mirror of
https://github.com/ton-blockchain/ton
synced 2025-03-09 15:40:10 +00:00
change order of assignment lhs=rhs evaluation
This commit is contained in:
tolk-vm
parent
3c245c6146
commit
01fc473801
20 changed files with 577 additions and 429 deletions
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@ -144,15 +144,16 @@ fun test95() {
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"""
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test95 PROC:<{
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...
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next GETGLOB // '10
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3 PUSHINT // '10 '12=3
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4 PUSHINT // '10 '12=3 '13=4
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5 PUSHINT // '10 '12=3 '13=4 '14=5
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TRIPLE // '15 '16
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next SETGLOB
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next GETGLOB // g_next
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3 PUSHINT // g_next '14=3
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4 PUSHINT // g_next '14=3 '15=4
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5 PUSHINT // g_next '14=3 '15=4 '16=5
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TRIPLE // '10 '11
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SWAP
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cur SETGLOB
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cur GETGLOB // '17
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next GETGLOB // '17 '18
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next SETGLOB
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cur GETGLOB // g_cur
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next GETGLOB // g_cur g_next
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}>
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"""
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*/
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@ -147,5 +147,5 @@ fun main() {
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// x.0 x.1
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"""
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@code_hash 7627024945492125068389905298530400936797031708759561372406088054030801992712
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@code_hash 61280273714870328160131559159866470128402169974050439159015534193532598351244
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*/
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@ -26,6 +26,176 @@ fun typesAsIdentifiers(builder: builder) {
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return int;
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}
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global callOrder: tuple;
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fun getTensor_12() {
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callOrder.tuplePush(100);
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return (1, 2);
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}
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fun getTensor_1X(x: int) {
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callOrder.tuplePush(101);
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return (1, x);
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}
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fun getTuple_12() {
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callOrder.tuplePush(110);
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return [1, 2];
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}
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fun getTuple_1X(x: int) {
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callOrder.tuplePush(111);
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return [1, x];
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}
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fun getUntypedTuple_12() {
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callOrder.tuplePush(120);
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var t = createEmptyTuple(); t.tuplePush(1); t.tuplePush(2);
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return t;
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}
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fun getUntypedTuple_1X(x: int) {
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callOrder.tuplePush(121);
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var t = createEmptyTuple(); t.tuplePush(1); t.tuplePush(x);
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return t;
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}
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fun getIntValue5() {
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callOrder.tuplePush(10);
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return 5;
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}
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fun getIntValueX(x: int) {
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callOrder.tuplePush(11);
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return x;
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}
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@method_id(102)
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fun test102() {
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callOrder = createEmptyTuple();
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var x = 0;
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getTensor_12().0 = getIntValue5();
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getTensor_1X(5).1 = getIntValue5();
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getTensor_1X(x = 10).0 = getIntValueX(x);
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return (callOrder, x);
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}
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@method_id(103)
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fun test103() {
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callOrder = createEmptyTuple();
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var x = 0;
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getTuple_12().0 = getIntValue5();
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getTuple_1X(5).1 = getIntValue5();
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getTuple_1X(x = 10).0 = getIntValueX(x);
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return (callOrder, x);
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}
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@method_id(104)
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fun test104() {
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callOrder = createEmptyTuple();
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var x = 0;
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getUntypedTuple_12().0 = getIntValue5();
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getUntypedTuple_1X(5).1 = getIntValue5();
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getUntypedTuple_1X(x = 10).0 = getIntValueX(x);
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return (callOrder, x);
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}
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@method_id(105)
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fun test105() {
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callOrder = createEmptyTuple();
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getTensor_12().0 = getTensor_1X(getIntValue5()).1 = getIntValueX(getTensor_12().1);
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return callOrder;
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}
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@method_id(106)
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fun test106() {
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callOrder = createEmptyTuple();
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getTuple_12().0 = getTuple_1X(getIntValue5()).1 = getIntValueX(getTuple_12().1);
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return callOrder;
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}
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global t107: (int, int);
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@method_id(107)
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fun test107() {
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((t107 = (1, 2)).0, (t107 = (3, 4)).1) = (5, 6);
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return t107;
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}
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global g108: int;
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fun assertEq(a: int, b: int) {
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assert(a == b, 10);
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return b;
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}
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@method_id(108)
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fun test108() {
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callOrder = createEmptyTuple();
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g108 = 0;
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getTensor_1X(g108 = 8).1 = assertEq(g108, 8);
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return (callOrder, g108);
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}
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@method_id(109)
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fun test109() {
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callOrder = createEmptyTuple();
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var x = 0;
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[getTuple_12().0, getTuple_1X(x = getIntValue5()).1, getTuple_1X(x += 10).0] = [getIntValue5(), getIntValue5(), getIntValueX(x)];
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return (callOrder, x);
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}
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global g110: int;
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global t110: (int, int);
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@method_id(110)
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fun test110() {
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callOrder = createEmptyTuple();
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var xy = [0, 0];
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[xy.0, getTuple_1X(g110 = 8).0] = [g110 += 5, getIntValueX(g110 += 10)];
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[xy.1, getTuple_1X((t110 = (8, 9)).0).1] = [t110.0 += 5, getIntValueX(t110.1 += 10)];
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return (xy, callOrder, g110, t110);
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}
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@method_id(111)
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fun test111() {
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callOrder = createEmptyTuple();
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var z = -1;
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var xy = [0, z = 0];
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var rhs = [getIntValueX(xy.1 += 10), xy.1, xy.0, z += 50];
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[xy.0, getTuple_1X(g110 = 8 + getIntValueX(xy.1)).0, xy.1, z] = rhs;
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return (xy, g110, callOrder, z);
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}
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@method_id(112)
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fun test112() {
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var xy = [1, 2];
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((((xy))).0, ((xy.1))) = ((xy).1, ((xy.0)));
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return xy;
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}
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@method_id(113)
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fun test113() {
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var (a, t, z) = (1, [2,3], (-1,-1));
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(a, t, a, z, t.1, z.1) = (10, [a,12], 13, (a, t.1), 14, t.1);
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return (a, t, z);
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}
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global g114: int;
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global t114: [int, int];
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global z114: (int, int);
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@method_id(114)
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fun test114() {
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g114 = 1;
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t114 = [2, 3];
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(g114, t114, g114, z114, t114.1, z114.1) = (10, [g114,12], 13, (g114, t114.1), 14, t114.1);
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return (g114, t114, z114);
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}
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@method_id(115)
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fun test115() {
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callOrder = createEmptyTuple();
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var x = 0;
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var y = 0;
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[getTensor_1X(x = 5).0, y] = getTuple_1X(x = 9);
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return (callOrder, x, y);
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}
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fun main(value: int) {
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var (x: int, y) = (autoInferIntNull(value), autoInferIntNull(value * 2));
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if (x == null && y == null) { return null; }
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@ -37,4 +207,18 @@ fun main(value: int) {
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@testcase | 0 | 6 | -1
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@testcase | 0 | 11 | (null)
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@testcase | 101 | 78 | 88
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@testcase | 102 | | [ 100 10 101 10 101 11 ] 10
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@testcase | 103 | | [ 110 10 111 10 111 11 ] 10
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@testcase | 104 | | [ 120 10 121 10 121 11 ] 10
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@testcase | 105 | | [ 100 10 101 100 11 ]
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@testcase | 106 | | [ 110 10 111 110 11 ]
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@testcase | 107 | | 3 4
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@testcase | 108 | | [ 101 ] 8
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@testcase | 109 | | [ 110 10 111 111 10 10 11 ] 15
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@testcase | 110 | | [ 13 13 ] [ 111 11 111 11 ] 23 13 19
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@testcase | 111 | | [ 10 0 ] 18 [ 11 11 111 ] 50
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@testcase | 112 | | [ 2 1 ]
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@testcase | 113 | | 13 [ 1 14 ] 1 3
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@testcase | 114 | | 13 [ 1 14 ] 1 3
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@testcase | 115 | | [ 101 111 ] 9 9
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*/
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@ -35,7 +35,7 @@ Below, I just give examples of @fif_codegen tag:
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"""
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main PROC:<{
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// s
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17 PUSHINT // s '1=17
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17 PUSHINT // s '3=17
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OVER // s z=17 t
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WHILE:<{
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...
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@ -21,6 +21,26 @@ fun plus(mutate self: int, y: int): int {
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fun eq<X>(v: X): X { return v; }
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global gTup: [int];
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global gTens: (int, int);
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@method_id(100)
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fun testCodegenSimple() {
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var t1 = [1];
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t1.0 = 2;
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debugPrintString("");
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var t2 = [[1]];
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t2.0.0 = 2;
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debugPrintString("");
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gTup = [1];
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gTup.0 = 2;
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debugPrintString("");
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gTens = (1,2);
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gTens.1 = 4;
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debugPrintString("");
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return (t1, t2, gTup, gTens);
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}
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@method_id(101)
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fun test101() {
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var t = (1, (2, 3), [4, 5, [6, 7]], 8);
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@ -241,30 +261,60 @@ fun main(){}
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@fif_codegen
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"""
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testCodegenNoPureIndexedAccess PROC:<{
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testCodegenSimple PROC:<{
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//
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0 PUSHINT // '8=0
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1 PUSHINT // '2=1
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SINGLE // t1
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2 PUSHINT // t1 '3=2
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0 SETINDEX // t1
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x{} PUSHSLICE // t1 '6
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STRDUMP DROP
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1 PUSHINT // t1 '10=1
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SINGLE // t1 '9
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SINGLE // t1 t2
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2 PUSHINT // t1 t2 '11=2
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OVER // t1 t2 '11=2 t2
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0 INDEX // t1 t2 '11=2 '14
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SWAP // t1 t2 '14 '11=2
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0 SETINDEX // t1 t2 '14
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0 SETINDEX // t1 t2
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x{} PUSHSLICE // t1 t2 '17
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STRDUMP DROP
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1 PUSHINT // t1 t2 '20=1
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SINGLE // t1 t2 '18
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gTup SETGLOB
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2 PUSHINT // t1 t2 '21=2
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gTup GETGLOB // t1 t2 '21=2 g_gTup
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SWAP // t1 t2 g_gTup '21=2
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0 SETINDEX // t1 t2 g_gTup
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gTup SETGLOB
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x{} PUSHSLICE // t1 t2 '25
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STRDUMP DROP
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1 PUSHINT // t1 t2 '28=1
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2 PUSHINT // t1 t2 '26=1 '27=2
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PAIR
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gTens SETGLOB
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4 PUSHINT // t1 t2 g_gTens.1=4
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gTens GETGLOB
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UNPAIR // t1 t2 g_gTens.1=4 g_gTens.0 g_gTens.1
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DROP // t1 t2 g_gTens.1=4 g_gTens.0
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SWAP // t1 t2 g_gTens.0 g_gTens.1=4
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PAIR
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gTens SETGLOB
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x{} PUSHSLICE // t1 t2 '36
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STRDUMP DROP
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gTup GETGLOB // t1 t2 g_gTup
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gTens GETGLOB
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UNPAIR // t1 t2 g_gTup g_gTens.0 g_gTens.1
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}>
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"""
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@fif_codegen
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"""
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test104 PROC:<{
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testCodegenNoPureIndexedAccess PROC:<{
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//
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5 PUSHINT // '2=5
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DUP // '2=5 '3=5
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PAIR // '1
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SINGLE // m
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10 PUSHINT // m '5=10
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20 PUSHINT // m '5=10 '6=20
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s2 PUSH // m '5=10 '6=20 m
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0 INDEX // m '10=10 '12=20 '8
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SWAP // m '10=10 '8 '12=20
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1 SETINDEX // m '10=10 '8
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SWAP // m '8 '10=10
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0 SETINDEX // m '8
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0 SETINDEX // m
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...
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0 PUSHINT // '8=0
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}>
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"""
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@fif_codegen
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@ -1,9 +1,9 @@
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fun main() {
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var c = 1;
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(c, c) = (2, 3);
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var t = createEmptyTuple();
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t.0 = (1, 2);
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}
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/**
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@compilation_should_fail
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@stderr one variable modified twice inside the same expression
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@stderr a tuple can not have `(int, int)` inside, because it occupies 2 stack slots in TVM, not 1
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*/
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@ -1,11 +1,8 @@
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fun incThree(mutate a: int, mutate b: int, mutate c: int) {}
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fun main() {
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var c = [[[1, 2]]];
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incThree(mutate c.0.0.0, mutate c.0.0.1, mutate c.0.0.0);
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fun main(cs: slice) {
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var cb = cs.tupleSize;
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}
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/**
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@compilation_should_fail
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@stderr one variable modified twice inside the same expression
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@stderr referencing a method for `tuple` with object of type `slice`
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*/
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@ -1,10 +1,9 @@
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global gg: (int, int);
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fun main() {
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[gg.0, gg.1, gg.0] = [0, 1, 0];
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var t = createEmptyTuple();
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var xy = t.0 as (int, int);
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}
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/**
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@compilation_should_fail
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@stderr one variable modified twice inside the same expression
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@stderr a tuple can not have `(int, int)` inside, because it occupies 2 stack slots in TVM, not 1
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*/
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@ -1,10 +0,0 @@
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global gg: (int, [int, int]);
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fun main() {
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(gg.1.0, gg.1, gg.1.1) = (0, [1, 2], 3);
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}
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/**
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@compilation_should_fail
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@stderr one variable both modified and read inside the same expression
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*/
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@ -1,9 +0,0 @@
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fun main() {
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var ab = (1, 2);
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(ab, ab.1) = ((2, 3), 4);
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}
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/**
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@compilation_should_fail
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@stderr one variable both modified and read inside the same expression
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*/
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@ -1,9 +0,0 @@
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fun main() {
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var t = createEmptyTuple();
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t.0 = (1, 2);
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}
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/**
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@compilation_should_fail
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@stderr can not put `(int, int)` into a tuple, because it occupies 2 stack slots in TVM, not 1
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*/
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@ -1,8 +0,0 @@
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fun main(cs: slice) {
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var cb = cs.tupleSize;
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}
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/**
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@compilation_should_fail
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@stderr referencing a method for `tuple` with object of type `slice`
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*/
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@ -7,5 +7,5 @@ fun main() {
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/**
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@compilation_should_fail
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@stderr can not put `(int, builder)` into a tuple, because it occupies 2 stack slots in TVM, not 1
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@stderr a tuple can not have `(int, builder)` inside, because it occupies 2 stack slots in TVM, not 1
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*/
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@ -307,7 +307,7 @@ fun main(){}
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...
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incrementTwoInPlace CALLDICT // x y sum1
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-ROT
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10 PUSHINT // sum1 x y '10=10
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10 PUSHINT // sum1 x y '11=10
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incrementTwoInPlace CALLDICT // sum1 x y sum2
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s1 s3 s0 XCHG3 // x y sum1 sum2
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}>
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@ -133,7 +133,7 @@ fun main() {
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"""
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test7 PROC:<{
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...
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LDOPTREF // b '8 '7
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LDOPTREF // b '9 '8
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DROP // b c
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ISNULL // b '11
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10 MULCONST // b '13
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@ -193,7 +193,7 @@ class ASTStringifier final : public ASTVisitor {
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}
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case ast_local_var_lhs: {
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std::ostringstream os;
|
||||
os << (v->as<ast_local_var_lhs>()->inferred_type ? v->as<ast_local_var_lhs>()->inferred_type : v->as<ast_local_var_lhs>()->declared_type);
|
||||
os << (v->as<ast_local_var_lhs>()->inferred_type ? v->as<ast_local_var_lhs>()->inferred_type->as_human_readable() : v->as<ast_local_var_lhs>()->declared_type->as_human_readable());
|
||||
if (v->as<ast_local_var_lhs>()->get_name().empty()) {
|
||||
return "_: " + os.str();
|
||||
}
|
||||
|
|
|
|||
|
|
@ -30,158 +30,17 @@
|
|||
* Up to this point, all types have been inferred, all validity checks have been passed, etc.
|
||||
* All properties in AST nodes are assigned and can be safely used (fun_ref, etc.).
|
||||
* So, if execution reaches this pass, the input is (almost) correct, and code generation should succeed.
|
||||
* The only thing additionally checked during this pass is tricky lvalue, like one and the same variable
|
||||
* assigned/mutated multiple times in same expression, e.g. `(t.0, t.0) = rhs` / `f(mutate x.1.2, mutate x)`.
|
||||
* (previously, there was a check for one variable modified twice like `(t.0, t.0) = rhs`, but after changing
|
||||
* execution order of assignment to "first lhs, then lhs", it was removed for several reasons)
|
||||
*/
|
||||
|
||||
namespace tolk {
|
||||
|
||||
// fire error on cases like `(a, a) = rhs` / `f(mutate t.1.0, mutate t.1.0)`
|
||||
GNU_ATTRIBUTE_NORETURN GNU_ATTRIBUTE_COLD
|
||||
static void fire_error_variable_modified_twice_inside_same_expression(SrcLocation loc) {
|
||||
throw ParseError(loc, "one variable modified twice inside the same expression");
|
||||
}
|
||||
class LValContext;
|
||||
std::vector<var_idx_t> pre_compile_expr(AnyExprV v, CodeBlob& code, LValContext* lval_ctx = nullptr);
|
||||
std::vector<var_idx_t> pre_compile_symbol(SrcLocation loc, const Symbol* sym, CodeBlob& code, LValContext* lval_ctx);
|
||||
void process_any_statement(AnyV v, CodeBlob& code);
|
||||
|
||||
// fire error on cases like `(m.1.0, m.1) = rhs` (m.1 inside m.1.0 is "rval inside lval")
|
||||
GNU_ATTRIBUTE_NORETURN GNU_ATTRIBUTE_COLD
|
||||
static void fire_error_variable_modified_and_read_inside_same_expression(SrcLocation loc) {
|
||||
throw ParseError(loc, "one variable both modified and read inside the same expression");
|
||||
}
|
||||
|
||||
// Main goal of LValContext is to handle non-primitive lvalues. At IR level, a usual local variable
|
||||
// exists, but on its change, something non-trivial should happen.
|
||||
// Example: `globalVar = 9` actually does `Const $5 = 9` + `Let $6 = $5` + `SetGlob "globVar" = $6`
|
||||
// Example: `tupleVar.0 = 9` actually does `Const $5 = 9` + `Let $6 = $5` + `Const $7 = 0` + `Call tupleSetAt($4, $6, $7)`
|
||||
// Of course, mixing globals with tuples should also be supported.
|
||||
// To achieve this, treat tupleObj inside "tupleObj.i" like "rvalue inside lvalue".
|
||||
// For instance, `globalTuple.0 = 9` reads global (like rvalue), assigns 9 to tmp var, modifies tuple, writes global.
|
||||
// A challenging thing is handling "unique" parts, to be read/updated only once.
|
||||
// Example: `f(mutate globalTensor.0, mutate globalTensor.1)`, then globalTensor should be read/written once.
|
||||
// Example: `(t.0.0, t.0.1) = rhs` (m is [[int, int]]), then t.0 should be read/updated once.
|
||||
// Solving this by calculating hashes of every lvalue or rvalue inside lvalue automatically gives an ability
|
||||
// to detect and fire "multiple writes inside expression", like `(a, a) = rhs` / `[t.0, (t.0.1, c)] = rhs`.
|
||||
// Note, that tensors (not tuples) `tensorVar.0 = 9` do not emit anything special (unless global).
|
||||
class LValContext {
|
||||
// every global variable used as lvalue is registered here
|
||||
// example: `globalInt = 9`, implicit var is created `$tmp = 9`, and `SetGlob "globalInt" $tmp` is done after
|
||||
// global tensors are stored as tuples (unpacked on reading, packed on writing), then multiple tmp vars are created
|
||||
struct ModifiedGlob {
|
||||
const GlobalVarData* glob_ref;
|
||||
std::vector<var_idx_t> local_ir_idx; // typically 1, generally calc_width_on_stack() of global var (tensors)
|
||||
|
||||
void apply(CodeBlob& code, SrcLocation loc) const {
|
||||
Op& op = code.emplace_back(loc, Op::_SetGlob, std::vector<var_idx_t>{}, local_ir_idx, glob_ref);
|
||||
op.set_impure_flag();
|
||||
}
|
||||
};
|
||||
|
||||
// every tuple index used as lvalue is registered here
|
||||
// example: `t.0 = 9`, implicit var is created `$tmp = 9`, as well as `$tmp_idx = 0` and `tupleSetAt()` is done after
|
||||
// for `t.0.0` if t is `[[int, ...]]`, `tupleAt()` for it is done since it's rvalue, and `tupleSetAt()` is done 2 times
|
||||
struct ModifiedTupleIndex {
|
||||
uint64_t hash;
|
||||
var_idx_t tuple_ir_idx;
|
||||
var_idx_t index_ir_idx;
|
||||
var_idx_t field_ir_idx;
|
||||
|
||||
void apply(CodeBlob& code, SrcLocation loc) const {
|
||||
const FunctionData* builtin_sym = lookup_global_symbol("tupleSetAt")->as<FunctionData>();
|
||||
code.emplace_back(loc, Op::_Call, std::vector{tuple_ir_idx}, std::vector{tuple_ir_idx, field_ir_idx, index_ir_idx}, builtin_sym);
|
||||
}
|
||||
};
|
||||
|
||||
int level_rval_inside_lval = 0;
|
||||
std::vector<std::variant<ModifiedGlob, ModifiedTupleIndex>> modifications;
|
||||
std::unordered_set<uint64_t> all_modified_hashes;
|
||||
|
||||
void fire_if_one_variable_modified_twice(SrcLocation loc, uint64_t modified_hash) {
|
||||
if (!is_rval_inside_lval()) {
|
||||
if (!all_modified_hashes.insert(modified_hash).second) {
|
||||
fire_error_variable_modified_twice_inside_same_expression(loc);
|
||||
}
|
||||
if (all_modified_hashes.contains(~modified_hash)) {
|
||||
fire_error_variable_modified_and_read_inside_same_expression(loc);
|
||||
}
|
||||
} else {
|
||||
all_modified_hashes.insert(~modified_hash);
|
||||
if (all_modified_hashes.contains(modified_hash)) {
|
||||
fire_error_variable_modified_and_read_inside_same_expression(loc);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public:
|
||||
void enter_rval_inside_lval() { level_rval_inside_lval++; }
|
||||
void exit_rval_inside_lval() { level_rval_inside_lval--; }
|
||||
bool is_rval_inside_lval() const { return level_rval_inside_lval > 0; }
|
||||
|
||||
uint64_t register_lval(SrcLocation loc, const LocalVarData* var_ref) {
|
||||
uint64_t hash = reinterpret_cast<uint64_t>(var_ref);
|
||||
fire_if_one_variable_modified_twice(loc, hash);
|
||||
return hash;
|
||||
}
|
||||
|
||||
uint64_t register_lval(SrcLocation loc, const GlobalVarData* glob_ref) {
|
||||
uint64_t hash = reinterpret_cast<uint64_t>(glob_ref);
|
||||
fire_if_one_variable_modified_twice(loc, hash);
|
||||
return hash;
|
||||
}
|
||||
|
||||
uint64_t register_lval(SrcLocation loc, V<ast_dot_access> v) {
|
||||
uint64_t hash = 7;
|
||||
AnyExprV leftmost_obj = v;
|
||||
while (auto v_dot = leftmost_obj->try_as<ast_dot_access>()) {
|
||||
if (!v_dot->is_target_indexed_access()) {
|
||||
break;
|
||||
}
|
||||
hash = hash * 1915239017 + std::get<int>(v_dot->target);
|
||||
leftmost_obj = v_dot->get_obj();
|
||||
}
|
||||
if (auto v_ref = leftmost_obj->try_as<ast_reference>()) {
|
||||
hash *= reinterpret_cast<uint64_t>(v_ref->sym); // `v.0` and `v.0` in 2 places is the same
|
||||
} else {
|
||||
hash *= reinterpret_cast<uint64_t>(leftmost_obj); // unlike `f().0` and `f().0` (pointers to AST nodes differ)
|
||||
}
|
||||
fire_if_one_variable_modified_twice(loc, hash);
|
||||
return hash;
|
||||
}
|
||||
|
||||
const std::vector<var_idx_t>* exists_already_known_global(const GlobalVarData* glob_ref) const {
|
||||
for (const auto& m : modifications) {
|
||||
if (const auto* m_glob = std::get_if<ModifiedGlob>(&m); m_glob && m_glob->glob_ref == glob_ref) {
|
||||
return &m_glob->local_ir_idx;
|
||||
}
|
||||
}
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
const var_idx_t* exists_already_known_tuple_index(uint64_t hash) const {
|
||||
for (const auto& m : modifications) {
|
||||
if (const auto* m_tup = std::get_if<ModifiedTupleIndex>(&m); m_tup && m_tup->hash == hash) {
|
||||
return &m_tup->field_ir_idx;
|
||||
}
|
||||
}
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
void register_modified_global(const GlobalVarData* glob_ref, std::vector<var_idx_t> local_ir_idx) {
|
||||
modifications.emplace_back(ModifiedGlob{glob_ref, std::move(local_ir_idx)});
|
||||
}
|
||||
|
||||
void register_modified_tuple_index(uint64_t hash, var_idx_t tuple_ir_idx, var_idx_t index_ir_idx, var_idx_t field_ir_idx) {
|
||||
modifications.emplace_back(ModifiedTupleIndex{hash, tuple_ir_idx, index_ir_idx, field_ir_idx});
|
||||
}
|
||||
|
||||
void gen_ops_if_nonempty(CodeBlob& code, SrcLocation loc) const {
|
||||
for (auto it = modifications.rbegin(); it != modifications.rend(); ++it) { // reverse, it's important
|
||||
if (const auto* m_glob = std::get_if<ModifiedGlob>(&*it)) {
|
||||
m_glob->apply(code, loc);
|
||||
} else if (const auto* m_tup = std::get_if<ModifiedTupleIndex>(&*it)) {
|
||||
m_tup->apply(code, loc);
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// The goal of VarsModificationWatcher is to detect such cases: `return (x, x += y, x)`.
|
||||
// Without any changes, ops will be { _Call $2 = +($0_x, $1_y); _Return $0_x, $2, $0_x } - incorrect
|
||||
|
|
@ -229,8 +88,176 @@ public:
|
|||
|
||||
static VarsModificationWatcher vars_modification_watcher;
|
||||
|
||||
std::vector<var_idx_t> pre_compile_expr(AnyExprV v, CodeBlob& code, LValContext* lval_ctx = nullptr);
|
||||
void process_any_statement(AnyV v, CodeBlob& code);
|
||||
|
||||
// Main goal of LValContext is to handle non-primitive lvalues. At IR level, a usual local variable
|
||||
// exists, but on its change, something non-trivial should happen.
|
||||
// Example: `globalVar = 9` actually does `Const $5 = 9` + `Let $6 = $5` + `SetGlob "globVar" = $6`
|
||||
// Example: `tupleVar.0 = 9` actually does `Const $5 = 9` + `Let $6 = $5` + `Const $7 = 0` + `Call tupleSetAt($4, $6, $7)`
|
||||
// Of course, mixing globals with tuples should also be supported.
|
||||
// To achieve this, treat tupleObj inside "tupleObj.i" like "rvalue inside lvalue".
|
||||
// For instance, `globalTuple.0 = 9` reads global (like rvalue), assigns 9 to tmp var, modifies tuple, writes global.
|
||||
// Note, that tensors (not tuples) `tensorVar.0 = 9` do not emit anything special (unless global).
|
||||
class LValContext {
|
||||
// every global variable used as lvalue is registered here
|
||||
// example: `globalInt = 9`, implicit var is created `$tmp = 9`, and `SetGlob "globalInt" $tmp` is done after
|
||||
struct ModifiedGlobal {
|
||||
const GlobalVarData* glob_ref;
|
||||
std::vector<var_idx_t> lval_ir_idx; // typically 1, generally calc_width_on_stack() of global var (tensors)
|
||||
|
||||
// for 1-slot globals int/cell/slice, assigning to them is just SETGLOB
|
||||
// same for tensors, if they are fully rewritten in an expression: `gTensor = (5,6)`
|
||||
void apply_fully_rewrite(CodeBlob& code, SrcLocation loc) const {
|
||||
Op& op = code.emplace_back(loc, Op::_SetGlob, std::vector<var_idx_t>{}, lval_ir_idx, glob_ref);
|
||||
op.set_impure_flag();
|
||||
}
|
||||
|
||||
// for N-slot globals tensor/struct/union, assigning to their parts, like `gTensor.1 = 6`
|
||||
// we need to read gTensor as a whole (0-th and 1-th component), rewrite 1-th component, and SETGLOB a whole back
|
||||
void apply_partially_rewrite(CodeBlob& code, SrcLocation loc, std::vector<bool>&& was_modified_by_let) const {
|
||||
LValContext local_lval;
|
||||
local_lval.enter_rval_inside_lval();
|
||||
std::vector<var_idx_t> local_ir_idx = pre_compile_symbol(loc, glob_ref, code, &local_lval);
|
||||
for (size_t i = 0; i < local_ir_idx.size(); ++i) {
|
||||
if (was_modified_by_let[i]) {
|
||||
code.emplace_back(loc, Op::_Let, std::vector{local_ir_idx[i]}, std::vector{lval_ir_idx[i]});
|
||||
}
|
||||
}
|
||||
|
||||
Op& op = code.emplace_back(loc, Op::_SetGlob, std::vector<var_idx_t>{}, local_ir_idx, glob_ref);
|
||||
op.set_impure_flag();
|
||||
}
|
||||
};
|
||||
|
||||
// every tensor index, when a tensor is a global, is registered here (same for structs and fields)
|
||||
// example: `global v: (int, int); v.1 = 5`, implicit var is created `$tmp = 5`, and when it's modified,
|
||||
// we need to partially update w; essentially, apply_partially_rewrite() above will be called
|
||||
struct ModifiedFieldOfGlobal {
|
||||
AnyExprV tensor_obj;
|
||||
int index_at;
|
||||
std::vector<var_idx_t> lval_ir_idx;
|
||||
|
||||
void apply(CodeBlob& code, SrcLocation loc) const {
|
||||
LValContext local_lval;
|
||||
local_lval.enter_rval_inside_lval();
|
||||
std::vector<var_idx_t> obj_ir_idx = pre_compile_expr(tensor_obj, code, &local_lval);
|
||||
const TypeDataTensor* t_tensor = tensor_obj->inferred_type->try_as<TypeDataTensor>();
|
||||
tolk_assert(t_tensor);
|
||||
int stack_width = t_tensor->items[index_at]->calc_width_on_stack();
|
||||
int stack_offset = 0;
|
||||
for (int i = 0; i < index_at; ++i) {
|
||||
stack_offset += t_tensor->items[i]->calc_width_on_stack();
|
||||
}
|
||||
std::vector<var_idx_t> field_ir_idx = {obj_ir_idx.begin() + stack_offset, obj_ir_idx.begin() + stack_offset + stack_width};
|
||||
tolk_assert(field_ir_idx.size() == lval_ir_idx.size());
|
||||
|
||||
vars_modification_watcher.trigger_callbacks(field_ir_idx, loc);
|
||||
code.emplace_back(loc, Op::_Let, field_ir_idx, lval_ir_idx);
|
||||
local_lval.after_let(std::move(field_ir_idx), code, loc);
|
||||
}
|
||||
};
|
||||
|
||||
// every tuple index used as lvalue is registered here
|
||||
// example: `t.0 = 9`, implicit var is created `$tmp = 9`, as well as `$tmp_idx = 0` and `tupleSetAt()` is done after
|
||||
// for `t.0.0` if t is `[[int, ...]]`, `tupleAt()` for it is done since it's rvalue, and `tupleSetAt()` is done 2 times
|
||||
struct ModifiedTupleIndex {
|
||||
AnyExprV tuple_obj;
|
||||
int index_at;
|
||||
std::vector<var_idx_t> lval_ir_idx;
|
||||
|
||||
void apply(CodeBlob& code, SrcLocation loc) const {
|
||||
LValContext local_lval;
|
||||
local_lval.enter_rval_inside_lval();
|
||||
std::vector<var_idx_t> tuple_ir_idx = pre_compile_expr(tuple_obj, code, &local_lval);
|
||||
std::vector<var_idx_t> index_ir_idx = code.create_tmp_var(TypeDataInt::create(), loc, "(tuple-idx)");
|
||||
code.emplace_back(loc, Op::_IntConst, index_ir_idx, td::make_refint(index_at));
|
||||
|
||||
vars_modification_watcher.trigger_callbacks(tuple_ir_idx, loc);
|
||||
const FunctionData* builtin_sym = lookup_global_symbol("tupleSetAt")->as<FunctionData>();
|
||||
code.emplace_back(loc, Op::_Call, std::vector{tuple_ir_idx}, std::vector{tuple_ir_idx[0], lval_ir_idx[0], index_ir_idx[0]}, builtin_sym);
|
||||
local_lval.after_let(std::move(tuple_ir_idx), code, loc);
|
||||
}
|
||||
};
|
||||
|
||||
int level_rval_inside_lval = 0;
|
||||
std::vector<std::variant<ModifiedGlobal, ModifiedTupleIndex, ModifiedFieldOfGlobal>> modifications;
|
||||
|
||||
static bool vector_contains(const std::vector<var_idx_t>& ir_vars, var_idx_t ir_idx) {
|
||||
for (var_idx_t var_in_vector : ir_vars) {
|
||||
if (var_in_vector == ir_idx) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
public:
|
||||
void enter_rval_inside_lval() { level_rval_inside_lval++; }
|
||||
void exit_rval_inside_lval() { level_rval_inside_lval--; }
|
||||
bool is_rval_inside_lval() const { return level_rval_inside_lval > 0; }
|
||||
|
||||
void capture_global_modification(const GlobalVarData* glob_ref, std::vector<var_idx_t> lval_ir_idx) {
|
||||
modifications.emplace_back(ModifiedGlobal{glob_ref, std::move(lval_ir_idx)});
|
||||
}
|
||||
|
||||
void capture_field_of_global_modification(AnyExprV tensor_obj, int index_at, std::vector<var_idx_t> lval_ir_idx) {
|
||||
modifications.emplace_back(ModifiedFieldOfGlobal{tensor_obj, index_at, std::move(lval_ir_idx)});
|
||||
}
|
||||
|
||||
void capture_tuple_index_modification(AnyExprV tuple_obj, int index_at, std::vector<var_idx_t> lval_ir_idx) {
|
||||
modifications.emplace_back(ModifiedTupleIndex{tuple_obj, index_at, std::move(lval_ir_idx)});
|
||||
}
|
||||
|
||||
void after_let(std::vector<var_idx_t>&& let_left_vars, CodeBlob& code, SrcLocation loc) const {
|
||||
for (const auto &modification : modifications) {
|
||||
if (const auto* m_glob = std::get_if<ModifiedGlobal>(&modification)) {
|
||||
int n_modified_by_let = 0;
|
||||
std::vector<bool> was_modified_by_let;
|
||||
was_modified_by_let.resize(m_glob->lval_ir_idx.size());
|
||||
for (size_t i = 0; i < m_glob->lval_ir_idx.size(); ++i) {
|
||||
if (vector_contains(let_left_vars, m_glob->lval_ir_idx[i])) {
|
||||
was_modified_by_let[i] = true;
|
||||
n_modified_by_let++;
|
||||
}
|
||||
}
|
||||
if (n_modified_by_let == static_cast<int>(m_glob->lval_ir_idx.size())) {
|
||||
m_glob->apply_fully_rewrite(code, loc);
|
||||
} else if (n_modified_by_let > 0) {
|
||||
m_glob->apply_partially_rewrite(code, loc, std::move(was_modified_by_let));
|
||||
}
|
||||
} else if (const auto* m_tup = std::get_if<ModifiedTupleIndex>(&modification)) {
|
||||
bool was_tuple_index_modified = false;
|
||||
for (var_idx_t field_ir_idx : m_tup->lval_ir_idx) {
|
||||
was_tuple_index_modified |= vector_contains(let_left_vars, field_ir_idx);
|
||||
}
|
||||
if (was_tuple_index_modified) {
|
||||
m_tup->apply(code, loc);
|
||||
}
|
||||
} else if (const auto* m_tens = std::get_if<ModifiedFieldOfGlobal>(&modification)) {
|
||||
bool was_tensor_index_modified = false;
|
||||
for (var_idx_t field_ir_idx : m_tens->lval_ir_idx) {
|
||||
was_tensor_index_modified |= vector_contains(let_left_vars, field_ir_idx);
|
||||
}
|
||||
if (was_tensor_index_modified) {
|
||||
m_tens->apply(code, loc);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// given `{some_expr}.{i}`, check it for pattern `some_var.0` / `some_var.0.1` / etc.
|
||||
// return some_var if satisfies (it may be a local or a global var, a tensor or a tuple)
|
||||
// return nullptr otherwise: `f().0` / `(v = rhs).0` / `some_var.method().0` / etc.
|
||||
static V<ast_reference> calc_sink_leftmost_obj(V<ast_dot_access> v) {
|
||||
AnyExprV leftmost_obj = v->get_obj();
|
||||
while (auto v_dot = leftmost_obj->try_as<ast_dot_access>()) {
|
||||
if (!v_dot->is_target_indexed_access()) {
|
||||
break;
|
||||
}
|
||||
leftmost_obj = v_dot->get_obj();
|
||||
}
|
||||
return leftmost_obj->type == ast_reference ? leftmost_obj->as<ast_reference>() : nullptr;
|
||||
}
|
||||
|
||||
|
||||
static std::vector<std::vector<var_idx_t>> pre_compile_tensor_inner(CodeBlob& code, const std::vector<AnyExprV>& args,
|
||||
|
|
@ -313,43 +340,43 @@ static std::vector<var_idx_t> pre_compile_tensor(CodeBlob& code, const std::vect
|
|||
static std::vector<var_idx_t> pre_compile_let(CodeBlob& code, AnyExprV lhs, AnyExprV rhs, SrcLocation loc) {
|
||||
// [lhs] = [rhs]; since type checking is ok, it's the same as "lhs = rhs"
|
||||
if (lhs->type == ast_typed_tuple && rhs->type == ast_typed_tuple) {
|
||||
std::vector<var_idx_t> right = pre_compile_tensor(code, rhs->as<ast_typed_tuple>()->get_items());
|
||||
LValContext local_lval;
|
||||
std::vector<var_idx_t> left = pre_compile_tensor(code, lhs->as<ast_typed_tuple>()->get_items(), &local_lval);
|
||||
vars_modification_watcher.trigger_callbacks(left, loc);
|
||||
code.emplace_back(loc, Op::_Let, std::move(left), right);
|
||||
local_lval.gen_ops_if_nonempty(code, loc);
|
||||
std::vector<var_idx_t> right = pre_compile_tensor(code, rhs->as<ast_typed_tuple>()->get_items());
|
||||
code.emplace_back(loc, Op::_Let, left, right);
|
||||
local_lval.after_let(std::move(left), code, loc);
|
||||
return right;
|
||||
}
|
||||
// [lhs] = rhs; it's un-tuple to N left vars
|
||||
if (lhs->type == ast_typed_tuple) {
|
||||
LValContext local_lval;
|
||||
std::vector<var_idx_t> left = pre_compile_tensor(code, lhs->as<ast_typed_tuple>()->get_items(), &local_lval);
|
||||
vars_modification_watcher.trigger_callbacks(left, loc);
|
||||
std::vector<var_idx_t> right = pre_compile_expr(rhs, code);
|
||||
const TypeDataTypedTuple* inferred_tuple = rhs->inferred_type->try_as<TypeDataTypedTuple>();
|
||||
std::vector<TypePtr> types_list = inferred_tuple->items;
|
||||
std::vector<var_idx_t> rvect = code.create_tmp_var(TypeDataTensor::create(std::move(types_list)), rhs->loc, "(unpack-tuple)");
|
||||
code.emplace_back(lhs->loc, Op::_UnTuple, rvect, std::move(right));
|
||||
LValContext local_lval;
|
||||
std::vector<var_idx_t> left = pre_compile_tensor(code, lhs->as<ast_typed_tuple>()->get_items(), &local_lval);
|
||||
vars_modification_watcher.trigger_callbacks(left, loc);
|
||||
code.emplace_back(loc, Op::_Let, std::move(left), rvect);
|
||||
local_lval.gen_ops_if_nonempty(code, loc);
|
||||
code.emplace_back(loc, Op::_Let, left, rvect);
|
||||
local_lval.after_let(std::move(left), code, loc);
|
||||
return rvect;
|
||||
}
|
||||
// small optimization: `var x = rhs` or `local_var = rhs` (90% cases), LValContext not needed actually
|
||||
if (lhs->type == ast_local_var_lhs || (lhs->type == ast_reference && lhs->as<ast_reference>()->sym->try_as<LocalVarData>())) {
|
||||
std::vector<var_idx_t> right = pre_compile_expr(rhs, code);
|
||||
std::vector<var_idx_t> left = pre_compile_expr(lhs, code); // effectively, local_var->ir_idx
|
||||
vars_modification_watcher.trigger_callbacks(left, loc);
|
||||
std::vector<var_idx_t> right = pre_compile_expr(rhs, code);
|
||||
code.emplace_back(loc, Op::_Let, std::move(left), right);
|
||||
return right;
|
||||
}
|
||||
// lhs = rhs
|
||||
std::vector<var_idx_t> right = pre_compile_expr(rhs, code);
|
||||
LValContext local_lval;
|
||||
std::vector<var_idx_t> left = pre_compile_expr(lhs, code, &local_lval);
|
||||
vars_modification_watcher.trigger_callbacks(left, loc);
|
||||
code.emplace_back(loc, Op::_Let, std::move(left), right);
|
||||
local_lval.gen_ops_if_nonempty(code, loc);
|
||||
std::vector<var_idx_t> right = pre_compile_expr(rhs, code);
|
||||
code.emplace_back(loc, Op::_Let, left, right);
|
||||
local_lval.after_let(std::move(left), code, loc);
|
||||
return right;
|
||||
}
|
||||
|
||||
|
|
@ -364,28 +391,22 @@ static std::vector<var_idx_t> gen_op_call(CodeBlob& code, TypePtr ret_type, SrcL
|
|||
}
|
||||
|
||||
|
||||
static std::vector<var_idx_t> pre_compile_symbol(SrcLocation loc, const Symbol* sym, CodeBlob& code, LValContext* lval_ctx) {
|
||||
std::vector<var_idx_t> pre_compile_symbol(SrcLocation loc, const Symbol* sym, CodeBlob& code, LValContext* lval_ctx) {
|
||||
if (const auto* glob_ref = sym->try_as<GlobalVarData>()) {
|
||||
if (!lval_ctx) {
|
||||
// `globalVar` is used for reading, just create local IR var to represent its value, Op GlobVar will fill it
|
||||
// note, that global tensors are stored as a tuple an unpacked to N vars on read, N determined by declared_type
|
||||
std::vector<var_idx_t> local_ir_idx = code.create_tmp_var(glob_ref->declared_type, loc, "(glob-var)");
|
||||
code.emplace_back(loc, Op::_GlobVar, local_ir_idx, std::vector<var_idx_t>{}, glob_ref);
|
||||
return local_ir_idx;
|
||||
} else {
|
||||
// `globalVar = rhs` / `mutate globalVar` / `globalTuple.0 = rhs`
|
||||
lval_ctx->register_lval(loc, glob_ref);
|
||||
if (const std::vector<var_idx_t>* local_ir_idx = lval_ctx->exists_already_known_global(glob_ref)) {
|
||||
return *local_ir_idx; // `f(mutate g.0, mutate g.1)`, then g will be read only once
|
||||
}
|
||||
std::vector<var_idx_t> local_ir_idx = code.create_tmp_var(glob_ref->declared_type, loc, "(glob-var)");
|
||||
if (lval_ctx->is_rval_inside_lval()) { // for `globalVar.0` "globalVar" is rvalue inside lvalue
|
||||
// for `globalVar = rhs` don't read a global actually, but for `globalVar.0 = rhs` do
|
||||
code.emplace_back(loc, Op::_GlobVar, local_ir_idx, std::vector<var_idx_t>{}, glob_ref);
|
||||
}
|
||||
lval_ctx->register_modified_global(glob_ref, local_ir_idx);
|
||||
return local_ir_idx;
|
||||
// handle `globalVar = rhs` / `mutate globalVar`
|
||||
if (lval_ctx && !lval_ctx->is_rval_inside_lval()) {
|
||||
std::vector<var_idx_t> lval_ir_idx = code.create_tmp_var(glob_ref->declared_type, loc, "(lval-glob)");
|
||||
lval_ctx->capture_global_modification(glob_ref, lval_ir_idx);
|
||||
return lval_ir_idx;
|
||||
}
|
||||
// `globalVar` is used for reading, just create local IR var to represent its value, Op GlobVar will fill it
|
||||
// note, that global tensors are stored as a tuple an unpacked to N vars on read, N determined by declared_type
|
||||
std::vector<var_idx_t> local_ir_idx = code.create_var(glob_ref->declared_type, loc, "g_" + glob_ref->name);
|
||||
code.emplace_back(loc, Op::_GlobVar, local_ir_idx, std::vector<var_idx_t>{}, glob_ref);
|
||||
if (lval_ctx) { // `globalVar.0 = rhs`, globalVar is rval inside lval
|
||||
lval_ctx->capture_global_modification(glob_ref, local_ir_idx);
|
||||
}
|
||||
return local_ir_idx;
|
||||
}
|
||||
if (const auto* const_ref = sym->try_as<GlobalConstData>()) {
|
||||
if (const_ref->is_int_const()) {
|
||||
|
|
@ -407,15 +428,12 @@ static std::vector<var_idx_t> pre_compile_symbol(SrcLocation loc, const Symbol*
|
|||
#ifdef TOLK_DEBUG
|
||||
tolk_assert(static_cast<int>(var_ref->ir_idx.size()) == var_ref->declared_type->calc_width_on_stack());
|
||||
#endif
|
||||
if (lval_ctx) {
|
||||
lval_ctx->register_lval(loc, var_ref);
|
||||
}
|
||||
return var_ref->ir_idx;
|
||||
}
|
||||
throw Fatal("pre_compile_symbol");
|
||||
}
|
||||
|
||||
static std::vector<var_idx_t> process_assign(V<ast_assign> v, CodeBlob& code) {
|
||||
static std::vector<var_idx_t> process_assignment(V<ast_assign> v, CodeBlob& code) {
|
||||
if (auto lhs_decl = v->get_lhs()->try_as<ast_local_vars_declaration>()) {
|
||||
return pre_compile_let(code, lhs_decl->get_expr(), v->get_rhs(), v->loc);
|
||||
} else {
|
||||
|
|
@ -492,12 +510,18 @@ static std::vector<var_idx_t> process_dot_access(V<ast_dot_access> v, CodeBlob&
|
|||
if (!v->is_target_fun_ref()) {
|
||||
TypePtr obj_type = v->get_obj()->inferred_type;
|
||||
int index_at = std::get<int>(v->target);
|
||||
// `tensorVar.0`; since a tensor of N elems are N vars on a stack actually, calculate offset
|
||||
// `tensorVar.0`
|
||||
if (const auto* t_tensor = obj_type->try_as<TypeDataTensor>()) {
|
||||
if (lval_ctx) lval_ctx->register_lval(v->loc, v);
|
||||
if (lval_ctx) lval_ctx->enter_rval_inside_lval();
|
||||
// handle `tensorVar.0 = rhs` if tensors is a global, special case, then the global will be read on demand
|
||||
if (lval_ctx && !lval_ctx->is_rval_inside_lval()) {
|
||||
if (auto sink = calc_sink_leftmost_obj(v); sink && sink->sym->try_as<GlobalVarData>()) {
|
||||
std::vector<var_idx_t> lval_ir_idx = code.create_tmp_var(v->inferred_type, v->loc, "(lval-global-tensor)");
|
||||
lval_ctx->capture_field_of_global_modification(v->get_obj(), index_at, lval_ir_idx);
|
||||
return lval_ir_idx;
|
||||
}
|
||||
}
|
||||
// since a tensor of N elems are N vars on a stack actually, calculate offset
|
||||
std::vector<var_idx_t> lhs_vars = pre_compile_expr(v->get_obj(), code, lval_ctx);
|
||||
if (lval_ctx) lval_ctx->exit_rval_inside_lval();
|
||||
int stack_width = t_tensor->items[index_at]->calc_width_on_stack();
|
||||
int stack_offset = 0;
|
||||
for (int i = 0; i < index_at; ++i) {
|
||||
|
|
@ -505,39 +529,26 @@ static std::vector<var_idx_t> process_dot_access(V<ast_dot_access> v, CodeBlob&
|
|||
}
|
||||
return {lhs_vars.begin() + stack_offset, lhs_vars.begin() + stack_offset + stack_width};
|
||||
}
|
||||
// `tupleVar.0`; not to mess up, separate rvalue and lvalue cases
|
||||
// `tupleVar.0`
|
||||
if (obj_type->try_as<TypeDataTypedTuple>() || obj_type->try_as<TypeDataTuple>()) {
|
||||
if (!lval_ctx) {
|
||||
// `tupleVar.0` as rvalue: the same as "tupleAt(tupleVar, 0)" written in terms of IR vars
|
||||
std::vector<var_idx_t> tuple_ir_idx = pre_compile_expr(v->get_obj(), code);
|
||||
std::vector<var_idx_t> index_ir_idx = code.create_tmp_var(TypeDataInt::create(), v->get_identifier()->loc, "(tuple-idx)");
|
||||
code.emplace_back(v->loc, Op::_IntConst, index_ir_idx, td::make_refint(index_at));
|
||||
std::vector<var_idx_t> field_ir_idx = code.create_tmp_var(v->inferred_type, v->loc, "(tuple-field)");
|
||||
tolk_assert(tuple_ir_idx.size() == 1 && field_ir_idx.size() == 1); // tuples contain only 1-slot values
|
||||
const FunctionData* builtin_sym = lookup_global_symbol("tupleAt")->as<FunctionData>();
|
||||
code.emplace_back(v->loc, Op::_Call, field_ir_idx, std::vector{tuple_ir_idx[0], index_ir_idx[0]}, builtin_sym);
|
||||
return field_ir_idx;
|
||||
} else {
|
||||
// `tupleVar.0 = rhs`: finally "tupleSetAt(tupleVar, rhs, 0)" will be done
|
||||
uint64_t hash = lval_ctx->register_lval(v->loc, v);
|
||||
if (const var_idx_t* field_ir_idx = lval_ctx->exists_already_known_tuple_index(hash)) {
|
||||
return {*field_ir_idx}; // `(t.0.0, t.0.1) = rhs`, then "t.0" will be read (tupleAt) once
|
||||
}
|
||||
lval_ctx->enter_rval_inside_lval();
|
||||
std::vector<var_idx_t> tuple_ir_idx = pre_compile_expr(v->get_obj(), code, lval_ctx);
|
||||
lval_ctx->exit_rval_inside_lval();
|
||||
std::vector<var_idx_t> index_ir_idx = code.create_tmp_var(TypeDataInt::create(), v->get_identifier()->loc, "(tuple-idx)");
|
||||
code.emplace_back(v->loc, Op::_IntConst, index_ir_idx, td::make_refint(index_at));
|
||||
std::vector<var_idx_t> field_ir_idx = code.create_tmp_var(v->inferred_type, v->loc, "(tuple-field)");
|
||||
if (lval_ctx->is_rval_inside_lval()) { // for `t.0.1 = rhs` "t.0" is rvalue inside lvalue
|
||||
// for `t.0 = rhs` don't call tupleAt, but for `t.0.1 = rhs` do for t.0 (still don't for t.0.1)
|
||||
const FunctionData* builtin_sym = lookup_global_symbol("tupleAt")->as<FunctionData>();
|
||||
code.emplace_back(v->loc, Op::_Call, field_ir_idx, std::vector{tuple_ir_idx[0], index_ir_idx[0]}, builtin_sym);
|
||||
}
|
||||
lval_ctx->register_modified_tuple_index(hash, tuple_ir_idx[0], index_ir_idx[0], field_ir_idx[0]);
|
||||
vars_modification_watcher.trigger_callbacks(tuple_ir_idx, v->loc);
|
||||
return field_ir_idx;
|
||||
// handle `tupleVar.0 = rhs`, "0 SETINDEX" will be called when this was is modified
|
||||
if (lval_ctx && !lval_ctx->is_rval_inside_lval() && calc_sink_leftmost_obj(v)) {
|
||||
std::vector<var_idx_t> lval_ir_idx = code.create_tmp_var(v->inferred_type, v->loc, "(lval-tuple-field)");
|
||||
lval_ctx->capture_tuple_index_modification(v->get_obj(), index_at, lval_ir_idx);
|
||||
return lval_ir_idx;
|
||||
}
|
||||
// `tupleVar.0` as rvalue: the same as "tupleAt(tupleVar, 0)" written in terms of IR vars
|
||||
std::vector<var_idx_t> tuple_ir_idx = pre_compile_expr(v->get_obj(), code);
|
||||
std::vector<var_idx_t> index_ir_idx = code.create_tmp_var(TypeDataInt::create(), v->get_identifier()->loc, "(tuple-idx)");
|
||||
code.emplace_back(v->loc, Op::_IntConst, index_ir_idx, td::make_refint(index_at));
|
||||
std::vector<var_idx_t> field_ir_idx = code.create_tmp_var(v->inferred_type, v->loc, "(tuple-field)");
|
||||
tolk_assert(tuple_ir_idx.size() == 1 && field_ir_idx.size() == 1); // tuples contain only 1-slot values
|
||||
const FunctionData* builtin_sym = lookup_global_symbol("tupleAt")->as<FunctionData>();
|
||||
code.emplace_back(v->loc, Op::_Call, field_ir_idx, std::vector{tuple_ir_idx[0], index_ir_idx[0]}, builtin_sym);
|
||||
if (lval_ctx && calc_sink_leftmost_obj(v)) { // `tupleVar.0.1 = rhs`, then `tupleVar.0` is rval inside lval
|
||||
lval_ctx->capture_tuple_index_modification(v->get_obj(), index_at, field_ir_idx);
|
||||
}
|
||||
return field_ir_idx;
|
||||
}
|
||||
tolk_assert(false);
|
||||
}
|
||||
|
|
@ -627,8 +638,8 @@ static std::vector<var_idx_t> process_function_call(V<ast_function_call> v, Code
|
|||
std::vector<var_idx_t> rvect = code.create_tmp_var(real_ret_type, v->loc, "(fun-call)");
|
||||
left.insert(left.end(), rvect.begin(), rvect.end());
|
||||
vars_modification_watcher.trigger_callbacks(left, v->loc);
|
||||
code.emplace_back(v->loc, Op::_Let, std::move(left), rvect_apply);
|
||||
local_lval.gen_ops_if_nonempty(code, v->loc);
|
||||
code.emplace_back(v->loc, Op::_Let, left, rvect_apply);
|
||||
local_lval.after_let(std::move(left), code, v->loc);
|
||||
rvect_apply = rvect;
|
||||
}
|
||||
|
||||
|
|
@ -710,7 +721,7 @@ std::vector<var_idx_t> pre_compile_expr(AnyExprV v, CodeBlob& code, LValContext*
|
|||
case ast_reference:
|
||||
return pre_compile_symbol(v->loc, v->as<ast_reference>()->sym, code, lval_ctx);
|
||||
case ast_assign:
|
||||
return process_assign(v->as<ast_assign>(), code);
|
||||
return process_assignment(v->as<ast_assign>(), code);
|
||||
case ast_set_assign:
|
||||
return process_set_assign(v->as<ast_set_assign>(), code);
|
||||
case ast_binary_operator:
|
||||
|
|
|
|||
|
|
@ -25,6 +25,8 @@
|
|||
*
|
||||
* Currently, it just replaces `-1` (ast_unary_operator ast_int_const) with a number -1
|
||||
* and `!true` with false.
|
||||
* Also, all parenthesized `((expr))` are replaced with `expr`, it's a constant transformation.
|
||||
* (not to handle parenthesized in optimization passes, like `((x)) == true`)
|
||||
* More rich constant folding should be done some day, but even without this, IR optimizations
|
||||
* (operating low-level stack variables) pretty manage to do all related optimizations.
|
||||
* Constant folding in the future, done at AST level, just would slightly reduce amount of work for optimizer.
|
||||
|
|
@ -47,6 +49,14 @@ class ConstantFoldingReplacer final : public ASTReplacerInFunctionBody {
|
|||
return v_bool;
|
||||
}
|
||||
|
||||
AnyExprV replace(V<ast_parenthesized_expression> v) override {
|
||||
AnyExprV inner = parent::replace(v->get_expr());
|
||||
if (v->is_lvalue) {
|
||||
inner->mutate()->assign_lvalue_true();
|
||||
}
|
||||
return inner;
|
||||
}
|
||||
|
||||
AnyExprV replace(V<ast_unary_operator> v) override {
|
||||
parent::replace(v);
|
||||
|
||||
|
|
|
|||
|
|
@ -133,8 +133,8 @@ static void fire_error_cannot_deduce_untyped_tuple_access(SrcLocation loc, int i
|
|||
|
||||
// fire an error on `untypedTupleVar.0` when inferred as (int,int), or `[int, (int,int)]`, or other non-1 width in a tuple
|
||||
GNU_ATTRIBUTE_NORETURN GNU_ATTRIBUTE_COLD
|
||||
static void fire_error_cannot_put_non1_stack_width_arg_to_tuple(SrcLocation loc, TypePtr inferred_type) {
|
||||
throw ParseError(loc, "can not put " + to_string(inferred_type) + " into a tuple, because it occupies " + std::to_string(inferred_type->calc_width_on_stack()) + " stack slots in TVM, not 1");
|
||||
static void fire_error_tuple_cannot_have_non1_stack_width_elem(SrcLocation loc, TypePtr inferred_type) {
|
||||
throw ParseError(loc, "a tuple can not have " + to_string(inferred_type) + " inside, because it occupies " + std::to_string(inferred_type->calc_width_on_stack()) + " stack slots in TVM, not 1");
|
||||
}
|
||||
|
||||
// check correctness of called arguments counts and their type matching
|
||||
|
|
@ -351,6 +351,8 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
return infer_bool_const(v->as<ast_bool_const>());
|
||||
case ast_local_vars_declaration:
|
||||
return infer_local_vars_declaration(v->as<ast_local_vars_declaration>());
|
||||
case ast_local_var_lhs:
|
||||
return infer_local_var_lhs(v->as<ast_local_var_lhs>());
|
||||
case ast_assign:
|
||||
return infer_assignment(v->as<ast_assign>());
|
||||
case ast_set_assign:
|
||||
|
|
@ -410,133 +412,71 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
assign_inferred_type(v, TypeDataBool::create());
|
||||
}
|
||||
|
||||
static void infer_local_vars_declaration(V<ast_local_vars_declaration>) {
|
||||
// it can not appear as a standalone expression
|
||||
// `var ... = rhs` is handled by ast_assign
|
||||
tolk_assert(false);
|
||||
void infer_local_vars_declaration(V<ast_local_vars_declaration> v) {
|
||||
infer_any_expr(v->get_expr());
|
||||
assign_inferred_type(v, v->get_expr());
|
||||
}
|
||||
|
||||
static void infer_local_var_lhs(V<ast_local_var_lhs> v) {
|
||||
// `var v = rhs`, inferring is called for `v`
|
||||
// at the moment of inferring left side of assignment, we don't know type of rhs (since lhs is executed first)
|
||||
// so, mark `v` as unknown
|
||||
// later, v's inferred_type will be reassigned; see process_assignment_lhs_after_infer_rhs()
|
||||
if (v->marked_as_redef) {
|
||||
assign_inferred_type(v, v->var_ref->declared_type);
|
||||
} else {
|
||||
assign_inferred_type(v, v->declared_type ? v->declared_type : TypeDataUnknown::create());
|
||||
}
|
||||
}
|
||||
|
||||
void infer_assignment(V<ast_assign> v) {
|
||||
// v is assignment: `x = 5` / `var x = 5` / `var x: slice = 5` / `(cs,_) = f()` / `val (a,[b],_) = (a,t,0)`
|
||||
// it's a tricky node to handle, because to infer rhs, at first we need to create hint from lhs
|
||||
// and then to apply/check inferred rhs onto lhs
|
||||
// about a hint: `var i: int = t.tupleAt(0)` is ok, but `var i = t.tupleAt(0)` not, since `tupleAt<T>(t,i): T`
|
||||
// execution flow is: lhs first, rhs second (at IR generation, also lhs is evaluated first, unlike FunC)
|
||||
// after inferring lhs, use it for hint when inferring rhs
|
||||
// example: `var i: int = t.tupleAt(0)` is ok (hint=int, T=int), but `var i = t.tupleAt(0)` not, since `tupleAt<T>(t,i): T`
|
||||
AnyExprV lhs = v->get_lhs();
|
||||
AnyExprV rhs = v->get_rhs();
|
||||
infer_any_expr(rhs, calc_hint_from_assignment_lhs(lhs));
|
||||
infer_any_expr(lhs);
|
||||
infer_any_expr(rhs, lhs->inferred_type);
|
||||
process_assignment_lhs_after_infer_rhs(lhs, rhs->inferred_type, rhs);
|
||||
assign_inferred_type(v, lhs);
|
||||
}
|
||||
|
||||
// having assignment like `var (i: int, s) = rhs` (its lhs is local vars declaration),
|
||||
// create a contextual infer hint for rhs, `(int, unknown)` in this case
|
||||
// this hint helps to deduce generics and to resolve unknown types while inferring rhs
|
||||
static TypePtr calc_hint_from_assignment_lhs(AnyExprV lhs) {
|
||||
// `var ... = rhs` - dig into left part
|
||||
if (auto lhs_decl = lhs->try_as<ast_local_vars_declaration>()) {
|
||||
return calc_hint_from_assignment_lhs(lhs_decl->get_expr());
|
||||
}
|
||||
|
||||
// inside `var v: int = rhs` / `var _ = rhs` / `var v redef = rhs` (lhs is "v" / "_" / "v")
|
||||
if (auto lhs_var = lhs->try_as<ast_local_var_lhs>()) {
|
||||
if (lhs_var->marked_as_redef) {
|
||||
return lhs_var->var_ref->declared_type;
|
||||
}
|
||||
if (lhs_var->declared_type) {
|
||||
return lhs_var->declared_type;
|
||||
}
|
||||
return TypeDataUnknown::create();
|
||||
}
|
||||
|
||||
// `v = rhs` / `(c1, c2) = rhs` (lhs is "v" / "_" / "c1" / "c2" after recursion)
|
||||
if (auto lhs_ref = lhs->try_as<ast_reference>()) {
|
||||
if (const auto* var_ref = lhs_ref->sym->try_as<LocalVarData>()) {
|
||||
return var_ref->declared_type;
|
||||
}
|
||||
if (const auto* glob_ref = lhs_ref->sym->try_as<GlobalVarData>()) {
|
||||
return glob_ref->declared_type;
|
||||
}
|
||||
return TypeDataUnknown::create();
|
||||
}
|
||||
|
||||
// `(v1, v2) = rhs` / `var (v1, v2) = rhs`
|
||||
if (auto lhs_tensor = lhs->try_as<ast_tensor>()) {
|
||||
std::vector<TypePtr> sub_hints;
|
||||
sub_hints.reserve(lhs_tensor->size());
|
||||
for (AnyExprV item : lhs_tensor->get_items()) {
|
||||
sub_hints.push_back(calc_hint_from_assignment_lhs(item));
|
||||
}
|
||||
return TypeDataTensor::create(std::move(sub_hints));
|
||||
}
|
||||
|
||||
// `[v1, v2] = rhs` / `var [v1, v2] = rhs`
|
||||
if (auto lhs_tuple = lhs->try_as<ast_typed_tuple>()) {
|
||||
std::vector<TypePtr> sub_hints;
|
||||
sub_hints.reserve(lhs_tuple->size());
|
||||
for (AnyExprV item : lhs_tuple->get_items()) {
|
||||
sub_hints.push_back(calc_hint_from_assignment_lhs(item));
|
||||
}
|
||||
return TypeDataTypedTuple::create(std::move(sub_hints));
|
||||
}
|
||||
|
||||
// `a.0 = rhs` / `b.1.0 = rhs` (remember, its target is not assigned yet)
|
||||
if (auto lhs_dot = lhs->try_as<ast_dot_access>()) {
|
||||
TypePtr obj_hint = calc_hint_from_assignment_lhs(lhs_dot->get_obj());
|
||||
std::string_view field_name = lhs_dot->get_field_name();
|
||||
if (field_name[0] >= '0' && field_name[0] <= '9') {
|
||||
int index_at = std::stoi(std::string(field_name));
|
||||
if (const auto* t_tensor = obj_hint->try_as<TypeDataTensor>(); t_tensor && index_at < t_tensor->size()) {
|
||||
return t_tensor->items[index_at];
|
||||
}
|
||||
if (const auto* t_tuple = obj_hint->try_as<TypeDataTypedTuple>(); t_tuple && index_at < t_tuple->size()) {
|
||||
return t_tuple->items[index_at];
|
||||
}
|
||||
}
|
||||
return TypeDataUnknown::create();
|
||||
}
|
||||
|
||||
return TypeDataUnknown::create();
|
||||
assign_inferred_type(v, rhs); // note, that the resulting type is rhs, not lhs
|
||||
}
|
||||
|
||||
// handle (and dig recursively) into `var lhs = rhs`
|
||||
// at this point, both lhs and rhs are already inferred, but lhs newly-declared vars are unknown (unless have declared_type)
|
||||
// examples: `var z = 5`, `var (x, [y]) = (2, [3])`, `var (x, [y]) = xy`
|
||||
// the purpose is to update inferred_type of lhs vars (z, x, y)
|
||||
// while recursing, keep track of rhs if lhs and rhs have common shape (5 for z, 2 for x, [3] for [y], 3 for y)
|
||||
// (so that on type mismatch, point to corresponding rhs, example: `var (x, y:slice) = (1, 2)` point to 2
|
||||
void process_assignment_lhs_after_infer_rhs(AnyExprV lhs, TypePtr rhs_type, AnyExprV corresponding_maybe_rhs) {
|
||||
static void process_assignment_lhs_after_infer_rhs(AnyExprV lhs, TypePtr rhs_type, AnyExprV corresponding_maybe_rhs) {
|
||||
tolk_assert(lhs->inferred_type != nullptr);
|
||||
AnyExprV err_loc = corresponding_maybe_rhs ? corresponding_maybe_rhs : lhs;
|
||||
|
||||
// `var ... = rhs` - dig into left part
|
||||
if (auto lhs_decl = lhs->try_as<ast_local_vars_declaration>()) {
|
||||
process_assignment_lhs_after_infer_rhs(lhs_decl->get_expr(), rhs_type, corresponding_maybe_rhs);
|
||||
assign_inferred_type(lhs, lhs_decl->get_expr()->inferred_type);
|
||||
return;
|
||||
}
|
||||
|
||||
// inside `var v: int = rhs` / `var _ = rhs` / `var v redef = rhs` (lhs is "v" / "_" / "v")
|
||||
if (auto lhs_var = lhs->try_as<ast_local_var_lhs>()) {
|
||||
TypePtr declared_type = lhs_var->declared_type; // `var v: int = rhs` (otherwise, nullptr)
|
||||
if (lhs_var->marked_as_redef) {
|
||||
tolk_assert(lhs_var->var_ref && lhs_var->var_ref->declared_type);
|
||||
declared_type = lhs_var->var_ref->declared_type;
|
||||
}
|
||||
if (declared_type) {
|
||||
if (lhs_var->inferred_type != TypeDataUnknown::create()) { // it's `var v: int` or redef
|
||||
TypePtr declared_type = lhs_var->inferred_type;
|
||||
if (!declared_type->can_rhs_be_assigned(rhs_type)) {
|
||||
err_loc->error("can not assign " + to_string(rhs_type) + " to variable of type " + to_string(declared_type));
|
||||
}
|
||||
assign_inferred_type(lhs, declared_type);
|
||||
} else {
|
||||
if (rhs_type == TypeDataNullLiteral::create()) {
|
||||
fire_error_assign_always_null_to_variable(err_loc->loc, lhs_var->var_ref->try_as<LocalVarData>(), corresponding_maybe_rhs && corresponding_maybe_rhs->type == ast_null_keyword);
|
||||
}
|
||||
assign_inferred_type(lhs, rhs_type);
|
||||
assign_inferred_type(lhs_var->var_ref, lhs_var->inferred_type);
|
||||
assign_inferred_type(lhs_var, rhs_type);
|
||||
assign_inferred_type(lhs_var->var_ref, rhs_type);
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
// `v = rhs` / `(c1, c2) = rhs` (lhs is "v" / "_" / "c1" / "c2" after recursion)
|
||||
if (lhs->try_as<ast_reference>()) {
|
||||
infer_any_expr(lhs);
|
||||
if (!lhs->inferred_type->can_rhs_be_assigned(rhs_type)) {
|
||||
err_loc->error("can not assign " + to_string(rhs_type) + " to variable of type " + to_string(lhs));
|
||||
}
|
||||
|
|
@ -554,13 +494,9 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
err_loc->error("can not assign " + to_string(rhs_type) + ", sizes mismatch");
|
||||
}
|
||||
V<ast_tensor> rhs_tensor_maybe = corresponding_maybe_rhs ? corresponding_maybe_rhs->try_as<ast_tensor>() : nullptr;
|
||||
std::vector<TypePtr> types_list;
|
||||
types_list.reserve(lhs_tensor->size());
|
||||
for (int i = 0; i < lhs_tensor->size(); ++i) {
|
||||
process_assignment_lhs_after_infer_rhs(lhs_tensor->get_item(i), rhs_type_tensor->items[i], rhs_tensor_maybe ? rhs_tensor_maybe->get_item(i) : nullptr);
|
||||
types_list.push_back(lhs_tensor->get_item(i)->inferred_type);
|
||||
}
|
||||
assign_inferred_type(lhs, TypeDataTensor::create(std::move(types_list)));
|
||||
return;
|
||||
}
|
||||
|
||||
|
|
@ -575,25 +511,23 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
err_loc->error("can not assign " + to_string(rhs_type) + ", sizes mismatch");
|
||||
}
|
||||
V<ast_typed_tuple> rhs_tuple_maybe = corresponding_maybe_rhs ? corresponding_maybe_rhs->try_as<ast_typed_tuple>() : nullptr;
|
||||
std::vector<TypePtr> types_list;
|
||||
types_list.reserve(lhs_tuple->size());
|
||||
for (int i = 0; i < lhs_tuple->size(); ++i) {
|
||||
process_assignment_lhs_after_infer_rhs(lhs_tuple->get_item(i), rhs_type_tuple->items[i], rhs_tuple_maybe ? rhs_tuple_maybe->get_item(i) : nullptr);
|
||||
types_list.push_back(lhs_tuple->get_item(i)->inferred_type);
|
||||
}
|
||||
assign_inferred_type(lhs, TypeDataTypedTuple::create(std::move(types_list)));
|
||||
return;
|
||||
}
|
||||
|
||||
// `_ = rhs`
|
||||
if (lhs->type == ast_underscore) {
|
||||
assign_inferred_type(lhs, TypeDataUnknown::create());
|
||||
return;
|
||||
// check `untypedTuple.0 = rhs_tensor` and other non-1 width elements
|
||||
if (auto lhs_dot = lhs->try_as<ast_dot_access>()) {
|
||||
if (lhs_dot->is_target_indexed_access() && lhs_dot->get_obj()->inferred_type == TypeDataTuple::create()) {
|
||||
if (rhs_type->calc_width_on_stack() != 1) {
|
||||
fire_error_tuple_cannot_have_non1_stack_width_elem(err_loc->loc, rhs_type);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// here is something unhandled like `a.0 = rhs`, run regular inferring on rhs
|
||||
// here is something unhandled like `a.0 = rhs`, just check type matching
|
||||
// for something strange like `f() = rhs` type inferring will pass, but will fail later
|
||||
infer_any_expr(lhs, rhs_type);
|
||||
if (!lhs->inferred_type->can_rhs_be_assigned(rhs_type)) {
|
||||
err_loc->error("can not assign " + to_string(rhs_type) + " to " + to_string(lhs));
|
||||
}
|
||||
|
|
@ -895,14 +829,20 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
return;
|
||||
}
|
||||
if (obj_type->try_as<TypeDataTuple>()) {
|
||||
if (hint == nullptr) {
|
||||
fire_error_cannot_deduce_untyped_tuple_access(v->loc, index_at);
|
||||
}
|
||||
if (hint->calc_width_on_stack() != 1) {
|
||||
fire_error_cannot_put_non1_stack_width_arg_to_tuple(v->loc, hint);
|
||||
TypePtr item_type = nullptr;
|
||||
if (v->is_lvalue && !hint) { // left side of assignment
|
||||
item_type = TypeDataUnknown::create();
|
||||
} else {
|
||||
if (hint == nullptr) {
|
||||
fire_error_cannot_deduce_untyped_tuple_access(v->loc, index_at);
|
||||
}
|
||||
if (hint->calc_width_on_stack() != 1) {
|
||||
fire_error_tuple_cannot_have_non1_stack_width_elem(v->loc, hint);
|
||||
}
|
||||
item_type = hint;
|
||||
}
|
||||
v->mutate()->assign_target(index_at);
|
||||
assign_inferred_type(v, hint);
|
||||
assign_inferred_type(v, item_type);
|
||||
return;
|
||||
}
|
||||
v_ident->error("type " + to_string(obj_type) + " is not indexable");
|
||||
|
|
@ -1081,7 +1021,7 @@ class InferCheckTypesAndCallsAndFieldsVisitor final {
|
|||
AnyExprV item = v->get_item(i);
|
||||
infer_any_expr(item, tuple_hint && i < tuple_hint->size() ? tuple_hint->items[i] : nullptr);
|
||||
if (item->inferred_type->calc_width_on_stack() != 1) {
|
||||
fire_error_cannot_put_non1_stack_width_arg_to_tuple(v->get_item(i)->loc, item->inferred_type);
|
||||
fire_error_tuple_cannot_have_non1_stack_width_elem(v->get_item(i)->loc, item->inferred_type);
|
||||
}
|
||||
types_list.emplace_back(item->inferred_type);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -25,7 +25,6 @@
|
|||
*
|
||||
* Example: `boolVar == true` -> `boolVar`.
|
||||
* Example: `!!boolVar` -> `boolVar`.
|
||||
* Also in unwraps parenthesis inside if condition and similar: `assert(((x)), 404)` -> `assert(x, 404)`
|
||||
*
|
||||
* todo some day, replace && || with & | when it's safe (currently, && always produces IFs in Fift)
|
||||
* It's tricky to implement whether replacing is safe.
|
||||
|
|
@ -35,13 +34,6 @@
|
|||
|
||||
namespace tolk {
|
||||
|
||||
static AnyExprV unwrap_parenthesis(AnyExprV v) {
|
||||
while (v->type == ast_parenthesized_expression) {
|
||||
v = v->as<ast_parenthesized_expression>()->get_expr();
|
||||
}
|
||||
return v;
|
||||
}
|
||||
|
||||
struct OptimizerBooleanExpressionsReplacer final : ASTReplacerInFunctionBody {
|
||||
static V<ast_int_const> create_int_const(SrcLocation loc, td::RefInt256&& intval) {
|
||||
auto v_int = createV<ast_int_const>(loc, std::move(intval), {});
|
||||
|
|
@ -118,7 +110,7 @@ protected:
|
|||
AnyV replace(V<ast_if_statement> v) override {
|
||||
parent::replace(v);
|
||||
if (v->get_cond()->type == ast_parenthesized_expression) {
|
||||
v = createV<ast_if_statement>(v->loc, v->is_ifnot, unwrap_parenthesis(v->get_cond()), v->get_if_body(), v->get_else_body());
|
||||
v = createV<ast_if_statement>(v->loc, v->is_ifnot, v->get_cond(), v->get_if_body(), v->get_else_body());
|
||||
}
|
||||
|
||||
// `if (!x)` -> ifnot(x)
|
||||
|
|
@ -136,7 +128,7 @@ protected:
|
|||
parent::replace(v);
|
||||
|
||||
if (v->get_cond()->type == ast_parenthesized_expression) {
|
||||
v = createV<ast_while_statement>(v->loc, unwrap_parenthesis(v->get_cond()), v->get_body());
|
||||
v = createV<ast_while_statement>(v->loc, v->get_cond(), v->get_body());
|
||||
}
|
||||
return v;
|
||||
}
|
||||
|
|
@ -145,7 +137,7 @@ protected:
|
|||
parent::replace(v);
|
||||
|
||||
if (v->get_cond()->type == ast_parenthesized_expression) {
|
||||
v = createV<ast_do_while_statement>(v->loc, v->get_body(), unwrap_parenthesis(v->get_cond()));
|
||||
v = createV<ast_do_while_statement>(v->loc, v->get_body(), v->get_cond());
|
||||
}
|
||||
return v;
|
||||
}
|
||||
|
|
@ -154,7 +146,7 @@ protected:
|
|||
parent::replace(v);
|
||||
|
||||
if (v->get_cond()->type == ast_parenthesized_expression) {
|
||||
v = createV<ast_assert_statement>(v->loc, unwrap_parenthesis(v->get_cond()), v->get_thrown_code());
|
||||
v = createV<ast_assert_statement>(v->loc, v->get_cond(), v->get_thrown_code());
|
||||
}
|
||||
return v;
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue