tensorflow_probability/examples/deep_exponential_family.py
def deep_exponential_family_variational(data_size, feature_size, units):
  """Posterior approx. for deep exponential family p(w{0,1,2}, z{1,2,3} | x)."""
  qw2 = trainable_positive_deterministic([units[2], units[1]], name="qw2")
  qw1 = trainable_positive_deterministic([units[1], units[0]], name="qw1")
  qw0 = trainable_positive_deterministic([units[0], feature_size], name="qw0")
  qz2 = trainable_gamma([data_size, units[2]], name="qz2")
  qz1 = trainable_gamma([data_size, units[1]], name="qz1")
  qz0 = trainable_gamma([data_size, units[0]], name="qz0")
  return qw2, qw1, qw0, qz2, qz1, qz0
def deep_exponential_family_variational(data_size, feature_size, units):
  """Posterior approx. for deep exponential family p(w{0,1,2}, z{1,2,3} | x)."""
  qw2 = trainable_positive_deterministic([units[2], units[1]], name="qw2")
  qw1 = trainable_positive_deterministic([units[1], units[0]], name="qw1")
  qw0 = trainable_positive_deterministic([units[0], feature_size], name="qw0")
  qz2 = trainable_gamma([data_size, units[2]], name="qz2")
  qz1 = trainable_gamma([data_size, units[1]], name="qz1")
  qz0 = trainable_gamma([data_size, units[0]], name="qz0")
  return qw2, qw1, qw0, qz2, qz1, qz0
def deep_exponential_family_variational ( data_size , feature_size , units ) : qw2 = trainable_positive_deterministic ( [ units [ 2 ] , units [ 1 ] ] , name = "qw2" ) qw1 = trainable_positive_deterministic ( [ units [ 1 ] , units [ 0 ] ] , name = "qw1" ) qw0 = trainable_positive_deterministic ( [ units [ 0 ] , feature_size ] , name = "qw0" ) qz2 = trainable_gamma ( [ data_size , units [ 2 ] ] , name = "qz2" ) qz1 = trainable_gamma ( [ data_size , units [ 1 ] ] , name = "qz1" ) qz0 = trainable_gamma ( [ data_size , units [ 0 ] ] , name = "qz0" ) return qw2 , qw1 , qw0 , qz2 , qz1 , qz0
Posterior approx. for deep exponential family p(w{0,1,2}, z{1,2,3} | x).
Posterior approx . for deep exponential family p ( w { 0 1 2 } z { 1 2 3 } | x ) .