Brian Broll
bfc1f08c7e
WIP #795 fixed the duplicate varnames WIP #795 only omit last unset values WIP #795 Replaced omitted, required values w/ nil WIP #795 Updated tests
342 linhas
9.8 KiB
Lua
342 linhas
9.8 KiB
Lua
require 'nn'
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require 'rnn'
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local net = nn.Sequential()
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net:add(nn.SpatialConvolution(3, 64, 7, 7, 2, 2, 3, 3))
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net:add(nn.ReLU(true))
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net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
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net:add(nn.SpatialConvolution(64, 64, 1, 1))
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net:add(nn.ReLU(true))
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net:add(nn.SpatialConvolution(64, 192, 3, 3, 1, 1, 1, 1))
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net:add(nn.ReLU(true))
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net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
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local net_2 = nn.Sequential()
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net_2:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
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net_2:add(nn.ReLU(true))
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net_2:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
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net_2:add(nn.ReLU(true))
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net_2:add(nn.SpatialConvolution(96, 96, 3, 3, 1, 1, 1, 1))
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net_2:add(nn.ReLU(true))
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local net_3 = nn.Sequential()
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net_3:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
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net_3:add(nn.ReLU(true))
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local net_4 = nn.Sequential()
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net_4:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
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net_4:add(nn.ReLU(true))
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net_4:add(nn.SpatialConvolution(64, 64, 3, 3, 1, 1, 1, 1))
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net_4:add(nn.ReLU(true))
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local net_5 = nn.Sequential()
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net_5:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_5:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_5:add(nn.SpatialConvolution(192, 32, 1, 1, 1, 1))
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net_5:add(nn.ReLU(true))
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local concat_24 = nn.Concat(2)
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concat_24:add(net_5)
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concat_24:add(net_4)
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concat_24:add(net_3)
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concat_24:add(net_2)
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net:add(concat_24)
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local net_6 = nn.Sequential()
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net_6:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
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net_6:add(nn.ReLU(true))
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local net_7 = nn.Sequential()
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net_7:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
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net_7:add(nn.ReLU(true))
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net_7:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
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net_7:add(nn.ReLU(true))
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local net_8 = nn.Sequential()
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net_8:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
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net_8:add(nn.ReLU(true))
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net_8:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
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net_8:add(nn.ReLU(true))
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net_8:add(nn.SpatialConvolution(96, 96, 3, 3, 1, 1, 1, 1))
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net_8:add(nn.ReLU(true))
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local net_9 = nn.Sequential()
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net_9:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_9:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_9:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
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net_9:add(nn.ReLU(true))
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local concat_41 = nn.Concat(2)
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concat_41:add(net_9)
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concat_41:add(net_8)
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concat_41:add(net_7)
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concat_41:add(net_6)
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net:add(concat_41)
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local net_10 = nn.Sequential()
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net_10:add(nn.SpatialConvolution(320, 128, 1, 1, 1, 1))
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net_10:add(nn.ReLU(true))
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net_10:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
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net_10:add(nn.ReLU(true))
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local net_11 = nn.Sequential()
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net_11:add(nn.SpatialConvolution(320, 64, 1, 1, 1, 1))
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net_11:add(nn.ReLU(true))
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net_11:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
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net_11:add(nn.ReLU(true))
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net_11:add(nn.SpatialConvolution(96, 96, 3, 3, 1, 1, 1, 1))
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net_11:add(nn.ReLU(true))
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local net_12 = nn.Sequential()
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net_12:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_12:add(nn.SpatialMaxPooling(3, 3, 1, 1))
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local concat_54 = nn.Concat(2)
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concat_54:add(net_12)
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concat_54:add(net_11)
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concat_54:add(net_10)
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net:add(concat_54)
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net:add(nn.SpatialConvolution(576, 576, 2, 2, 2, 2))
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local net_13 = nn.Sequential()
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net_13:add(nn.SpatialConvolution(576, 224, 1, 1, 1, 1))
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net_13:add(nn.ReLU(true))
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local net_14 = nn.Sequential()
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net_14:add(nn.SpatialConvolution(576, 64, 1, 1, 1, 1))
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net_14:add(nn.ReLU(true))
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net_14:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
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net_14:add(nn.ReLU(true))
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local net_15 = nn.Sequential()
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net_15:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_15:add(nn.ReLU(true))
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net_15:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
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net_15:add(nn.ReLU(true))
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net_15:add(nn.SpatialConvolution(128, 128, 3, 3, 1, 1, 1, 1))
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net_15:add(nn.ReLU(true))
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local net_16 = nn.Sequential()
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net_16:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_16:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_16:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_16:add(nn.ReLU(true))
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local concat_72 = nn.Concat(2)
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concat_72:add(net_16)
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concat_72:add(net_15)
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concat_72:add(net_14)
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concat_72:add(net_13)
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net:add(concat_72)
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local net_17 = nn.Sequential()
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net_17:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
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net_17:add(nn.ReLU(true))
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local net_18 = nn.Sequential()
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net_18:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_18:add(nn.ReLU(true))
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net_18:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
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net_18:add(nn.ReLU(true))
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local net_19 = nn.Sequential()
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net_19:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_19:add(nn.ReLU(true))
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net_19:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
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net_19:add(nn.ReLU(true))
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net_19:add(nn.SpatialConvolution(128, 128, 3, 3, 1, 1, 1, 1))
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net_19:add(nn.ReLU(true))
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local net_20 = nn.Sequential()
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net_20:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_20:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_20:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_20:add(nn.ReLU(true))
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local concat_89 = nn.Concat(2)
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concat_89:add(net_20)
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concat_89:add(net_19)
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concat_89:add(net_18)
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concat_89:add(net_17)
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net:add(concat_89)
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local net_21 = nn.Sequential()
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net_21:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
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net_21:add(nn.ReLU(true))
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local net_22 = nn.Sequential()
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net_22:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_22:add(nn.ReLU(true))
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net_22:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
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net_22:add(nn.ReLU(true))
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local net_23 = nn.Sequential()
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net_23:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_23:add(nn.ReLU(true))
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net_23:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
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net_23:add(nn.ReLU(true))
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net_23:add(nn.SpatialConvolution(160, 160, 3, 3, 1, 1, 1, 1))
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net_23:add(nn.ReLU(true))
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local net_24 = nn.Sequential()
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net_24:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_24:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_24:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_24:add(nn.ReLU(true))
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local concat_106 = nn.Concat(2)
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concat_106:add(net_24)
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concat_106:add(net_23)
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concat_106:add(net_22)
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concat_106:add(net_21)
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net:add(concat_106)
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local net_25 = nn.Sequential()
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net_25:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_25:add(nn.ReLU(true))
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local net_26 = nn.Sequential()
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net_26:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_26:add(nn.ReLU(true))
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net_26:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
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net_26:add(nn.ReLU(true))
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local net_27 = nn.Sequential()
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net_27:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
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net_27:add(nn.ReLU(true))
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net_27:add(nn.SpatialConvolution(160, 192, 3, 3, 1, 1, 1, 1))
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net_27:add(nn.ReLU(true))
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net_27:add(nn.SpatialConvolution(192, 192, 3, 3, 1, 1, 1, 1))
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net_27:add(nn.ReLU(true))
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local net_28 = nn.Sequential()
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net_28:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_28:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_28:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
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net_28:add(nn.ReLU(true))
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local concat_123 = nn.Concat(2)
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concat_123:add(net_28)
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concat_123:add(net_27)
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concat_123:add(net_26)
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concat_123:add(net_25)
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net:add(concat_123)
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local net_29 = nn.Sequential()
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net_29:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
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net_29:add(nn.ReLU(true))
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net_29:add(nn.SpatialConvolution(192, 256, 3, 3, 1, 1, 1, 1))
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net_29:add(nn.ReLU(true))
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net_29:add(nn.SpatialConvolution(256, 256, 3, 3, 1, 1, 1, 1))
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net_29:add(nn.ReLU(true))
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local net_30 = nn.Sequential()
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net_30:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_30:add(nn.SpatialMaxPooling(3, 3, 1, 1))
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local net_31 = nn.Sequential()
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net_31:add(nn.SpatialAveragePooling(5, 5, 3, 3))
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net_31:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_31:add(nn.View())
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net_31:add(nn.Linear(2048, 768))
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net_31:add(nn.ReLU())
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net_31:add(nn.Linear(768, 4))
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net_31:add(nn.LogSoftMax())
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local net_32 = nn.Sequential()
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net_32:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
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net_32:add(nn.ReLU(true))
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net_32:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
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net_32:add(nn.ReLU(true))
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local concat_143 = nn.Concat(2)
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concat_143:add(net_32)
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concat_143:add(net_30)
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concat_143:add(net_29)
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net:add(concat_143)
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local net_33 = nn.Sequential()
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net_33:add(nn.SpatialConvolution(1024, 1024, 2, 2, 2, 2))
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local net_34 = nn.Sequential()
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net_34:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
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net_34:add(nn.ReLU(true))
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local net_35 = nn.Sequential()
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net_35:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
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net_35:add(nn.ReLU(true))
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net_35:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
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net_35:add(nn.ReLU(true))
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local net_36 = nn.Sequential()
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net_36:add(nn.SpatialConvolution(1024, 160, 1, 1, 1, 1))
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net_36:add(nn.ReLU(true))
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net_36:add(nn.SpatialConvolution(160, 224, 3, 3, 1, 1, 1, 1))
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net_36:add(nn.ReLU(true))
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net_36:add(nn.SpatialConvolution(224, 224, 3, 3, 1, 1, 1, 1))
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net_36:add(nn.ReLU(true))
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local net_37 = nn.Sequential()
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net_37:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_37:add(nn.SpatialAveragePooling(3, 3, 1, 1))
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net_37:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
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net_37:add(nn.ReLU(true))
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local concat_161 = nn.Concat(2)
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concat_161:add(net_37)
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concat_161:add(net_36)
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concat_161:add(net_35)
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concat_161:add(net_34)
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net_33:add(concat_161)
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local net_38 = nn.Sequential()
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net_38:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
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net_38:add(nn.ReLU(true))
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local net_39 = nn.Sequential()
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net_39:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
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net_39:add(nn.ReLU(true))
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net_39:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
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net_39:add(nn.ReLU(true))
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local net_40 = nn.Sequential()
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net_40:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
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net_40:add(nn.ReLU(true))
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net_40:add(nn.SpatialConvolution(192, 224, 3, 3, 1, 1, 1, 1))
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net_40:add(nn.ReLU(true))
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net_40:add(nn.SpatialConvolution(224, 224, 3, 3, 1, 1, 1, 1))
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net_40:add(nn.ReLU(true))
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local net_41 = nn.Sequential()
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net_41:add(nn.SpatialZeroPadding(1, 1, 1, 1))
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net_41:add(nn.SpatialMaxPooling(3, 3, 1, 1))
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net_41:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
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net_41:add(nn.ReLU(true))
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local concat_178 = nn.Concat(2)
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concat_178:add(net_41)
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concat_178:add(net_40)
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concat_178:add(net_39)
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concat_178:add(net_38)
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net_33:add(concat_178)
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net_33:add(nn.SpatialAveragePooling(7, 7, 1, 1))
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net_33:add(nn.View())
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net_33:add(nn.Linear(1024, 4))
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net_33:add(nn.LogSoftMax())
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local concat_183 = nn.Concat(2)
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concat_183:add(net_33)
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concat_183:add(net_31)
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net:add(concat_183)
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return net |