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fix: atrous_rates for deeplabv3_mobilenet_v3_large (fixes #7956) #8019
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Thanks for the PR @nvs-abhilash .
I made a few comments below regarding preserving backward compatibility.
@fmassa , do you remember why the values [12, 24, 36]
were used for the atrous rates in #820, instead of [6, 12, 18]
?
@@ -220,7 +220,7 @@ def _deeplabv3_mobilenetv3( | |||
backbone = IntermediateLayerGetter(backbone, return_layers=return_layers) | |||
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aux_classifier = FCNHead(aux_inplanes, num_classes) if aux else None | |||
classifier = DeepLabHead(out_inplanes, num_classes) | |||
classifier = DeepLabHead(out_inplanes, num_classes, atrous_rates=(6, 12, 18)) |
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Unfortunately this would be BC-breaking. We'll have to preserve the values that are currently used here (relying on the default).
classifier = DeepLabHead(out_inplanes, num_classes, atrous_rates=(6, 12, 18)) | |
classifier = DeepLabHead(out_inplanes, num_classes) |
@@ -83,7 +83,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor: | |||
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class ASPP(nn.Module): | |||
def __init__(self, in_channels: int, atrous_rates: List[int], out_channels: int = 256) -> None: | |||
def __init__(self, in_channels: int, atrous_rates: Tuple[int, int, int], out_channels: int = 256) -> None: |
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From my understanding, using List[int]
instead of a fixed 3-tuple was intended (details in #2136).
def __init__(self, in_channels: int, atrous_rates: Tuple[int, int, int], out_channels: int = 256) -> None: | |
def __init__(self, in_channels: int, atrous_rates: List[int], out_channels: int = 256) -> None: |
@@ -46,9 +46,9 @@ class DeepLabV3(_SimpleSegmentationModel): | |||
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class DeepLabHead(nn.Sequential): | |||
def __init__(self, in_channels: int, num_classes: int) -> None: | |||
def __init__(self, in_channels: int, num_classes: int, atrous_rates: Tuple[int, int, int] = (12, 24, 36)) -> None: |
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def __init__(self, in_channels: int, num_classes: int, atrous_rates: Tuple[int, int, int] = (12, 24, 36)) -> None: | |
def __init__(self, in_channels: int, num_classes: int, atrous_rates: List[int] = [12, 24, 36]) -> None: |
Hi, Thanks for the PR! The dilation rates could have been an oversight when porting the DeepLab head into MobileNetV3. Changing the defaults will change the outputs produced by the models, so I agree with @NicolasHug to keep the same defaults as before. |
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Thanks, @NicolasHug and @fmassa for reviewing my code. Post your comments, the only change that seems to make sense is just to parameterise the Also, what can be the path to solve #7956 ? |
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Thanks @nvs-abhilash , LGTM with one last comment below
@@ -46,9 +46,9 @@ class DeepLabV3(_SimpleSegmentationModel): | |||
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class DeepLabHead(nn.Sequential): | |||
def __init__(self, in_channels: int, num_classes: int) -> None: | |||
def __init__(self, in_channels: int, num_classes: int, atrous_rates: List[int] = [12, 24, 36]) -> None: |
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We should avoid setting mutables as default values in general as there's a risk that we will change that value inplace, and subsequent calls would be using the wrong default.
def __init__(self, in_channels: int, num_classes: int, atrous_rates: List[int] = [12, 24, 36]) -> None: | |
def __init__(self, in_channels: int, num_classes: int, atrous_rates: Sequence[int] = (12, 24, 36)) -> None: |
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Yeah, makes sense. I thought the same, therefore had made it tuple before. 😅
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Updated the PR.
Would documenting the atrous rates being used be enough? |
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Thanks a lot @nvs-abhilash
Hey @NicolasHug! You merged this PR, but no labels were added. The list of valid labels is available at https://github.com/pytorch/vision/blob/main/.github/process_commit.py |
) (#8019) Summary: Co-authored-by: Nicolas Hug <[email protected]> Reviewed By: vmoens Differential Revision: D50789082 fbshipit-source-id: 02bbe21ba09522b2db1552c6a677b89ff4247392
This PR addresses the issue reffered in #7956
The PR proposes the following changes to address the issues:
DeepLabHead
.Send (6, 12, 18) atrous_rates for mobilenet backbone