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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
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 int s. The (possibly partial) shape of
the tensor.
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as input .
|