本文整理匯總了Python中nn.AffineChannel2d方法的典型用法代碼示例。如果您正苦於以下問題：Python nn.AffineChannel2d方法的具體用法？Python nn.AffineChannel2d怎麽用？Python nn.AffineChannel2d使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nn的用法示例。
在下文中一共展示了nn.AffineChannel2d方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: _init_modules
# 需要導入模塊: import nn [as 別名]
# 或者: from nn import AffineChannel2d [as 別名]
def _init_modules(self):
assert cfg.RESNETS.FREEZE_AT in [0, 2, 3, 4, 5]
assert cfg.RESNETS.FREEZE_AT <= self.convX
for i in range(1, cfg.RESNETS.FREEZE_AT + 1):
freeze_params(getattr(self, 'res%d' % i))
# Freeze all bn (affine) layers !!!
self.apply(lambda m: freeze_params(m) if isinstance(m, mynn.AffineChannel2d) else None) 示例2: basic_bn_shortcut
# 需要導入模塊: import nn [as 別名]
# 或者: from nn import AffineChannel2d [as 別名]
def basic_bn_shortcut(inplanes, outplanes, stride):
return nn.Sequential(
nn.Conv2d(inplanes,
outplanes,
kernel_size=1,
stride=stride,
bias=False),
mynn.AffineChannel2d(outplanes),
) 示例3: basic_bn_stem
# 需要導入模塊: import nn [as 別名]
# 或者: from nn import AffineChannel2d [as 別名]
def basic_bn_stem():
return nn.Sequential(OrderedDict([
('conv1', nn.Conv2d(3, 64, 7, stride=2, padding=3, bias=False)),
('bn1', mynn.AffineChannel2d(64)),
('relu', nn.ReLU(inplace=True)),
# ('maxpool', nn.MaxPool2d(kernel_size=3, stride=2, padding=0, ceil_mode=True))]))
('maxpool', nn.MaxPool2d(kernel_size=3, stride=2, padding=1))])) 示例4: __init__
# 需要導入模塊: import nn [as 別名]
# 或者: from nn import AffineChannel2d [as 別名]
def __init__(self, dim_in, roi_xform_func, spatial_scale):
super().__init__()
self.dim_in = dim_in
self.roi_xform = roi_xform_func
self.spatial_scale = spatial_scale
self.dim_out = cfg.MRCNN.DIM_REDUCED
self.res5, dim_out = ResNet_roi_conv5_head_for_masks(dim_in)
self.upconv5 = nn.ConvTranspose2d(dim_out, self.dim_out, 2, 2, 0)
# Freeze all bn (affine) layers in resnet!!!
self.res5.apply(
lambda m: ResNet.freeze_params(m)
if isinstance(m, mynn.AffineChannel2d) else None)
self._init_weights()