def _transformed_t(self, info, t, consumer_op):
"""Return tre transformed tensor of `t`."""
if t in info.transformed_ts:
# If op is in the subgraph, just return its transformed counterpart.
return info.transformed_ts[t]
if t in info.sgv_inputs_set:
# `t` is an input of the subgraph.
return self.transform_external_input_handler(info, t)
elif t.op in info.ops:
# `t` is an internal tensor but is not transformed yet because it
# belongs to a graph cycle.
logging.debug("Cyclic tensor: t.name = %s", t.name)
# Try to find an existing tensor we can use for now,
# otherwise create one. We'll rewire this later.
if consumer_op.type == "Merge":
first_input = consumer_op.inputs[0]
tmp_t_ = self._transformed_t(info, first_input, consumer_op)
elif t.op.type == "Enter":
enter_input = t.op.inputs[0]
tmp_t_ = self._transformed_t(info, enter_input, consumer_op)
else:
with info.graph_.as_default():
tmp_t_ = util.make_placeholder_from_tensor(t, scope=info.scope_,
prefix="geph_tmp")
logging.debug("Created temporary placeholder: %s.", tmp_t_.name)
# Register as temporary and return.
info.tmp_cyclic_ts.append((t, tmp_t_, consumer_op))
return tmp_t_
else:
# `t` is a hidden input of the subgraph.
return self.transform_external_hidden_input_handler(info, t)
def _transformed_t(self, info, t, consumer_op):
"""Return tre transformed tensor of `t`."""
if t in info.transformed_ts:
# If op is in the subgraph, just return its transformed counterpart.
return info.transformed_ts[t]
if t in info.sgv_inputs_set:
# `t` is an input of the subgraph.
return self.transform_external_input_handler(info, t)
elif t.op in info.ops:
# `t` is an internal tensor but is not transformed yet because it
# belongs to a graph cycle.
logging.debug("Cyclic tensor: t.name = %s", t.name)
# Try to find an existing tensor we can use for now,
# otherwise create one. We'll rewire this later.
if consumer_op.type == "Merge":
first_input = consumer_op.inputs[0]
tmp_t_ = self._transformed_t(info, first_input, consumer_op)
elif t.op.type == "Enter":
enter_input = t.op.inputs[0]
tmp_t_ = self._transformed_t(info, enter_input, consumer_op)
else:
with info.graph_.as_default():
tmp_t_ = util.make_placeholder_from_tensor(t, scope=info.scope_,
prefix="geph_tmp")
logging.debug("Created temporary placeholder: %s.", tmp_t_.name)
# Register as temporary and return.
info.tmp_cyclic_ts.append((t, tmp_t_, consumer_op))
return tmp_t_
else:
# `t` is a hidden input of the subgraph.
return self.transform_external_hidden_input_handler(info, t)
def detach_outputs(sgv):
"""Detach the outputa of a subgraph view.
Args:
sgv: the subgraph view to be detached. This argument is converted to a
subgraph using the same rules than the function subgraph.make_view.
Returns:
A new subgraph view of the detached subgraph.
Note that sgv is also modified in place.
Raises:
StandardError: if sgv cannot be converted to a SubGraphView using
the same rules than the function subgraph.make_view.
"""
sgv = subgraph.make_view(sgv)
# only select outputs with consumers
sgv_ = sgv.remap_outputs([output_id
for output_id, output_t in enumerate(sgv.outputs)
if output_t.consumers()])
# create consumer subgraph and remap
consumers_sgv = subgraph.SubGraphView(sgv_.consumers())
consumers_sgv = consumers_sgv.remap_inputs(
[input_id for input_id, input_t in enumerate(consumers_sgv.inputs)
if input_t in sgv_.outputs])
with sgv_.graph.as_default():
output_placeholders = [
util.make_placeholder_from_tensor(input_t)
for input_t in consumers_sgv.inputs
]
return swap_outputs(sgv_, output_placeholders)
def detach_outputs(sgv):
"""Detach the outputa of a subgraph view.
Args:
sgv: the subgraph view to be detached. This argument is converted to a
subgraph using the same rules than the function subgraph.make_view.
Returns:
A new subgraph view of the detached subgraph.
Note that sgv is also modified in place.
Raises:
StandardError: if sgv cannot be converted to a SubGraphView using
the same rules than the function subgraph.make_view.
"""
sgv = subgraph.make_view(sgv)
# only select outputs with consumers
sgv_ = sgv.remap_outputs([
output_id for output_id, output_t in enumerate(sgv.outputs)
if output_t.consumers()
])
# create consumer subgraph and remap
consumers_sgv = subgraph.SubGraphView(sgv_.consumers())
consumers_sgv = consumers_sgv.remap_inputs([
input_id for input_id, input_t in enumerate(consumers_sgv.inputs)
if input_t in sgv_.outputs
])
with sgv_.graph.as_default():
output_placeholders = [
util.make_placeholder_from_tensor(input_t)
for input_t in consumers_sgv.inputs
]
return swap_outputs(sgv_, output_placeholders)
def replace_t_with_placeholder_handler(info, t):
"""Transform a tensor into a placeholder tensor.
This handler is typically used to transform a subgraph input tensor into a
placeholder.
Args:
info: Transform._Info instance.
t: tensor whose input must be transformed into a place holder.
Returns:
The tensor generated by the newly created place holder.
"""
with info.graph_.as_default():
t_ = util.make_placeholder_from_tensor(t, scope=info.scope_)
return t_
def replace_t_with_placeholder_handler(info, t):
"""Transform a tensor into a placeholder tensor.
This handler is typically used to transform a subgraph input tensor into a
placeholder.
Args:
info: Transform._TmpInfo instance.
t: tensor whose input must be transformed into a place holder.
Returns:
The tensor generated by the newly created place holder.
"""
with info.graph_.as_default():
t_ = util.make_placeholder_from_tensor(t, scope=info.scope_)
return t_
def detach_outputs(sgv, control_outputs=None):
"""Detach the output of a subgraph view.
Args:
sgv: the subgraph view to be detached. This argument is converted to a
subgraph using the same rules as the function subgraph.make_view.
Note that sgv is modified in place.
control_outputs: a util.ControlOutputs instance or None. If not None the
control outputs are also detached.
Returns:
A tuple `(sgv, output_placeholders)` where
`sgv` is a new subgraph view of the detached subgraph;
`output_placeholders` is a list of the created output placeholders.
Raises:
StandardError: if sgv cannot be converted to a SubGraphView using
the same rules than the function subgraph.make_view.
"""
sgv = subgraph.make_view(sgv)
# only select outputs with consumers
sgv_ = sgv.remap_outputs([
output_id for output_id, output_t in enumerate(sgv.outputs)
if output_t.consumers()
])
# create consumer subgraph and remap
consumers_sgv = subgraph.SubGraphView(sgv_.consumers())
consumers_sgv = consumers_sgv.remap_inputs([
input_id for input_id, input_t in enumerate(consumers_sgv.inputs)
if input_t in sgv_.outputs
])
with sgv_.graph.as_default():
output_placeholders = [
util.make_placeholder_from_tensor(input_t)
for input_t in consumers_sgv.inputs
]
reroute.swap_outputs(sgv_, output_placeholders)
if control_outputs is not None:
detach_control_outputs(sgv_, control_outputs)
return sgv_, output_placeholders
def detach_outputs(sgv, control_outputs=None):
"""Detach the outputa of a subgraph view.
Args:
sgv: the subgraph view to be detached. This argument is converted to a
subgraph using the same rules as the function subgraph.make_view.
Note that sgv is modified in place.
control_outputs: a util.ControlOutputs instance or None. If not None the
control outputs are also detached.
Returns:
A tuple `(sgv, output_placeholders)` where
`sgv` is a new subgraph view of the detached subgraph;
`output_placeholders` is a list of the created output placeholders.
Raises:
StandardError: if sgv cannot be converted to a SubGraphView using
the same rules than the function subgraph.make_view.
"""
sgv = subgraph.make_view(sgv)
# only select outputs with consumers
sgv_ = sgv.remap_outputs([output_id
for output_id, output_t in enumerate(sgv.outputs)
if output_t.consumers()])
# create consumer subgraph and remap
consumers_sgv = subgraph.SubGraphView(sgv_.consumers())
consumers_sgv = consumers_sgv.remap_inputs(
[input_id for input_id, input_t in enumerate(consumers_sgv.inputs)
if input_t in sgv_.outputs])
with sgv_.graph.as_default():
output_placeholders = [
util.make_placeholder_from_tensor(input_t)
for input_t in consumers_sgv.inputs
]
reroute.swap_outputs(sgv_, output_placeholders)
if control_outputs is not None:
detach_control_outputs(sgv_, control_outputs)
return sgv_, output_placeholders
