


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


__UpperCAmelCase : int 			=				logging.get_logger(__name__)

__UpperCAmelCase : List[str] 			=				{
    "RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
    "RWKV/rwkv-4-430m-pile": "https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json",
    "RWKV/rwkv-4-1b5-pile": "https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json",
    "RWKV/rwkv-4-3b-pile": "https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json",
    "RWKV/rwkv-4-7b-pile": "https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json",
    "RWKV/rwkv-4-14b-pile": "https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json",
    "RWKV/rwkv-raven-1b5": "https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json",
    "RWKV/rwkv-raven-3b": "https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json",
    "RWKV/rwkv-raven-7b": "https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json",
    "RWKV/rwkv-raven-14b": "https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json",
}



class    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     Any							=					"rwkv"
       __UpperCamelCase      :     Any							=					{"max_position_embeddings": "context_length"}






       def __init__(     self ,					__SCREAMING_SNAKE_CASE=50_277 ,					__SCREAMING_SNAKE_CASE=1_024 ,					__SCREAMING_SNAKE_CASE=4_096 ,					__SCREAMING_SNAKE_CASE=32 ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=1e-5 ,					__SCREAMING_SNAKE_CASE=0 ,					__SCREAMING_SNAKE_CASE=0 ,					__SCREAMING_SNAKE_CASE=6 ,					__SCREAMING_SNAKE_CASE=False ,					__SCREAMING_SNAKE_CASE=True ,					**__SCREAMING_SNAKE_CASE ,					):




              """simple docstring"""




              UpperCamelCase    :	Optional[Any]   	=		vocab_size
              UpperCamelCase    :	Optional[int]   	=		context_length
              UpperCamelCase    :	str   	=		hidden_size
              UpperCamelCase    :	Dict   	=		num_hidden_layers
              UpperCamelCase    :	List[str]   	=		attention_hidden_size if attention_hidden_size is not None else hidden_size
              UpperCamelCase    :	Union[str, Any]   	=		intermediate_size if intermediate_size is not None else 4 * hidden_size
              UpperCamelCase    :	List[str]   	=		layer_norm_epsilon
              UpperCamelCase    :	Optional[int]   	=		rescale_every
              UpperCamelCase    :	Dict   	=		use_cache

              UpperCamelCase    :	str   	=		bos_token_id
              UpperCamelCase    :	Optional[int]   	=		eos_token_id

              super().__init__(
                  tie_word_embeddings=__SCREAMING_SNAKE_CASE ,					bos_token_id=__SCREAMING_SNAKE_CASE ,					eos_token_id=__SCREAMING_SNAKE_CASE ,					**__SCREAMING_SNAKE_CASE						)





import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


__UpperCAmelCase : Dict 			=				False



class    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''
       pass




@slow
@require_torch_gpu
class    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''						)
              pipe.to(__SCREAMING_SNAKE_CASE						)
              pipe.set_progress_bar_config(disable=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Union[str, Any]   	=		load_image(
                  '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''						)
              UpperCamelCase    :	str   	=		torch.manual_seed(0						)
              UpperCamelCase    :	Union[str, Any]   	=		pipe(
                  image=__SCREAMING_SNAKE_CASE ,					generator=__SCREAMING_SNAKE_CASE ,					guidance_scale=7.5 ,					num_inference_steps=50 ,					output_type='''numpy''' ,					).images

              UpperCamelCase    :	List[Any]   	=		image[0, 253:256, 253:256, -1]

              assert image.shape == (1, 512, 512, 3)
              UpperCamelCase    :	Dict   	=		np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]						)

              assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-2

