def _get_handle_mover(graph, feeder, handle):
"""Return a move subgraph for this pair of feeder and handle."""
dtype = _get_handle_feeder(graph, feeder)
if dtype is None:
return None
handle_device = TensorHandle._get_device_name(handle)
if feeder.op.device == handle_device:
return None
# Now we know we have to move the tensor.
graph_key = TensorHandle._get_mover_key(feeder, handle)
result = graph._handle_movers.get(graph_key)
if result is None:
# Create mover if we haven't done it.
holder, reader = _get_handle_reader(graph, handle, dtype)
with graph.as_default(), graph.device(feeder.op.device):
mover = gen_data_flow_ops._get_session_handle(reader)
result = (holder, mover)
graph._handle_movers[graph_key] = result
return result
def _get_handle_mover(graph, feeder, handle):
"""Return a move subgraph for this pair of feeder and handle."""
dtype = _get_handle_feeder(graph, feeder)
if dtype is None:
return None
handle_device = TensorHandle._get_device_name(handle)
if feeder.op.device == handle_device:
return None
# Now we know we have to move the tensor.
graph_key = TensorHandle._get_mover_key(feeder, handle)
result = graph._handle_movers.get(graph_key)
if result is None:
# Create mover if we haven't done it.
holder, reader = _get_handle_reader(graph, handle, dtype)
with graph.as_default(), graph.device(feeder.op.device):
mover = gen_data_flow_ops._get_session_handle(reader) # pylint: disable=protected-access
result = (holder, mover)
graph._handle_movers[graph_key] = result
return result
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.multiply(a, b)
h = tf.get_session_handle(c)
h = sess.run(h)
p, a = tf.get_session_tensor(h.handle, tf.float32)
b = tf.multiply(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)
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.multiply(a, b)
h = tf.get_session_handle(c)
h = sess.run(h)
p, a = tf.get_session_tensor(h.handle, tf.float32)
b = tf.multiply(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) # pylint: disable=protected-access
def _get_handle_mover(graph, feeder, handle):
"""Return a move subgraph for this pair of feeder and handle."""
dtype = _get_handle_feeder(graph, feeder)
if dtype is None:
return None
handle_device = TensorHandle._get_device_name(handle)
if not feeder.op.device:
feeder.op._set_device(handle_device)
feeder.consumers()[0]._set_device(handle_device)
return None
if feeder.op.device == handle_device:
return None
# Now we know we have to move the tensor.
graph_key = TensorHandle._get_mover_key(feeder, handle)
result = graph._handle_movers.get(graph_key)
if result is None:
# Create mover if we haven't done it.
holder, reader = _get_handle_reader(graph, handle, dtype)
with ops.device(feeder.op.device):
mover = gen_data_flow_ops._get_session_handle(reader)
result = (holder, mover)
graph._handle_movers[graph_key] = result
return result
