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)
"Plan",
"codes",
"LoggingTensor",
"PointerTensor",
"VirtualGrid",
"ObjectWrapper",
"LargePrecisionTensor",
]
local_worker = None
torch = None
if "ID_PROVIDER" not in globals():
from syft.generic import IdProvider
ID_PROVIDER = IdProvider()
def create_sandbox(gbs, verbose=True, download_data=True):
"""There's some boilerplate stuff that most people who are
just playing around would like to have. This will create
that for you"""
try:
torch = gbs["torch"]
except:
torch = gbs["th"]
global hook
global bob
global theo