tfp.experimental.distributions.marginal_fns.ps.zeros_like

Creates a tensor with all elements set to zero.

tfp.experimental.distributions.marginal_fns.ps.zeros_like(
    input, dtype=None, name=None, layout=None
)

See also tf.zeros.

Given a single tensor or array-like object (input), this operation returns a tensor of the same type and shape as input with all elements set to zero. Optionally, you can use dtype to specify a new type for the returned tensor.

Note that the layout of the input tensor is not preserved if the op is used inside tf.function. To obtain a tensor with the same layout as the input, chain the returned value to a dtensor.relayout_like.

>>> tensor = tf.constant([[1, 2, 3], [4, 5, 6]])
>>> tf.zeros_like(tensor)
<tf.Tensor: shape=(2, 3), dtype=int32, numpy=
array([[0, 0, 0],
       [0, 0, 0]], dtype=int32)>

tf.zeros_like(tensor, dtype=tf.float32)
<tf.Tensor: shape=(2, 3), dtype=float32, numpy=
array([[0., 0., 0.],
       [0., 0., 0.]], dtype=float32)>
 
tf.zeros_like([[1, 2, 3], [4, 5, 6]])
<tf.Tensor: shape=(2, 3), dtype=int32, numpy=
array([[0, 0, 0],
       [0, 0, 0]], dtype=int32)>

input A Tensor or array-like object.
dtype A type for the returned Tensor. Must be float16, float32, float64, int8, uint8, int16, uint16, int32, int64, complex64, complex128, bool or string (optional).
name A name for the operation (optional).
layout Optional, tf.experimental.dtensor.Layout. If provided, the result is a DTensor with the provided layout.

A Tensor with all elements set to zero.