def execute_command(self, message: tuple) -> PointerTensor:
"""
Executes commands received from other workers.
Args:
message: A tuple specifying the command and the args.
Returns:
A pointer to the result.
"""
(command_name, _self, args, kwargs), return_ids = message
# TODO add kwargs
command_name = command_name
# Handle methods
if _self is not None:
if sy.torch.is_inplace_method(command_name):
getattr(_self, command_name)(*args, **kwargs)
return
else:
response = getattr(_self, command_name)(*args, **kwargs)
# Handle functions
else:
# At this point, the command is ALWAYS a path to a
# function (i.e., torch.nn.functional.relu). Thus,
# we need to fetch this function and run it.
sy.torch.command_guard(command_name, "torch_modules")
paths = command_name.split(".")
command = self
for path in paths:
command = getattr(command, path)
response = command(*args, **kwargs)
# some functions don't return anything (such as .backward())
# so we need to check for that here.
if response is not None:
# Register response et create pointers for tensor elements
try:
response = sy.frameworks.torch.hook_args.register_response(
command_name, response, list(return_ids), self)
return response
except ResponseSignatureError:
return_ids = IdProvider(return_ids)
response = sy.frameworks.torch.hook_args.register_response(
command_name, response, return_ids, self)
raise ResponseSignatureError(return_ids.generated)
def execute_command(self, message: tuple) -> PointerTensor:
"""
Executes commands received from other workers.
Args:
message: A tuple specifying the command and the args.
Returns:
A pointer to the result.
"""
(command_name, _self, args, kwargs), return_ids = message
# TODO add kwargs
command_name = command_name
# Handle methods
if _self is not None:
if type(_self) == int:
_self = BaseWorker.get_obj(self, _self)
if _self is None:
return
if type(_self) == str and _self == "self":
_self = self
if sy.framework.is_inplace_method(command_name):
# TODO[jvmancuso]: figure out a good way to generalize the
# above check (#2530)
getattr(_self, command_name)(*args, **kwargs)
return
else:
try:
response = getattr(_self, command_name)(*args, **kwargs)
except TypeError:
# TODO Andrew thinks this is gross, please fix. Instead need to properly deserialize strings
new_args = [
arg.decode("utf-8") if isinstance(arg, bytes) else arg
for arg in args
]
response = getattr(_self, command_name)(*new_args,
**kwargs)
# Handle functions
else:
# At this point, the command is ALWAYS a path to a
# function (i.e., torch.nn.functional.relu). Thus,
# we need to fetch this function and run it.
sy.framework.command_guard(command_name)
paths = command_name.split(".")
command = self
for path in paths:
command = getattr(command, path)
response = command(*args, **kwargs)
# some functions don't return anything (such as .backward())
# so we need to check for that here.
if response is not None:
# Register response and create pointers for tensor elements
try:
response = hook_args.register_response(command_name, response,
list(return_ids), self)
return response
except ResponseSignatureError:
return_id_provider = sy.ID_PROVIDER
return_id_provider.set_next_ids(return_ids, check_ids=False)
return_id_provider.start_recording_ids()
response = hook_args.register_response(command_name, response,
return_id_provider,
self)
new_ids = return_id_provider.get_recorded_ids()
raise ResponseSignatureError(new_ids)
def execute_computation_action(self, action: ComputationAction) -> PointerTensor:
"""
Executes commands received from other workers.
Args:
message: A tuple specifying the command and the args.
Returns:
The result or None if return_value is False.
"""
op_name = action.name
_self = action.target
args_ = action.args
kwargs_ = action.kwargs
return_ids = action.return_ids
return_value = action.return_value
# Handle methods
if _self is not None:
if type(_self) == int:
_self = self.get_obj(_self)
if _self is None:
return
elif isinstance(_self, str):
if _self == "self":
_self = self.worker
else:
res: list = self.worker.search(_self)
if len(res) != 1:
raise ValueError(
f"Searching for {_self} on {self.worker.id}. /!\\ {len(res)} found"
)
_self = res[0]
if sy.framework.is_inplace_method(op_name):
# TODO[jvmancuso]: figure out a good way to generalize the
# above check (#2530)
getattr(_self, op_name)(*args_, **kwargs_)
return
else:
try:
response = getattr(_self, op_name)(*args_, **kwargs_)
except TypeError:
# TODO Andrew thinks this is gross, please fix. Instead need to
# properly deserialize strings
new_args = [
arg.decode("utf-8") if isinstance(arg, bytes) else arg for arg in args_
]
response = getattr(_self, op_name)(*new_args, **kwargs_)
# Handle functions
else:
# At this point, the command is ALWAYS a path to a
# function (i.e., torch.nn.functional.relu). Thus,
# we need to fetch this function and run it.
sy.framework.command_guard(op_name)
paths = op_name.split(".")
command = self.worker
for path in paths:
command = getattr(command, path)
response = command(*args_, **kwargs_)
# some functions don't return anything (such as .backward())
# so we need to check for that here.
if response is not None:
# Register response and create pointers for tensor elements
try:
response = hook_args.register_response(
op_name, response, list(return_ids), self.worker
)
# TODO: Does this mean I can set return_value to False and still
# get a response? That seems surprising.
if return_value or isinstance(response, (int, float, bool, str)):
return response
else:
return None
except ResponseSignatureError:
return_id_provider = sy.ID_PROVIDER
return_id_provider.set_next_ids(return_ids, check_ids=False)
return_id_provider.start_recording_ids()
response = hook_args.register_response(
op_name, response, return_id_provider, self.worker
)
new_ids = return_id_provider.get_recorded_ids()
raise ResponseSignatureError(new_ids)
