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8cd3a3a599
For now what it works are only levelled ops with user parameters. (take a look to the tests) Done: - Add parameters to the fhe parameters to support CRT-based large integers - Add command line options and tests options to allows the user to give those new parameters - Update the dialects and pipeline to handle new fhe parameters for CRT-based large integers - Update the client parameters and the client library to handle the CRT-based large integers Todo: - Plug the optimizer to compute the CRT-based large interger parameters - Plug the pbs for the CRT-based large integer
28 lines
770 B
C++
28 lines
770 B
C++
// Part of the Concrete Compiler Project, under the BSD3 License with Zama
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// Exceptions. See
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// https://github.com/zama-ai/concrete-compiler-internal/blob/main/LICENSE.txt
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// for license information.
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#ifndef CONCRETELANG_CONVERSION_FHETOTFHE_PASS_H_
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#define CONCRETELANG_CONVERSION_FHETOTFHE_PASS_H_
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#include "mlir/Pass/Pass.h"
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namespace mlir {
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namespace concretelang {
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// ApplyLookupTableLowering indicates the strategy to lower an
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// FHE.apply_loopup_table ops
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enum ApplyLookupTableLowering {
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KeySwitchBoostrapLowering,
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WopPBSLowering,
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};
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/// Create a pass to convert `FHE` dialect to `TFHE` dialect.
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std::unique_ptr<OperationPass<ModuleOp>>
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createConvertFHEToTFHEPass(ApplyLookupTableLowering lower);
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} // namespace concretelang
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} // namespace mlir
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#endif
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