JoshVarty

var tree = SyntaxFactory.ParseSyntaxTree(@"
using System;
namespace NS1
{
    public class C
    {
        int InstanceField = 0;
        internal void InstanceMethod()
        {
            Console.WriteLine(InstanceField);

JoshVarty

public class EmtpyStatementRemoval : CSharpSyntaxRewriter
{
    public override SyntaxNode VisitEmptyStatement(EmptyStatementSyntax node)
    {
        //Simply remove all Empty Statements
        return null;
    }
}

public static void Main(string[] args)

JoshVarty

using Microsoft.CodeAnalysis.CSharp;
using Microsoft.CodeAnalysis.CSharp.Syntax;

var tree = CSharpSyntaxTree.ParseText(@"
    public class MyClass
    {
        public void MyMethod()
        {
        }
    }");

JoshVarty

// Place your key bindings in this file to override the defaults
[
  {
  "key": "ctrl+k ctrl+o",
  "command": "workbench.action.files.openFolder"
  },
  {
  "key": "ctrl+o",
  "command": "workbench.action.files.openFile"
  },

JoshVarty

learner = load_learner('../data/cropped_faces','effnet_test.pkl',
                    test=ImageList.from_folder('/home/josh/git/kgl_deepfake/data/cropped_faces/valid'))

# Opening an image with fastai
fastai_img = open_image('/home/josh/git/kgl_deepfake/data/cropped_faces/valid/vylzsyazmx.mp4_1_REAL.jpg')
print(fastai_img.shape)

# Opening an image manually
manual_img = PILImage.open('/home/josh/git/kgl_deepfake/data/cropped_faces/valid/vylzsyazmx.mp4_1_REAL.jpg')
manual_img_array = np.array(manual_img, dtype=np.float32) / 255.

JoshVarty

var tree = CSharpSyntaxTree.ParseText(@"
    class MyClass
    {
        int myField = 0;
        public int MyProperty {get; set;}
        public void MyMethod() { }
    }");

var Mscorlib = PortableExecutableReference.CreateFromAssembly(typeof(object).Assembly);
var compilation = CSharpCompilation.Create("MyCompilation",

JoshVarty

def get_img_pil(path):
    img = Image.open(path)
    arr = np.asarray(img)
    img.close()
    del img
    return arr


def get_img_cv2(path):
    img = cv2.imread(path)

JoshVarty

learn.fit_one_cycle(10, max_lr=(1e-2))

JoshVarty

learn.fit_one_cycle(10, max_lr=(1e-2))

JoshVarty

learn = cnn_learner(data, models.resnet18, pretrained=False, metrics=[f_score])
learn.unfreeze()
learn.fit_one_cycle(10, max_lr=slice(1e-6,1e-2))