本文整理匯總了Python中torch.nn.Conv2DBatchNorm方法的典型用法代碼示例。如果您正苦於以下問題：Python nn.Conv2DBatchNorm方法的具體用法？Python nn.Conv2DBatchNorm怎麽用？Python nn.Conv2DBatchNorm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torch.nn的用法示例。
在下文中一共展示了nn.Conv2DBatchNorm方法的3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__
# 需要導入模塊: from torch import nn [as 別名]
# 或者: from torch.nn import Conv2DBatchNorm [as 別名]
def __init__(self, in_channels, n_filters, stride=1, downsample=None):
super(residualBottleneck, self).__init__()
self.convbn1 = nn.Conv2DBatchNorm(in_channels, n_filters, k_size=1, bias=False)
self.convbn2 = nn.Conv2DBatchNorm(n_filters, n_filters, k_size=3, padding=1, stride=stride, bias=False)
self.convbn3 = nn.Conv2DBatchNorm(n_filters, n_filters * 4, k_size=1, bias=False)
self.relu = nn.ReLU(inplace=True)
self.downsample = downsample
self.stride = stride 示例2: __init__
# 需要導入模塊: from torch import nn [as 別名]
# 或者: from torch.nn import Conv2DBatchNorm [as 別名]
def __init__(self, in_channels, n_filters, stride=1, downsample=None):
super(residualBottleneck, self).__init__()
self.convbn1 = nn.Conv2DBatchNorm(in_channels, n_filters, k_size=1, bias=False)
self.convbn2 = nn.Conv2DBatchNorm(
n_filters, n_filters, k_size=3, padding=1, stride=stride, bias=False
)
self.convbn3 = nn.Conv2DBatchNorm(
n_filters, n_filters * 4, k_size=1, bias=False
)
self.relu = nn.ReLU(inplace=True)
self.downsample = downsample
self.stride = stride 示例3: __init__
# 需要導入模塊: from torch import nn [as 別名]
# 或者: from torch.nn import Conv2DBatchNorm [as 別名]
def __init__(self, in_channels, n_filters, stride=1, downsample=None):
super(residualBottleneck, self).__init__()
self.convbn1 = nn.Conv2DBatchNorm(in_channels, n_filters, k_size=1, bias=False)
self.convbn2 = nn.Conv2DBatchNorm(
n_filters, n_filters, k_size=3, padding=1, stride=stride, bias=False
)
self.convbn3 = nn.Conv2DBatchNorm(n_filters, n_filters * 4, k_size=1, bias=False)
self.relu = nn.ReLU(inplace=True)
self.downsample = downsample
self.stride = stride