tf.compat.v1.placeholder_with_default

A placeholder op that passes through input when its output is not fed.

tf.compat.v1.placeholder_with_default(
    input, shape, name=None
)

Migrate to TF2

Caution: This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the TensorFlow v1 to TensorFlow v2 migration guide for instructions on how to migrate the rest of your code.

This API is strongly discouraged for use with eager execution and tf.function. The primary use of this API is for testing computation wrapped within a tf.function where the input tensors might not have statically known fully-defined shapes. The same can be achieved by creating a concrete function from the tf.function with a tf.TensorSpec input which has partially defined shapes. For example, the code

@tf.function
def f():
  x = tf.compat.v1.placeholder_with_default(
      tf.constant([[1., 2., 3.], [4., 5., 6.]]), [None, 3])
  y = tf.constant([[1.],[2.], [3.]])
  z = tf.matmul(x, y)
  assert z.shape[0] == None
  assert z.shape[1] == 1

f()

can easily be replaced by

@tf.function
def f(x):
  y = tf.constant([[1.],[2.], [3.]])
  z = tf.matmul(x, y)
  assert z.shape[0] == None
  assert z.shape[1] == 1

g = f.get_concrete_function(tf.TensorSpec([None, 3]))

You can learn more about tf.function at Better performance with tf.function.

Description

Args
input	A Tensor. The default value to produce when output is not fed.
shape	A tf.TensorShape or list of ints. The (possibly partial) shape of the tensor.
name	A name for the operation (optional).

Returns
A Tensor. Has the same type as input.