@@ -74,10 +74,14 @@ class DynUNet(nn.Module):
7474 is no less than 3 in order to have at least one downsample and upsample blocks.
7575
7676 To meet the requirements of the structure, the input size for each spatial dimension should be divisible
77- by `2 * the product of all strides in the corresponding dimension`. The output size for each spatial dimension
78- equals to the input size of the corresponding dimension divided by the stride in strides[0].
79- For example, if `strides=((1, 2, 4), 2, 1, 1)`, the minimal spatial size of the input is `(8, 16, 32)`, and
80- the spatial size of the output is `(8, 8, 8)`.
77+ by the product of all strides in the corresponding dimension. In addition, the minimal spatial size should have
78+ at least one dimension that has twice the size of the product of all strides.
79+ For example, if `strides=((1, 2, 4), 2, 2, 1)`, the spatial size should be divisible by `(4, 8, 16)`,
80+ and the minimal spatial size is `(8, 8, 16)` or `(4, 16, 16)` or `(4, 8, 32)`.
81+
82+ The output size for each spatial dimension equals to the input size of the corresponding dimension divided by the
83+ stride in strides[0].
84+ For example, if `strides=((1, 2, 4), 2, 2, 1)` and the input size is `(64, 32, 32)`, the output size is `(64, 16, 8)`.
8185
8286 For backwards compatibility with old weights, please set `strict=False` when calling `load_state_dict`.
8387
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