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src/diffusers/pipelines/sana/pipeline_sana_sprint_img2img.py

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@@ -18,9 +18,9 @@
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import urllib.parse as ul
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import warnings
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from typing import Any, Callable, Dict, List, Optional, Tuple, Union
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import torch.nn.functional as F
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import torch
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import torch.nn.functional as F
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from transformers import Gemma2PreTrainedModel, GemmaTokenizer, GemmaTokenizerFast
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from ...callbacks import MultiPipelineCallbacks, PipelineCallback
@@ -591,8 +591,7 @@ def prepare_image(
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image = image.unsqueeze(0)
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# Resize if current dimensions do not match target dimensions.
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if image.shape[2] != height or image.shape[3] != width:
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image = F.interpolate(image, size=(height, width), mode="bilinear",
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align_corners=False)
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image = F.interpolate(image, size=(height, width), mode="bilinear", align_corners=False)
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image = self.image_processor.preprocess(image, height=height, width=width)
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