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4073 Enhance DynUNet doc-strings (#4102)
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* Fix doc strings error

Signed-off-by: Yiheng Wang <[email protected]>

* remove duplicate places

Signed-off-by: Yiheng Wang <[email protected]>
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yiheng-wang-nv authored Apr 11, 2022
1 parent 6602303 commit af6560a
Showing 1 changed file with 8 additions and 4 deletions.
12 changes: 8 additions & 4 deletions monai/networks/nets/dynunet.py
Original file line number Diff line number Diff line change
Expand Up @@ -74,10 +74,14 @@ class DynUNet(nn.Module):
is no less than 3 in order to have at least one downsample and upsample blocks.
To meet the requirements of the structure, the input size for each spatial dimension should be divisible
by `2 * the product of all strides in the corresponding dimension`. The output size for each spatial dimension
equals to the input size of the corresponding dimension divided by the stride in strides[0].
For example, if `strides=((1, 2, 4), 2, 1, 1)`, the minimal spatial size of the input is `(8, 16, 32)`, and
the spatial size of the output is `(8, 8, 8)`.
by the product of all strides in the corresponding dimension. In addition, the minimal spatial size should have
at least one dimension that has twice the size of the product of all strides.
For example, if `strides=((1, 2, 4), 2, 2, 1)`, the spatial size should be divisible by `(4, 8, 16)`,
and the minimal spatial size is `(8, 8, 16)` or `(4, 16, 16)` or `(4, 8, 32)`.
The output size for each spatial dimension equals to the input size of the corresponding dimension divided by the
stride in strides[0].
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)`.
For backwards compatibility with old weights, please set `strict=False` when calling `load_state_dict`.
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