Add remaining weights

Author: darsnack

Artifacts.toml

@@ -5,3 +5,67 @@ lazy = true
     [[vgg11.download]]
     sha256 = "9703268c19ca2ae34036ca3588664a96dc0ca8d9d6458db78657299c6879880c"
     url = "https://huggingface.co/FluxML/vgg11/resolve/275b202a8a4d10b59eef74285921d278b51fdbdb/vgg11.tar.gz"
+
+[vgg13]
+git-tree-sha1 = "ed006dd09cc24342d4dcd9e2cfaa8c84f063c27a"
+lazy = true
+
+    [[vgg13.download]]
+    sha256 = "ef27949024f5716f7656b3318b06964d76587851f15d9a9127c2b55e5faee288"
+    url = "https://huggingface.co/FluxML/vgg13/resolve/9593b269ee2c24ce5924d3667496a0d7458a6cb4/vgg13.tar.gz"
+
+[vgg16]
+git-tree-sha1 = "759df92ca502324d8624e1c5a940db227908fb9e"
+lazy = true
+
+    [[vgg16.download]]
+    sha256 = "f9bad8d9d2c79bc4ebab840f2faded2a0c26c6b2a84f979525964eebcd1886ab"
+    url = "https://huggingface.co/FluxML/vgg16/resolve/57fdb74b1640815f17eae1a28ae67f0fc1c603db/vgg16.tar.gz"
+
+[vgg19]
+git-tree-sha1 = "67f5e867f297086cc911c2cb7985bec8ac1ab23d"
+lazy = true
+
+    [[vgg19.download]]
+    sha256 = "5fe26391572b9f6ac84eaa0541d27e959f673f82e6515026cdcd3262cbd93ceb"
+    url = "https://huggingface.co/FluxML/vgg19/resolve/88e9056f60b054eccdc190a2eeb23731d5c693b6/vgg19.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"
+
+[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"

src/convnets/resnet.jl

@@ -258,6 +258,6 @@ function ResNet(depth::Integer = 50; pretrain = false, nclasses = 1000)
     @assert depth in keys(resnet_config) "`depth` must be one of $(sort(collect(keys(resnet_config))))"
     config, block = resnet_config[depth]
     model = ResNet(config...; block = block, nclasses = nclasses)
-    pretrain && loadpretrain!(model, string("ResNet", depth))
+    pretrain && loadpretrain!(model, string("resnet", depth))
     return model
 end

test/runtests.jl

@@ -3,7 +3,17 @@ using Flux
 using Flux: Zygote
 using Images
 
-const PRETRAINED_MODELS = [(VGG, 11, false)]
+const PRETRAINED_MODELS = [
+  (VGG, 11, false),
+  (VGG, 13, false),
+  (VGG, 16, false),
+  (VGG, 19, false),
+  (ResNet, 18),
+  (ResNet, 34),
+  (ResNet, 50),
+  (ResNet, 101),
+  (ResNet, 152),
+]
 
 function gradtest(model, input)
     y, pb = Zygote.pullback(() -> model(input), Flux.params(model))
@@ -29,9 +39,9 @@ const TEST_X = permutedims(convert(Array{Float32}, channelview(TEST_IMG)), (3,2,
 const TEST_LBLS = readlines(download("https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt"))
 
 function acctest(model)
-  @show ypred = Flux.onecold(model(TEST_X), TEST_LBLS)
+  ypred = Flux.onecold(model(TEST_X), TEST_LBLS)
 
-  return ypred == "acoustic guitar"
+  return only(ypred) == "acoustic guitar"
 end
 
 x_224 = rand(Float32, 224, 224, 3, 1)