Regression tests of all methods on VGG19

[adrhill]

Metalhead disabled pretrained weights in 0.6.0 due to model inaccuracies.
These can technically still be loaded while they are being fixed:

model = VGG19()
Flux.loadparams!(model.layers, weights("vgg19"))

However, the VGG19 weights are a 548 MB download every time CI is run. It might therefore be more reasonable to use a smaller model. Currently, MetalheadWeights contains (in ascending size):

• SqueezeNet (5 MB) -> requires Parallel for "fire" modules
• GoogLeNet (27 MB) -> requires Parallel
• Densenet121 (31 MB) -> requires SkipConnection
• ResNet-50 (98 MB) -> requires Parallel, skip_identity
• VGG-19 (548 MB)

An easy workaround would be to run the methods on randomly initialized parameters (with fixed seed). The explanations w.r.t. to this model should still stay constant.