tf.contrib.distributions.bijectors.masked_dense

A autoregressively masked dense layer. (deprecated)

tf.contrib.distributions.bijectors.masked_dense(
    inputs, units, num_blocks=None, exclusive=False, kernel_initializer=None,
    reuse=None, name=None, *args, **kwargs
)

Analogous to tf.compat.v1.layers.dense.

See [Germain et al. (2015)][1] for detailed explanation.

Arguments
inputs	Tensor input.
units	Python int scalar representing the dimensionality of the output space.
num_blocks	Python int scalar representing the number of blocks for the MADE masks.
exclusive	Python bool scalar representing whether to zero the diagonal of the mask, used for the first layer of a MADE.
kernel_initializer	Initializer function for the weight matrix. If None (default), weights are initialized using the tf.glorot_random_initializer.
reuse	Python bool scalar representing whether to reuse the weights of a previous layer by the same name.
name	Python str used to describe ops managed by this function.
*args	tf.compat.v1.layers.dense arguments.
**kwargs	tf.compat.v1.layers.dense keyword arguments.

Returns
Output tensor.

Raises
NotImplementedError	if rightmost dimension of inputs is unknown prior to graph execution.

References

[1]: Mathieu Germain, Karol Gregor, Iain Murray, and Hugo Larochelle. MADE: Masked Autoencoder for Distribution Estimation. In International Conference on Machine Learning, 2015. https://arxiv.org/abs/1502.03509