Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tfl.lattice_lib.random_monotonic_initializer

View source on GitHub

Returns a uniformly random sampled monotonic lattice layer weight tensor.

tfl.lattice_lib.random_monotonic_initializer(
    lattice_sizes, output_min, output_max, units=1, dtype=tf.float32
)
  • The uniform random monotonic function will initilaize the lattice parameters uniformly at random and make it such that the parameters are monotonically increasing for each input.
  • The random parameters will be sampled from [output_min, output_max]

Args:

  • lattice_sizes: List or tuple of integers which represents lattice sizes.
  • output_min: Minimum output of lattice layer after initialization.
  • output_max: Maximum output of lattice layer after initialization.
  • units: Output dimension of the layer. Each of units lattices will be initialized identically.
  • dtype: dtype.

Returns:

Lattice weights tensor of shape: (prod(lattice_sizes), units).