public override JObject ToJObject() { var jobj = new JObject(); jobj["units"] = _units; if (_inputShape != null) { jobj["input_shape"] = new JArray(_inputShape); } jobj["use_bias"] = _useBias; KerasUtils.AddActivation(jobj, _activation); KerasUtils.AddActivation(jobj, "recurrent_activation", _recurrentActivation); KerasUtils.AddStringOrObject(jobj, "kernel_initializer", _kernelInitializer); KerasUtils.AddStringOrObject(jobj, "recurrent_initializer", _recurrentInitializer); KerasUtils.AddStringOrObject(jobj, "bias_initializer", _biasInitializer); jobj["unit_forget_bias"] = _unitForgetBias; KerasUtils.AddStringOrObject(jobj, "kernel_regularizer", _kernelRegularizer); KerasUtils.AddStringOrObject(jobj, "recurrent_regularizer", _recurrentRegularizer); KerasUtils.AddStringOrObject(jobj, "bias_regularizer", _biasRegularizer); KerasUtils.AddStringOrObject(jobj, "activity_regularizer", _activityRegularizer); jobj["dropout"] = _dropout; jobj["recurrent_dropout"] = _recurrentDropout; jobj["op"] = "LSTM"; return(jobj); }
public override JObject ToJObject() { var jobj = new JObject(); jobj["units"] = _units; if (_inputShape != null) { jobj["input_shape"] = new JArray(_inputShape); } KerasUtils.AddActivation(jobj, _activation); if (_kernelInitializer.GetType() == typeof(string)) { jobj["kernel_initializer"] = (string)_kernelInitializer; } else { jobj["kernel_initializer"] = (_kernelInitializer as GraphOp).ToJObject(); } jobj["op"] = "Dense"; return(jobj); }
public override JObject ToJObject() { var jobj = new JObject(); jobj["filters"] = _filters; jobj["kernel_size"] = new JArray(_kernelSize); jobj["strides"] = new JArray(_strides); jobj["use_bias"] = _useBias; if (_inputShape != null) { jobj["input_shape"] = new JArray(_inputShape); } KerasUtils.AddActivation(jobj, _activation); jobj["bias_initializer"] = "zeros"; jobj.Add("op", "Conv2D"); return(jobj); }