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Return the handle of data.
tf.compat.v1.get_session_handle(
data, name=None
)
This is EXPERIMENTAL and subject to change.
Keep data "in-place" in the runtime and create a handle that can be
used to retrieve data in a subsequent run().
Combined with get_session_tensor, we can keep a tensor produced in
one run call in place, and use it as the input in a future run call.
Args | |
|---|---|
data
|
A tensor to be stored in the session. |
name
|
Optional name prefix for the return tensor. |
Returns | |
|---|---|
A scalar string tensor representing a unique handle for data.
|
Raises | |
|---|---|
TypeError
|
if data is not a Tensor.
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Example:
c = tf.multiply(a, b)
h = tf.compat.v1.get_session_handle(c)
h = sess.run(h)
p, a = tf.compat.v1.get_session_tensor(h.handle, tf.float32)
b = tf.multiply(a, 10)
c = sess.run(b, feed_dict={p: h.handle})