Make pretrain condition explicit

src/convnets/alexnet.jl

@@ -49,7 +49,9 @@ end
 
 function AlexNet(; pretrain = false, nclasses = 1000)
     layers = alexnet(; nclasses = nclasses)
-    pretrain && loadpretrain!(layers, "AlexNet")
+    if pretrain
+        loadpretrain!(layers, "AlexNet")
+    end
     return AlexNet(layers)
 end
 

src/convnets/densenet.jl

@@ -162,6 +162,8 @@ See also [`Metalhead.densenet`](#).
 function DenseNet(config::Integer = 121; pretrain = false, nclasses = 1000)
     @assert config in keys(densenet_config) "`config` must be one out of $(sort(collect(keys(densenet_config))))."
     model = DenseNet(densenet_config[config]; nclasses = nclasses)
-    pretrain && loadpretrain!(model, string("DenseNet", config))
+    if pretrain
+        loadpretrain!(model, string("DenseNet", config))
+    end
     return model
 end

src/convnets/googlenet.jl

@@ -86,7 +86,9 @@ end
 
 function GoogLeNet(; pretrain = false, nclasses = 1000)
     layers = googlenet(; nclasses = nclasses)
-    pretrain && loadpretrain!(layers, "GoogLeNet")
+    if pretrain
+        loadpretrain!(layers, "GoogLeNet")
+    end
     return GoogLeNet(layers)
 end
 

src/convnets/inception.jl

@@ -182,7 +182,9 @@ end
 
 function Inceptionv3(; pretrain = false, nclasses = 1000)
     layers = inceptionv3(; nclasses = nclasses)
-    pretrain && loadpretrain!(layers, "Inceptionv3")
+    if pretrain
+        loadpretrain!(layers, "Inceptionv3")
+    end
     return Inceptionv3(layers)
 end
 
@@ -341,7 +343,9 @@ end
 
 function Inceptionv4(; pretrain = false, inchannels = 3, drop_rate = 0.0, nclasses = 1000)
     layers = inceptionv4(; inchannels, drop_rate, nclasses)
-    pretrain && loadpretrain!(layers, "Inceptionv4")
+    if pretrain
+        loadpretrain!(layers, "Inceptionv4")
+    end
     return Inceptionv4(layers)
 end
 
@@ -476,7 +480,9 @@ end
 function InceptionResNetv2(; pretrain = false, inchannels = 3, drop_rate = 0.0,
                            nclasses = 1000)
     layers = inceptionresnetv2(; inchannels, drop_rate, nclasses)
-    pretrain && loadpretrain!(layers, "InceptionResNetv2")
+    if pretrain
+        loadpretrain!(layers, "InceptionResNetv2")
+    end
     return InceptionResNetv2(layers)
 end
 
@@ -584,7 +590,9 @@ Creates an Xception model.
 """
 function Xception(; pretrain = false, inchannels = 3, drop_rate = 0.0, nclasses = 1000)
     layers = xception(; inchannels, drop_rate, nclasses)
-    pretrain && loadpretrain!(layers, "xception")
+    if pretrain
+        loadpretrain!(layers, "xception")
+    end
     return Xception(layers)
 end
 

src/convnets/mobilenet.jl

@@ -90,7 +90,9 @@ end
 function MobileNetv1(width_mult::Number = 1; inchannels = 3, pretrain = false,
                      nclasses = 1000)
     layers = mobilenetv1(width_mult, mobilenetv1_configs; inchannels, nclasses)
-    pretrain && loadpretrain!(layers, string("MobileNetv1"))
+    if pretrain
+        loadpretrain!(layers, string("MobileNetv1"))
+    end
     return MobileNetv1(layers)
 end
 
@@ -189,6 +191,9 @@ function MobileNetv2(width_mult::Number = 1; inchannels = 3, pretrain = false,
                      nclasses = 1000)
     layers = mobilenetv2(width_mult, mobilenetv2_configs; inchannels, nclasses)
     pretrain && loadpretrain!(layers, string("MobileNetv2"))
+    if pretrain
+        loadpretrain!(layers, string("MobileNetv2"))
+    end
     return MobileNetv2(layers)
 end
 
@@ -319,7 +324,9 @@ function MobileNetv3(mode::Symbol = :small, width_mult::Number = 1; inchannels =
     max_width = (mode == :large) ? 1280 : 1024
     layers = mobilenetv3(width_mult, mobilenetv3_configs[mode]; inchannels, max_width,
                          nclasses)
-    pretrain && loadpretrain!(layers, string("MobileNetv3", mode))
+    if pretrain
+        loadpretrain!(layers, string("MobileNetv3", mode))
+    end
     return MobileNetv3(layers)
 end
 

src/convnets/squeezenet.jl

@@ -68,7 +68,9 @@ end
 
 function SqueezeNet(; pretrain = false)
     layers = squeezenet()
-    pretrain && loadpretrain!(layers, "SqueezeNet")
+    if pretrain
+        loadpretrain!(layers, "SqueezeNet")
+    end
     return SqueezeNet(layers)
 end