# tf.contrib.distributions.tridiag

tf.contrib.distributions.tridiag(
below=None,
diag=None,
above=None,
name=None
)


Creates a matrix with values set above, below, and on the diagonal.

Example:

tridiag(below=[1., 2., 3.],
diag=[4., 5., 6., 7.],
above=[8., 9., 10.])
# ==> array([[  4.,   8.,   0.,   0.],
#            [  1.,   5.,   9.,   0.],
#            [  0.,   2.,   6.,  10.],
#            [  0.,   0.,   3.,   7.]], dtype=float32)


#### Args:

• below: Tensor of shape [B1, ..., Bb, d-1] corresponding to the below diagonal part. None is logically equivalent to below = 0.
• diag: Tensor of shape [B1, ..., Bb, d] corresponding to the diagonal part. None is logically equivalent to diag = 0.
• above: Tensor of shape [B1, ..., Bb, d-1] corresponding to the above diagonal part. None is logically equivalent to above = 0.
• name: Python str. The name to give this op.

#### Returns:

• tridiag: Tensor with values set above, below and on the diagonal.

#### Raises:

• ValueError: if all inputs are None.