void FixedUpdate()
{
Input2D input = InputManager.Instance.Input;
if (input.magnitude > 0.0f)
{
rb.position += input.vector * Time.deltaTime * DifficultyManager.Instance.playerSpeed;
rb.rotation = input.angle - 90;
}
}
public void Compile(ISequentialExecutor compiler)
{
// Compiling the model
compiler.Compile(descriptors);
compiled = compiler;
// Saving the input dimension
Input2D input = descriptors[0] as Input2D;
dim = new Dimension(input.Height, input.Width, input.Channels, input.Batch);
}
/** 作成。
*/
public static Input2D Create(Fee.Deleter.Deleter a_deleter, long a_drawpriority)
{
Input2D t_this = new Input2D();
{
t_this.inputfield = Fee.Render2D.InputField2D.Create(null, a_drawpriority);
if (a_deleter != null)
{
a_deleter.Regist(t_this);
}
}
return(t_this);
}
public ILayer CreateProduct(IKernelDescriptor descriptor)
{
if (descriptor is Input2D)
{
Input2D inputDescriptor = descriptor as Input2D;
Data2D data = new Data2D(inputDescriptor.Height, inputDescriptor.Width,
inputDescriptor.Channels, inputDescriptor.Batch);
data.ToZeros();
Input2DLayer layer = new Input2DLayer();
layer.SetInput(data);
return(layer);
}
return(null);
}
public void updateInput()
{
Vector2 inputVector = new Vector2(joystick.Horizontal, joystick.Vertical);
Input = new Input2D(inputVector);
}
// Start is called before the first frame update
void Start()
{
Input = new Input2D(Vector2.zero);
}
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);
}
