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Add activations_shape info in UNet models (#7482)
* Add activations_shape info in UNet models * activations_shape should be a list
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@ -847,6 +847,7 @@ class SpatialTransformer(nn.Module):
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if not isinstance(context, list):
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context = [context] * len(self.transformer_blocks)
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b, c, h, w = x.shape
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transformer_options["activations_shape"] = list(x.shape)
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x_in = x
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x = self.norm(x)
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if not self.use_linear:
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@ -962,6 +963,7 @@ class SpatialVideoTransformer(SpatialTransformer):
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transformer_options={}
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) -> torch.Tensor:
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_, _, h, w = x.shape
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transformer_options["activations_shape"] = list(x.shape)
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x_in = x
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spatial_context = None
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if exists(context):
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