MobileNet tweaks

Author: theabhirath

src/convnets/mobilenet.jl

@@ -2,7 +2,6 @@
     mobilenetv1(width_mult, config;
                 activation = relu,
                 inchannels = 3,
-                fcsize = 1024,
                 nclasses = 1000)
 
 Create a MobileNetv1 model ([reference](https://arxiv.org/abs/1704.04861v1)).
@@ -19,14 +18,12 @@ Create a MobileNetv1 model ([reference](https://arxiv.org/abs/1704.04861v1)).
       + `s`: The stride of the convolutional kernel
       + `r`: The number of time this configuration block is repeated
   - `activate`: The activation function to use throughout the network
-  - `inchannels`: The number of input channels.
-  - `fcsize`: The intermediate fully-connected size between the convolution and final layers
+  - `inchannels`: The number of input channels. The default value is 3.
   - `nclasses`: The number of output classes
 """
 function mobilenetv1(width_mult, config;
                      activation = relu,
                      inchannels = 3,
-                     fcsize = 1024,
                      nclasses = 1000)
     layers = []
     for (dw, outch, stride, nrepeats) in config
@@ -35,8 +32,7 @@ function mobilenetv1(width_mult, config;
             layer = dw ?
                     depthwise_sep_conv_bn((3, 3), inchannels, outch, activation;
                                           stride = stride, pad = 1, bias = false) :
-                    conv_norm((3, 3), inchannels, outch, activation; stride = stride,
-                              pad = 1,
+                    conv_norm((3, 3), inchannels, outch, activation; stride, pad = 1,
                               bias = false)
             append!(layers, layer)
             inchannels = outch
@@ -46,8 +42,7 @@ function mobilenetv1(width_mult, config;
     return Chain(Chain(layers),
                  Chain(GlobalMeanPool(),
                        MLUtils.flatten,
-                       Dense(inchannels, fcsize, activation),
-                       Dense(fcsize, nclasses)))
+                       Dense(inchannels, nclasses)))
 end
 
 const mobilenetv1_configs = [