I code a model for testing which takes 2 differnt tensors as input as follows:
Tensor input_wide = keras.Input(5);
Tensor input_deep = keras.Input(6);
var hidden1 = keras.layers.Dense(30, activation: keras.activations.Relu).Apply(input_deep);
var hidden2 = keras.layers.Dense(30, activation: keras.activations.Relu).Apply(hidden1);
var concat = keras.layers.Concatenate().Apply(new Tensors(input_wide, hidden2));
var output1 = keras.layers.Dense(1, activation: keras.activations.Relu).Apply(concat);
var output2 = keras.layers.Dense(1, activation: keras.activations.Relu).Apply(hidden2);
var model = keras.Model(new Tensors(input_wide, input_deep),
new Tensors(output1, output2)
);
model.compile(optimizer: keras.optimizers.Adam(),
loss: keras.losses.MeanSquaredError(),
new[] { "accuracy" });
Here I construct a Tensors with 2 tensor, which is assigned to the inputs of model. This model can be compiled without problems. Then I try to predict by this model:
// Just test data
var x1 = np.array(new float[,] { { 1, 2, 3, 4, 5 }, { 1, 3, 5, 7, 9 } });
var x2 = np.array(new float[,] { { 1, 2, 3, 4, 5, 6 }, { 1, 3, 5, 7, 9, 11 } });
var x = new Tensors(x1, x2);
var pred = model.predict(x);
Here I got an exception System.Collections.Generic.KeyNotFoundException:“The given key '3' was not present in the dictionary.”.Did I make a mistake or is it a bug? Many thanks.
I code a model for testing which takes 2 differnt tensors as input as follows:
Here I construct a Tensors with 2 tensor, which is assigned to the inputs of model. This model can be compiled without problems. Then I try to predict by this model:
Here I got an exception
System.Collections.Generic.KeyNotFoundException:“The given key '3' was not present in the dictionary.”.Did I make a mistake or is it a bug? Many thanks.