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Fix typo in BaseHead default loss_factor. #446

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merged 4 commits into from
Dec 16, 2020
Merged

Fix typo in BaseHead default loss_factor. #446

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eab20ff
Fix typo in default BaseHead.
Dec 15, 2020
7f6e9ea
Minor fix unittest.
Dec 15, 2020
cb61191
Add changelog.
Dec 15, 2020
3a6f1f0
Fix docstring.
Dec 15, 2020
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1 change: 1 addition & 0 deletions docs/changelog.md
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@


**Bug and Typo Fixes**
- Fix typo in default argument of BaseHead. ([#446](https://github.com/open-mmlab/mmaction2/pull/446))

**ModelZoo**

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4 changes: 2 additions & 2 deletions mmaction/models/heads/base.py
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Expand Up @@ -36,7 +36,7 @@ class BaseHead(nn.Module, metaclass=ABCMeta):
num_classes (int): Number of classes to be classified.
in_channels (int): Number of channels in input feature.
loss_cls (dict): Config for building loss.
Default: dict(type='CrossEntropyLoss').
Default: dict(type='CrossEntropyLoss', loss_weight=1.0).
multi_class (bool): Determines whether it is a multi-class
recognition task. Default: False.
label_smooth_eps (float): Epsilon used in label smooth.
Expand All @@ -46,7 +46,7 @@ class BaseHead(nn.Module, metaclass=ABCMeta):
def __init__(self,
num_classes,
in_channels,
loss_cls=dict(type='CrossEntropyLoss', loss_factor=1.0),
loss_cls=dict(type='CrossEntropyLoss', loss_weight=1.0),
multi_class=False,
label_smooth_eps=0.0):
super().__init__()
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11 changes: 10 additions & 1 deletion tests/test_models/test_head.py
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Expand Up @@ -6,7 +6,7 @@


class ExampleHead(BaseHead):
# use a ExampleHead to success BaseHead
# use an ExampleHead to test BaseHead
def init_weights(self):
pass

Expand All @@ -24,6 +24,15 @@ def test_base_head():
assert 'loss_cls' in losses.keys()
assert losses.get('loss_cls') > 0, 'cls loss should be non-zero'

head = ExampleHead(3, 400, dict(type='CrossEntropyLoss', loss_weight=2.0))

cls_scores = torch.rand((3, 4))
# When truth is non-empty then cls loss should be nonzero for random inputs
gt_labels = torch.LongTensor([2] * 3).squeeze()
losses = head.loss(cls_scores, gt_labels)
assert 'loss_cls' in losses.keys()
assert losses.get('loss_cls') > 0, 'cls loss should be non-zero'


def test_i3d_head():
"""Test loss method, layer construction, attributes and forward function in
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