_round_channels all the way

And `max_width` doesn't get width scaled

Author: theabhirath

src/convnets/builders/mbconv.jl

@@ -1,9 +1,9 @@
 function dwsepconv_builder(block_configs, inplanes::Integer, stage_idx::Integer,
                            width_mult::Real; norm_layer = BatchNorm, kwargs...)
     block_fn, k, outplanes, stride, nrepeats, activation = block_configs[stage_idx]
-    outplanes = floor(Int, outplanes * width_mult)
+    outplanes = _round_channels(outplanes * width_mult)
     if stage_idx != 1
-        inplanes = floor(Int, block_configs[stage_idx - 1][3] * width_mult)
+        inplanes = _round_channels(block_configs[stage_idx - 1][3] * width_mult)
     end
     function get_layers(block_idx::Integer)
         inplanes = block_idx == 1 ? inplanes : outplanes

src/convnets/mobilenets/mnasnet.jl

@@ -36,10 +36,9 @@ function mnasnet(block_configs::AbstractVector{<:Tuple}; width_mult::Real = 1,
     append!(layers, cnn_stages(get_layers, block_repeats, +))
     # building last layers
     outplanes = _round_channels(block_configs[end][3] * width_mult)
-    headplanes = _round_channels(max_width * max(1, width_mult))
     append!(layers,
-            conv_norm((1, 1), outplanes, headplanes, relu; norm_layer))
-    return Chain(Chain(layers...), create_classifier(headplanes, nclasses; dropout_rate))
+            conv_norm((1, 1), outplanes, max_width, relu; norm_layer))
+    return Chain(Chain(layers...), create_classifier(max_width, nclasses; dropout_rate))
 end
 
 # Layer configurations for MNasNet
@@ -115,7 +114,7 @@ function MNASNet(config::Symbol; width_mult::Real = 1, pretrain::Bool = false,
     inplanes, block_configs = MNASNET_CONFIGS[config]
     layers = mnasnet(block_configs; width_mult, inplanes, inchannels, nclasses)
     if pretrain
-        load_pretrained!(layers, "mnasnet$(width_mult)")
+        loadpretrain!(layers, "mnasnet$(width_mult)")
     end
     return MNASNet(layers)
 end

src/convnets/mobilenets/mobilenetv1.jl

@@ -27,13 +27,13 @@ function mobilenetv1(config::AbstractVector{<:Tuple}; width_mult::Real = 1,
                      nclasses::Integer = 1000)
     layers = []
     # stem of the model
-    inplanes = floor(Int, inplanes * width_mult)
+    inplanes = _round_channels(inplanes * width_mult)
     append!(layers,
             conv_norm((3, 3), inchannels, inplanes, activation; stride = 2, pad = 1))
     # building inverted residual blocks
     get_layers, block_repeats = mbconv_stack_builder(config, inplanes; width_mult)
     append!(layers, cnn_stages(get_layers, block_repeats))
-    outplanes = floor(Int, config[end][3] * width_mult)
+    outplanes = _round_channels(config[end][3] * width_mult)
     return Chain(Chain(layers...), create_classifier(outplanes, nclasses; dropout_rate))
 end
 

src/convnets/mobilenets/mobilenetv2.jl

@@ -44,7 +44,7 @@ function mobilenetv2(block_configs::AbstractVector{<:Tuple}; width_mult::Real =
 end
 
 # Layer configurations for MobileNetv2
-# f: block function - we use `dwsep_conv_bn` for the first block and `mbconv` for the rest
+# f: block function - we use `mbconv` for all blocks
 # k: kernel size
 # c: output channels
 # e: expansion factor