DenseNet should actually return a DenseNet

Author: theabhirath

Artifacts.toml

@@ -1,83 +1,3 @@
-[densenet121]
-git-tree-sha1 = "e929cd4de9255f65fe85e9365a0223e5876e7fb0"
-lazy = true
-
-    [[densenet121.download]]
-    sha256 = "0e9259a45097ded4d79a7b30d41ded7d799c7b08134ca65c84635b92100ce440"
-    url = "https://huggingface.co/FluxML/densenet121/resolve/442cd2e85d63b3aa7340deb786a02c2ccffa1590/densenet121.tar.gz"
-
-[densenet161]
-git-tree-sha1 = "d780a8eb8667bb2a840ed0685d937d311490aa1e"
-lazy = true
-
-    [[densenet161.download]]
-    sha256 = "5eb8a7c69c353a7e5756dfc041850e59b34b97821789fea8f73f1eff2d7c10d8"
-    url = "https://huggingface.co/FluxML/densenet161/resolve/dd02e5e0562620d187b2fd9b3a0994b0e2d85054/densenet161.tar.gz"
-
-[densenet169]
-git-tree-sha1 = "b8cc68d9554f8274d0c3e0385e04d2ee41090831"
-lazy = true
-
-    [[densenet169.download]]
-    sha256 = "8b9b182670ea6053f51db1542c133f183b4c0aa45f56e635598994a2f77fa39a"
-    url = "https://huggingface.co/FluxML/densenet169/resolve/9868bf1fb24592b6d7ee9aca70844eda859a3d3a/densenet169.tar.gz"
-
-[densenet201]
-git-tree-sha1 = "8d581b667da3e64a557a251876ebde6ee115a504"
-lazy = true
-
-    [[densenet201.download]]
-    sha256 = "4d6c6bae58ff586a82c8a4941cfba1709d1b1aec013fa3b188ce60df3e23e2aa"
-    url = "https://huggingface.co/FluxML/densenet201/resolve/4a39454fa8039b8d0546d8e60e2c98aa58e7a421/densenet201.tar.gz"
-
-[resnet101]
-git-tree-sha1 = "694a8563ec20fb826334dd663d532b10bb2b3c97"
-lazy = true
-
-    [[resnet101.download]]
-    sha256 = "f4d737ce640957c30f76bfa642fc9da23e6852d81474d58a2338c1148e55bff0"
-    url = "https://huggingface.co/FluxML/resnet101/resolve/ea37819163cc3f4a41989a6239ce505e483b112d/resnet101.tar.gz"
-
-[resnet152]
-git-tree-sha1 = "55eb883248a276d710d75ecaecfbd2427e50cc0a"
-lazy = true
-
-    [[resnet152.download]]
-    sha256 = "57be335e6828d1965c9d11f933d2d41f51e5e534f9bfdbde01c6144fa8862a4d"
-    url = "https://huggingface.co/FluxML/resnet152/resolve/ba28814d5746643387b5c0e1d2269104e5e9bc8d/resnet152.tar.gz"
-
-[resnet18]
-git-tree-sha1 = "7b555ed2708e551bfdbcb7e71b25001f4b3731c6"
-lazy = true
-
-    [[resnet18.download]]
-    sha256 = "d5782fd873a3072df251c7a4b3cf16efca8ee1da1180ff815bc107833f84bb26"
-    url = "https://huggingface.co/FluxML/resnet18/resolve/ef9c74047fda4a4a503b1f72553ec05acc90929f/resnet18.tar.gz"
-
-[resnet34]
-git-tree-sha1 = "e6e79666cd0fc81cd828508314e6c7f66df8d43d"
-lazy = true
-
-    [[resnet34.download]]
-    sha256 = "a8dec13609a86f7a2adac6a44b3af912a863bc2d7319120066c5fdaa04c3f395"
-    url = "https://huggingface.co/FluxML/resnet34/resolve/42061ddb463902885eea4fcc85275462a5445987/resnet34.tar.gz"
-
-[resnet50]
-git-tree-sha1 = "5c442ffd6c51a70c3bc36d849fca86beced446d4"
-lazy = true
-
-    [[resnet50.download]]
-    sha256 = "5325920ec91c2a4499ad7e659961f9eaac2b1a3a2905ca6410eaa593ecd35503"
-    url = "https://huggingface.co/FluxML/resnet50/resolve/10e601719e1cd5b0cab87ce7fd1e8f69a07ce042/resnet50.tar.gz"
-
-[squeezenet]
-git-tree-sha1 = "434ccb7258ebab5ca370cae40d13066539c28ca4"
-lazy = true
-
-    [[squeezenet.download]]
-    sha256 = "514d227721fd2e22ff664f94bb7fb7a6ebd668926705a19fe2209c0e9184ea3b"
-    url = "https://huggingface.co/FluxML/squeezenet/resolve/2ffca83e6317a7364459b1a249810637ab874077/squeezenet.tar.gz"
-
 [vgg11]
 git-tree-sha1 = "78ffe7d74c475cc28175f9e23a545ce2f17b1520"
 lazy = true

src/convnets/densenet.jl

@@ -100,8 +100,7 @@ Create a DenseNet model
   - `nclasses`: the number of output classes
 """
 function densenet(nblocks::AbstractVector{<:Integer}; growth_rate::Integer = 32,
-                  reduction = 0.5,
-                  inchannels::Integer = 3, nclasses::Integer = 1000)
+                  reduction = 0.5, inchannels::Integer = 3, nclasses::Integer = 1000)
     return densenet(2 * growth_rate, [fill(growth_rate, n) for n in nblocks];
                     reduction, inchannels, nclasses)
 end
@@ -133,11 +132,11 @@ end
 function DenseNet(config::Integer; pretrain::Bool = false, growth_rate::Integer = 32,
                   reduction = 0.5, inchannels::Integer = 3, nclasses::Integer = 1000)
     _checkconfig(config, keys(DENSENET_CONFIGS))
-    model = densenet(DENSENET_CONFIGS[config]; growth_rate, reduction, inchannels, nclasses)
+    layers = densenet(DENSENET_CONFIGS[config]; growth_rate, reduction, inchannels, nclasses)
     if pretrain
-        loadpretrain!(model, string("densenet", config))
+        loadpretrain!(layers, string("densenet", config))
     end
-    return model
+    return DenseNet(layers)
 end
 
 (m::DenseNet)(x) = m.layers(x)