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7cc0c01326
C-style casts between function pointers result in an error using g++ 8.3.0. This patch introduces a workaround based on `reinterpret_cast`, in which the original function pointer is first cast into an unsigned integer of sufficient size and then cast into the target function pointer type. TODO: Check that this is actually valid C++ with defined behavior on all implementations / platforms.
63 lines
2.2 KiB
Python
63 lines
2.2 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/master/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/master/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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TensorData multi_arity_call_dynamic_rank(void *(*func)(void *...),
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std::vector<void *> args,
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size_t rank) {
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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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for tensor_rank in range(0, 33):
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memref_rank = tensor_rank + 1
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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}, m.allocated, m.aligned, 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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