From 88e6370527dbd602851de07d957a8f17b3ca9447 Mon Sep 17 00:00:00 2001 From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com> Date: Sun, 15 Feb 2026 17:43:53 -0800 Subject: [PATCH] Remove workaround for old pytorch. (#12480) --- comfy/ldm/modules/diffusionmodules/model.py | 14 +------------- 1 file changed, 1 insertion(+), 13 deletions(-) diff --git a/comfy/ldm/modules/diffusionmodules/model.py b/comfy/ldm/modules/diffusionmodules/model.py index 5a22ef030..805592aa5 100644 --- a/comfy/ldm/modules/diffusionmodules/model.py +++ b/comfy/ldm/modules/diffusionmodules/model.py @@ -102,19 +102,7 @@ class VideoConv3d(nn.Module): return self.conv(x) def interpolate_up(x, scale_factor): - try: - return torch.nn.functional.interpolate(x, scale_factor=scale_factor, mode="nearest") - except: #operation not implemented for bf16 - orig_shape = list(x.shape) - out_shape = orig_shape[:2] - for i in range(len(orig_shape) - 2): - out_shape.append(round(orig_shape[i + 2] * scale_factor[i])) - out = torch.empty(out_shape, dtype=x.dtype, layout=x.layout, device=x.device) - split = 8 - l = out.shape[1] // split - for i in range(0, out.shape[1], l): - out[:,i:i+l] = torch.nn.functional.interpolate(x[:,i:i+l].to(torch.float32), scale_factor=scale_factor, mode="nearest").to(x.dtype) - return out + return torch.nn.functional.interpolate(x, scale_factor=scale_factor, mode="nearest") class Upsample(nn.Module): def __init__(self, in_channels, with_conv, conv_op=ops.Conv2d, scale_factor=2.0):