parameters: (handle, dtype, name=None)
return_statement: return (holder, tensor)
docstring: Get the tensor of type `dtype` by feeding a tensor handle.
  
    This is EXPERIMENTAL and subject to change.
  
    Get the value of the tensor from a tensor handle. The tensor
    is produced in a previous run() and stored in the state of the
    session.
  
    Args:
      handle: The string representation of a persistent tensor handle.
      dtype: The type of the output tensor.
      name: Optional name prefix for the return tensor.
  
    Returns:
      A pair of tensors. The first is a placeholder for feeding a
      tensor handle and the second is the tensor in the session state
      keyed by the tensor handle.
  
    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: Get the tensor of type `dtype` by feeding a tensor handle.
docstring_tokens: Get the tensor of type dtype by feeding a tensor handle .
function: def get_session_tensor(handle, dtype, name=None):
    """Get the tensor of type `dtype` by feeding a tensor handle.
  
    This is EXPERIMENTAL and subject to change.
  
    Get the value of the tensor from a tensor handle. The tensor
    is produced in a previous run() and stored in the state of the
    session.
  
    Args:
      handle: The string representation of a persistent tensor handle.
      dtype: The type of the output tensor.
      name: Optional name prefix for the return tensor.
  
    Returns:
      A pair of tensors. The first is a placeholder for feeding a
      tensor handle and the second is the tensor in the session state
      keyed by the tensor handle.
  
    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})
    ```
  
    """
    handle_device = TensorHandle._get_device_name(handle)
    with ops.device(handle_device):
      holder = array_ops.placeholder(dtypes.string)
      _register_handle_feeder(holder.graph, holder, dtype)
      tensor = gen_data_flow_ops._get_session_tensor(holder, dtype, name=name)
    return (holder, tensor)
function_tokens: def get_session_tensor ( handle , dtype , name = None ) : handle_device = TensorHandle . _get_device_name ( handle ) with ops . device ( handle_device ) : holder = array_ops . placeholder ( dtypes . string ) _register_handle_feeder ( holder . graph , holder , dtype ) tensor = gen_data_flow_ops . _get_session_tensor ( holder , dtype , name = name ) return ( holder , tensor )