Basic tiled decoding for audio VAE.
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comfy/sd.py
14
comfy/sd.py
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@ -298,6 +298,17 @@ class VAE:
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/ 3.0)
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return output
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def decode_tiled_1d(self, samples, tile_x=128, overlap=64):
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output = torch.empty((samples.shape[0], self.output_channels) + tuple(map(lambda a: a * self.upscale_ratio, samples.shape[2:])), device=self.output_device)
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for j in range(samples.shape[0]):
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for i in range(0, samples.shape[-1], tile_x - overlap):
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f = i
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t = i + tile_x
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output[j:j+1,:,f * self.upscale_ratio:t * self.upscale_ratio] = self.first_stage_model.decode(samples[j:j+1,:,f:t].to(self.vae_dtype).to(self.device)).float()
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return output
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def encode_tiled_(self, pixel_samples, tile_x=512, tile_y=512, overlap = 64):
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steps = pixel_samples.shape[0] * comfy.utils.get_tiled_scale_steps(pixel_samples.shape[3], pixel_samples.shape[2], tile_x, tile_y, overlap)
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steps += pixel_samples.shape[0] * comfy.utils.get_tiled_scale_steps(pixel_samples.shape[3], pixel_samples.shape[2], tile_x // 2, tile_y * 2, overlap)
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@ -325,6 +336,9 @@ class VAE:
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pixel_samples[x:x+batch_number] = self.process_output(self.first_stage_model.decode(samples).to(self.output_device).float())
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except model_management.OOM_EXCEPTION as e:
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logging.warning("Warning: Ran out of memory when regular VAE decoding, retrying with tiled VAE decoding.")
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if len(samples_in.shape) == 3:
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pixel_samples = self.decode_tiled_1d(samples_in)
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else:
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pixel_samples = self.decode_tiled_(samples_in)
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pixel_samples = pixel_samples.to(self.output_device).movedim(1,-1)
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