Interpolate fix on cuda for large output tensors (#10067)

* Workaround for upscale with large output tensors.

Fixes #10040.

* Fix scale when output_size is given

* Style

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Co-authored-by: Sayak Paul <[email protected]>

Author: pcuenca

src/diffusers/models/upsampling.py

@@ -165,6 +165,14 @@ def forward(self, hidden_states: torch.Tensor, output_size: Optional[int] = None
         # if `output_size` is passed we force the interpolation output
         # size and do not make use of `scale_factor=2`
         if self.interpolate:
+            # upsample_nearest_nhwc also fails when the number of output elements is large
+            # https://github.com/pytorch/pytorch/issues/141831
+            scale_factor = (
+                2 if output_size is None else max([f / s for f, s in zip(output_size, hidden_states.shape[-2:])])
+            )
+            if hidden_states.numel() * scale_factor > pow(2, 31):
+                hidden_states = hidden_states.contiguous()
+
             if output_size is None:
                 hidden_states = F.interpolate(hidden_states, scale_factor=2.0, mode="nearest")
             else: