Thresholded Rectified Linear Unit.

    It follows: f(x) = x for x > theta, f(x) = 0 otherwise.

    layer_activation_thresholded_relu(
      object,
      theta = 1,
      input_shape = NULL,
      batch_input_shape = NULL,
      batch_size = NULL,
      dtype = NULL,
      name = NULL,
      trainable = NULL,
      weights = NULL
    )

    Arguments

    object

    Model or layer object

    theta

    float >= 0. Threshold location of activation.

    input_shape

    Input shape (list of integers, does not include the samples axis) which is required when using this layer as the first layer in a model.

    batch_input_shape

    Shapes, including the batch size. For instance, batch_input_shape=c(10, 32) indicates that the expected input will be batches of 10 32-dimensional vectors. batch_input_shape=list(NULL, 32) indicates batches of an arbitrary number of 32-dimensional vectors.

    batch_size

    Fixed batch size for layer

    dtype

    The data type expected by the input, as a string (float32, float64, int32...)

    name

    An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.

    trainable

    Whether the layer weights will be updated during training.

    weights

    Initial weights for layer.

    See also