Files
concrete/compiler/include/concretelang/ClientLib/EncryptedArguments.h
Andi Drebes a7051c2c9c enhance(client/server): Add support for scalar results
This patch adds support for scalar results to the client/server
protocol and tests. In addition to `TensorData`, a new type
`ScalarData` is added. Previous representations of scalar values using
one-dimensional `TensorData` instances have been replaced with proper
instantiations of `ScalarData`.

The generic use of `TensorData` for scalar and tensor values has been
replaced with uses of a new variant `ScalarOrTensorData`, which can
either hold an instance of `TensorData` or `ScalarData`.
2022-10-04 14:40:40 +02:00

246 lines
8.5 KiB
C++

// Part of the Concrete Compiler Project, under the BSD3 License with Zama
// Exceptions. See
// https://github.com/zama-ai/concrete-compiler-internal/blob/main/LICENSE.txt
// for license information.
#ifndef CONCRETELANG_CLIENTLIB_ENCRYPTED_ARGS_H
#define CONCRETELANG_CLIENTLIB_ENCRYPTED_ARGS_H
#include <ostream>
#include "boost/outcome.h"
#include "../Common/Error.h"
#include "concretelang/ClientLib/ClientParameters.h"
#include "concretelang/ClientLib/KeySet.h"
#include "concretelang/ClientLib/Types.h"
#include "concretelang/Common/BitsSize.h"
namespace concretelang {
namespace clientlib {
using concretelang::error::StringError;
class PublicArguments;
/// Temporary object used to hold and encrypt parameters before calling a
/// ClientLambda. Use preferably TypeClientLambda and serializeCall(Args...).
/// Otherwise convert it to a PublicArguments and use
/// serializeCall(PublicArguments, KeySet).
class EncryptedArguments {
public:
EncryptedArguments() : currentPos(0) {}
/// Encrypts args thanks the given KeySet and pack the encrypted arguments to
/// an EncryptedArguments
template <typename... Args>
static outcome::checked<std::unique_ptr<EncryptedArguments>, StringError>
create(KeySet &keySet, Args... args) {
auto encryptedArgs = std::make_unique<EncryptedArguments>();
OUTCOME_TRYV(encryptedArgs->pushArgs(keySet, args...));
return std::move(encryptedArgs);
}
template <typename ArgT>
static outcome::checked<std::unique_ptr<EncryptedArguments>, StringError>
create(KeySet &keySet, const llvm::ArrayRef<ArgT> args) {
auto encryptedArgs = EncryptedArguments::empty();
for (size_t i = 0; i < args.size(); i++) {
OUTCOME_TRYV(encryptedArgs->pushArg(args[i], keySet));
}
OUTCOME_TRYV(encryptedArgs->checkAllArgs(keySet));
return std::move(encryptedArgs);
}
static std::unique_ptr<EncryptedArguments> empty() {
return std::make_unique<EncryptedArguments>();
}
/// Export encrypted arguments as public arguments, reset the encrypted
/// arguments, i.e. move all buffers to the PublicArguments and reset the
/// positional counter.
outcome::checked<std::unique_ptr<PublicArguments>, StringError>
exportPublicArguments(ClientParameters clientParameters,
RuntimeContext runtimeContext);
/// Check that all arguments as been pushed.
// TODO: Remove public method here
outcome::checked<void, StringError> checkAllArgs(KeySet &keySet);
public:
/// Add a uint64_t scalar argument.
outcome::checked<void, StringError> pushArg(uint64_t arg, KeySet &keySet);
/// Add a vector-tensor argument.
outcome::checked<void, StringError> pushArg(std::vector<uint8_t> arg,
KeySet &keySet) {
return pushArg((uint8_t *)arg.data(),
llvm::ArrayRef<int64_t>{(int64_t)arg.size()}, keySet);
}
/// Add a 1D tensor argument with data and size of the dimension.
template <typename T>
outcome::checked<void, StringError> pushArg(const T *data, int64_t dim1,
KeySet &keySet) {
return pushArg(std::vector<uint8_t>(data, data + dim1), keySet);
}
/// Add a 1D tensor argument.
template <size_t size>
outcome::checked<void, StringError> pushArg(std::array<uint8_t, size> arg,
KeySet &keySet) {
return pushArg((uint8_t *)arg.data(), llvm::ArrayRef<int64_t>{size},
keySet);
}
/// Add a 2D tensor argument.
template <size_t size0, size_t size1>
outcome::checked<void, StringError>
pushArg(std::array<std::array<uint8_t, size1>, size0> arg, KeySet &keySet) {
return pushArg((uint8_t *)arg.data(), llvm::ArrayRef<int64_t>{size0, size1},
keySet);
}
/// Add a 3D tensor argument.
template <size_t size0, size_t size1, size_t size2>
outcome::checked<void, StringError>
pushArg(std::array<std::array<std::array<uint8_t, size2>, size1>, size0> arg,
KeySet &keySet) {
return pushArg((uint8_t *)arg.data(),
llvm::ArrayRef<int64_t>{size0, size1, size2}, keySet);
}
// Generalize by computing shape by template recursion
/// Set a argument at the given pos as a 1D tensor of T.
template <typename T>
outcome::checked<void, StringError> pushArg(T *data, int64_t dim1,
KeySet &keySet) {
return pushArg<T>(data, llvm::ArrayRef<int64_t>(&dim1, 1), keySet);
}
/// Set a argument at the given pos as a tensor of T.
template <typename T>
outcome::checked<void, StringError>
pushArg(T *data, llvm::ArrayRef<int64_t> shape, KeySet &keySet) {
return pushArg(static_cast<const T *>(data), shape, keySet);
}
template <typename T>
outcome::checked<void, StringError>
pushArg(const T *data, llvm::ArrayRef<int64_t> shape, KeySet &keySet) {
OUTCOME_TRYV(checkPushTooManyArgs(keySet));
auto pos = currentPos;
CircuitGate input = keySet.inputGate(pos);
// Check the width of data
if (input.shape.width > 64) {
return StringError("argument #")
<< pos << " width > 64 bits is not supported";
}
// Check the shape of tensor
if (input.shape.dimensions.empty()) {
return StringError("argument #") << pos << "is not a tensor";
}
if (shape.size() != input.shape.dimensions.size()) {
return StringError("argument #")
<< pos << "has not the expected number of dimension, got "
<< shape.size() << " expected " << input.shape.dimensions.size();
}
// Check shape
for (size_t i = 0; i < shape.size(); i++) {
if (shape[i] != input.shape.dimensions[i]) {
return StringError("argument #")
<< pos << " has not the expected dimension #" << i << " , got "
<< shape[i] << " expected " << input.shape.dimensions[i];
}
}
// Set sizes
std::vector<int64_t> sizes = keySet.clientParameters().bufferShape(input);
if (input.encryption.hasValue()) {
TensorData td(sizes, EncryptedScalarElementType,
EncryptedScalarElementWidth);
auto lweSize = keySet.clientParameters().lweBufferSize(input);
for (size_t i = 0, offset = 0; i < input.shape.size;
i++, offset += lweSize) {
OUTCOME_TRYV(keySet.encrypt_lwe(
pos, td.getElementPointer<uint64_t>(offset), data[i]));
}
ciphertextBuffers.push_back(std::move(td));
} else {
auto bitsPerValue = bitWidthAsWord(input.shape.width);
TensorData td(sizes, bitsPerValue, input.shape.sign);
llvm::ArrayRef<T> values(data, TensorData::getNumElements(sizes));
td.bulkAssign(values);
ciphertextBuffers.push_back(std::move(td));
}
TensorData &td = ciphertextBuffers.back().getTensor();
// allocated
preparedArgs.push_back(nullptr);
// aligned
preparedArgs.push_back(td.getValuesAsOpaquePointer());
// offset
preparedArgs.push_back((void *)0);
// sizes
for (size_t size : td.getDimensions()) {
preparedArgs.push_back((void *)size);
}
// Set the stride for each dimension, equal to the product of the
// following dimensions.
int64_t stride = td.getNumElements();
for (size_t size : td.getDimensions()) {
stride = (size == 0 ? 0 : (stride / size));
preparedArgs.push_back((void *)stride);
}
currentPos++;
return outcome::success();
}
/// Recursive case for scalars: extract first scalar argument from
/// parameter pack and forward rest
template <typename Arg0, typename... OtherArgs>
outcome::checked<void, StringError> pushArgs(KeySet &keySet, Arg0 arg0,
OtherArgs... others) {
OUTCOME_TRYV(pushArg(arg0, keySet));
return pushArgs(keySet, others...);
}
/// Recursive case for tensors: extract pointer and size from
/// parameter pack and forward rest
template <typename Arg0, typename... OtherArgs>
outcome::checked<void, StringError>
pushArgs(KeySet &keySet, Arg0 *arg0, size_t size, OtherArgs... others) {
OUTCOME_TRYV(pushArg(arg0, size, keySet));
return pushArgs(keySet, others...);
}
/// Terminal case of pushArgs
outcome::checked<void, StringError> pushArgs(KeySet &keySet) {
return checkAllArgs(keySet);
}
private:
outcome::checked<void, StringError> checkPushTooManyArgs(KeySet &keySet);
private:
/// Position of the next pushed argument
size_t currentPos;
std::vector<void *> preparedArgs;
/// Store buffers of ciphertexts
std::vector<ScalarOrTensorData> ciphertextBuffers;
};
} // namespace clientlib
} // namespace concretelang
#endif