Skip to content

Commit

Permalink
WIP #541 Updated the GenArch tests
Browse files Browse the repository at this point in the history
  • Loading branch information
@brollb
brollb committed Jul 27, 2016
1 parent aae75c3 commit c9b7fd6
Show file tree
Hide file tree
Showing 3 changed files with 61 additions and 61 deletions.
2 changes: 1 addition & 1 deletion src/plugins/GenerateArchitecture/GenerateArchitecture.js
View file
Original file line number Diff line number Diff line change
Expand Up @@ -200,7 +200,7 @@ define([
fn = desc.setterFn[layer[setterNames[i]]];
layerCode += `:${fn}()`;
}
} else {
} else if (layer[setterNames[i]] !== null) {
fn = desc.setterFn;
layerCode += `:${fn}(${layer[setterNames[i]]})`;
}
Expand Down
108 changes: 54 additions & 54 deletions test/test-cases/generated-code/googlenet.lua
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,35 +3,35 @@ require 'nn'
local net = nn.Sequential()
net:add(nn.SpatialConvolution(3, 64, 7, 7, 2, 2, 3, 3))
net:add(nn.ReLU(true))
net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
net:add(nn.SpatialConvolution(64, 64, 1, 1))
net:add(nn.SpatialMaxPooling(3, 3, 2, 2, 0, 0))
net:add(nn.SpatialConvolution(64, 64, 1, 1, 0))
net:add(nn.ReLU(true))
net:add(nn.SpatialConvolution(64, 192, 3, 3, 1, 1, 1, 1))
net:add(nn.ReLU(true))
net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
net:add(nn.SpatialMaxPooling(3, 3, 2, 2, 0, 0))

local net_2 = nn.Sequential()
net_2:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
net_2:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
net_2:add(nn.ReLU(true))
net_2:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
net_2:add(nn.ReLU(true))
net_2:add(nn.SpatialConvolution(96, 96, 3, 3, 1, 1, 1, 1))
net_2:add(nn.ReLU(true))

local net_3 = nn.Sequential()
net_3:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
net_3:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
net_3:add(nn.ReLU(true))

local net_4 = nn.Sequential()
net_4:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
net_4:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
net_4:add(nn.ReLU(true))
net_4:add(nn.SpatialConvolution(64, 64, 3, 3, 1, 1, 1, 1))
net_4:add(nn.ReLU(true))

local net_5 = nn.Sequential()
net_5:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_5:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_5:add(nn.SpatialConvolution(192, 32, 1, 1, 1, 1))
net_5:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_5:add(nn.SpatialConvolution(192, 32, 1, 1, 1, 1, 0))
net_5:add(nn.ReLU(true))

local concat_24 = nn.Concat(2)
Expand All @@ -43,17 +43,17 @@ concat_24:add(net_2)
net:add(concat_24)

local net_6 = nn.Sequential()
net_6:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
net_6:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
net_6:add(nn.ReLU(true))

local net_7 = nn.Sequential()
net_7:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
net_7:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
net_7:add(nn.ReLU(true))
net_7:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
net_7:add(nn.ReLU(true))

local net_8 = nn.Sequential()
net_8:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
net_8:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
net_8:add(nn.ReLU(true))
net_8:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
net_8:add(nn.ReLU(true))
Expand All @@ -62,8 +62,8 @@ net_8:add(nn.ReLU(true))

local net_9 = nn.Sequential()
net_9:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_9:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_9:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
net_9:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_9:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
net_9:add(nn.ReLU(true))

local concat_41 = nn.Concat(2)
Expand All @@ -75,13 +75,13 @@ concat_41:add(net_6)
net:add(concat_41)

local net_10 = nn.Sequential()
net_10:add(nn.SpatialConvolution(320, 128, 1, 1, 1, 1))
net_10:add(nn.SpatialConvolution(320, 128, 1, 1, 1, 1, 0))
net_10:add(nn.ReLU(true))
net_10:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
net_10:add(nn.ReLU(true))

local net_11 = nn.Sequential()
net_11:add(nn.SpatialConvolution(320, 64, 1, 1, 1, 1))
net_11:add(nn.SpatialConvolution(320, 64, 1, 1, 1, 1, 0))
net_11:add(nn.ReLU(true))
net_11:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
net_11:add(nn.ReLU(true))
Expand All @@ -90,28 +90,28 @@ net_11:add(nn.ReLU(true))

local net_12 = nn.Sequential()
net_12:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_12:add(nn.SpatialMaxPooling(3, 3, 1, 1))
net_12:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))

local concat_54 = nn.Concat(2)
concat_54:add(net_12)
concat_54:add(net_11)
concat_54:add(net_10)

net:add(concat_54)
net:add(nn.SpatialConvolution(576, 576, 2, 2, 2, 2))
net:add(nn.SpatialConvolution(576, 576, 2, 2, 2, 2, 0))

local net_13 = nn.Sequential()
net_13:add(nn.SpatialConvolution(576, 224, 1, 1, 1, 1))
net_13:add(nn.SpatialConvolution(576, 224, 1, 1, 1, 1, 0))
net_13:add(nn.ReLU(true))

local net_14 = nn.Sequential()
net_14:add(nn.SpatialConvolution(576, 64, 1, 1, 1, 1))
net_14:add(nn.SpatialConvolution(576, 64, 1, 1, 1, 1, 0))
net_14:add(nn.ReLU(true))
net_14:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
net_14:add(nn.ReLU(true))

local net_15 = nn.Sequential()
net_15:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_15:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_15:add(nn.ReLU(true))
net_15:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
net_15:add(nn.ReLU(true))
Expand All @@ -120,8 +120,8 @@ net_15:add(nn.ReLU(true))

local net_16 = nn.Sequential()
net_16:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_16:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_16:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_16:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_16:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_16:add(nn.ReLU(true))

local concat_72 = nn.Concat(2)
Expand All @@ -133,17 +133,17 @@ concat_72:add(net_13)
net:add(concat_72)

local net_17 = nn.Sequential()
net_17:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
net_17:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1, 0))
net_17:add(nn.ReLU(true))

local net_18 = nn.Sequential()
net_18:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_18:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_18:add(nn.ReLU(true))
net_18:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
net_18:add(nn.ReLU(true))

local net_19 = nn.Sequential()
net_19:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_19:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_19:add(nn.ReLU(true))
net_19:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
net_19:add(nn.ReLU(true))
Expand All @@ -152,8 +152,8 @@ net_19:add(nn.ReLU(true))

local net_20 = nn.Sequential()
net_20:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_20:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_20:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_20:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_20:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_20:add(nn.ReLU(true))

local concat_89 = nn.Concat(2)
Expand All @@ -165,17 +165,17 @@ concat_89:add(net_17)
net:add(concat_89)

local net_21 = nn.Sequential()
net_21:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
net_21:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1, 0))
net_21:add(nn.ReLU(true))

local net_22 = nn.Sequential()
net_22:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_22:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_22:add(nn.ReLU(true))
net_22:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
net_22:add(nn.ReLU(true))

local net_23 = nn.Sequential()
net_23:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_23:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_23:add(nn.ReLU(true))
net_23:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
net_23:add(nn.ReLU(true))
Expand All @@ -184,8 +184,8 @@ net_23:add(nn.ReLU(true))

local net_24 = nn.Sequential()
net_24:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_24:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_24:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_24:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_24:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_24:add(nn.ReLU(true))

local concat_106 = nn.Concat(2)
Expand All @@ -197,17 +197,17 @@ concat_106:add(net_21)
net:add(concat_106)

local net_25 = nn.Sequential()
net_25:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_25:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_25:add(nn.ReLU(true))

local net_26 = nn.Sequential()
net_26:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_26:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_26:add(nn.ReLU(true))
net_26:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
net_26:add(nn.ReLU(true))

local net_27 = nn.Sequential()
net_27:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
net_27:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1, 0))
net_27:add(nn.ReLU(true))
net_27:add(nn.SpatialConvolution(160, 192, 3, 3, 1, 1, 1, 1))
net_27:add(nn.ReLU(true))
Expand All @@ -216,8 +216,8 @@ net_27:add(nn.ReLU(true))

local net_28 = nn.Sequential()
net_28:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_28:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_28:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
net_28:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_28:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
net_28:add(nn.ReLU(true))

local concat_123 = nn.Concat(2)
Expand All @@ -229,7 +229,7 @@ concat_123:add(net_25)
net:add(concat_123)

local net_29 = nn.Sequential()
net_29:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
net_29:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1, 0))
net_29:add(nn.ReLU(true))
net_29:add(nn.SpatialConvolution(192, 256, 3, 3, 1, 1, 1, 1))
net_29:add(nn.ReLU(true))
Expand All @@ -238,19 +238,19 @@ net_29:add(nn.ReLU(true))

local net_30 = nn.Sequential()
net_30:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_30:add(nn.SpatialMaxPooling(3, 3, 1, 1))
net_30:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))

local net_31 = nn.Sequential()
net_31:add(nn.SpatialAveragePooling(5, 5, 3, 3))
net_31:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_31:add(nn.SpatialAveragePooling(5, 5, 3, 3, 0, 0))
net_31:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_31:add(nn.View())
net_31:add(nn.Linear(2048, 768))
net_31:add(nn.ReLU())
net_31:add(nn.Linear(768, 4))
net_31:add(nn.LogSoftMax())

local net_32 = nn.Sequential()
net_32:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
net_32:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
net_32:add(nn.ReLU(true))
net_32:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
net_32:add(nn.ReLU(true))
Expand All @@ -262,20 +262,20 @@ concat_136:add(net_29)

net:add(concat_136)
local net_33 = nn.Sequential()
net_33:add(nn.SpatialConvolution(1024, 1024, 2, 2, 2, 2))
net_33:add(nn.SpatialConvolution(1024, 1024, 2, 2, 2, 2, 0))

local net_34 = nn.Sequential()
net_34:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
net_34:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1, 0))
net_34:add(nn.ReLU(true))

local net_35 = nn.Sequential()
net_35:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
net_35:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
net_35:add(nn.ReLU(true))
net_35:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
net_35:add(nn.ReLU(true))

local net_36 = nn.Sequential()
net_36:add(nn.SpatialConvolution(1024, 160, 1, 1, 1, 1))
net_36:add(nn.SpatialConvolution(1024, 160, 1, 1, 1, 1, 0))
net_36:add(nn.ReLU(true))
net_36:add(nn.SpatialConvolution(160, 224, 3, 3, 1, 1, 1, 1))
net_36:add(nn.ReLU(true))
Expand All @@ -284,8 +284,8 @@ net_36:add(nn.ReLU(true))

local net_37 = nn.Sequential()
net_37:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_37:add(nn.SpatialAveragePooling(3, 3, 1, 1))
net_37:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
net_37:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
net_37:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1, 0))
net_37:add(nn.ReLU(true))

local concat_154 = nn.Concat(2)
Expand All @@ -297,17 +297,17 @@ concat_154:add(net_34)
net_33:add(concat_154)

local net_38 = nn.Sequential()
net_38:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
net_38:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1, 0))
net_38:add(nn.ReLU(true))

local net_39 = nn.Sequential()
net_39:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
net_39:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
net_39:add(nn.ReLU(true))
net_39:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
net_39:add(nn.ReLU(true))

local net_40 = nn.Sequential()
net_40:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
net_40:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
net_40:add(nn.ReLU(true))
net_40:add(nn.SpatialConvolution(192, 224, 3, 3, 1, 1, 1, 1))
net_40:add(nn.ReLU(true))
Expand All @@ -316,8 +316,8 @@ net_40:add(nn.ReLU(true))

local net_41 = nn.Sequential()
net_41:add(nn.SpatialZeroPadding(1, 1, 1, 1))
net_41:add(nn.SpatialMaxPooling(3, 3, 1, 1))
net_41:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
net_41:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))
net_41:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1, 0))
net_41:add(nn.ReLU(true))

local concat_171 = nn.Concat(2)
Expand All @@ -327,7 +327,7 @@ concat_171:add(net_39)
concat_171:add(net_38)

net_33:add(concat_171)
net_33:add(nn.SpatialAveragePooling(7, 7, 1, 1))
net_33:add(nn.SpatialAveragePooling(7, 7, 1, 1, 0, 0))
net_33:add(nn.View())
net_33:add(nn.Linear(1024, 4))
net_33:add(nn.LogSoftMax())
Expand Down
12 changes: 6 additions & 6 deletions test/test-cases/generated-code/overfeat.lua
View file
Original file line number Diff line number Diff line change
@@ -1,19 +1,19 @@
require 'nn'

local net = nn.Sequential()
net:add(nn.SpatialConvolution(3, 96, 11, 11, 4, 4))
net:add(nn.SpatialConvolution(3, 96, 11, 11, 4, 4, 0))
net:add(nn.ReLU(true))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
net:add(nn.SpatialConvolution(96, 256, 5, 5, 1, 1))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
net:add(nn.SpatialConvolution(96, 256, 5, 5, 1, 1, 0))
net:add(nn.ReLU(true))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
net:add(nn.SpatialConvolution(256, 512, 3, 3, 1, 1, 1, 1))
net:add(nn.ReLU(true))
net:add(nn.SpatialConvolution(512, 1024, 3, 3, 1, 1, 1, 1))
net:add(nn.ReLU(true))
net:add(nn.SpatialConvolution(1024, 1024, 3, 3, 1, 1, 1, 1))
net:add(nn.ReLU(true))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
net:add(nn.View())
net:add(nn.Dropout(0.5))
net:add(nn.Linear(25600, 3072))
Expand All @@ -24,4 +24,4 @@ net:add(nn.Threshold(0, 0.000001))
net:add(nn.Linear(4096, 7))
net:add(nn.LogSoftMax())

return net
return net

0 comments on commit c9b7fd6

Please sign in to comment.