tf.contrib.distributions.MultivariateNormalCholesky.sample_n()

tf.contrib.distributions.MultivariateNormalCholesky.sample_n(n, seed=None, name='sample_n')

Generate n samples.

Args:

• n: Scalar Tensor of type int32 or int64, the number of observations to sample.
• seed: Python integer seed for RNG
• name: name to give to the op.

Returns:

• samples: a Tensor with a prepended dimension (n,).

Raises:

• TypeError: if n is not an integer type.