mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Remove legacy/unused code
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@ -4,7 +4,6 @@ from invokeai.app.models.exceptions import CanceledException
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from invokeai.app.models.image import ProgressImage
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from ..invocations.baseinvocation import InvocationContext
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from ...backend.util.util import image_to_dataURL
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from ...backend.generator.base import Generator
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from ...backend.stable_diffusion import PipelineIntermediateState
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from invokeai.app.services.config import InvokeAIAppConfig
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from ...backend.model_management.models import BaseModelType
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@ -118,57 +117,3 @@ def stable_diffusion_step_callback(
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step=intermediate_state.step,
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total_steps=node["steps"],
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)
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def stable_diffusion_xl_step_callback(
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context: InvocationContext,
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node: dict,
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source_node_id: str,
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sample,
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step,
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total_steps,
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):
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if context.services.queue.is_canceled(context.graph_execution_state_id):
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raise CanceledException
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sdxl_latent_rgb_factors = torch.tensor(
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[
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# R G B
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[0.3816, 0.4930, 0.5320],
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[-0.3753, 0.1631, 0.1739],
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[0.1770, 0.3588, -0.2048],
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[-0.4350, -0.2644, -0.4289],
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],
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dtype=sample.dtype,
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device=sample.device,
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)
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sdxl_smooth_matrix = torch.tensor(
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[
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# [ 0.0478, 0.1285, 0.0478],
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# [ 0.1285, 0.2948, 0.1285],
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# [ 0.0478, 0.1285, 0.0478],
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[0.0358, 0.0964, 0.0358],
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[0.0964, 0.4711, 0.0964],
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[0.0358, 0.0964, 0.0358],
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],
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dtype=sample.dtype,
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device=sample.device,
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)
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image = sample_to_lowres_estimated_image(sample, sdxl_latent_rgb_factors, sdxl_smooth_matrix)
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(width, height) = image.size
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width *= 8
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height *= 8
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dataURL = image_to_dataURL(image, image_format="JPEG")
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context.services.events.emit_generator_progress(
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graph_execution_state_id=context.graph_execution_state_id,
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node=node,
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source_node_id=source_node_id,
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progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
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step=step,
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total_steps=total_steps,
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)
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