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()
{
["input_dim"] = _inputDim,
["output_dim"] = _outputDim,
["mask_zero"] = _maskZero
};
KerasUtils.AddStringOrObject(jobj, "embedding_initializer", _embeddingInitializer);
KerasUtils.AddStringOrObject(jobj, "embedding_regularizer", _embeddingRegularizer);
if (_inputLength.HasValue)
{
jobj.Add("input_length", _inputLength.Value);
}
if (_inputShape != null)
{
jobj["input_shape"] = new JArray(_inputShape);
}
jobj["op"] = "Embedding";
return(jobj);
}
