tfp.experimental.distributions.marginal_fns.ps.linspace

Generates evenly-spaced values in an interval along a given axis.

tfp.experimental.distributions.marginal_fns.ps.linspace(
    start, stop, num, name=None, axis=0
)

A sequence of num evenly-spaced values are generated beginning at start along a given axis. If num > 1, the values in the sequence increase by (stop - start) / (num - 1), so that the last one is exactly stop. If num <= 0, ValueError is raised.

Matches np.linspace's behaviour except when num == 0.

For example:

tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0  11.0  12.0]

Start and stop can be tensors of arbitrary size:

tf.linspace([0., 5.], [10., 40.], 5, axis=0)
<tf.Tensor: shape=(5, 2), dtype=float32, numpy=
array([[ 0.  ,  5.  ],
       [ 2.5 , 13.75],
       [ 5.  , 22.5 ],
       [ 7.5 , 31.25],
       [10.  , 40.  ]], dtype=float32)>

Axis is where the values will be generated (the dimension in the returned tensor which corresponds to the axis will be equal to num)

tf.linspace([0., 5.], [10., 40.], 5, axis=-1)
<tf.Tensor: shape=(2, 5), dtype=float32, numpy=
array([[ 0.  ,  2.5 ,  5.  ,  7.5 , 10.  ],
       [ 5.  , 13.75, 22.5 , 31.25, 40.  ]], dtype=float32)>

start A Tensor. Must be one of the following types: bfloat16, float32, float64. N-D tensor. First entry in the range.
stop A Tensor. Must have the same type and shape as start. N-D tensor. Last entry in the range.
num A Tensor. Must be one of the following types: int32, int64. 0-D tensor. Number of values to generate.
name A name for the operation (optional).
axis Axis along which the operation is performed (used only when N-D tensors are provided).

A Tensor. Has the same type as start.