b0cd6a1df09c7157dea48265a5c21c3b7cc37399,softlearning/misc/nn.py,,feedforward_model,#Any#Any#Any#Any#Any#Any#,4

Before Change

            " shapes as an input. It might be possible that you passed in a"
            " list/tuple of dimension objects. Those should be accepted"
            " but have not yet been implemented.")
    inputs = [
        tf.keras.layers.Input(shape=input_shape)
        for input_shape in input_shapes
    ]

    if len(inputs) > 1:
        out = tf.keras.layers.Concatenate(axis=-1)(inputs)
    else:
        out = inputs[0]

    for units in hidden_layer_sizes:
        out = tf.keras.layers.Dense(
            units, *args, activation=activation, **kwargs)(out)

    out = tf.keras.layers.Dense(
        output_size, *args, activation=output_activation, **kwargs)(out)

After Change

    model.add(tf.keras.layers.Lambda(lambda x: tf.concat(x, axis=-1)))

    for units in hidden_layer_sizes:
        model.add(tf.keras.layers.Dense(
            units, *args, activation=activation, **kwargs))

    model.add(tf.keras.layers.Dense(
        output_size, *args, activation=output_activation, **kwargs))

Instances