

import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


a_      =     logging.get_logger(__name__)






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			def __init__(      self				:			List[str]   ,   *a				:			Optional[int]   ,   **a				:			Dict						)				->							None:

				"""simple docstring"""

				warnings.warn(
				    "The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
				    " Please use LayoutLMv2ImageProcessor instead."   ,   a   ,   )
				super().__init__(*a   ,   **a						)


a_      =     frozenset(
    [
        'prompt',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
        'cross_attention_kwargs',
    ]
)

a_      =     frozenset(['prompt', 'negative_prompt'])

a_      =     frozenset([])

a_      =     frozenset(['image'])

a_      =     frozenset(
    [
        'image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['image'])

a_      =     frozenset(
    [
        'prompt',
        'image',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
    ]
)

a_      =     frozenset(['prompt', 'image', 'negative_prompt'])

a_      =     frozenset(
    [
        # Text guided image variation with an image mask
        'prompt',
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
    ]
)

a_      =     frozenset(['prompt', 'image', 'mask_image', 'negative_prompt'])

a_      =     frozenset(
    [
        # image variation with an image mask
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['image', 'mask_image'])

a_      =     frozenset(
    [
        'example_image',
        'image',
        'mask_image',
        'height',
        'width',
        'guidance_scale',
    ]
)

a_      =     frozenset(['example_image', 'image', 'mask_image'])

a_      =     frozenset(['class_labels'])

a_      =     frozenset(['class_labels'])

a_      =     frozenset(['batch_size'])

a_      =     frozenset([])

a_      =     frozenset(['batch_size'])

a_      =     frozenset([])

a_      =     frozenset(
    [
        'prompt',
        'audio_length_in_s',
        'guidance_scale',
        'negative_prompt',
        'prompt_embeds',
        'negative_prompt_embeds',
        'cross_attention_kwargs',
    ]
)

a_      =     frozenset(['prompt', 'negative_prompt'])
a_      =     frozenset(['input_tokens'])

a_      =     frozenset(['input_tokens'])