



"""simple docstring"""




import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, 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      UpperCAmelCase_  (    unittest.TestCase						):



      def 						snake_case_ (					self					:     int						):
           # clean up the VRAM after each test
           super().tearDown()
           gc.collect()



      def 						snake_case_ (					self					:     Tuple						):
           _UpperCAmelCase    ,	_UpperCAmelCase      :     Optional[Any]        =   FlaxControlNetModel.from_pretrained(
               "lllyasviel/sd-controlnet-canny"					,     from_pt=A					,     dtype=jnp.bfloataa						)
           _UpperCAmelCase    ,	_UpperCAmelCase      :     Optional[Any]        =   FlaxStableDiffusionControlNetPipeline.from_pretrained(
               "runwayml/stable-diffusion-v1-5"					,     controlnet=A					,     from_pt=A					,     dtype=jnp.bfloataa						)
           _UpperCAmelCase      :     Dict        =   controlnet_params

           _UpperCAmelCase      :     Optional[int]        =   "bird"
           _UpperCAmelCase      :     Optional[int]        =   jax.device_count()
           _UpperCAmelCase      :     Union[str, Any]        =   pipe.prepare_text_inputs([prompts] * num_samples						)

           _UpperCAmelCase      :     Union[str, Any]        =   load_image(
               "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png"						)
           _UpperCAmelCase      :     Optional[int]        =   pipe.prepare_image_inputs([canny_image] * num_samples						)

           _UpperCAmelCase      :     Tuple        =   jax.random.PRNGKey(0						)
           _UpperCAmelCase      :     Optional[Any]        =   jax.random.split(A					,     jax.device_count()						)

           _UpperCAmelCase      :     Optional[int]        =   replicate(A						)
           _UpperCAmelCase      :     Union[str, Any]        =   shard(A						)
           _UpperCAmelCase      :     int        =   shard(A						)

           _UpperCAmelCase      :     Tuple        =   pipe(
               prompt_ids=A					,     image=A					,     params=A					,     prng_seed=A					,     num_inference_steps=5_0					,     jit=A					,     ).images
           assert images.shape == (jax.device_count(), 1, 7_6_8, 5_1_2, 3)

           _UpperCAmelCase      :     int        =   images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]						)
           _UpperCAmelCase      :     Union[str, Any]        =   images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

           _UpperCAmelCase      :     Any        =   jnp.asarray(jax.device_get(image_slice.flatten()						)						)
           _UpperCAmelCase      :     Optional[int]        =   jnp.array(
               [0.167_969, 0.116_699, 0.081_543, 0.154_297, 0.132_812, 0.108_887, 0.169_922, 0.169_922, 0.205_078]						)
           print(f'output_slice: {output_slice}'						)
           assert jnp.abs(output_slice - expected_slice						).max() < 1e-2



      def 						snake_case_ (					self					:     Optional[Any]						):
           _UpperCAmelCase    ,	_UpperCAmelCase      :     Union[str, Any]        =   FlaxControlNetModel.from_pretrained(
               "lllyasviel/sd-controlnet-openpose"					,     from_pt=A					,     dtype=jnp.bfloataa						)
           _UpperCAmelCase    ,	_UpperCAmelCase      :     Tuple        =   FlaxStableDiffusionControlNetPipeline.from_pretrained(
               "runwayml/stable-diffusion-v1-5"					,     controlnet=A					,     from_pt=A					,     dtype=jnp.bfloataa						)
           _UpperCAmelCase      :     Optional[int]        =   controlnet_params

           _UpperCAmelCase      :     Any        =   "Chef in the kitchen"
           _UpperCAmelCase      :     List[str]        =   jax.device_count()
           _UpperCAmelCase      :     Optional[Any]        =   pipe.prepare_text_inputs([prompts] * num_samples						)

           _UpperCAmelCase      :     Optional[int]        =   load_image(
               "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png"						)
           _UpperCAmelCase      :     Tuple        =   pipe.prepare_image_inputs([pose_image] * num_samples						)

           _UpperCAmelCase      :     List[Any]        =   jax.random.PRNGKey(0						)
           _UpperCAmelCase      :     Dict        =   jax.random.split(A					,     jax.device_count()						)

           _UpperCAmelCase      :     str        =   replicate(A						)
           _UpperCAmelCase      :     Tuple        =   shard(A						)
           _UpperCAmelCase      :     Optional[int]        =   shard(A						)

           _UpperCAmelCase      :     Optional[int]        =   pipe(
               prompt_ids=A					,     image=A					,     params=A					,     prng_seed=A					,     num_inference_steps=5_0					,     jit=A					,     ).images
           assert images.shape == (jax.device_count(), 1, 7_6_8, 5_1_2, 3)

           _UpperCAmelCase      :     int        =   images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]						)
           _UpperCAmelCase      :     List[str]        =   images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

           _UpperCAmelCase      :     Dict        =   jnp.asarray(jax.device_get(image_slice.flatten()						)						)
           _UpperCAmelCase      :     Optional[Any]        =   jnp.array(
               [[0.271_484, 0.261_719, 0.275_391, 0.277_344, 0.279_297, 0.291_016, 0.294_922, 0.302_734, 0.302_734]]						)
           print(f'output_slice: {output_slice}'						)
           assert jnp.abs(output_slice - expected_slice						).max() < 1e-2





"""simple docstring"""




import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version

def 						__snake_case						(				*SCREAMING_SNAKE_CASE__     :						List[Any]						,  SCREAMING_SNAKE_CASE__     :						Optional[Union[Dict, Any]] = None						,  SCREAMING_SNAKE_CASE__     :						int=True						,  SCREAMING_SNAKE_CASE__     :						Tuple=2    )  ->       Optional[Any]:





     '''simple docstring'''

     from .. import __version__

     _UpperCAmelCase      :     Tuple        =   take_from
     _UpperCAmelCase      :     Optional[int]        =   ()
     if not isinstance(args[0]						,  SCREAMING_SNAKE_CASE__    ):
          _UpperCAmelCase      :     int        =   (args,)

     for attribute, version_name, message in args:
          if version.parse(version.parse(SCREAMING_SNAKE_CASE__    ).base_version    ) >= version.parse(SCREAMING_SNAKE_CASE__    ):
               raise ValueError(
                   f'The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers\''
                   f' version {__version__} is >= {version_name}'    )

          _UpperCAmelCase      :     Any        =   None
          if isinstance(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    ) and attribute in deprecated_kwargs:
               values += (deprecated_kwargs.pop(SCREAMING_SNAKE_CASE__    ),)
               _UpperCAmelCase      :     Tuple        =   f'The `{attribute}` argument is deprecated and will be removed in version {version_name}.'
          elif hasattr(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    ):
               values += (getattr(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    ),)
               _UpperCAmelCase      :     str        =   f'The `{attribute}` attribute is deprecated and will be removed in version {version_name}.'
          elif deprecated_kwargs is None:
               _UpperCAmelCase      :     Tuple        =   f'`{attribute}` is deprecated and will be removed in version {version_name}.'

          if warning is not None:
               _UpperCAmelCase      :     Optional[int]        =   warning + " " if standard_warn else ""
               warnings.warn(warning + message						,  SCREAMING_SNAKE_CASE__						,  stacklevel=SCREAMING_SNAKE_CASE__    )

     if isinstance(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    ) and len(SCREAMING_SNAKE_CASE__    ) > 0:
          _UpperCAmelCase      :     List[Any]        =   inspect.getouterframes(inspect.currentframe()    )[1]
          _UpperCAmelCase      :     Optional[int]        =   call_frame.filename
          _UpperCAmelCase      :     Dict        =   call_frame.lineno
          _UpperCAmelCase      :     List[Any]        =   call_frame.function
          _UpperCAmelCase    ,	_UpperCAmelCase      :     Optional[int]        =   next(iter(deprecated_kwargs.items()    )    )
          raise TypeError(f'{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`'    )

     if len(SCREAMING_SNAKE_CASE__    ) == 0:
          return
     elif len(SCREAMING_SNAKE_CASE__    ) == 1:
          return values[0]
     return values
