예제 #1
0
파일: protocol.py 프로젝트: ganesan5/PySyft
    def detail(worker: AbstractWorker, protocol_tuple: tuple) -> "Protocol":
        """This function reconstructs a Protocol object given its attributes in the form of a tuple.
        Args:
            worker: the worker doing the deserialization
            protocol_tuple: a tuple holding the attributes of the Protocol
        Returns:
            protocol: a Protocol object
        """

        id, tags, description, plans_reference, workers_resolved = map(
            lambda o: sy.serde._detail(worker, o), protocol_tuple
        )

        plans = []
        for owner_id, plan_id in plans_reference:
            if workers_resolved:
                plan_owner = worker.get_worker(owner_id, fail_hard=True)
                plan_pointer = worker.request_search(plan_id, location=plan_owner)[0]
                worker.register_obj(plan_pointer)
                plans.append((plan_owner, plan_pointer))
            else:
                try:
                    plan_owner = worker.get_worker(owner_id, fail_hard=True)
                    plan_pointer = worker.request_search(plan_id, location=plan_owner)[0]
                    plan = plan_pointer.get()
                except WorkerNotFoundException:
                    plan = worker.get_obj(plan_id)
                plans.append((worker.id, plan))

        protocol = sy.Protocol(plans=plans, id=id, owner=worker, tags=tags, description=description)

        return protocol
예제 #2
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    def detail(worker: AbstractWorker,
               tensor_tuple: tuple) -> "AdditiveSharingTensor":
        """
            This function reconstructs a AdditiveSharingTensor given it's attributes in form of a tuple.
            Args:
                worker: the worker doing the deserialization
                tensor_tuple: a tuple holding the attributes of the AdditiveSharingTensor
            Returns:
                AdditiveSharingTensor: a AdditiveSharingTensor
            Examples:
                shared_tensor = detail(data)
            """
        tensor_id, field, dtype, crypto_provider, chain, garbage_collect = tensor_tuple

        crypto_provider = sy.serde.msgpack.serde._detail(
            worker, crypto_provider)

        tensor = AdditiveSharingTensor(
            owner=worker,
            id=sy.serde.msgpack.serde._detail(worker, tensor_id),
            field=sy.serde.msgpack.serde._detail(worker, field),
            dtype=dtype.decode("utf-8"),
            crypto_provider=worker.get_worker(crypto_provider),
        )

        if chain is not None:
            chain = sy.serde.msgpack.serde._detail(worker, chain)
            tensor.child = chain

        tensor.set_garbage_collect_data(garbage_collect)

        return tensor
예제 #3
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    def detail(worker: AbstractWorker,
               tensor_tuple: tuple) -> "AdditiveSharingTensor":
        """
            This function reconstructs a AdditiveSharingTensor given it's attributes in form of a tuple.
            Args:
                worker: the worker doing the deserialization
                tensor_tuple: a tuple holding the attributes of the AdditiveSharingTensor
            Returns:
                AdditiveSharingTensor: a AdditiveSharingTensor
            Examples:
                shared_tensor = detail(data)
            """

        tensor_id, field, crypto_provider, chain = tensor_tuple

        tensor = AdditiveSharingTensor(
            owner=worker,
            id=tensor_id,
            field=field,
            crypto_provider=worker.get_worker(crypto_provider),
        )

        if chain is not None:
            chain = sy.serde._detail(worker, chain)
            tensor.child = chain

        return tensor
예제 #4
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    def unbufferize(
        worker: AbstractWorker, protobuf_tensor: "AdditiveSharingTensorPB"
    ) -> "AdditiveSharingTensor":
        """
            This function reconstructs a AdditiveSharingTensor given its' attributes in form of a protobuf object.
            Args:
                worker: the worker doing the deserialization
                protobuf_tensor: a protobuf object holding the attributes of the AdditiveSharingTensor
            Returns:
                AdditiveSharingTensor: a AdditiveSharingTensor
            Examples:
                shared_tensor = unprotobuf(data)
            """

        tensor_id = sy.serde.protobuf.proto.get_protobuf_id(protobuf_tensor.id)
        crypto_provider_id = sy.serde.protobuf.proto.get_protobuf_id(
            protobuf_tensor.crypto_provider_id
        )
        field = protobuf_tensor.field_size

        tensor = AdditiveSharingTensor(
            owner=worker,
            id=tensor_id,
            field=field,
            crypto_provider=worker.get_worker(crypto_provider_id),
        )

        if protobuf_tensor.location_ids is not None:
            chain = {}
            for pb_location_id, share in zip(protobuf_tensor.location_ids, protobuf_tensor.shares):
                location_id = sy.serde.protobuf.proto.get_protobuf_id(pb_location_id)
                chain[location_id] = sy.serde.protobuf.serde._unbufferize(worker, share)
            tensor.child = chain

        return tensor
예제 #5
0
파일: base.py 프로젝트: kylinLiu/PySyft
    def detail(worker: AbstractWorker, worker_tuple: tuple) -> Union[AbstractWorker, int, str]:
        """
        This function reconstructs a PlanPointer given it's attributes in form of a tuple.

        Args:
            worker: the worker doing the deserialization
            plan_pointer_tuple: a tuple holding the attributes of the PlanPointer
        Returns:
            A worker id or worker instance.
        """
        worker_id = sy.serde.msgpack.serde._detail(worker, worker_tuple[0])

        referenced_worker = worker.get_worker(worker_id)

        return referenced_worker
예제 #6
0
    def detail(worker: AbstractWorker,
               tensor_tuple: tuple) -> "AdditiveSharingTensor":
        """
            This function reconstructs a AdditiveSharingTensor given it's attributes in
        form of a tuple.
        Args:
            worker: the worker doing the deserialization
            tensor_tuple: a tuple holding the attributes of the AdditiveSharingTensor
        Returns:
            AdditiveSharingTensor: a AdditiveSharingTensor
        Examples:
            shared_tensor = detail(data)
        """
        _detail = lambda x: sy.serde.msgpack.serde._detail(worker, x)

        tensor_id, field, protocol, dtype, crypto_provider, chain, garbage_collect = tensor_tuple

        crypto_provider = _detail(crypto_provider)

        tensor = AdditiveSharingTensor(
            owner=worker,
            id=_detail(tensor_id),
            field=_detail(field),
            protocol=_detail(protocol),
            dtype=dtype.decode("utf-8"),
            crypto_provider=worker.get_worker(crypto_provider),
        )

        chain = _detail(chain)
        tensor.child = {}
        for share in chain:
            if share.location is not None:
                # Remote
                tensor.child[share.location.id] = share
            else:
                # Local
                tensor.child[share.owner.id] = share

        tensor.set_garbage_collect_data(garbage_collect)

        return tensor