tfp.experimental.distributions.marginal_fns.ps.identity

Return a Tensor with the same shape and contents as input.

tfp.experimental.distributions.marginal_fns.ps.identity(
    input, name=None
)

The return value is not the same Tensor as the original, but contains the same values. This operation is fast when used on the same device.

For example:

a = tf.constant([0.78])
a_identity = tf.identity(a)
a.numpy()
array([0.78], dtype=float32)
a_identity.numpy()
array([0.78], dtype=float32)

Calling tf.identity on a variable will make a Tensor that represents the value of that variable at the time it is called. This is equivalent to calling <variable>.read_value().

a = tf.Variable(5)
a_identity = tf.identity(a)
a.assign_add(1)
<tf.Variable ... shape=() dtype=int32, numpy=6>
a.numpy()
6
a_identity.numpy()
5

This function can also be used to explicitly transfer tensors between devices. For example, to transfer a tensor in GPU memory back to host memory, one can use:

with tf.device("/gpu:0"):
  x_on_gpu = tf.constant(1)
with tf.device("/cpu:0"):
  x_on_cpu = tf.identity(x_on_gpu)
x_on_cpu.device
'/job:localhost/replica:0/task:0/device:CPU:0'

input A Tensor, a Variable, a CompositeTensor or anything that can be converted to a tensor using tf.convert_to_tensor.
name A name for the operation (optional).

A Tensor or CompositeTensor. Has the same type and contents as input.