAMING_SNAKE_CASE_: Tuple     			=sd_pipe(lowerCAmelCase       ,		lowerCAmelCase       ,		lowerCAmelCase       ,		num_inference_steps=25       ,		jit=lowerCAmelCase		)[0]
     assert images.shape == (jax.device_count(), 1, 768, 768, 3)

     SCREAMING_SNAKE_CASE_: str     			=images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
     SCREAMING_SNAKE_CASE_: Any     			=images[0, 253:256, 253:256, -1]

     SCREAMING_SNAKE_CASE_: Optional[Any]     			=jnp.asarray(jax.device_get(image_slice.flatten()		)		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			=jnp.array([0.4_3_3_6, 0.4_2_9_6_9, 0.4_4_5_3, 0.4_1_9_9, 0.4_2_9_7, 0.4_5_3_1, 0.4_4_3_4, 0.4_4_3_4, 0.4_2_9_7]		)
     print(f'''output_slice: {output_slice}'''		)
     assert jnp.abs(output_slice - expected_slice		).max() < 1E-2



