def __init__(self,
owner=None,
id=None,
tags: set = None,
description: str = None,
shape=None):
"""A PlaceHolder acts as a tensor but does nothing special. It can get
"instantiated" when a real tensor is appended as a child attribute. It
will send forward all the commands it receives to its child tensor.
When you send a PlaceHolder, you don't sent the instantiated tensors.
Args:
owner: An optional BaseWorker object to specify the worker on which
the tensor is located.
id: An optional string or integer id of the PlaceHolder.
"""
super().__init__(id=id,
owner=owner,
tags=tags,
description=description)
if not isinstance(self.id, PlaceholderId):
self.id = PlaceholderId(self.id)
self.expected_shape = tuple(shape) if shape is not None else None
self.child = None
def read(self):
"""
Return state tensors that are from this plan specifically, but not those
of plans including in this plan.
If run while a plan is building, declare all the state tensors to the plan
currently building.
"""
# If there is a plan building, it is referenced in init_plan
if self.owner.init_plan:
parent_plan = self.owner.init_plan
# to see if we are in a sub plan, we use state objects equality
if parent_plan.state != self:
# for all the placeholders in this sub plan, we report a copy of them
# in the parent plan and notify their origin using the #inner tag
for placeholder in self.state_placeholders:
placeholder = placeholder.copy()
placeholder.id = PlaceholderId(placeholder.child.id)
placeholder.tags = set()
placeholder.tag("#inner")
parent_plan.state.state_placeholders.append(placeholder)
parent_plan.role.placeholders[
placeholder.child.id] = placeholder
tensors = []
for placeholder in self.state_placeholders:
# State elements from sub plan should not be reported when read() is used
if "#inner" not in placeholder.tags:
tensor = placeholder.child
tensors.append(tensor)
return tensors
def read(self):
"""
Return state tensors that are from this plan specifically, but not those
of plans including in this plan.
If run while a plan is building, declare all the state tensors to the plan
currently building.
"""
# TODO clean this function
# If there is a plan building, it is referenced in init_plan
if self.owner.init_plan:
parent_plan = self.owner.init_plan
# to see if we are in a sub plan, we use state objects equality
if parent_plan.state != self:
# for all the placeholders in this sub plan, we report a copy of them
# in the parent plan and notify their origin using the #inner tag
for placeholder in self.state_placeholders:
placeholder = placeholder.copy()
placeholder.id = PlaceholderId(placeholder.child.id)
placeholder.tags = set(("#inner", ))
parent_plan.state.state_placeholders.append(placeholder)
parent_plan.role.placeholders[
placeholder.child.id] = placeholder
if self.read_placeholders or self.owner.init_plan:
return [
ph for ph in self.state_placeholders if "#inner" not in ph.tags
]
else:
return [
ph.child for ph in self.state_placeholders
if "#inner" not in ph.tags
]
def _replace_placeholder_ids(obj):
if isinstance(obj, (tuple, list)):
r = [_replace_placeholder_ids(o) for o in obj]
return type(obj)(r)
elif isinstance(obj, dict):
return {key: _replace_placeholder_ids(value) for key, value in obj.items()}
elif isinstance(obj, PlaceholderId):
return PlaceholderId(old_ids_2_new_ids[obj.value])
else:
return obj
def add_placeholder(self, tensor, arg_ids, result_ids, node_type=None):
"""
Create and register a new placeholder if not already existing (else return
the existing one).
The placeholder is tagged by a unique and incremental index for a given plan.
Args:
tensor: the tensor to replace with a placeholder
node_type: Should be "input" or "output", used to tag like this: #<type>-*
"""
if tensor.id not in self.placeholders:
placeholder = sy.PlaceHolder(tags={f"#{self.var_count + 1}"},
id=tensor.id,
owner=self.owner)
self.placeholders[tensor.id] = placeholder
if node_type == "input":
if tensor.id not in arg_ids:
raise ValueError(
f"The following tensor was used but is not known in "
f"this plan: \n{tensor}\nPossible reasons for this can be:\n"
f"- This tensor is external to the plan and should be provided "
f"using the state. See more about plan.state to fix this.\n"
f"- This tensor was created internally using torch.Tensor, "
f"torch.FloatTensor, torch.IntTensor, etc, which are not supported. "
f"Please use instead torch.tensor(..., dtype=torch.int32) for example."
)
placeholder.tags.add(f"#input-{arg_ids.index(tensor.id)}")
if tensor.id in result_ids:
placeholder.tags.add(
f"#output-{result_ids.index(tensor.id)}")
elif node_type == "output":
if tensor.id in result_ids:
placeholder.tags.add(
f"#output-{result_ids.index(tensor.id)}")
if tensor.id in arg_ids:
placeholder.tags.add(
f"#input-{result_ids.index(tensor.id)}")
else:
raise ValueError("node_type should be 'input' or 'output'.")
self.var_count += 1
return PlaceholderId(tensor.id)
def copy(self):
# TODO not the cleanest method ever
placeholders = {}
old_ids_2_new_ids = {}
for ph in self.placeholders.values():
copy = ph.copy()
old_ids_2_new_ids[ph.id.value] = copy.id.value
placeholders[copy.id.value] = copy
new_input_placeholder_ids = tuple(
old_ids_2_new_ids[self.placeholders[input_id].id.value]
for input_id in self.input_placeholder_ids)
new_output_placeholder_ids = tuple(
old_ids_2_new_ids[self.placeholders[output_id].id.value]
for output_id in self.output_placeholder_ids)
state_placeholders = []
for ph in self.state.state_placeholders:
new_ph = PlaceHolder(
id=old_ids_2_new_ids[ph.id.value]).instantiate(ph.child)
state_placeholders.append(new_ph)
state = State(state_placeholders)
_replace_placeholder_ids = lambda obj: Role.nested_object_traversal(
obj, lambda x: PlaceholderId(old_ids_2_new_ids[x.value]),
PlaceholderId)
new_actions = []
for action in self.actions:
action_type = type(action)
target = _replace_placeholder_ids(action.target)
args_ = _replace_placeholder_ids(action.args)
kwargs_ = _replace_placeholder_ids(action.kwargs)
return_ids = _replace_placeholder_ids(action.return_ids)
new_actions.append(
action_type(action.name, target, args_, kwargs_, return_ids))
return Role(
state=state,
actions=new_actions,
placeholders=placeholders,
input_placeholder_ids=new_input_placeholder_ids,
output_placeholder_ids=new_output_placeholder_ids,
id=sy.ID_PROVIDER.pop(),
)
