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[Fix] Rename init_weight to init_weights #971

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Apr 20, 2021
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[Fix] Rename init_weight to init_weights #971

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[Fix] Rename init_weight to init_weights
MeowZheng Apr 20, 2021
0cd43df
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MeowZheng Apr 20, 2021
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8 changes: 4 additions & 4 deletions mmcv/runner/base_module.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,19 +34,19 @@ def __init__(self, init_cfg=None):
def is_init(self):
return self._is_init

def init_weight(self):
def init_weights(self):
"""Initialize the weights."""
from ..cnn import initialize

if not self._is_init:
if self.init_cfg:
initialize(self, self.init_cfg)
for m in self.children():
if hasattr(m, 'init_weight'):
m.init_weight()
if hasattr(m, 'init_weights'):
m.init_weights()
self._is_init = True
else:
warnings.warn(f'init_weight of {self.__class__.__name__} has '
warnings.warn(f'init_weights of {self.__class__.__name__} has '
f'been called more than once.')

def __repr__(self):
Expand Down
18 changes: 9 additions & 9 deletions tests/test_runner/test_basemodule.py
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Expand Up @@ -119,7 +119,7 @@ def test_model_weight_init():
conv1d=dict(type='FooConv1d')))

model = build_from_cfg(model_cfg, FOOMODELS)
model.init_weight()
model.init_weights()

assert torch.equal(model.component1.conv1d.weight,
torch.full(model.component1.conv1d.weight.shape, 3.0))
Expand Down Expand Up @@ -199,7 +199,7 @@ def test_nest_components_weight_init():
conv1d=dict(type='FooConv1d')))

model = build_from_cfg(model_cfg, FOOMODELS)
model.init_weight()
model.init_weights()

assert torch.equal(model.component1.conv1d.weight,
torch.full(model.component1.conv1d.weight.shape, 7.0))
Expand Down Expand Up @@ -243,7 +243,7 @@ def test_without_layer_weight_init():
component2=dict(type='FooConv2d'),
component3=dict(type='FooLinear'))
model = build_from_cfg(model_cfg, FOOMODELS)
model.init_weight()
model.init_weights()

assert torch.equal(model.component1.conv1d.weight,
torch.full(model.component1.conv1d.weight.shape, 3.0))
Expand Down Expand Up @@ -276,7 +276,7 @@ def test_override_weight_init():
component1=dict(type='FooConv1d'),
component3=dict(type='FooLinear'))
model = build_from_cfg(model_cfg, FOOMODELS)
model.init_weight()
model.init_weights()
assert torch.equal(model.reg.weight,
torch.full(model.reg.weight.shape, 10.0))
assert torch.equal(model.reg.bias, torch.full(model.reg.bias.shape, 20.0))
Expand Down Expand Up @@ -308,7 +308,7 @@ def test_override_weight_init():
component2=dict(type='FooConv2d'),
component3=dict(type='FooLinear'))
model = build_from_cfg(model_cfg, FOOMODELS)
model.init_weight()
model.init_weights()

assert torch.equal(model.reg.weight,
torch.full(model.reg.weight.shape, 30.0))
Expand All @@ -326,7 +326,7 @@ def test_sequential_model_weight_init():
]
layers = [build_from_cfg(cfg, COMPONENTS) for cfg in seq_model_cfg]
seq_model = Sequential(*layers)
seq_model.init_weight()
seq_model.init_weights()
assert torch.equal(seq_model[0].conv1d.weight,
torch.full(seq_model[0].conv1d.weight.shape, 0.))
assert torch.equal(seq_model[0].conv1d.bias,
Expand All @@ -341,7 +341,7 @@ def test_sequential_model_weight_init():
*layers,
init_cfg=dict(
type='Constant', layer=['Conv1d', 'Conv2d'], val=4., bias=5.))
seq_model.init_weight()
seq_model.init_weights()
assert torch.equal(seq_model[0].conv1d.weight,
torch.full(seq_model[0].conv1d.weight.shape, 0.))
assert torch.equal(seq_model[0].conv1d.bias,
Expand All @@ -363,7 +363,7 @@ def test_modulelist_weight_init():
]
layers = [build_from_cfg(cfg, COMPONENTS) for cfg in models_cfg]
modellist = ModuleList(layers)
modellist.init_weight()
modellist.init_weights()
assert torch.equal(modellist[0].conv1d.weight,
torch.full(modellist[0].conv1d.weight.shape, 0.))
assert torch.equal(modellist[0].conv1d.bias,
Expand All @@ -378,7 +378,7 @@ def test_modulelist_weight_init():
layers,
init_cfg=dict(
type='Constant', layer=['Conv1d', 'Conv2d'], val=4., bias=5.))
modellist.init_weight()
modellist.init_weights()
assert torch.equal(modellist[0].conv1d.weight,
torch.full(modellist[0].conv1d.weight.shape, 0.))
assert torch.equal(modellist[0].conv1d.bias,
Expand Down