Inline InputPadder (#6582)

inline InputPadder

examples/community/rerender_a_video.py

@@ -32,7 +32,6 @@ from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionS
 from diffusers.schedulers import KarrasDiffusionSchedulers
 from diffusers.utils import BaseOutput, deprecate, logging
 from diffusers.utils.torch_utils import is_compiled_module, randn_tensor
-from utils.utils import InputPadder  # noqa: E402
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
@@ -1172,3 +1171,24 @@ class RerenderAVideoPipeline(StableDiffusionControlNetImg2ImgPipeline):
             return output_frames
 
         return TextToVideoSDPipelineOutput(frames=output_frames)
+
+
+class InputPadder:
+    """Pads images such that dimensions are divisible by 8"""
+
+    def __init__(self, dims, mode="sintel", padding_factor=8):
+        self.ht, self.wd = dims[-2:]
+        pad_ht = (((self.ht // padding_factor) + 1) * padding_factor - self.ht) % padding_factor
+        pad_wd = (((self.wd // padding_factor) + 1) * padding_factor - self.wd) % padding_factor
+        if mode == "sintel":
+            self._pad = [pad_wd // 2, pad_wd - pad_wd // 2, pad_ht // 2, pad_ht - pad_ht // 2]
+        else:
+            self._pad = [pad_wd // 2, pad_wd - pad_wd // 2, 0, pad_ht]
+
+    def pad(self, *inputs):
+        return [F.pad(x, self._pad, mode="replicate") for x in inputs]
+
+    def unpad(self, x):
+        ht, wd = x.shape[-2:]
+        c = [self._pad[2], ht - self._pad[3], self._pad[0], wd - self._pad[1]]
+        return x[..., c[0] : c[1], c[2] : c[3]]