parameters: (data, name=None)
docstring: Return the handle of `data`.
  
    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.
  
    Example:
  
    ```python
    c = tf.mul(a, b)
    h = tf.get_session_handle(c)
    h = sess.run(h)
  
    p, a = tf.get_session_tensor(h.handle, tf.float32)
    b = tf.mul(a, 10)
    c = sess.run(b, feed_dict={p: h.handle})
    ```
docstring_summary: Return the handle of `data`.
docstring_tokens: Return the handle of data .
function: def get_session_handle(data, name=None):
    """Return the handle of `data`.
  
    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.
  
    Example:
  
    ```python
    c = tf.mul(a, b)
    h = tf.get_session_handle(c)
    h = sess.run(h)
  
    p, a = tf.get_session_tensor(h.handle, tf.float32)
    b = tf.mul(a, 10)
    c = sess.run(b, feed_dict={p: h.handle})
    ```
  
    """
    if not isinstance(data, ops.Tensor):
      raise TypeError("`data` must be of type Tensor.")
  
    # Colocate this operation with data.
    with ops.colocate_with(data):
      return gen_data_flow_ops._get_session_handle(data, name=name)
function_tokens: def get_session_handle ( data , name = None ) : if not isinstance ( data , ops . Tensor ) : raise TypeError ( "`data` must be of type Tensor." ) # Colocate this operation with data. with ops . colocate_with ( data ) : return gen_data_flow_ops . _get_session_handle ( data , name = name )