


"""simple docstring"""




import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
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		):



    """simple docstring"""






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






    def _a (      self   )  ->	str:
         __UpperCamelCase   							=load_image(
             'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
             '/sd2-inpaint/init_image.png'   )
         __UpperCamelCase   							=load_image(
             'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png'   )

         __UpperCamelCase   							="xvjiarui/stable-diffusion-2-inpainting"
         __UpperCamelCase   							=FlaxStableDiffusionInpaintPipeline.from_pretrained(_SCREAMING_SNAKE_CASE ,       safety_checker=_SCREAMING_SNAKE_CASE   )

         __UpperCamelCase   							="Face of a yellow cat, high resolution, sitting on a park bench"

         __UpperCamelCase   							=jax.random.PRNGKey(0   )
         __UpperCamelCase   							=50

         __UpperCamelCase   							=jax.device_count()
         __UpperCamelCase   							=num_samples * [prompt]
         __UpperCamelCase   							=num_samples * [init_image]
         __UpperCamelCase   							=num_samples * [mask_image]
         __UpperCamelCase   							=pipeline.prepare_inputs(_SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE   )

         # shard inputs and rng
         __UpperCamelCase   							=replicate(_SCREAMING_SNAKE_CASE   )
         __UpperCamelCase   							=jax.random.split(_SCREAMING_SNAKE_CASE ,       jax.device_count()   )
         __UpperCamelCase   							=shard(_SCREAMING_SNAKE_CASE   )
         __UpperCamelCase   							=shard(_SCREAMING_SNAKE_CASE   )
         __UpperCamelCase   							=shard(_SCREAMING_SNAKE_CASE   )

         __UpperCamelCase   							=pipeline(
             _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       _SCREAMING_SNAKE_CASE ,       jit=_SCREAMING_SNAKE_CASE   )

         __UpperCamelCase   							=output.images.reshape(_SCREAMING_SNAKE_CASE ,       512 ,       512 ,       3   )

         __UpperCamelCase   							=images[0, 253:256, 253:256, -1]

         __UpperCamelCase   							=jnp.asarray(jax.device_get(image_slice.flatten()   )   )
         __UpperCamelCase   							=jnp.array(
             [0.361_1307, 0.3764_9736, 0.375_7408, 0.3821_3953, 0.3929_5167, 0.384_1631, 0.4155_4978, 0.413_7475, 0.421_7084]   )
         print(f'output_slice: {output_slice}'   )
         assert jnp.abs(output_slice - expected_slice   ).max() < 1E-2









from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A			=						logging.get_logger(__name__)

_A			=						{
    'google/realm-cc-news-pretrained-embedder': (
        'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-encoder': (
        'https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-scorer': (
        'https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json'
    ),
    'google/realm-cc-news-pretrained-openqa': (
        'https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json'
    ),
    'google/realm-orqa-nq-openqa': 'https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json',
    'google/realm-orqa-nq-reader': 'https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json',
    'google/realm-orqa-wq-openqa': 'https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json',
    'google/realm-orqa-wq-reader': 'https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json',
    # See all REALM models at https://huggingface.co/models?filter=realm
}






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    UpperCAmelCase__						:		str              =  "realm"






    def __init__(      self ,       A_=30522 ,       A_=768 ,       A_=128 ,       A_=12 ,       A_=12 ,       A_=8 ,       A_=3072 ,       A_="gelu_new" ,       A_=0.1 ,       A_=0.1 ,       A_=512 ,       A_=2 ,       A_=0.02 ,       A_=1E-12 ,       A_=256 ,       A_=10 ,       A_=1E-3 ,       A_=5 ,       A_=320 ,       A_=13353718 ,       A_=5000 ,       A_=1 ,       A_=0 ,       A_=2 ,       **A_ ,       )  ->	Dict:
         super().__init__(pad_token_id=A_ ,       bos_token_id=A_ ,       eos_token_id=A_ ,       **A_   )

         # Common config
         __UpperCamelCase   							=vocab_size
         __UpperCamelCase   							=max_position_embeddings
         __UpperCamelCase   							=hidden_size
         __UpperCamelCase   							=retriever_proj_size
         __UpperCamelCase   							=num_hidden_layers
         __UpperCamelCase   							=num_attention_heads
         __UpperCamelCase   							=num_candidates
         __UpperCamelCase   							=intermediate_size
         __UpperCamelCase   							=hidden_act
         __UpperCamelCase   							=hidden_dropout_prob
         __UpperCamelCase   							=attention_probs_dropout_prob
         __UpperCamelCase   							=initializer_range
         __UpperCamelCase   							=type_vocab_size
         __UpperCamelCase   							=layer_norm_eps

         # Reader config
         __UpperCamelCase   							=span_hidden_size
         __UpperCamelCase   							=max_span_width
         __UpperCamelCase   							=reader_layer_norm_eps
         __UpperCamelCase   							=reader_beam_size
         __UpperCamelCase   							=reader_seq_len

         # Retrieval config
         __UpperCamelCase   							=num_block_records
         __UpperCamelCase   							=searcher_beam_size





