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[FunC] Deprecate pragma compute-asm-ltr

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It changes all hashes, since the compiler needs to manipulate the stack
in a different way now.
This commit is contained in:
Aleksandr Kirsanov 2024-05-10 16:08:50 +03:00
parent aaf3ca335d
commit 1e4b20a061
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GPG key ID: B758BBAA01FFB3D3
11 changed files with 41 additions and 71 deletions
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24
crypto/func/gen-abscode.cpp
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@ -267,14 +267,8 @@ std::vector<var_idx_t> pre_compile_let(CodeBlob& code, Expr* lhs, Expr* rhs, con
return right;
}
std::vector<var_idx_t> pre_compile_tensor(const std::vector<Expr *> args, CodeBlob &code,
std::vector<std::pair<SymDef*, var_idx_t>> *lval_globs,
std::vector<int> arg_order) {
if (arg_order.empty()) {
arg_order.resize(args.size());
std::iota(arg_order.begin(), arg_order.end(), 0);
}
func_assert(args.size() == arg_order.size());
std::vector<var_idx_t> pre_compile_tensor(const std::vector<Expr *>& args, CodeBlob &code,
std::vector<std::pair<SymDef*, var_idx_t>> *lval_globs) {
std::vector<std::vector<var_idx_t>> res_lists(args.size());
struct ModifiedVar {
@ -282,7 +276,7 @@ std::vector<var_idx_t> pre_compile_tensor(const std::vector<Expr *> args, CodeBl
Op* op;
};
auto modified_vars = std::make_shared<std::vector<ModifiedVar>>();
for (size_t i : arg_order) {
for (size_t i = 0; i < args.size(); ++i) {
res_lists[i] = args[i]->pre_compile(code, lval_globs);
for (size_t j = 0; j < res_lists[i].size(); ++j) {
TmpVar& var = code.vars.at(res_lists[i][j]);
@ -329,7 +323,7 @@ std::vector<var_idx_t> Expr::pre_compile(CodeBlob& code, std::vector<std::pair<S
}
switch (cls) {
case _Tensor: {
return pre_compile_tensor(args, code, lval_globs, {});
return pre_compile_tensor(args, code, lval_globs);
}
case _Apply: {
func_assert(sym);
@ -344,22 +338,16 @@ std::vector<var_idx_t> Expr::pre_compile(CodeBlob& code, std::vector<std::pair<S
op_call = op_call->next.get();
}
applied_sym = op_call->fun_ref;
func = dynamic_cast<SymValFunc*>(applied_sym->value);
// soon we'll get rid of this pragma: it will be always on, we'll pass just {} here and below
bool compute_asm_ltr = code.flags & CodeBlob::_ComputeAsmLtr;
// a function may call anotherF with shuffled arguments: f(x,y) { return anotherF(y,x) }
// then op_call looks like (_1,_0), so use op_call->right for correct positions in Op::_Call below
// it's correct, since every argument has width 1
std::vector<var_idx_t> res_inner = pre_compile_tensor(args, code, lval_globs, compute_asm_ltr ? std::vector<var_idx_t>{} : func->arg_order);
std::vector<var_idx_t> res_inner = pre_compile_tensor(args, code, lval_globs);
res.reserve(res_inner.size());
for (var_idx_t right_idx : op_call->right) {
res.emplace_back(res_inner[right_idx]);
}
} else if (func && func->arg_order.size() == args.size() && !(code.flags & CodeBlob::_ComputeAsmLtr)) {
//std::cerr << "!!! reordering " << args.size() << " arguments of " << sym->name() << std::endl;
res = pre_compile_tensor(args, code, lval_globs, func->arg_order);
} else {
res = pre_compile_tensor(args, code, lval_globs, {});
res = pre_compile_tensor(args, code, lval_globs);
}
auto rvect = new_tmp_vect(code);
auto& op = code.emplace_back(here, Op::_Call, rvect, res, applied_sym);