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Python FunctionSet.conv4_29_1方法代码示例

本文整理汇总了Python中chainer.FunctionSet.conv4_29_1方法的典型用法代码示例。如果您正苦于以下问题:Python FunctionSet.conv4_29_1方法的具体用法?Python FunctionSet.conv4_29_1怎么用?Python FunctionSet.conv4_29_1使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在chainer.FunctionSet的用法示例。


在下文中一共展示了FunctionSet.conv4_29_1方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: __init__

# 需要导入模块: from chainer import FunctionSet [as 别名]
# 或者: from chainer.FunctionSet import conv4_29_1 [as 别名]

#.........这里部分代码省略.........
            conv4_18_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_18_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_18_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_19_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_19_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_19_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_20_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_20_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_20_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_21_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_21_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_21_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_22_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_22_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_22_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_23_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_23_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_23_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_24_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_24_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_24_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_25_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_25_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_25_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_26_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_26_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_26_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_27_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_27_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_27_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_28_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_28_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_28_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_29_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_29_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_29_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_30_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_30_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_30_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_31_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_31_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_31_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_32_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_32_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_32_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_33_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_33_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_33_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_34_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_34_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_34_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_35_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_35_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_35_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv4_36_1=F.Convolution2D(1024,  256,  1, wscale=w, stride=1),
            conv4_36_2=F.Convolution2D(256,  256,  3, wscale=w, stride=1, pad=1),
            conv4_36_3=F.Convolution2D(256,  1024,  1, wscale=w, stride=1),
            conv5_1_1=F.Convolution2D(1024,  512,  1, wscale=w, stride=2),
            conv5_1_2=F.Convolution2D(512,  512,  3, wscale=w, stride=1, pad=1),
            conv5_1_3=F.Convolution2D(512,  2048,  1, wscale=w, stride=1),
            conv5_1_ex=F.Convolution2D(1024,  2048,  1, wscale=w, stride=2),
            conv5_2_1=F.Convolution2D(2048,  512,  1, wscale=w, stride=1),
            conv5_2_2=F.Convolution2D(512,  512,  3, wscale=w, stride=1, pad=1),
            conv5_2_3=F.Convolution2D(512,  2048,  1, wscale=w, stride=1),
            conv5_3_1=F.Convolution2D(2048,  512,  1, wscale=w, stride=1),
            conv5_3_2=F.Convolution2D(512,  512,  3, wscale=w, stride=1, pad=1),
开发者ID:imenurok,项目名称:TouhouAItest,代码行数:70,代码来源:DQN.py


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