def _private_mul(self, other, equation: str):
"""Abstractly Multiplies two tensors
Args:
self: an AdditiveSharingTensor
other: another AdditiveSharingTensor
equation: a string representation of the equation to be computed in einstein
summation form
"""
# check to see that operation is either mul or matmul
assert equation == "mul" or equation == "matmul"
cmd = getattr(torch, equation)
assert isinstance(other, AdditiveSharingTensor)
assert len(self.child) == len(other.child)
if self.crypto_provider is None:
raise AttributeError(
"For multiplication a crypto_provider must be passed.")
shares = spdz.spdz_mul(cmd, self, other, self.crypto_provider,
self.field, self.dtype)
return shares
def _private_mul(self, other, equation: str):
"""Abstractly Multiplies two tensors
Args:
self: an AdditiveSharingTensor
other: another AdditiveSharingTensor
equation: a string representation of the equation to be computed in einstein
summation form
"""
# check to see that operation is either mul or matmul
if equation != "mul" and equation != "matmul":
raise NotImplementedError(
f"Operation({equation}) is not possible, only mul or matmul are allowed"
)
cmd = getattr(torch, equation)
if not isinstance(other, AdditiveSharingTensor):
raise TypeError("other is not an AdditiveSharingTensor")
if self.crypto_provider is None:
raise AttributeError(
"For multiplication a crypto_provider must be passed.")
shares = spdz.spdz_mul(equation, self, other, self.crypto_provider,
self.dtype, self.torch_dtype, self.field)
return shares
