public static void Main()
{
Console.Write("Enter the password --> ");
string password = Console.ReadLine();
Permute perm = new Permute();
Console.Write("It takes {0} seconds.\n", perm.GetSeconds(perm.GetPermutations(password), 500000));
}
public static void PermuteExample()
{
Console.WriteLine("\nPermute Algorithm:");
var str = "abc";
char[] arr = str.ToCharArray();
Permute.GetPer(arr);
}
public ILayer CreateProduct(IKernelDescriptor descriptor)
{
if (descriptor is Permute)
{
Permute permute = descriptor as Permute;
ILayer layer = new PermuteLayer(permute.Dim1, permute.Dim2, permute.Dim3);
return(layer);
}
return(null);
}
static void Main()
{
Permute p = new Permute();
Console.WriteLine("Please enter N: ");
int n = int.Parse(Console.ReadLine());
int[] arr = new int[n];
for (int i = 0; i < arr.Length; i++)
{
arr[i] = i + 1;
}
Console.WriteLine();
Console.WriteLine("Permutations: ");
p.Setper(arr);
}
public Symmetric Extend(int len)
{
if (len < Size)
{
throw new ArgumentException("should be larger than size", nameof(len));
}
var res = new int[len];
Permute.CopyTo(res, 0);
for (int i = Size; i < len; i++)
{
res[i] = i;
}
return(new Symmetric(res));
}
static void Main()
{
Permute perm = new Permute();
int n = int.Parse(Console.ReadLine());
int[] arr = new int[n];
for (int i = 0; i < n; i++)
{
arr[i] = int.Parse(Console.ReadLine());
}
string permArr = string.Join("", arr);
char[] permCharArr = permArr.ToCharArray();
perm.setper(permCharArr);
}
public void GetPermutationsTest()
{
List <string> list = new List <string> {
"1", "2", "3", "4", "5"
};
IEnumerable <IEnumerable <string> > tmp = Permute.GetPermutations(list, list.Count);
foreach (IEnumerable <string> s in tmp)
{
Console.WriteLine(s.ToList());
}
int expected = 120;
int result = tmp.Count();
Assert.AreEqual(expected, result);
}
private List <IKernelDescriptor> ReadDescriptors(JObject model)
{
List <IKernelDescriptor> dscps = model.SelectToken("descriptors").Select(layer => {
IKernelDescriptor descriptor = null;
String layerName = (String)layer.SelectToken("layer");
switch (layerName)
{
case "AvgPooling1D":
descriptor = new AvgPooling1D(
(int)layer.SelectToken("padding"),
(int)layer.SelectToken("stride"),
(int)layer.SelectToken("kernel_size"));
break;
case "GlobalAveragePooling1D":
descriptor = new GlobalAvgPooling1D();
break;
case "AvgPooling2D":
descriptor = new AvgPooling2D((int)layer.SelectToken("padding_vl"), (int)layer.SelectToken("padding_hz"),
(int)layer.SelectToken("stride_vl"), (int)layer.SelectToken("stride_hz"),
(int)layer.SelectToken("kernel_height"), (int)layer.SelectToken("kernel_width"));
break;
case "GlobalAveragePooling2D":
descriptor = new GlobalAvgPooling2D();
break;
case "BatchNormalization":
descriptor = new BatchNormalization(
(int)layer.SelectToken("epsilon"));
break;
case "Cropping1D":
descriptor = new Cropping1D(
(int)layer.SelectToken("trimBegin"),
(int)layer.SelectToken("trimEnd"));
break;
case "Cropping2D":
descriptor = new Cropping2D(
(int)layer.SelectToken("topTrim"),
(int)layer.SelectToken("bottomTrim"),
(int)layer.SelectToken("leftTrim"),
(int)layer.SelectToken("rightTrim"));
break;
case "MaxPooling1D":
descriptor = new MaxPooling1D(
(int)layer.SelectToken("padding"),
(int)layer.SelectToken("stride"),
(int)layer.SelectToken("kernel_size"));
break;
case "GlobalMaxPooling1D":
descriptor = new GlobalMaxPooling1D();
break;
case "MaxPooling2D":
descriptor = new MaxPooling2D((int)layer.SelectToken("padding_vl"), (int)layer.SelectToken("padding_hz"),
(int)layer.SelectToken("stride_vl"), (int)layer.SelectToken("stride_hz"),
(int)layer.SelectToken("kernel_height"), (int)layer.SelectToken("kernel_width"));
break;
case "GlobalMaxPooling2D":
descriptor = new GlobalMaxPooling2D();
break;
case "Convolution1D":
descriptor = new Convolution1D(
(int)layer.SelectToken("padding"),
(int)layer.SelectToken("stride"),
(int)layer.SelectToken("kernel_size"),
(int)layer.SelectToken("kernel_num"));
break;
case "Convolution2D":
descriptor = new Convolution2D((int)layer.SelectToken("padding_vl"), (int)layer.SelectToken("padding_hz"),
(int)layer.SelectToken("stride_vl"), (int)layer.SelectToken("stride_hz"),
(int)layer.SelectToken("kernel_height"), (int)layer.SelectToken("kernel_width"),
(int)layer.SelectToken("kernel_num"));
break;
case "Dense2D":
descriptor = new Dense2D((int)layer.SelectToken("units"));
break;
case "Input2D":
descriptor = new Input2D((int)layer.SelectToken("height"), (int)layer.SelectToken("width"),
(int)layer.SelectToken("channel"), (int)layer.SelectToken("batch"));
break;
case "Bias2D":
descriptor = new Bias2D();
break;
case "Permute":
descriptor = new Permute(
(int)layer.SelectToken("dim1"),
(int)layer.SelectToken("dim2"),
(int)layer.SelectToken("dim3"));
break;
case "Reshape":
descriptor = new Reshape2D(
(int)layer.SelectToken("height"),
(int)layer.SelectToken("width"),
(int)layer.SelectToken("channel"),
1);
break;
case "RepeatVector":
descriptor = new RepeatVector(
(int)layer.SelectToken("num"));
break;
case "SimpleRNN":
descriptor = new SimpleRNN(
(int)layer.SelectToken("units"),
(int)layer.SelectToken("input_dim"),
ANR((string)layer.SelectToken("activation")));
break;
case "LSTM":
descriptor = new LSTM(
(int)layer.SelectToken("units"),
(int)layer.SelectToken("input_dim"),
ANR((string)layer.SelectToken("activation")),
ANR((string)layer.SelectToken("rec_act")));
break;
case "GRU":
descriptor = new GRU(
(int)layer.SelectToken("units"),
(int)layer.SelectToken("input_dim"),
ANR((string)layer.SelectToken("activation")),
ANR((string)layer.SelectToken("rec_act")));
break;
case "ELu":
descriptor = new ELu(1);
break;
case "HardSigmoid":
descriptor = new HardSigmoid();
break;
case "ReLu":
descriptor = new ReLu();
break;
case "Sigmoid":
descriptor = new Sigmoid();
break;
case "Flatten":
descriptor = new Flatten();
break;
case "Softmax":
descriptor = new Softmax();
break;
case "SoftPlus":
descriptor = new SoftPlus();
break;
case "SoftSign":
descriptor = new Softsign();
break;
case "TanH":
descriptor = new TanH();
break;
default:
throw new Exception("Unknown layer type!");
}
return(descriptor);
}).ToList();
return(dscps);
}
