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Revert exposing convNormActivation in ops #5472

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merged 2 commits into from
Feb 24, 2022
Merged

Revert exposing convNormActivation in ops #5472

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10e469e
Revert exposing convNormActivation in ops
jdsgomes Feb 24, 2022
3a7695c
Merge branch 'main' into revert_exposing_conv_norm_act
jdsgomes Feb 24, 2022
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1 change: 0 additions & 1 deletion docs/source/ops.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -45,5 +45,4 @@ Operators
FeaturePyramidNetwork
StochasticDepth
FrozenBatchNorm2d
ConvNormActivation
SqueezeExcitation
2 changes: 1 addition & 1 deletion torchvision/models/optical_flow/raft.py
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Expand Up @@ -6,7 +6,7 @@
from torch import Tensor
from torch.nn.modules.batchnorm import BatchNorm2d
from torch.nn.modules.instancenorm import InstanceNorm2d
from torchvision.ops import ConvNormActivation
from torchvision.ops.misc import ConvNormActivation
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@NicolasHug I added you are reviewer as this change touches the RAFT model and is meant to be cherrypicked in the v12.0 release, so I want to double check with you if you spot any problems with this?

For context on this discussion you can have a look at #5445

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I think this should be fine and we will literally undo this change immediately after introducing the Conv2dNormActivation


from ..._internally_replaced_utils import load_state_dict_from_url
from ...utils import _log_api_usage_once
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3 changes: 1 addition & 2 deletions torchvision/ops/__init__.py
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Expand Up @@ -14,7 +14,7 @@
from .feature_pyramid_network import FeaturePyramidNetwork
from .focal_loss import sigmoid_focal_loss
from .giou_loss import generalized_box_iou_loss
from .misc import FrozenBatchNorm2d, ConvNormActivation, SqueezeExcitation
from .misc import FrozenBatchNorm2d, SqueezeExcitation
from .poolers import MultiScaleRoIAlign
from .ps_roi_align import ps_roi_align, PSRoIAlign
from .ps_roi_pool import ps_roi_pool, PSRoIPool
Expand Down Expand Up @@ -51,7 +51,6 @@
"stochastic_depth",
"StochasticDepth",
"FrozenBatchNorm2d",
"ConvNormActivation",
"SqueezeExcitation",
"generalized_box_iou_loss",
]