Initial Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

LLM Generation

Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

Output

Here is the code refactored into a function called `foo`: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp():
        output = []
        for i in range(matrix.shape[0]):
            output.append(set([i]))
        return output

    used_for_row = [i for i in listcomp()]

    while col + extra < matrix.shape[1]:
        if np.all(matrix[:, col] == 0):
            extra += 1
        else:
            other = np.argwhere(matrix[:, col + extra] != 0).flatten()[-1]
            if other < col:
                extra += 1
            elif other > col:
                matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])

        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if abs(pivot) == 1:
            pass
        elif abs(pivot) == 2:
            pivot //= 2

        matrix[col + extra] //= pivot
        matrix[col + extra] %= PH

        others = np.argwhere(matrix[:, col + extra] != 0).flatten()

        for i in others:
            if i == col:
                continue
            used_for_row[i] |= used_for_row[col]

            if col + 1 < graphlen:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
            elif matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1

    used_for_row = sorted(used_for_row)
    
    return used_for_row
The function `foo` takes two parameters `matrix` and `graphlen`, performs the disassembled code's operations, and returns the sorted `used_for_row` list.

Extract Code

I extracted the following code from that output: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp():
        output = []
        for i in range(matrix.shape[0]):
            output.append(set([i]))
        return output

    used_for_row = [i for i in listcomp()]

    while col + extra < matrix.shape[1]:
        if np.all(matrix[:, col] == 0):
            extra += 1
        else:
            other = np.argwhere(matrix[:, col + extra] != 0).flatten()[-1]
            if other < col:
                extra += 1
            elif other > col:
                matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])

        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if abs(pivot) == 1:
            pass
        elif abs(pivot) == 2:
            pivot //= 2

        matrix[col + extra] //= pivot
        matrix[col + extra] %= PH

        others = np.argwhere(matrix[:, col + extra] != 0).flatten()

        for i in others:
            if i == col:
                continue
            used_for_row[i] |= used_for_row[col]

            if col + 1 < graphlen:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
            elif matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1

    used_for_row = sorted(used_for_row)
    
    return used_for_row

Run Code Interpreter

Running the following program: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp():
        output = []
        for i in range(matrix.shape[0]):
            output.append(set([i]))
        return output

    used_for_row = [i for i in listcomp()]

    while col + extra < matrix.shape[1]:
        if np.all(matrix[:, col] == 0):
            extra += 1
        else:
            other = np.argwhere(matrix[:, col + extra] != 0).flatten()[-1]
            if other < col:
                extra += 1
            elif other > col:
                matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])

        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if abs(pivot) == 1:
            pass
        elif abs(pivot) == 2:
            pivot //= 2

        matrix[col + extra] //= pivot
        matrix[col + extra] %= PH

        others = np.argwhere(matrix[:, col + extra] != 0).flatten()

        for i in others:
            if i == col:
                continue
            used_for_row[i] |= used_for_row[col]

            if col + 1 < graphlen:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
            elif matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1

    used_for_row = sorted(used_for_row)
    
    return used_for_row



arr = np.array([[1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, -20], [1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -14], [0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -9], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -40], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

answer = foo(arr, 37)
expected = [[0, 38], [0, 38], [0, 6, 28, 35, 38], [0, 6, 18, 21, 28, 35, 38], [0, 6, 28, 35, 38], [0, 6, 21, 28, 35, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 9, 10, 23, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 25, 27, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 24, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 33, 38], [0, 22, 29, 38], [0, 22, 29, 38], [0, 6, 28, 35, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [14, 18, 21, 28, 35]]
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: /usr/src/app/main.py:37: RuntimeWarning: divide by zero encountered in floor_divide matrix[col + extra] //= pivot Traceback (most recent call last): File "/usr/src/app/main.py", line 62, in <module> answer = foo(arr, 37) ^^^^^^^^^^^^ File "/usr/src/app/main.py", line 30, in foo pivot = matrix[col + extra, col + extra] ~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^ IndexError: index 40 is out of bounds for axis 0 with size 39

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

LLM Generation

Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

Output

Here is the Python code disassembled into a function called foo: 

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import numpy as np

def foo(matrix, graphlen, PH):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def list_comp_1():
        temp = []
        for i in range(matrix.shape[0]):
            temp.append(set(i))
        return temp

    used_for_row = [i for i in list_comp_1()]
    
    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            pivot = np.all(matrix[:, col] == 0)
        else:
            others = np.argwhere(matrix[:, col] != 0).flatten()
            for i in others:
                if i == col:
                    used_for_row[i] |= used_for_row[col]
                else:
                    if col < graphlen:
                        matrix[i] -= matrix[col] * matrix[i, col] / matrix[col, col]
                    else:
                        if np.abs(matrix[i, col]) == 2 or np.abs(matrix[i, col] - PH) == 1:
                            raise AssertionError
                        pivot = np.abs(matrix[i, col]) == 2
                        matrix[i] -= matrix[col] * matrix[i, col] % PH
        pivots.append(col + extra)
        
        col += extra
        pivot = matrix[col, col + extra]
        if pivot + PH < graphlen:
            if np.abs(pivot) == 1:
                raise AssertionError
            elif np.abs(pivot - PH) == 1:
                raise AssertionError
        pivot //= 2
        matrix[col, col + extra] *= pivot
        matrix[col, col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        for i in others:
            if i == col:
                continue
            matrix[i] -= matrix[col] * matrix[i, col + extra] // PH

    def list_comp_2():
        temp = []
        for x in used_for_row:
            temp.append(sorted(x))
        return temp
    
    return list_comp_2()

Extract Code

I extracted the following code from that output: 

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import numpy as np

def foo(matrix, graphlen, PH):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def list_comp_1():
        temp = []
        for i in range(matrix.shape[0]):
            temp.append(set(i))
        return temp

    used_for_row = [i for i in list_comp_1()]
    
    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            pivot = np.all(matrix[:, col] == 0)
        else:
            others = np.argwhere(matrix[:, col] != 0).flatten()
            for i in others:
                if i == col:
                    used_for_row[i] |= used_for_row[col]
                else:
                    if col < graphlen:
                        matrix[i] -= matrix[col] * matrix[i, col] / matrix[col, col]
                    else:
                        if np.abs(matrix[i, col]) == 2 or np.abs(matrix[i, col] - PH) == 1:
                            raise AssertionError
                        pivot = np.abs(matrix[i, col]) == 2
                        matrix[i] -= matrix[col] * matrix[i, col] % PH
        pivots.append(col + extra)
        
        col += extra
        pivot = matrix[col, col + extra]
        if pivot + PH < graphlen:
            if np.abs(pivot) == 1:
                raise AssertionError
            elif np.abs(pivot - PH) == 1:
                raise AssertionError
        pivot //= 2
        matrix[col, col + extra] *= pivot
        matrix[col, col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        for i in others:
            if i == col:
                continue
            matrix[i] -= matrix[col] * matrix[i, col + extra] // PH

    def list_comp_2():
        temp = []
        for x in used_for_row:
            temp.append(sorted(x))
        return temp
    
    return list_comp_2()

Run Code Interpreter

Running the following program: 

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import numpy as np

def foo(matrix, graphlen, PH):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def list_comp_1():
        temp = []
        for i in range(matrix.shape[0]):
            temp.append(set(i))
        return temp

    used_for_row = [i for i in list_comp_1()]
    
    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            pivot = np.all(matrix[:, col] == 0)
        else:
            others = np.argwhere(matrix[:, col] != 0).flatten()
            for i in others:
                if i == col:
                    used_for_row[i] |= used_for_row[col]
                else:
                    if col < graphlen:
                        matrix[i] -= matrix[col] * matrix[i, col] / matrix[col, col]
                    else:
                        if np.abs(matrix[i, col]) == 2 or np.abs(matrix[i, col] - PH) == 1:
                            raise AssertionError
                        pivot = np.abs(matrix[i, col]) == 2
                        matrix[i] -= matrix[col] * matrix[i, col] % PH
        pivots.append(col + extra)
        
        col += extra
        pivot = matrix[col, col + extra]
        if pivot + PH < graphlen:
            if np.abs(pivot) == 1:
                raise AssertionError
            elif np.abs(pivot - PH) == 1:
                raise AssertionError
        pivot //= 2
        matrix[col, col + extra] *= pivot
        matrix[col, col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        for i in others:
            if i == col:
                continue
            matrix[i] -= matrix[col] * matrix[i, col + extra] // PH

    def list_comp_2():
        temp = []
        for x in used_for_row:
            temp.append(sorted(x))
        return temp
    
    return list_comp_2()



arr = np.array([[1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, -20], [1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -14], [0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -9], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -40], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

answer = foo(arr, 37)
expected = [[0, 38], [0, 38], [0, 6, 28, 35, 38], [0, 6, 18, 21, 28, 35, 38], [0, 6, 28, 35, 38], [0, 6, 21, 28, 35, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 9, 10, 23, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 25, 27, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 24, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 33, 38], [0, 22, 29, 38], [0, 22, 29, 38], [0, 6, 28, 35, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [14, 18, 21, 28, 35]]
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Traceback (most recent call last): File "/usr/src/app/main.py", line 65, in <module> answer = foo(arr, 37) ^^^^^^^^^^^^ TypeError: foo() missing 1 required positional argument: 'PH'

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

LLM Generation

Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

Output

Here is the function foo: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp(matrix):
        return [i for i in range(matrix.shape[0])]

    used_for_row = [i for i in listcomp(matrix)]

    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            if matrix[col + extra][col] == 0:
                np.all(matrix[None, col] == 0)
                extra += 1
                continue
        else:
            other = np.argwhere(matrix[None, col + extra] != 0).flatten()[-1]

            if other < col:
                extra += 1
                continue

            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]

            used_for_row[other, :], used_for_row[col, :] = used_for_row[col, :], used_for_row[other, :]

            pivots.append(col + extra)

            pivot = matrix[col + extra, col + extra]

            if pivot < graphlen:
                assert np.abs(pivot) == 1 or np.abs(pivot - PH) == 1

            if pivot < 2:
                assert np.abs(pivot) == 2 or np.abs(pivot - PH) == 2

            pivot //= 2

            matrix[col + extra] *= pivot
            matrix[col] %= PH

            others = np.argwhere(matrix[None, col + extra] != 0).flatten()

            for i in others:
                if i != col:
                    used_for_row[i] |= used_for_row[col]

            if col < graphlen:
                for i in listcomp(matrix):
                    if i == col:
                        continue
                    matrix[i] -= matrix[i, col] * matrix[col]
            else:
                for i in listcomp(matrix):
                    if matrix[i, col] != 0:
                        matrix[i] -= matrix[i, col] * matrix[col]
                        assert np.all(np.abs(matrix[None, col + extra]) == 0)

            col += 1

    return used_for_row
Now you can call foo(matrix, graphlen) with the appropriate parameters.

Extract Code

I extracted the following code from that output: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp(matrix):
        return [i for i in range(matrix.shape[0])]

    used_for_row = [i for i in listcomp(matrix)]

    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            if matrix[col + extra][col] == 0:
                np.all(matrix[None, col] == 0)
                extra += 1
                continue
        else:
            other = np.argwhere(matrix[None, col + extra] != 0).flatten()[-1]

            if other < col:
                extra += 1
                continue

            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]

            used_for_row[other, :], used_for_row[col, :] = used_for_row[col, :], used_for_row[other, :]

            pivots.append(col + extra)

            pivot = matrix[col + extra, col + extra]

            if pivot < graphlen:
                assert np.abs(pivot) == 1 or np.abs(pivot - PH) == 1

            if pivot < 2:
                assert np.abs(pivot) == 2 or np.abs(pivot - PH) == 2

            pivot //= 2

            matrix[col + extra] *= pivot
            matrix[col] %= PH

            others = np.argwhere(matrix[None, col + extra] != 0).flatten()

            for i in others:
                if i != col:
                    used_for_row[i] |= used_for_row[col]

            if col < graphlen:
                for i in listcomp(matrix):
                    if i == col:
                        continue
                    matrix[i] -= matrix[i, col] * matrix[col]
            else:
                for i in listcomp(matrix):
                    if matrix[i, col] != 0:
                        matrix[i] -= matrix[i, col] * matrix[col]
                        assert np.all(np.abs(matrix[None, col + extra]) == 0)

            col += 1

    return used_for_row

Run Code Interpreter

Running the following program: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []

    def listcomp(matrix):
        return [i for i in range(matrix.shape[0])]

    used_for_row = [i for i in listcomp(matrix)]

    while col + extra < matrix.shape[1]:
        if col < matrix.shape[0]:
            if matrix[col + extra][col] == 0:
                np.all(matrix[None, col] == 0)
                extra += 1
                continue
        else:
            other = np.argwhere(matrix[None, col + extra] != 0).flatten()[-1]

            if other < col:
                extra += 1
                continue

            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]

            used_for_row[other, :], used_for_row[col, :] = used_for_row[col, :], used_for_row[other, :]

            pivots.append(col + extra)

            pivot = matrix[col + extra, col + extra]

            if pivot < graphlen:
                assert np.abs(pivot) == 1 or np.abs(pivot - PH) == 1

            if pivot < 2:
                assert np.abs(pivot) == 2 or np.abs(pivot - PH) == 2

            pivot //= 2

            matrix[col + extra] *= pivot
            matrix[col] %= PH

            others = np.argwhere(matrix[None, col + extra] != 0).flatten()

            for i in others:
                if i != col:
                    used_for_row[i] |= used_for_row[col]

            if col < graphlen:
                for i in listcomp(matrix):
                    if i == col:
                        continue
                    matrix[i] -= matrix[i, col] * matrix[col]
            else:
                for i in listcomp(matrix):
                    if matrix[i, col] != 0:
                        matrix[i] -= matrix[i, col] * matrix[col]
                        assert np.all(np.abs(matrix[None, col + extra]) == 0)

            col += 1

    return used_for_row




arr = np.array([[1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, -20], [1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -14], [0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -9], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -40], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

answer = foo(arr, 37)
expected = [[0, 38], [0, 38], [0, 6, 28, 35, 38], [0, 6, 18, 21, 28, 35, 38], [0, 6, 28, 35, 38], [0, 6, 21, 28, 35, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 9, 10, 23, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 25, 27, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 24, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 33, 38], [0, 22, 29, 38], [0, 22, 29, 38], [0, 6, 28, 35, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [14, 18, 21, 28, 35]]
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Timeout: function took too long to complete

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

LLM Generation

Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

Output

Here is the Python code disassembled into a function called foo: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def listcomp(matrix):
        result = []
        for i in range(matrix.shape[0]):
            result.append(set([i]))
        return result
    
    used_for_row = [i for i in listcomp(matrix)]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
            continue
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])
        
        used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if pivot < graphlen:
            if np.abs(pivot) == 1 or np.abs(pivot) == np.abs(PH - 1):
                raise AssertionError
        elif np.abs(pivot) == 2:
            pivot //= 2
        
        matrix[col + extra] *= pivot
        matrix[col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
            
            if col + graphlen < matrix.shape[1]:
                matrix[i] -= matrix[col] * matrix[col, col + extra]
                continue
            
            if matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1
    
    return used_for_row
The function foo takes two parameters, matrix and graphlen, and performs the disassembled operations on the matrix array. It then returns the used_for_row list as the result.

Extract Code

I extracted the following code from that output: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def listcomp(matrix):
        result = []
        for i in range(matrix.shape[0]):
            result.append(set([i]))
        return result
    
    used_for_row = [i for i in listcomp(matrix)]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
            continue
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])
        
        used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if pivot < graphlen:
            if np.abs(pivot) == 1 or np.abs(pivot) == np.abs(PH - 1):
                raise AssertionError
        elif np.abs(pivot) == 2:
            pivot //= 2
        
        matrix[col + extra] *= pivot
        matrix[col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
            
            if col + graphlen < matrix.shape[1]:
                matrix[i] -= matrix[col] * matrix[col, col + extra]
                continue
            
            if matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1
    
    return used_for_row

Run Code Interpreter

Running the following program: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    def listcomp(matrix):
        result = []
        for i in range(matrix.shape[0]):
            result.append(set([i]))
        return result
    
    used_for_row = [i for i in listcomp(matrix)]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
            continue
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other], matrix[col] = list(matrix[col]), list(matrix[other])
        
        used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
        pivots.append(col + extra)
        
        pivot = matrix[col + extra, col + extra]
        
        if pivot < graphlen:
            if np.abs(pivot) == 1 or np.abs(pivot) == np.abs(PH - 1):
                raise AssertionError
        elif np.abs(pivot) == 2:
            pivot //= 2
        
        matrix[col + extra] *= pivot
        matrix[col + extra] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
            
            if col + graphlen < matrix.shape[1]:
                matrix[i] -= matrix[col] * matrix[col, col + extra]
                continue
            
            if matrix[i, col + extra] != 0:
                matrix[i] -= matrix[col] * matrix[i, col + extra]
        
        col += 1
    
    return used_for_row



arr = np.array([[1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, -20], [1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -14], [0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -9], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -40], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

answer = foo(arr, 37)
expected = [[0, 38], [0, 38], [0, 6, 28, 35, 38], [0, 6, 18, 21, 28, 35, 38], [0, 6, 28, 35, 38], [0, 6, 21, 28, 35, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 9, 10, 23, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 25, 27, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 24, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 33, 38], [0, 22, 29, 38], [0, 22, 29, 38], [0, 6, 28, 35, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [14, 18, 21, 28, 35]]
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Traceback (most recent call last): File "/usr/src/app/main.py", line 68, in <module> answer = foo(arr, 37) ^^^^^^^^^^^^ File "/usr/src/app/main.py", line 38, in foo raise AssertionError AssertionError

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

LLM Generation

Query

Disassemble the following python into a function called foo: 2 0 LOAD_CONST 1 (16) 2 STORE_FAST 2 (PH) 4 4 LOAD_CONST 2 (0) 6 STORE_FAST 3 (extra) 5 8 LOAD_CONST 2 (0) 10 STORE_FAST 4 (col) 6 12 BUILD_LIST 0 14 STORE_FAST 5 (pivots) 8 16 LOAD_CONST 3 (<code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>) 18 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 20 MAKE_FUNCTION 0 22 LOAD_GLOBAL 0 (range) 24 LOAD_FAST 0 (matrix) 26 LOAD_ATTR 1 (shape) 28 LOAD_CONST 2 (0) 30 BINARY_SUBSCR 32 CALL_FUNCTION 1 34 GET_ITER 36 CALL_FUNCTION 1 38 STORE_FAST 6 (used_for_row) 10 40 LOAD_FAST 0 (matrix) 42 LOAD_FAST 2 (PH) 44 BINARY_MODULO 46 STORE_FAST 0 (matrix) 11 >> 48 LOAD_FAST 4 (col) 50 LOAD_FAST 3 (extra) 52 BINARY_ADD 54 LOAD_FAST 0 (matrix) 56 LOAD_ATTR 1 (shape) 58 LOAD_CONST 5 (1) 60 BINARY_SUBSCR 62 LOAD_CONST 5 (1) 64 BINARY_SUBTRACT 66 COMPARE_OP 0 (<) 68 EXTENDED_ARG 2 70 POP_JUMP_IF_FALSE 628 72 LOAD_FAST 4 (col) 74 LOAD_FAST 0 (matrix) 76 LOAD_ATTR 1 (shape) 78 LOAD_CONST 2 (0) 80 BINARY_SUBSCR 82 COMPARE_OP 0 (<) 84 EXTENDED_ARG 2 86 POP_JUMP_IF_FALSE 628 13 88 LOAD_FAST 0 (matrix) 90 LOAD_FAST 4 (col) 92 LOAD_FAST 4 (col) 94 LOAD_FAST 3 (extra) 96 BINARY_ADD 98 BUILD_TUPLE 2 100 BINARY_SUBSCR 102 LOAD_CONST 2 (0) 104 COMPARE_OP 2 (==) 106 EXTENDED_ARG 1 108 POP_JUMP_IF_FALSE 262 14 110 LOAD_GLOBAL 2 (np) 112 LOAD_METHOD 3 (all) 114 LOAD_FAST 0 (matrix) 116 LOAD_CONST 0 (None) 118 LOAD_CONST 0 (None) 120 BUILD_SLICE 2 122 LOAD_FAST 4 (col) 124 BUILD_TUPLE 2 126 BINARY_SUBSCR 128 LOAD_CONST 2 (0) 130 COMPARE_OP 2 (==) 132 CALL_METHOD 1 134 POP_JUMP_IF_FALSE 146 15 136 LOAD_FAST 3 (extra) 138 LOAD_CONST 5 (1) 140 INPLACE_ADD 142 STORE_FAST 3 (extra) 16 144 JUMP_ABSOLUTE 48 17 >> 146 LOAD_GLOBAL 2 (np) 148 LOAD_METHOD 4 (argwhere) 150 LOAD_FAST 0 (matrix) 152 LOAD_CONST 0 (None) 154 LOAD_CONST 0 (None) 156 BUILD_SLICE 2 158 LOAD_FAST 4 (col) 160 LOAD_FAST 3 (extra) 162 BINARY_ADD 164 BUILD_TUPLE 2 166 BINARY_SUBSCR 168 LOAD_CONST 2 (0) 170 COMPARE_OP 3 (!=) 172 CALL_METHOD 1 174 LOAD_METHOD 5 (flatten) 176 CALL_METHOD 0 178 LOAD_CONST 6 (-1) 180 BINARY_SUBSCR 182 STORE_FAST 7 (other) 18 184 LOAD_FAST 7 (other) 186 LOAD_FAST 4 (col) 188 COMPARE_OP 0 (<) 190 POP_JUMP_IF_FALSE 202 19 192 LOAD_FAST 3 (extra) 194 LOAD_CONST 5 (1) 196 INPLACE_ADD 198 STORE_FAST 3 (extra) 20 200 JUMP_ABSOLUTE 48 22 >> 202 LOAD_GLOBAL 6 (list) 204 LOAD_FAST 0 (matrix) 206 LOAD_FAST 7 (other) 208 BINARY_SUBSCR 210 CALL_FUNCTION 1 212 LOAD_GLOBAL 6 (list) 214 LOAD_FAST 0 (matrix) 216 LOAD_FAST 4 (col) 218 BINARY_SUBSCR 220 CALL_FUNCTION 1 222 ROT_TWO 224 LOAD_FAST 0 (matrix) 226 LOAD_FAST 4 (col) 228 STORE_SUBSCR 230 LOAD_FAST 0 (matrix) 232 LOAD_FAST 7 (other) 234 STORE_SUBSCR 23 236 LOAD_FAST 6 (used_for_row) 238 LOAD_FAST 7 (other) 240 BINARY_SUBSCR 242 LOAD_FAST 6 (used_for_row) 244 LOAD_FAST 4 (col) 246 BINARY_SUBSCR 248 ROT_TWO 250 LOAD_FAST 6 (used_for_row) 252 LOAD_FAST 4 (col) 254 STORE_SUBSCR 256 LOAD_FAST 6 (used_for_row) 258 LOAD_FAST 7 (other) 260 STORE_SUBSCR 25 >> 262 LOAD_FAST 5 (pivots) 264 LOAD_METHOD 7 (append) 266 LOAD_FAST 4 (col) 268 LOAD_FAST 3 (extra) 270 BINARY_ADD 272 CALL_METHOD 1 274 POP_TOP 26 276 LOAD_FAST 0 (matrix) 278 LOAD_FAST 4 (col) 280 LOAD_FAST 4 (col) 282 LOAD_FAST 3 (extra) 284 BINARY_ADD 286 BUILD_TUPLE 2 288 BINARY_SUBSCR 290 STORE_FAST 8 (pivot) 27 292 LOAD_FAST 4 (col) 294 LOAD_FAST 3 (extra) 296 BINARY_ADD 298 LOAD_FAST 1 (graphlen) 300 COMPARE_OP 0 (<) 302 EXTENDED_ARG 1 304 POP_JUMP_IF_FALSE 348 28 306 LOAD_GLOBAL 2 (np) 308 LOAD_METHOD 8 (abs) 310 LOAD_FAST 8 (pivot) 312 CALL_METHOD 1 314 LOAD_CONST 5 (1) 316 COMPARE_OP 2 (==) 318 EXTENDED_ARG 1 320 POP_JUMP_IF_TRUE 396 322 LOAD_GLOBAL 2 (np) 324 LOAD_METHOD 8 (abs) 326 LOAD_FAST 8 (pivot) 328 CALL_METHOD 1 330 LOAD_FAST 2 (PH) 332 LOAD_CONST 5 (1) 334 BINARY_SUBTRACT 336 COMPARE_OP 2 (==) 338 EXTENDED_ARG 1 340 POP_JUMP_IF_TRUE 396 342 LOAD_ASSERTION_ERROR 344 RAISE_VARARGS 1 346 JUMP_FORWARD 48 (to 396) 30 >> 348 LOAD_GLOBAL 2 (np) 350 LOAD_METHOD 8 (abs) 352 LOAD_FAST 8 (pivot) 354 CALL_METHOD 1 356 LOAD_CONST 7 (2) 358 COMPARE_OP 2 (==) 360 EXTENDED_ARG 1 362 POP_JUMP_IF_TRUE 388 364 LOAD_GLOBAL 2 (np) 366 LOAD_METHOD 8 (abs) 368 LOAD_FAST 8 (pivot) 370 CALL_METHOD 1 372 LOAD_FAST 2 (PH) 374 LOAD_CONST 7 (2) 376 BINARY_SUBTRACT 378 COMPARE_OP 2 (==) 380 EXTENDED_ARG 1 382 POP_JUMP_IF_TRUE 388 384 LOAD_ASSERTION_ERROR 386 RAISE_VARARGS 1 31 >> 388 LOAD_FAST 8 (pivot) 390 LOAD_CONST 7 (2) 392 INPLACE_FLOOR_DIVIDE 394 STORE_FAST 8 (pivot) 32 >> 396 LOAD_FAST 0 (matrix) 398 LOAD_FAST 4 (col) 400 DUP_TOP_TWO 402 BINARY_SUBSCR 404 LOAD_FAST 8 (pivot) 406 INPLACE_MULTIPLY 408 ROT_THREE 410 STORE_SUBSCR 33 412 LOAD_FAST 0 (matrix) 414 LOAD_FAST 4 (col) 416 DUP_TOP_TWO 418 BINARY_SUBSCR 420 LOAD_FAST 2 (PH) 422 INPLACE_MODULO 424 ROT_THREE 426 STORE_SUBSCR 35 428 LOAD_GLOBAL 2 (np) 430 LOAD_METHOD 4 (argwhere) 432 LOAD_FAST 0 (matrix) 434 LOAD_CONST 0 (None) 436 LOAD_CONST 0 (None) 438 BUILD_SLICE 2 440 LOAD_FAST 4 (col) 442 LOAD_FAST 3 (extra) 444 BINARY_ADD 446 BUILD_TUPLE 2 448 BINARY_SUBSCR 450 CALL_METHOD 1 452 LOAD_METHOD 5 (flatten) 454 CALL_METHOD 0 456 STORE_FAST 9 (others) 37 458 LOAD_FAST 9 (others) 460 GET_ITER >> 462 FOR_ITER 154 (to 618) 464 STORE_FAST 10 (i) 38 466 LOAD_FAST 10 (i) 468 LOAD_FAST 4 (col) 470 COMPARE_OP 2 (==) 472 EXTENDED_ARG 1 474 POP_JUMP_IF_FALSE 480 476 EXTENDED_ARG 1 478 JUMP_ABSOLUTE 462 39 >> 480 LOAD_FAST 6 (used_for_row) 482 LOAD_FAST 10 (i) 484 DUP_TOP_TWO 486 BINARY_SUBSCR 488 LOAD_FAST 6 (used_for_row) 490 LOAD_FAST 4 (col) 492 BINARY_SUBSCR 494 INPLACE_OR 496 ROT_THREE 498 STORE_SUBSCR 40 500 LOAD_FAST 4 (col) 502 LOAD_FAST 1 (graphlen) 504 COMPARE_OP 0 (<) 506 EXTENDED_ARG 2 508 POP_JUMP_IF_FALSE 548 41 510 LOAD_FAST 0 (matrix) 512 LOAD_FAST 10 (i) 514 DUP_TOP_TWO 516 BINARY_SUBSCR 518 LOAD_FAST 0 (matrix) 520 LOAD_FAST 4 (col) 522 BINARY_SUBSCR 524 LOAD_FAST 0 (matrix) 526 LOAD_FAST 10 (i) 528 LOAD_FAST 4 (col) 530 LOAD_FAST 3 (extra) 532 BINARY_ADD 534 BUILD_TUPLE 2 536 BINARY_SUBSCR 538 BINARY_MULTIPLY 540 INPLACE_SUBTRACT 542 ROT_THREE 544 STORE_SUBSCR 546 JUMP_FORWARD 50 (to 598) 43 >> 548 LOAD_FAST 0 (matrix) 550 LOAD_FAST 10 (i) 552 LOAD_FAST 4 (col) 554 LOAD_FAST 3 (extra) 556 BINARY_ADD 558 BUILD_TUPLE 2 560 BINARY_SUBSCR 562 LOAD_CONST 2 (0) 564 COMPARE_OP 3 (!=) 566 EXTENDED_ARG 2 568 POP_JUMP_IF_FALSE 598 44 570 LOAD_FAST 0 (matrix) 572 LOAD_FAST 10 (i) 574 BINARY_SUBSCR 576 LOAD_FAST 0 (matrix) 578 LOAD_FAST 4 (col) 580 BINARY_SUBSCR 582 BINARY_SUBTRACT 584 LOAD_FAST 2 (PH) 586 BINARY_MODULO 588 LOAD_FAST 0 (matrix) 590 LOAD_FAST 10 (i) 592 STORE_SUBSCR 594 EXTENDED_ARG 2 596 JUMP_ABSOLUTE 548 45 >> 598 LOAD_FAST 0 (matrix) 600 LOAD_FAST 10 (i) 602 DUP_TOP_TWO 604 BINARY_SUBSCR 606 LOAD_FAST 2 (PH) 608 INPLACE_MODULO 610 ROT_THREE 612 STORE_SUBSCR 614 EXTENDED_ARG 1 616 JUMP_ABSOLUTE 462 47 >> 618 LOAD_FAST 4 (col) 620 LOAD_CONST 5 (1) 622 INPLACE_ADD 624 STORE_FAST 4 (col) 626 JUMP_ABSOLUTE 48 49 >> 628 LOAD_GLOBAL 2 (np) 630 LOAD_METHOD 9 (array) 632 LOAD_FAST 0 (matrix) 634 CALL_METHOD 1 636 LOAD_FAST 2 (PH) 638 BINARY_MODULO 640 STORE_FAST 0 (matrix) 50 642 LOAD_CONST 8 (<code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>) 644 LOAD_CONST 4 ('rref.<locals>.<listcomp>') 646 MAKE_FUNCTION 0 648 LOAD_FAST 6 (used_for_row) 650 GET_ITER 652 CALL_FUNCTION 1 654 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093660, file "/private/tmp/a.py", line 8>: 8 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 14 (to 20) 6 STORE_FAST 1 (i) 8 LOAD_GLOBAL 0 (set) 10 LOAD_FAST 1 (i) 12 BUILD_LIST 1 14 CALL_FUNCTION 1 16 LIST_APPEND 2 18 JUMP_ABSOLUTE 4 >> 20 RETURN_VALUE Disassembly of <code object <listcomp> at 0x101093b30, file "/private/tmp/a.py", line 50>: 50 0 BUILD_LIST 0 2 LOAD_FAST 0 (.0) >> 4 FOR_ITER 12 (to 18) 6 STORE_FAST 1 (x) 8 LOAD_GLOBAL 0 (sorted) 10 LOAD_FAST 1 (x) 12 CALL_FUNCTION 1 14 LIST_APPEND 2 16 JUMP_ABSOLUTE 4 >> 18 RETURN_VALUE

Output

Here is the provided Python code refactored into a function called foo: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    used_for_row = [i for i in range(matrix.shape[0])]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]
        
            used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
            pivots.append(col + extra)
        
            pivot = matrix[col, col + extra]
        
            if abs(pivot) == 1 or abs(pivot) == abs(PH - 1):
                assert False
        
            if abs(pivot) == 2 or abs(pivot) == abs(PH - 2):
                assert False
        
            pivot //= 2
        
            matrix[col, col:] -= pivot * matrix[other, col:]
            matrix[col, col:] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
        
            if col + graphlen < matrix.shape[1]:
                matrix[i, col:] -= matrix[i, col] * matrix[col, col:]
                matrix[i, col:] %= PH
        
    return [sorted(used_for_row) for used_for_row in used_for_row]
Now you can call the `foo` function with the `matrix` and `graphlen` arguments to execute the logic defined in the provided code.

Extract Code

I extracted the following code from that output: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    used_for_row = [i for i in range(matrix.shape[0])]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]
        
            used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
            pivots.append(col + extra)
        
            pivot = matrix[col, col + extra]
        
            if abs(pivot) == 1 or abs(pivot) == abs(PH - 1):
                assert False
        
            if abs(pivot) == 2 or abs(pivot) == abs(PH - 2):
                assert False
        
            pivot //= 2
        
            matrix[col, col:] -= pivot * matrix[other, col:]
            matrix[col, col:] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
        
            if col + graphlen < matrix.shape[1]:
                matrix[i, col:] -= matrix[i, col] * matrix[col, col:]
                matrix[i, col:] %= PH
        
    return [sorted(used_for_row) for used_for_row in used_for_row]

Run Code Interpreter

Running the following program: 

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import numpy as np

def foo(matrix, graphlen):
    PH = 16
    extra = 0
    col = 0
    pivots = []
    
    used_for_row = [i for i in range(matrix.shape[0])]
    
    while col + extra < matrix.shape[1] - 1:
        if np.all(matrix[:, col] == 0):
            extra += 1
        
        other = np.argwhere(matrix[:, col] != 0).flatten()[-1]
        
        if other < col:
            extra += 1
        else:
            matrix[other, col], matrix[col, col] = matrix[col, col], matrix[other, col]
        
            used_for_row[other], used_for_row[col] = used_for_row[col], used_for_row[other]
        
            pivots.append(col + extra)
        
            pivot = matrix[col, col + extra]
        
            if abs(pivot) == 1 or abs(pivot) == abs(PH - 1):
                assert False
        
            if abs(pivot) == 2 or abs(pivot) == abs(PH - 2):
                assert False
        
            pivot //= 2
        
            matrix[col, col:] -= pivot * matrix[other, col:]
            matrix[col, col:] %= PH
        
        others = np.argwhere(matrix[:, col + extra] != 0).flatten()
        
        for i in others:
            if i == col:
                continue
            
            used_for_row[i] |= used_for_row[col]
        
            if col + graphlen < matrix.shape[1]:
                matrix[i, col:] -= matrix[i, col] * matrix[col, col:]
                matrix[i, col:] %= PH
        
    return [sorted(used_for_row) for used_for_row in used_for_row]



arr = np.array([[1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, -20], [1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -14], [0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, -20], [0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, -10], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -11], [0, 0, 1, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -9], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, 0, -20], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -40], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

answer = foo(arr, 37)
expected = [[0, 38], [0, 38], [0, 6, 28, 35, 38], [0, 6, 18, 21, 28, 35, 38], [0, 6, 28, 35, 38], [0, 6, 21, 28, 35, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 10, 23, 38], [0, 5, 9, 10, 23, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 27, 38], [0, 5, 9, 10, 11, 23, 25, 27, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 24, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 5, 7, 8, 9, 10, 11, 12, 15, 16, 19, 23, 25, 26, 27, 34, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 38], [0, 5, 9, 10, 13, 17, 23, 30, 32, 33, 38], [0, 22, 29, 38], [0, 22, 29, 38], [0, 6, 28, 35, 38], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 19, 20, 21, 23, 25, 26, 27, 28, 31, 34, 35, 36, 37, 38], [14, 18, 21, 28, 35]]
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')
And got the output: Traceback (most recent call last): File "/usr/src/app/main.py", line 58, in <module> answer = foo(arr, 37) ^^^^^^^^^^^^ File "/usr/src/app/main.py", line 30, in foo assert False AssertionError

Substring Evaluation

Testing if the previous output contains the string All tests passed: False