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a7051c2c9c
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`.
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
# Part of the Concrete Compiler Project, under the BSD3 License with Zama Exceptions.
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# See https://github.com/zama-ai/concrete-compiler-internal/blob/main/LICENSE.txt for license information.
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print(
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"""// 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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// generated: see genDynamicRandCall.py
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#include <cassert>
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#include <vector>
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#include "concretelang/ClientLib/Types.h"
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#include "concretelang/ServerLib/DynamicArityCall.h"
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#include "concretelang/ServerLib/ServerLambda.h"
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namespace concretelang {
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namespace serverlib {
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/// Helper class template that yields an unsigned integer type given a
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/// size in bytes
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template <std::size_t size> struct int_type_of_size {};
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template <> struct int_type_of_size<4> { typedef uint32_t type; };
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template <> struct int_type_of_size<8> { typedef uint64_t type; };
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/// Converts one function pointer into another
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// TODO: Not sure this is valid in all implementations / on all
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// architectures
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template <typename FnDstT, typename FnSrcT> FnDstT convert_fnptr(FnSrcT src) {
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static_assert(sizeof(FnDstT) == sizeof(FnSrcT),
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"Size of function types must match");
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using inttype = typename int_type_of_size<sizeof(FnDstT)>::type;
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inttype raw = reinterpret_cast<inttype>(src);
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return reinterpret_cast<FnDstT>(raw);
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}
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ScalarOrTensorData multi_arity_call_dynamic_rank(void *(*func)(void *...),
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std::vector<void *> args, size_t rank,
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size_t element_width, bool is_signed) {
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using concretelang::clientlib::MemRefDescriptor;
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constexpr auto convert = concretelang::clientlib::tensorDataFromMemRef;
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switch (rank) {
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case 0: {
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auto m =
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multi_arity_call(convert_fnptr<uint64_t (*)(void *...)>(func), args);
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return concretelang::clientlib::ScalarData(m, is_signed, element_width);
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}""")
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for tensor_rank in range(1, 33):
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memref_rank = tensor_rank
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print(f""" case {tensor_rank}: {{
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auto m = multi_arity_call(
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convert_fnptr<MemRefDescriptor<{memref_rank}> (*)(void *...)>(func), args);
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return convert({memref_rank}, element_width, is_signed, m.allocated, m.aligned,
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m.offset, m.sizes, m.strides);
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}}""")
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print("""
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default:
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assert(false);
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}
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}""")
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print("""
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} // namespace serverlib
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} // namespace concretelang""")
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