def get_session_tensor(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:
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.
"""
with ops.device(None):
# Commit the device when it is used the first time.
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)
def _get_handle_reader(graph, handle, dtype):
"""Return a read subgraph for this handle."""
graph_key = TensorHandle._get_reader_key(handle)
result = graph._handle_readers.get(graph_key)
if result is None:
# Create reader if we haven't done it.
handle_device = TensorHandle._get_device_name(handle)
with graph.as_default(), graph.device(handle_device):
holder = array_ops.placeholder(dtypes.string)
_register_handle_feeder(holder.graph, holder, dtype)
reader = gen_data_flow_ops._get_session_tensor(holder, dtype)
result = (holder, reader)
graph._handle_readers[graph_key] = result
return result
def _get_handle_reader(graph, handle, dtype):
"""Return a read subgraph for this handle."""
graph_key = TensorHandle._get_reader_key(handle)
result = graph._handle_readers.get(graph_key)
if result is None:
# Create reader if we haven't done it.
handle_device = TensorHandle._get_device_name(handle)
with graph.as_default(), graph.device(handle_device):
holder = array_ops.placeholder(dtypes.string)
_register_handle_feeder(holder.graph, holder, dtype)
reader = gen_data_flow_ops._get_session_tensor(holder, dtype)
result = (holder, reader)
graph._handle_readers[graph_key] = result
return result
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.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})
```
"""
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)
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.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})
```
"""
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)
def get_session_tensor(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:
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.
"""
with ops.device(None):
# Commit the device when it is used the first time.
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)
