def _unbufferize_torch_parameter(
worker: AbstractWorker,
protobuf_param: ParameterPB) -> torch.nn.Parameter:
data = syft.serde.protobuf.serde._unbufferize(worker,
protobuf_param.tensor)
param = torch.nn.Parameter(data,
requires_grad=protobuf_param.requires_grad)
param.id = get_protobuf_id(protobuf_param.id)
if protobuf_param.HasField("grad"):
param.grad = syft.serde.protobuf.serde._unbufferize(
worker, protobuf_param.grad)
return param
def unbufferize(worker: AbstractWorker,
protobuf_tensor: "TorchTensorPB") -> torch.Tensor:
"""
This method converts a Protobuf torch tensor back into a
Torch tensor. The tensor contents can be deserialized from
binary representations produced by Torch or Numpy, or from
the generic Protobuf message format for cross-platform
communication.
Args:
protobuf_tensor (bin): Protobuf message of torch tensor.
Returns:
tensor (torch.Tensor): a torch tensor converted from Protobuf
"""
tensor_id = get_protobuf_id(protobuf_tensor.id)
tags = protobuf_tensor.tags
description = protobuf_tensor.description
contents_type = protobuf_tensor.WhichOneof("contents")
serialized_tensor = getattr(protobuf_tensor, contents_type)
serializer = SERIALIZERS_PROTOBUF_TO_SYFT[protobuf_tensor.serializer]
tensor = _deserialize_tensor(worker, (serializer), serialized_tensor)
# note we need to do this explicitly because torch.load does not
# include .grad information
if protobuf_tensor.HasField("grad_chain"):
grad_chain = protobuf_tensor.grad_chain
tensor.grad = TorchTensorWrapper.unbufferize(worker, grad_chain)
initialize_tensor(
hook=syft.torch.hook,
obj=tensor,
owner=worker,
id=tensor_id,
init_args=[],
init_kwargs={},
)
if protobuf_tensor.HasField("chain"):
chain = protobuf_tensor.chain
chain = TorchTensorWrapper.unbufferize(worker, chain)
tensor.child = chain
tensor.is_wrapper = True
tensor.tags = set(tags)
tensor.description = description
return tensor
def unbufferize(worker: AbstractWorker, protobuf_param: ParameterPB) -> torch.nn.Parameter:
"""
This method converts a ParameterPB into a torch.nn.Parameter.
Args:
protobuf_param (ParameterPB): input ParameterPB to be deserialized.
Returns:
param: (torch.nn.Parameter): deserialized ParameterPB.
"""
data = syft.serde.protobuf.serde._unbufferize(worker, protobuf_param.tensor)
param = torch.nn.Parameter(data, requires_grad=protobuf_param.requires_grad)
param.id = get_protobuf_id(protobuf_param.id)
if protobuf_param.HasField("grad"):
param.grad = syft.serde.protobuf.serde._unbufferize(worker, protobuf_param.grad)
return param