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); }