File size: 490,294 Bytes
bd54785 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467 1468 1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112 2113 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128 2129 2130 2131 2132 2133 2134 2135 2136 2137 2138 2139 2140 2141 2142 2143 2144 2145 2146 2147 2148 2149 2150 2151 2152 2153 2154 2155 2156 2157 2158 2159 2160 2161 2162 2163 2164 2165 2166 2167 2168 2169 2170 2171 2172 2173 2174 2175 2176 2177 2178 2179 2180 2181 2182 2183 2184 2185 2186 2187 2188 2189 2190 2191 2192 2193 2194 2195 2196 2197 2198 2199 2200 2201 2202 2203 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 2219 2220 2221 2222 2223 2224 2225 2226 2227 2228 2229 2230 2231 2232 2233 2234 2235 2236 2237 2238 2239 2240 2241 2242 2243 2244 2245 2246 2247 2248 2249 2250 2251 2252 2253 2254 2255 2256 2257 2258 2259 2260 2261 2262 2263 2264 2265 2266 2267 2268 2269 2270 2271 | program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.0.1"}, {"coremltools-version", "7.0b2"}})]
{
func main<ios16>(tensor<fp32, [1, 77]> input_ids) {
tensor<int32, []> var_5 = const()[name = tensor<string, []>("op_5"), val = tensor<int32, []>(-1)];
tensor<bool, []> var_6 = const()[name = tensor<string, []>("op_6"), val = tensor<bool, []>(false)];
tensor<string, []> cast_1_dtype_0 = const()[name = tensor<string, []>("cast_1_dtype_0"), val = tensor<string, []>("int32")];
tensor<int32, []> inputs_embeds_axis_0 = const()[name = tensor<string, []>("inputs_embeds_axis_0"), val = tensor<int32, []>(0)];
tensor<int32, []> inputs_embeds_batch_dims_0 = const()[name = tensor<string, []>("inputs_embeds_batch_dims_0"), val = tensor<int32, []>(0)];
tensor<fp16, [49408, 1280]> text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor<fp16, [49408, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
tensor<int32, [1, 77]> cast_1326 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor<string, []>("cast_1326")];
tensor<fp16, [1, 77, 1280]> inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_1326, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor<string, []>("inputs_embeds_cast")];
tensor<fp16, [1, 77, 1280]> position_embeddings_to_fp16 = const()[name = tensor<string, []>("position_embeddings_to_fp16"), val = tensor<fp16, [1, 77, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126484608)))];
tensor<fp16, [1, 77, 1280]> input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16)[name = tensor<string, []>("input_3_cast")];
tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = tensor<string, []>("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126681792)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126684416)))];
tensor<fp16, []> var_15_to_fp16 = const()[name = tensor<string, []>("op_15_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 77, 1280]> hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast)[name = tensor<string, []>("hidden_states_1_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126687040)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129963904)))];
tensor<fp16, [1, 77, 1280]> var_148_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("op_148_cast")];
tensor<fp16, []> var_149_to_fp16 = const()[name = tensor<string, []>("op_149_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_5_cast = mul(x = var_148_cast, y = var_149_to_fp16)[name = tensor<string, []>("tensor_5_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129966528)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133243392)))];
tensor<fp16, [1, 77, 1280]> tensor_1_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_1_cast")];
tensor<int32, [4]> var_154 = const()[name = tensor<string, []>("op_154"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_155_cast = reshape(shape = var_154, x = tensor_1_cast)[name = tensor<string, []>("op_155_cast")];
tensor<int32, [4]> var_156_perm_0 = const()[name = tensor<string, []>("op_156_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133246016)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136522880)))];
tensor<fp16, [1, 77, 1280]> tensor_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16, x = hidden_states_1_cast)[name = tensor<string, []>("tensor_3_cast")];
tensor<int32, [4]> var_161 = const()[name = tensor<string, []>("op_161"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_162_cast = reshape(shape = var_161, x = tensor_3_cast)[name = tensor<string, []>("op_162_cast")];
tensor<int32, [4]> var_163_perm_0 = const()[name = tensor<string, []>("op_163_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_170 = const()[name = tensor<string, []>("op_170"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_171_cast = reshape(shape = var_170, x = tensor_5_cast)[name = tensor<string, []>("op_171_cast")];
tensor<int32, [4]> var_172_perm_0 = const()[name = tensor<string, []>("op_172_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_174 = const()[name = tensor<string, []>("op_174"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_158 = transpose(perm = var_172_perm_0, x = var_171_cast)[name = tensor<string, []>("transpose_158")];
tensor<fp16, [20, 77, 64]> query_states_1_cast = reshape(shape = var_174, x = transpose_158)[name = tensor<string, []>("query_states_1_cast")];
tensor<int32, [3]> var_176 = const()[name = tensor<string, []>("op_176"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_160 = transpose(perm = var_156_perm_0, x = var_155_cast)[name = tensor<string, []>("transpose_160")];
tensor<fp16, [20, 77, 64]> key_states_3_cast = reshape(shape = var_176, x = transpose_160)[name = tensor<string, []>("key_states_3_cast")];
tensor<int32, [3]> var_178 = const()[name = tensor<string, []>("op_178"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_159 = transpose(perm = var_163_perm_0, x = var_162_cast)[name = tensor<string, []>("transpose_159")];
tensor<fp16, [20, 77, 64]> value_states_3_cast = reshape(shape = var_178, x = transpose_159)[name = tensor<string, []>("value_states_3_cast")];
tensor<int32, [3]> var_181_perm_0 = const()[name = tensor<string, []>("op_181_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_1_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_1_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_1_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_157 = transpose(perm = var_181_perm_0, x = key_states_3_cast)[name = tensor<string, []>("transpose_157")];
tensor<fp16, [20, 77, 77]> attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_157)[name = tensor<string, []>("attn_weights_1_cast")];
tensor<int32, [4]> var_183 = const()[name = tensor<string, []>("op_183"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_184_cast = reshape(shape = var_183, x = attn_weights_1_cast)[name = tensor<string, []>("op_184_cast")];
tensor<fp16, [1, 1, 77, 77]> var_58_to_fp16 = const()[name = tensor<string, []>("op_58_to_fp16"), val = tensor<fp16, [1, 1, 77, 77]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136525504)))];
tensor<fp16, [1, 20, 77, 77]> attn_weights_3_cast = add(x = var_184_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_3_cast")];
tensor<int32, [3]> var_189 = const()[name = tensor<string, []>("op_189"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_5_cast = reshape(shape = var_189, x = attn_weights_3_cast)[name = tensor<string, []>("input_5_cast")];
tensor<fp16, [20, 77, 77]> input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor<string, []>("input_7_cast")];
tensor<bool, []> attn_output_1_transpose_x_0 = const()[name = tensor<string, []>("attn_output_1_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_1_transpose_y_0 = const()[name = tensor<string, []>("attn_output_1_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor<string, []>("attn_output_1_cast")];
tensor<int32, [4]> var_194 = const()[name = tensor<string, []>("op_194"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_3_cast = reshape(shape = var_194, x = attn_output_1_cast)[name = tensor<string, []>("attn_output_3_cast")];
tensor<int32, [4]> attn_output_5_perm_0 = const()[name = tensor<string, []>("attn_output_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_197 = const()[name = tensor<string, []>("op_197"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_156 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor<string, []>("transpose_156")];
tensor<fp16, [1, 77, 1280]> input_9_cast = reshape(shape = var_197, x = transpose_156)[name = tensor<string, []>("input_9_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136537472)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139814336)))];
tensor<fp16, [1, 77, 1280]> hidden_states_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16, x = input_9_cast)[name = tensor<string, []>("hidden_states_3_cast")];
tensor<fp16, [1, 77, 1280]> input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor<string, []>("input_11_cast")];
tensor<int32, [1]> input_13_axes_0 = const()[name = tensor<string, []>("input_13_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139816960)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139819584)))];
tensor<fp16, [1, 77, 1280]> input_13_cast = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast)[name = tensor<string, []>("input_13_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139822208)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152929472)))];
tensor<fp16, [1, 77, 5120]> input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16, x = input_13_cast)[name = tensor<string, []>("input_15_cast")];
tensor<string, []> input_17_mode_0 = const()[name = tensor<string, []>("input_17_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_17_cast = gelu(mode = input_17_mode_0, x = input_15_cast)[name = tensor<string, []>("input_17_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152939776)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166047040)))];
tensor<fp16, [1, 77, 1280]> hidden_states_5_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16, x = input_17_cast)[name = tensor<string, []>("hidden_states_5_cast")];
tensor<fp16, [1, 77, 1280]> input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor<string, []>("input_19_cast")];
tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = tensor<string, []>("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166049664)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166052288)))];
tensor<fp16, [1, 77, 1280]> hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast)[name = tensor<string, []>("hidden_states_7_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166054912)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169331776)))];
tensor<fp16, [1, 77, 1280]> var_235_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("op_235_cast")];
tensor<fp16, []> var_236_to_fp16 = const()[name = tensor<string, []>("op_236_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_11_cast = mul(x = var_235_cast, y = var_236_to_fp16)[name = tensor<string, []>("tensor_11_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(169334400)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172611264)))];
tensor<fp16, [1, 77, 1280]> tensor_7_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_7_cast")];
tensor<int32, [4]> var_241 = const()[name = tensor<string, []>("op_241"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_242_cast = reshape(shape = var_241, x = tensor_7_cast)[name = tensor<string, []>("op_242_cast")];
tensor<int32, [4]> var_243_perm_0 = const()[name = tensor<string, []>("op_243_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172613888)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175890752)))];
tensor<fp16, [1, 77, 1280]> tensor_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16, x = hidden_states_7_cast)[name = tensor<string, []>("tensor_9_cast")];
tensor<int32, [4]> var_248 = const()[name = tensor<string, []>("op_248"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_249_cast = reshape(shape = var_248, x = tensor_9_cast)[name = tensor<string, []>("op_249_cast")];
tensor<int32, [4]> var_250_perm_0 = const()[name = tensor<string, []>("op_250_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_257 = const()[name = tensor<string, []>("op_257"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_258_cast = reshape(shape = var_257, x = tensor_11_cast)[name = tensor<string, []>("op_258_cast")];
tensor<int32, [4]> var_259_perm_0 = const()[name = tensor<string, []>("op_259_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_261 = const()[name = tensor<string, []>("op_261"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_153 = transpose(perm = var_259_perm_0, x = var_258_cast)[name = tensor<string, []>("transpose_153")];
tensor<fp16, [20, 77, 64]> query_states_3_cast = reshape(shape = var_261, x = transpose_153)[name = tensor<string, []>("query_states_3_cast")];
tensor<int32, [3]> var_263 = const()[name = tensor<string, []>("op_263"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_155 = transpose(perm = var_243_perm_0, x = var_242_cast)[name = tensor<string, []>("transpose_155")];
tensor<fp16, [20, 77, 64]> key_states_7_cast = reshape(shape = var_263, x = transpose_155)[name = tensor<string, []>("key_states_7_cast")];
tensor<int32, [3]> var_265 = const()[name = tensor<string, []>("op_265"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_154 = transpose(perm = var_250_perm_0, x = var_249_cast)[name = tensor<string, []>("transpose_154")];
tensor<fp16, [20, 77, 64]> value_states_7_cast = reshape(shape = var_265, x = transpose_154)[name = tensor<string, []>("value_states_7_cast")];
tensor<int32, [3]> var_268_perm_0 = const()[name = tensor<string, []>("op_268_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_7_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_7_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_7_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_152 = transpose(perm = var_268_perm_0, x = key_states_7_cast)[name = tensor<string, []>("transpose_152")];
tensor<fp16, [20, 77, 77]> attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_152)[name = tensor<string, []>("attn_weights_7_cast")];
tensor<int32, [4]> var_270 = const()[name = tensor<string, []>("op_270"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_271_cast = reshape(shape = var_270, x = attn_weights_7_cast)[name = tensor<string, []>("op_271_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_9_cast = add(x = var_271_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_9_cast")];
tensor<int32, [3]> var_276 = const()[name = tensor<string, []>("op_276"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_21_cast = reshape(shape = var_276, x = attn_weights_9_cast)[name = tensor<string, []>("input_21_cast")];
tensor<fp16, [20, 77, 77]> input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor<string, []>("input_23_cast")];
tensor<bool, []> attn_output_7_transpose_x_0 = const()[name = tensor<string, []>("attn_output_7_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_7_transpose_y_0 = const()[name = tensor<string, []>("attn_output_7_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor<string, []>("attn_output_7_cast")];
tensor<int32, [4]> var_281 = const()[name = tensor<string, []>("op_281"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_9_cast = reshape(shape = var_281, x = attn_output_7_cast)[name = tensor<string, []>("attn_output_9_cast")];
tensor<int32, [4]> attn_output_11_perm_0 = const()[name = tensor<string, []>("attn_output_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_284 = const()[name = tensor<string, []>("op_284"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_151 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor<string, []>("transpose_151")];
tensor<fp16, [1, 77, 1280]> input_25_cast = reshape(shape = var_284, x = transpose_151)[name = tensor<string, []>("input_25_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175893376)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179170240)))];
tensor<fp16, [1, 77, 1280]> hidden_states_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16, x = input_25_cast)[name = tensor<string, []>("hidden_states_9_cast")];
tensor<fp16, [1, 77, 1280]> input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor<string, []>("input_27_cast")];
tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179172864)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179175488)))];
tensor<fp16, [1, 77, 1280]> input_29_cast = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor<string, []>("input_29_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179178112)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192285376)))];
tensor<fp16, [1, 77, 5120]> input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16, x = input_29_cast)[name = tensor<string, []>("input_31_cast")];
tensor<string, []> input_33_mode_0 = const()[name = tensor<string, []>("input_33_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_33_cast = gelu(mode = input_33_mode_0, x = input_31_cast)[name = tensor<string, []>("input_33_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(192295680)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205402944)))];
tensor<fp16, [1, 77, 1280]> hidden_states_11_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16, x = input_33_cast)[name = tensor<string, []>("hidden_states_11_cast")];
tensor<fp16, [1, 77, 1280]> input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor<string, []>("input_35_cast")];
tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = tensor<string, []>("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205405568)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205408192)))];
tensor<fp16, [1, 77, 1280]> hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor<string, []>("hidden_states_13_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205410816)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208687680)))];
tensor<fp16, [1, 77, 1280]> var_322_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("op_322_cast")];
tensor<fp16, []> var_323_to_fp16 = const()[name = tensor<string, []>("op_323_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_17_cast = mul(x = var_322_cast, y = var_323_to_fp16)[name = tensor<string, []>("tensor_17_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208690304)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211967168)))];
tensor<fp16, [1, 77, 1280]> tensor_13_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_13_cast")];
tensor<int32, [4]> var_328 = const()[name = tensor<string, []>("op_328"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_329_cast = reshape(shape = var_328, x = tensor_13_cast)[name = tensor<string, []>("op_329_cast")];
tensor<int32, [4]> var_330_perm_0 = const()[name = tensor<string, []>("op_330_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211969792)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215246656)))];
tensor<fp16, [1, 77, 1280]> tensor_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16, x = hidden_states_13_cast)[name = tensor<string, []>("tensor_15_cast")];
tensor<int32, [4]> var_335 = const()[name = tensor<string, []>("op_335"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_336_cast = reshape(shape = var_335, x = tensor_15_cast)[name = tensor<string, []>("op_336_cast")];
tensor<int32, [4]> var_337_perm_0 = const()[name = tensor<string, []>("op_337_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_344 = const()[name = tensor<string, []>("op_344"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_345_cast = reshape(shape = var_344, x = tensor_17_cast)[name = tensor<string, []>("op_345_cast")];
tensor<int32, [4]> var_346_perm_0 = const()[name = tensor<string, []>("op_346_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_348 = const()[name = tensor<string, []>("op_348"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_148 = transpose(perm = var_346_perm_0, x = var_345_cast)[name = tensor<string, []>("transpose_148")];
tensor<fp16, [20, 77, 64]> query_states_5_cast = reshape(shape = var_348, x = transpose_148)[name = tensor<string, []>("query_states_5_cast")];
tensor<int32, [3]> var_350 = const()[name = tensor<string, []>("op_350"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_150 = transpose(perm = var_330_perm_0, x = var_329_cast)[name = tensor<string, []>("transpose_150")];
tensor<fp16, [20, 77, 64]> key_states_11_cast = reshape(shape = var_350, x = transpose_150)[name = tensor<string, []>("key_states_11_cast")];
tensor<int32, [3]> var_352 = const()[name = tensor<string, []>("op_352"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_149 = transpose(perm = var_337_perm_0, x = var_336_cast)[name = tensor<string, []>("transpose_149")];
tensor<fp16, [20, 77, 64]> value_states_11_cast = reshape(shape = var_352, x = transpose_149)[name = tensor<string, []>("value_states_11_cast")];
tensor<int32, [3]> var_355_perm_0 = const()[name = tensor<string, []>("op_355_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_13_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_13_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_13_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_147 = transpose(perm = var_355_perm_0, x = key_states_11_cast)[name = tensor<string, []>("transpose_147")];
tensor<fp16, [20, 77, 77]> attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_147)[name = tensor<string, []>("attn_weights_13_cast")];
tensor<int32, [4]> var_357 = const()[name = tensor<string, []>("op_357"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_358_cast = reshape(shape = var_357, x = attn_weights_13_cast)[name = tensor<string, []>("op_358_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_15_cast = add(x = var_358_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_15_cast")];
tensor<int32, [3]> var_363 = const()[name = tensor<string, []>("op_363"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_37_cast = reshape(shape = var_363, x = attn_weights_15_cast)[name = tensor<string, []>("input_37_cast")];
tensor<fp16, [20, 77, 77]> input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor<string, []>("input_39_cast")];
tensor<bool, []> attn_output_13_transpose_x_0 = const()[name = tensor<string, []>("attn_output_13_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_13_transpose_y_0 = const()[name = tensor<string, []>("attn_output_13_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor<string, []>("attn_output_13_cast")];
tensor<int32, [4]> var_368 = const()[name = tensor<string, []>("op_368"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_15_cast = reshape(shape = var_368, x = attn_output_13_cast)[name = tensor<string, []>("attn_output_15_cast")];
tensor<int32, [4]> attn_output_17_perm_0 = const()[name = tensor<string, []>("attn_output_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_371 = const()[name = tensor<string, []>("op_371"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_146 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor<string, []>("transpose_146")];
tensor<fp16, [1, 77, 1280]> input_41_cast = reshape(shape = var_371, x = transpose_146)[name = tensor<string, []>("input_41_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215249280)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218526144)))];
tensor<fp16, [1, 77, 1280]> hidden_states_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16, x = input_41_cast)[name = tensor<string, []>("hidden_states_15_cast")];
tensor<fp16, [1, 77, 1280]> input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor<string, []>("input_43_cast")];
tensor<int32, [1]> input_45_axes_0 = const()[name = tensor<string, []>("input_45_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218528768)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218531392)))];
tensor<fp16, [1, 77, 1280]> input_45_cast = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast)[name = tensor<string, []>("input_45_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(218534016)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231641280)))];
tensor<fp16, [1, 77, 5120]> input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16, x = input_45_cast)[name = tensor<string, []>("input_47_cast")];
tensor<string, []> input_49_mode_0 = const()[name = tensor<string, []>("input_49_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_49_cast = gelu(mode = input_49_mode_0, x = input_47_cast)[name = tensor<string, []>("input_49_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231651584)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244758848)))];
tensor<fp16, [1, 77, 1280]> hidden_states_17_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16, x = input_49_cast)[name = tensor<string, []>("hidden_states_17_cast")];
tensor<fp16, [1, 77, 1280]> input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor<string, []>("input_51_cast")];
tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = tensor<string, []>("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244761472)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244764096)))];
tensor<fp16, [1, 77, 1280]> hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast)[name = tensor<string, []>("hidden_states_19_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(244766720)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248043584)))];
tensor<fp16, [1, 77, 1280]> var_409_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("op_409_cast")];
tensor<fp16, []> var_410_to_fp16 = const()[name = tensor<string, []>("op_410_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_23_cast = mul(x = var_409_cast, y = var_410_to_fp16)[name = tensor<string, []>("tensor_23_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(248046208)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(251323072)))];
tensor<fp16, [1, 77, 1280]> tensor_19_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_19_cast")];
tensor<int32, [4]> var_415 = const()[name = tensor<string, []>("op_415"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_416_cast = reshape(shape = var_415, x = tensor_19_cast)[name = tensor<string, []>("op_416_cast")];
tensor<int32, [4]> var_417_perm_0 = const()[name = tensor<string, []>("op_417_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(251325696)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254602560)))];
tensor<fp16, [1, 77, 1280]> tensor_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16, x = hidden_states_19_cast)[name = tensor<string, []>("tensor_21_cast")];
tensor<int32, [4]> var_422 = const()[name = tensor<string, []>("op_422"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_423_cast = reshape(shape = var_422, x = tensor_21_cast)[name = tensor<string, []>("op_423_cast")];
tensor<int32, [4]> var_424_perm_0 = const()[name = tensor<string, []>("op_424_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_431 = const()[name = tensor<string, []>("op_431"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_432_cast = reshape(shape = var_431, x = tensor_23_cast)[name = tensor<string, []>("op_432_cast")];
tensor<int32, [4]> var_433_perm_0 = const()[name = tensor<string, []>("op_433_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_435 = const()[name = tensor<string, []>("op_435"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_143 = transpose(perm = var_433_perm_0, x = var_432_cast)[name = tensor<string, []>("transpose_143")];
tensor<fp16, [20, 77, 64]> query_states_7_cast = reshape(shape = var_435, x = transpose_143)[name = tensor<string, []>("query_states_7_cast")];
tensor<int32, [3]> var_437 = const()[name = tensor<string, []>("op_437"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_145 = transpose(perm = var_417_perm_0, x = var_416_cast)[name = tensor<string, []>("transpose_145")];
tensor<fp16, [20, 77, 64]> key_states_15_cast = reshape(shape = var_437, x = transpose_145)[name = tensor<string, []>("key_states_15_cast")];
tensor<int32, [3]> var_439 = const()[name = tensor<string, []>("op_439"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_144 = transpose(perm = var_424_perm_0, x = var_423_cast)[name = tensor<string, []>("transpose_144")];
tensor<fp16, [20, 77, 64]> value_states_15_cast = reshape(shape = var_439, x = transpose_144)[name = tensor<string, []>("value_states_15_cast")];
tensor<int32, [3]> var_442_perm_0 = const()[name = tensor<string, []>("op_442_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_19_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_19_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_19_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_142 = transpose(perm = var_442_perm_0, x = key_states_15_cast)[name = tensor<string, []>("transpose_142")];
tensor<fp16, [20, 77, 77]> attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_142)[name = tensor<string, []>("attn_weights_19_cast")];
tensor<int32, [4]> var_444 = const()[name = tensor<string, []>("op_444"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_445_cast = reshape(shape = var_444, x = attn_weights_19_cast)[name = tensor<string, []>("op_445_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_21_cast = add(x = var_445_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_21_cast")];
tensor<int32, [3]> var_450 = const()[name = tensor<string, []>("op_450"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_53_cast = reshape(shape = var_450, x = attn_weights_21_cast)[name = tensor<string, []>("input_53_cast")];
tensor<fp16, [20, 77, 77]> input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor<string, []>("input_55_cast")];
tensor<bool, []> attn_output_19_transpose_x_0 = const()[name = tensor<string, []>("attn_output_19_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_19_transpose_y_0 = const()[name = tensor<string, []>("attn_output_19_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor<string, []>("attn_output_19_cast")];
tensor<int32, [4]> var_455 = const()[name = tensor<string, []>("op_455"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_21_cast = reshape(shape = var_455, x = attn_output_19_cast)[name = tensor<string, []>("attn_output_21_cast")];
tensor<int32, [4]> attn_output_23_perm_0 = const()[name = tensor<string, []>("attn_output_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_458 = const()[name = tensor<string, []>("op_458"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_141 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor<string, []>("transpose_141")];
tensor<fp16, [1, 77, 1280]> input_57_cast = reshape(shape = var_458, x = transpose_141)[name = tensor<string, []>("input_57_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254605184)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257882048)))];
tensor<fp16, [1, 77, 1280]> hidden_states_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16, x = input_57_cast)[name = tensor<string, []>("hidden_states_21_cast")];
tensor<fp16, [1, 77, 1280]> input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor<string, []>("input_59_cast")];
tensor<int32, [1]> input_61_axes_0 = const()[name = tensor<string, []>("input_61_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257884672)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257887296)))];
tensor<fp16, [1, 77, 1280]> input_61_cast = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast)[name = tensor<string, []>("input_61_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(257889920)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270997184)))];
tensor<fp16, [1, 77, 5120]> input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16, x = input_61_cast)[name = tensor<string, []>("input_63_cast")];
tensor<string, []> input_65_mode_0 = const()[name = tensor<string, []>("input_65_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_65_cast = gelu(mode = input_65_mode_0, x = input_63_cast)[name = tensor<string, []>("input_65_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(271007488)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284114752)))];
tensor<fp16, [1, 77, 1280]> hidden_states_23_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16, x = input_65_cast)[name = tensor<string, []>("hidden_states_23_cast")];
tensor<fp16, [1, 77, 1280]> input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor<string, []>("input_67_cast")];
tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = tensor<string, []>("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284117376)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284120000)))];
tensor<fp16, [1, 77, 1280]> hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast)[name = tensor<string, []>("hidden_states_25_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284122624)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287399488)))];
tensor<fp16, [1, 77, 1280]> var_496_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("op_496_cast")];
tensor<fp16, []> var_497_to_fp16 = const()[name = tensor<string, []>("op_497_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_29_cast = mul(x = var_496_cast, y = var_497_to_fp16)[name = tensor<string, []>("tensor_29_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(287402112)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290678976)))];
tensor<fp16, [1, 77, 1280]> tensor_25_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_25_cast")];
tensor<int32, [4]> var_502 = const()[name = tensor<string, []>("op_502"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_503_cast = reshape(shape = var_502, x = tensor_25_cast)[name = tensor<string, []>("op_503_cast")];
tensor<int32, [4]> var_504_perm_0 = const()[name = tensor<string, []>("op_504_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(290681600)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293958464)))];
tensor<fp16, [1, 77, 1280]> tensor_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16, x = hidden_states_25_cast)[name = tensor<string, []>("tensor_27_cast")];
tensor<int32, [4]> var_509 = const()[name = tensor<string, []>("op_509"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_510_cast = reshape(shape = var_509, x = tensor_27_cast)[name = tensor<string, []>("op_510_cast")];
tensor<int32, [4]> var_511_perm_0 = const()[name = tensor<string, []>("op_511_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_518 = const()[name = tensor<string, []>("op_518"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_519_cast = reshape(shape = var_518, x = tensor_29_cast)[name = tensor<string, []>("op_519_cast")];
tensor<int32, [4]> var_520_perm_0 = const()[name = tensor<string, []>("op_520_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_522 = const()[name = tensor<string, []>("op_522"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_138 = transpose(perm = var_520_perm_0, x = var_519_cast)[name = tensor<string, []>("transpose_138")];
tensor<fp16, [20, 77, 64]> query_states_9_cast = reshape(shape = var_522, x = transpose_138)[name = tensor<string, []>("query_states_9_cast")];
tensor<int32, [3]> var_524 = const()[name = tensor<string, []>("op_524"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_140 = transpose(perm = var_504_perm_0, x = var_503_cast)[name = tensor<string, []>("transpose_140")];
tensor<fp16, [20, 77, 64]> key_states_19_cast = reshape(shape = var_524, x = transpose_140)[name = tensor<string, []>("key_states_19_cast")];
tensor<int32, [3]> var_526 = const()[name = tensor<string, []>("op_526"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_139 = transpose(perm = var_511_perm_0, x = var_510_cast)[name = tensor<string, []>("transpose_139")];
tensor<fp16, [20, 77, 64]> value_states_19_cast = reshape(shape = var_526, x = transpose_139)[name = tensor<string, []>("value_states_19_cast")];
tensor<int32, [3]> var_529_perm_0 = const()[name = tensor<string, []>("op_529_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_25_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_25_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_25_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_137 = transpose(perm = var_529_perm_0, x = key_states_19_cast)[name = tensor<string, []>("transpose_137")];
tensor<fp16, [20, 77, 77]> attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_137)[name = tensor<string, []>("attn_weights_25_cast")];
tensor<int32, [4]> var_531 = const()[name = tensor<string, []>("op_531"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_532_cast = reshape(shape = var_531, x = attn_weights_25_cast)[name = tensor<string, []>("op_532_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_27_cast = add(x = var_532_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_27_cast")];
tensor<int32, [3]> var_537 = const()[name = tensor<string, []>("op_537"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_69_cast = reshape(shape = var_537, x = attn_weights_27_cast)[name = tensor<string, []>("input_69_cast")];
tensor<fp16, [20, 77, 77]> input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor<string, []>("input_71_cast")];
tensor<bool, []> attn_output_25_transpose_x_0 = const()[name = tensor<string, []>("attn_output_25_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_25_transpose_y_0 = const()[name = tensor<string, []>("attn_output_25_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor<string, []>("attn_output_25_cast")];
tensor<int32, [4]> var_542 = const()[name = tensor<string, []>("op_542"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_27_cast = reshape(shape = var_542, x = attn_output_25_cast)[name = tensor<string, []>("attn_output_27_cast")];
tensor<int32, [4]> attn_output_29_perm_0 = const()[name = tensor<string, []>("attn_output_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_545 = const()[name = tensor<string, []>("op_545"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_136 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor<string, []>("transpose_136")];
tensor<fp16, [1, 77, 1280]> input_73_cast = reshape(shape = var_545, x = transpose_136)[name = tensor<string, []>("input_73_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(293961088)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297237952)))];
tensor<fp16, [1, 77, 1280]> hidden_states_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16, x = input_73_cast)[name = tensor<string, []>("hidden_states_27_cast")];
tensor<fp16, [1, 77, 1280]> input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor<string, []>("input_75_cast")];
tensor<int32, [1]> input_77_axes_0 = const()[name = tensor<string, []>("input_77_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297240576)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297243200)))];
tensor<fp16, [1, 77, 1280]> input_77_cast = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast)[name = tensor<string, []>("input_77_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297245824)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310353088)))];
tensor<fp16, [1, 77, 5120]> input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16, x = input_77_cast)[name = tensor<string, []>("input_79_cast")];
tensor<string, []> input_81_mode_0 = const()[name = tensor<string, []>("input_81_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_81_cast = gelu(mode = input_81_mode_0, x = input_79_cast)[name = tensor<string, []>("input_81_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(310363392)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323470656)))];
tensor<fp16, [1, 77, 1280]> hidden_states_29_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16, x = input_81_cast)[name = tensor<string, []>("hidden_states_29_cast")];
tensor<fp16, [1, 77, 1280]> input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor<string, []>("input_83_cast")];
tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = tensor<string, []>("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323473280)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323475904)))];
tensor<fp16, [1, 77, 1280]> hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast)[name = tensor<string, []>("hidden_states_31_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(323478528)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326755392)))];
tensor<fp16, [1, 77, 1280]> var_583_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("op_583_cast")];
tensor<fp16, []> var_584_to_fp16 = const()[name = tensor<string, []>("op_584_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_35_cast = mul(x = var_583_cast, y = var_584_to_fp16)[name = tensor<string, []>("tensor_35_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326758016)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330034880)))];
tensor<fp16, [1, 77, 1280]> tensor_31_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_31_cast")];
tensor<int32, [4]> var_589 = const()[name = tensor<string, []>("op_589"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_590_cast = reshape(shape = var_589, x = tensor_31_cast)[name = tensor<string, []>("op_590_cast")];
tensor<int32, [4]> var_591_perm_0 = const()[name = tensor<string, []>("op_591_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(330037504)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333314368)))];
tensor<fp16, [1, 77, 1280]> tensor_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16, x = hidden_states_31_cast)[name = tensor<string, []>("tensor_33_cast")];
tensor<int32, [4]> var_596 = const()[name = tensor<string, []>("op_596"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_597_cast = reshape(shape = var_596, x = tensor_33_cast)[name = tensor<string, []>("op_597_cast")];
tensor<int32, [4]> var_598_perm_0 = const()[name = tensor<string, []>("op_598_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_605 = const()[name = tensor<string, []>("op_605"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_606_cast = reshape(shape = var_605, x = tensor_35_cast)[name = tensor<string, []>("op_606_cast")];
tensor<int32, [4]> var_607_perm_0 = const()[name = tensor<string, []>("op_607_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_609 = const()[name = tensor<string, []>("op_609"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_133 = transpose(perm = var_607_perm_0, x = var_606_cast)[name = tensor<string, []>("transpose_133")];
tensor<fp16, [20, 77, 64]> query_states_11_cast = reshape(shape = var_609, x = transpose_133)[name = tensor<string, []>("query_states_11_cast")];
tensor<int32, [3]> var_611 = const()[name = tensor<string, []>("op_611"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_135 = transpose(perm = var_591_perm_0, x = var_590_cast)[name = tensor<string, []>("transpose_135")];
tensor<fp16, [20, 77, 64]> key_states_23_cast = reshape(shape = var_611, x = transpose_135)[name = tensor<string, []>("key_states_23_cast")];
tensor<int32, [3]> var_613 = const()[name = tensor<string, []>("op_613"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_134 = transpose(perm = var_598_perm_0, x = var_597_cast)[name = tensor<string, []>("transpose_134")];
tensor<fp16, [20, 77, 64]> value_states_23_cast = reshape(shape = var_613, x = transpose_134)[name = tensor<string, []>("value_states_23_cast")];
tensor<int32, [3]> var_616_perm_0 = const()[name = tensor<string, []>("op_616_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_31_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_31_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_31_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_132 = transpose(perm = var_616_perm_0, x = key_states_23_cast)[name = tensor<string, []>("transpose_132")];
tensor<fp16, [20, 77, 77]> attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_132)[name = tensor<string, []>("attn_weights_31_cast")];
tensor<int32, [4]> var_618 = const()[name = tensor<string, []>("op_618"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_619_cast = reshape(shape = var_618, x = attn_weights_31_cast)[name = tensor<string, []>("op_619_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_33_cast = add(x = var_619_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_33_cast")];
tensor<int32, [3]> var_624 = const()[name = tensor<string, []>("op_624"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_85_cast = reshape(shape = var_624, x = attn_weights_33_cast)[name = tensor<string, []>("input_85_cast")];
tensor<fp16, [20, 77, 77]> input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor<string, []>("input_87_cast")];
tensor<bool, []> attn_output_31_transpose_x_0 = const()[name = tensor<string, []>("attn_output_31_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_31_transpose_y_0 = const()[name = tensor<string, []>("attn_output_31_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor<string, []>("attn_output_31_cast")];
tensor<int32, [4]> var_629 = const()[name = tensor<string, []>("op_629"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_33_cast = reshape(shape = var_629, x = attn_output_31_cast)[name = tensor<string, []>("attn_output_33_cast")];
tensor<int32, [4]> attn_output_35_perm_0 = const()[name = tensor<string, []>("attn_output_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_632 = const()[name = tensor<string, []>("op_632"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_131 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor<string, []>("transpose_131")];
tensor<fp16, [1, 77, 1280]> input_89_cast = reshape(shape = var_632, x = transpose_131)[name = tensor<string, []>("input_89_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333316992)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336593856)))];
tensor<fp16, [1, 77, 1280]> hidden_states_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16, x = input_89_cast)[name = tensor<string, []>("hidden_states_33_cast")];
tensor<fp16, [1, 77, 1280]> input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor<string, []>("input_91_cast")];
tensor<int32, [1]> input_93_axes_0 = const()[name = tensor<string, []>("input_93_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336596480)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336599104)))];
tensor<fp16, [1, 77, 1280]> input_93_cast = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast)[name = tensor<string, []>("input_93_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(336601728)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349708992)))];
tensor<fp16, [1, 77, 5120]> input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16, x = input_93_cast)[name = tensor<string, []>("input_95_cast")];
tensor<string, []> input_97_mode_0 = const()[name = tensor<string, []>("input_97_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_97_cast = gelu(mode = input_97_mode_0, x = input_95_cast)[name = tensor<string, []>("input_97_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(349719296)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362826560)))];
tensor<fp16, [1, 77, 1280]> hidden_states_35_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16, x = input_97_cast)[name = tensor<string, []>("hidden_states_35_cast")];
tensor<fp16, [1, 77, 1280]> input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor<string, []>("input_99_cast")];
tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = tensor<string, []>("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362829184)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362831808)))];
tensor<fp16, [1, 77, 1280]> hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast)[name = tensor<string, []>("hidden_states_37_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(362834432)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366111296)))];
tensor<fp16, [1, 77, 1280]> var_670_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("op_670_cast")];
tensor<fp16, []> var_671_to_fp16 = const()[name = tensor<string, []>("op_671_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_41_cast = mul(x = var_670_cast, y = var_671_to_fp16)[name = tensor<string, []>("tensor_41_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(366113920)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369390784)))];
tensor<fp16, [1, 77, 1280]> tensor_37_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_37_cast")];
tensor<int32, [4]> var_676 = const()[name = tensor<string, []>("op_676"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_677_cast = reshape(shape = var_676, x = tensor_37_cast)[name = tensor<string, []>("op_677_cast")];
tensor<int32, [4]> var_678_perm_0 = const()[name = tensor<string, []>("op_678_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369393408)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372670272)))];
tensor<fp16, [1, 77, 1280]> tensor_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16, x = hidden_states_37_cast)[name = tensor<string, []>("tensor_39_cast")];
tensor<int32, [4]> var_683 = const()[name = tensor<string, []>("op_683"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_684_cast = reshape(shape = var_683, x = tensor_39_cast)[name = tensor<string, []>("op_684_cast")];
tensor<int32, [4]> var_685_perm_0 = const()[name = tensor<string, []>("op_685_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_692 = const()[name = tensor<string, []>("op_692"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_693_cast = reshape(shape = var_692, x = tensor_41_cast)[name = tensor<string, []>("op_693_cast")];
tensor<int32, [4]> var_694_perm_0 = const()[name = tensor<string, []>("op_694_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_696 = const()[name = tensor<string, []>("op_696"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_128 = transpose(perm = var_694_perm_0, x = var_693_cast)[name = tensor<string, []>("transpose_128")];
tensor<fp16, [20, 77, 64]> query_states_13_cast = reshape(shape = var_696, x = transpose_128)[name = tensor<string, []>("query_states_13_cast")];
tensor<int32, [3]> var_698 = const()[name = tensor<string, []>("op_698"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_130 = transpose(perm = var_678_perm_0, x = var_677_cast)[name = tensor<string, []>("transpose_130")];
tensor<fp16, [20, 77, 64]> key_states_27_cast = reshape(shape = var_698, x = transpose_130)[name = tensor<string, []>("key_states_27_cast")];
tensor<int32, [3]> var_700 = const()[name = tensor<string, []>("op_700"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_129 = transpose(perm = var_685_perm_0, x = var_684_cast)[name = tensor<string, []>("transpose_129")];
tensor<fp16, [20, 77, 64]> value_states_27_cast = reshape(shape = var_700, x = transpose_129)[name = tensor<string, []>("value_states_27_cast")];
tensor<int32, [3]> var_703_perm_0 = const()[name = tensor<string, []>("op_703_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_37_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_37_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_37_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_127 = transpose(perm = var_703_perm_0, x = key_states_27_cast)[name = tensor<string, []>("transpose_127")];
tensor<fp16, [20, 77, 77]> attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_127)[name = tensor<string, []>("attn_weights_37_cast")];
tensor<int32, [4]> var_705 = const()[name = tensor<string, []>("op_705"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_706_cast = reshape(shape = var_705, x = attn_weights_37_cast)[name = tensor<string, []>("op_706_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_39_cast = add(x = var_706_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_39_cast")];
tensor<int32, [3]> var_711 = const()[name = tensor<string, []>("op_711"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_101_cast = reshape(shape = var_711, x = attn_weights_39_cast)[name = tensor<string, []>("input_101_cast")];
tensor<fp16, [20, 77, 77]> input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor<string, []>("input_103_cast")];
tensor<bool, []> attn_output_37_transpose_x_0 = const()[name = tensor<string, []>("attn_output_37_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_37_transpose_y_0 = const()[name = tensor<string, []>("attn_output_37_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor<string, []>("attn_output_37_cast")];
tensor<int32, [4]> var_716 = const()[name = tensor<string, []>("op_716"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_39_cast = reshape(shape = var_716, x = attn_output_37_cast)[name = tensor<string, []>("attn_output_39_cast")];
tensor<int32, [4]> attn_output_41_perm_0 = const()[name = tensor<string, []>("attn_output_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_719 = const()[name = tensor<string, []>("op_719"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_126 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor<string, []>("transpose_126")];
tensor<fp16, [1, 77, 1280]> input_105_cast = reshape(shape = var_719, x = transpose_126)[name = tensor<string, []>("input_105_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(372672896)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375949760)))];
tensor<fp16, [1, 77, 1280]> hidden_states_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16, x = input_105_cast)[name = tensor<string, []>("hidden_states_39_cast")];
tensor<fp16, [1, 77, 1280]> input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor<string, []>("input_107_cast")];
tensor<int32, [1]> input_109_axes_0 = const()[name = tensor<string, []>("input_109_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375952384)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375955008)))];
tensor<fp16, [1, 77, 1280]> input_109_cast = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast)[name = tensor<string, []>("input_109_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375957632)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389064896)))];
tensor<fp16, [1, 77, 5120]> input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16, x = input_109_cast)[name = tensor<string, []>("input_111_cast")];
tensor<string, []> input_113_mode_0 = const()[name = tensor<string, []>("input_113_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_113_cast = gelu(mode = input_113_mode_0, x = input_111_cast)[name = tensor<string, []>("input_113_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(389075200)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402182464)))];
tensor<fp16, [1, 77, 1280]> hidden_states_41_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16, x = input_113_cast)[name = tensor<string, []>("hidden_states_41_cast")];
tensor<fp16, [1, 77, 1280]> input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor<string, []>("input_115_cast")];
tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = tensor<string, []>("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402185088)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402187712)))];
tensor<fp16, [1, 77, 1280]> hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast)[name = tensor<string, []>("hidden_states_43_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(402190336)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405467200)))];
tensor<fp16, [1, 77, 1280]> var_757_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("op_757_cast")];
tensor<fp16, []> var_758_to_fp16 = const()[name = tensor<string, []>("op_758_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_47_cast = mul(x = var_757_cast, y = var_758_to_fp16)[name = tensor<string, []>("tensor_47_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(405469824)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408746688)))];
tensor<fp16, [1, 77, 1280]> tensor_43_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_43_cast")];
tensor<int32, [4]> var_763 = const()[name = tensor<string, []>("op_763"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_764_cast = reshape(shape = var_763, x = tensor_43_cast)[name = tensor<string, []>("op_764_cast")];
tensor<int32, [4]> var_765_perm_0 = const()[name = tensor<string, []>("op_765_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(408749312)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412026176)))];
tensor<fp16, [1, 77, 1280]> tensor_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16, x = hidden_states_43_cast)[name = tensor<string, []>("tensor_45_cast")];
tensor<int32, [4]> var_770 = const()[name = tensor<string, []>("op_770"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_771_cast = reshape(shape = var_770, x = tensor_45_cast)[name = tensor<string, []>("op_771_cast")];
tensor<int32, [4]> var_772_perm_0 = const()[name = tensor<string, []>("op_772_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_779 = const()[name = tensor<string, []>("op_779"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_780_cast = reshape(shape = var_779, x = tensor_47_cast)[name = tensor<string, []>("op_780_cast")];
tensor<int32, [4]> var_781_perm_0 = const()[name = tensor<string, []>("op_781_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_783 = const()[name = tensor<string, []>("op_783"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_123 = transpose(perm = var_781_perm_0, x = var_780_cast)[name = tensor<string, []>("transpose_123")];
tensor<fp16, [20, 77, 64]> query_states_15_cast = reshape(shape = var_783, x = transpose_123)[name = tensor<string, []>("query_states_15_cast")];
tensor<int32, [3]> var_785 = const()[name = tensor<string, []>("op_785"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_125 = transpose(perm = var_765_perm_0, x = var_764_cast)[name = tensor<string, []>("transpose_125")];
tensor<fp16, [20, 77, 64]> key_states_31_cast = reshape(shape = var_785, x = transpose_125)[name = tensor<string, []>("key_states_31_cast")];
tensor<int32, [3]> var_787 = const()[name = tensor<string, []>("op_787"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_124 = transpose(perm = var_772_perm_0, x = var_771_cast)[name = tensor<string, []>("transpose_124")];
tensor<fp16, [20, 77, 64]> value_states_31_cast = reshape(shape = var_787, x = transpose_124)[name = tensor<string, []>("value_states_31_cast")];
tensor<int32, [3]> var_790_perm_0 = const()[name = tensor<string, []>("op_790_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_43_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_43_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_43_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_122 = transpose(perm = var_790_perm_0, x = key_states_31_cast)[name = tensor<string, []>("transpose_122")];
tensor<fp16, [20, 77, 77]> attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_122)[name = tensor<string, []>("attn_weights_43_cast")];
tensor<int32, [4]> var_792 = const()[name = tensor<string, []>("op_792"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_793_cast = reshape(shape = var_792, x = attn_weights_43_cast)[name = tensor<string, []>("op_793_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_45_cast = add(x = var_793_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_45_cast")];
tensor<int32, [3]> var_798 = const()[name = tensor<string, []>("op_798"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_117_cast = reshape(shape = var_798, x = attn_weights_45_cast)[name = tensor<string, []>("input_117_cast")];
tensor<fp16, [20, 77, 77]> input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor<string, []>("input_119_cast")];
tensor<bool, []> attn_output_43_transpose_x_0 = const()[name = tensor<string, []>("attn_output_43_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_43_transpose_y_0 = const()[name = tensor<string, []>("attn_output_43_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor<string, []>("attn_output_43_cast")];
tensor<int32, [4]> var_803 = const()[name = tensor<string, []>("op_803"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_45_cast = reshape(shape = var_803, x = attn_output_43_cast)[name = tensor<string, []>("attn_output_45_cast")];
tensor<int32, [4]> attn_output_47_perm_0 = const()[name = tensor<string, []>("attn_output_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_806 = const()[name = tensor<string, []>("op_806"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_121 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor<string, []>("transpose_121")];
tensor<fp16, [1, 77, 1280]> input_121_cast = reshape(shape = var_806, x = transpose_121)[name = tensor<string, []>("input_121_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(412028800)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415305664)))];
tensor<fp16, [1, 77, 1280]> hidden_states_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16, x = input_121_cast)[name = tensor<string, []>("hidden_states_45_cast")];
tensor<fp16, [1, 77, 1280]> input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor<string, []>("input_123_cast")];
tensor<int32, [1]> input_125_axes_0 = const()[name = tensor<string, []>("input_125_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415308288)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415310912)))];
tensor<fp16, [1, 77, 1280]> input_125_cast = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast)[name = tensor<string, []>("input_125_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(415313536)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(428420800)))];
tensor<fp16, [1, 77, 5120]> input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16, x = input_125_cast)[name = tensor<string, []>("input_127_cast")];
tensor<string, []> input_129_mode_0 = const()[name = tensor<string, []>("input_129_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_129_cast = gelu(mode = input_129_mode_0, x = input_127_cast)[name = tensor<string, []>("input_129_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(428431104)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441538368)))];
tensor<fp16, [1, 77, 1280]> hidden_states_47_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16, x = input_129_cast)[name = tensor<string, []>("hidden_states_47_cast")];
tensor<fp16, [1, 77, 1280]> input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor<string, []>("input_131_cast")];
tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = tensor<string, []>("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441540992)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441543616)))];
tensor<fp16, [1, 77, 1280]> hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast)[name = tensor<string, []>("hidden_states_49_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(441546240)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(444823104)))];
tensor<fp16, [1, 77, 1280]> var_844_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("op_844_cast")];
tensor<fp16, []> var_845_to_fp16 = const()[name = tensor<string, []>("op_845_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_53_cast = mul(x = var_844_cast, y = var_845_to_fp16)[name = tensor<string, []>("tensor_53_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(444825728)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(448102592)))];
tensor<fp16, [1, 77, 1280]> tensor_49_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_49_cast")];
tensor<int32, [4]> var_850 = const()[name = tensor<string, []>("op_850"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_851_cast = reshape(shape = var_850, x = tensor_49_cast)[name = tensor<string, []>("op_851_cast")];
tensor<int32, [4]> var_852_perm_0 = const()[name = tensor<string, []>("op_852_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(448105216)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451382080)))];
tensor<fp16, [1, 77, 1280]> tensor_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16, x = hidden_states_49_cast)[name = tensor<string, []>("tensor_51_cast")];
tensor<int32, [4]> var_857 = const()[name = tensor<string, []>("op_857"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_858_cast = reshape(shape = var_857, x = tensor_51_cast)[name = tensor<string, []>("op_858_cast")];
tensor<int32, [4]> var_859_perm_0 = const()[name = tensor<string, []>("op_859_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_866 = const()[name = tensor<string, []>("op_866"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_867_cast = reshape(shape = var_866, x = tensor_53_cast)[name = tensor<string, []>("op_867_cast")];
tensor<int32, [4]> var_868_perm_0 = const()[name = tensor<string, []>("op_868_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_870 = const()[name = tensor<string, []>("op_870"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_118 = transpose(perm = var_868_perm_0, x = var_867_cast)[name = tensor<string, []>("transpose_118")];
tensor<fp16, [20, 77, 64]> query_states_17_cast = reshape(shape = var_870, x = transpose_118)[name = tensor<string, []>("query_states_17_cast")];
tensor<int32, [3]> var_872 = const()[name = tensor<string, []>("op_872"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_120 = transpose(perm = var_852_perm_0, x = var_851_cast)[name = tensor<string, []>("transpose_120")];
tensor<fp16, [20, 77, 64]> key_states_35_cast = reshape(shape = var_872, x = transpose_120)[name = tensor<string, []>("key_states_35_cast")];
tensor<int32, [3]> var_874 = const()[name = tensor<string, []>("op_874"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_119 = transpose(perm = var_859_perm_0, x = var_858_cast)[name = tensor<string, []>("transpose_119")];
tensor<fp16, [20, 77, 64]> value_states_35_cast = reshape(shape = var_874, x = transpose_119)[name = tensor<string, []>("value_states_35_cast")];
tensor<int32, [3]> var_877_perm_0 = const()[name = tensor<string, []>("op_877_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_49_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_49_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_49_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_117 = transpose(perm = var_877_perm_0, x = key_states_35_cast)[name = tensor<string, []>("transpose_117")];
tensor<fp16, [20, 77, 77]> attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_117)[name = tensor<string, []>("attn_weights_49_cast")];
tensor<int32, [4]> var_879 = const()[name = tensor<string, []>("op_879"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_880_cast = reshape(shape = var_879, x = attn_weights_49_cast)[name = tensor<string, []>("op_880_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_51_cast = add(x = var_880_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_51_cast")];
tensor<int32, [3]> var_885 = const()[name = tensor<string, []>("op_885"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_133_cast = reshape(shape = var_885, x = attn_weights_51_cast)[name = tensor<string, []>("input_133_cast")];
tensor<fp16, [20, 77, 77]> input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor<string, []>("input_135_cast")];
tensor<bool, []> attn_output_49_transpose_x_0 = const()[name = tensor<string, []>("attn_output_49_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_49_transpose_y_0 = const()[name = tensor<string, []>("attn_output_49_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor<string, []>("attn_output_49_cast")];
tensor<int32, [4]> var_890 = const()[name = tensor<string, []>("op_890"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_51_cast = reshape(shape = var_890, x = attn_output_49_cast)[name = tensor<string, []>("attn_output_51_cast")];
tensor<int32, [4]> attn_output_53_perm_0 = const()[name = tensor<string, []>("attn_output_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_893 = const()[name = tensor<string, []>("op_893"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_116 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor<string, []>("transpose_116")];
tensor<fp16, [1, 77, 1280]> input_137_cast = reshape(shape = var_893, x = transpose_116)[name = tensor<string, []>("input_137_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(451384704)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454661568)))];
tensor<fp16, [1, 77, 1280]> hidden_states_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16, x = input_137_cast)[name = tensor<string, []>("hidden_states_51_cast")];
tensor<fp16, [1, 77, 1280]> input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor<string, []>("input_139_cast")];
tensor<int32, [1]> input_141_axes_0 = const()[name = tensor<string, []>("input_141_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454664192)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454666816)))];
tensor<fp16, [1, 77, 1280]> input_141_cast = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor<string, []>("input_141_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(454669440)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467776704)))];
tensor<fp16, [1, 77, 5120]> input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16, x = input_141_cast)[name = tensor<string, []>("input_143_cast")];
tensor<string, []> input_145_mode_0 = const()[name = tensor<string, []>("input_145_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_145_cast = gelu(mode = input_145_mode_0, x = input_143_cast)[name = tensor<string, []>("input_145_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467787008)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480894272)))];
tensor<fp16, [1, 77, 1280]> hidden_states_53_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16, x = input_145_cast)[name = tensor<string, []>("hidden_states_53_cast")];
tensor<fp16, [1, 77, 1280]> input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor<string, []>("input_147_cast")];
tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = tensor<string, []>("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480896896)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480899520)))];
tensor<fp16, [1, 77, 1280]> hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor<string, []>("hidden_states_55_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480902144)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(484179008)))];
tensor<fp16, [1, 77, 1280]> var_931_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("op_931_cast")];
tensor<fp16, []> var_932_to_fp16 = const()[name = tensor<string, []>("op_932_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_59_cast = mul(x = var_931_cast, y = var_932_to_fp16)[name = tensor<string, []>("tensor_59_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(484181632)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(487458496)))];
tensor<fp16, [1, 77, 1280]> tensor_55_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_55_cast")];
tensor<int32, [4]> var_937 = const()[name = tensor<string, []>("op_937"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_938_cast = reshape(shape = var_937, x = tensor_55_cast)[name = tensor<string, []>("op_938_cast")];
tensor<int32, [4]> var_939_perm_0 = const()[name = tensor<string, []>("op_939_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(487461120)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490737984)))];
tensor<fp16, [1, 77, 1280]> tensor_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16, x = hidden_states_55_cast)[name = tensor<string, []>("tensor_57_cast")];
tensor<int32, [4]> var_944 = const()[name = tensor<string, []>("op_944"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_945_cast = reshape(shape = var_944, x = tensor_57_cast)[name = tensor<string, []>("op_945_cast")];
tensor<int32, [4]> var_946_perm_0 = const()[name = tensor<string, []>("op_946_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_953 = const()[name = tensor<string, []>("op_953"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_954_cast = reshape(shape = var_953, x = tensor_59_cast)[name = tensor<string, []>("op_954_cast")];
tensor<int32, [4]> var_955_perm_0 = const()[name = tensor<string, []>("op_955_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_957 = const()[name = tensor<string, []>("op_957"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_113 = transpose(perm = var_955_perm_0, x = var_954_cast)[name = tensor<string, []>("transpose_113")];
tensor<fp16, [20, 77, 64]> query_states_19_cast = reshape(shape = var_957, x = transpose_113)[name = tensor<string, []>("query_states_19_cast")];
tensor<int32, [3]> var_959 = const()[name = tensor<string, []>("op_959"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_115 = transpose(perm = var_939_perm_0, x = var_938_cast)[name = tensor<string, []>("transpose_115")];
tensor<fp16, [20, 77, 64]> key_states_39_cast = reshape(shape = var_959, x = transpose_115)[name = tensor<string, []>("key_states_39_cast")];
tensor<int32, [3]> var_961 = const()[name = tensor<string, []>("op_961"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_114 = transpose(perm = var_946_perm_0, x = var_945_cast)[name = tensor<string, []>("transpose_114")];
tensor<fp16, [20, 77, 64]> value_states_39_cast = reshape(shape = var_961, x = transpose_114)[name = tensor<string, []>("value_states_39_cast")];
tensor<int32, [3]> var_964_perm_0 = const()[name = tensor<string, []>("op_964_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_55_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_55_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_55_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_112 = transpose(perm = var_964_perm_0, x = key_states_39_cast)[name = tensor<string, []>("transpose_112")];
tensor<fp16, [20, 77, 77]> attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_112)[name = tensor<string, []>("attn_weights_55_cast")];
tensor<int32, [4]> var_966 = const()[name = tensor<string, []>("op_966"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_967_cast = reshape(shape = var_966, x = attn_weights_55_cast)[name = tensor<string, []>("op_967_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_57_cast = add(x = var_967_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_57_cast")];
tensor<int32, [3]> var_972 = const()[name = tensor<string, []>("op_972"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_149_cast = reshape(shape = var_972, x = attn_weights_57_cast)[name = tensor<string, []>("input_149_cast")];
tensor<fp16, [20, 77, 77]> input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor<string, []>("input_151_cast")];
tensor<bool, []> attn_output_55_transpose_x_0 = const()[name = tensor<string, []>("attn_output_55_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_55_transpose_y_0 = const()[name = tensor<string, []>("attn_output_55_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor<string, []>("attn_output_55_cast")];
tensor<int32, [4]> var_977 = const()[name = tensor<string, []>("op_977"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_57_cast = reshape(shape = var_977, x = attn_output_55_cast)[name = tensor<string, []>("attn_output_57_cast")];
tensor<int32, [4]> attn_output_59_perm_0 = const()[name = tensor<string, []>("attn_output_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_980 = const()[name = tensor<string, []>("op_980"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_111 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor<string, []>("transpose_111")];
tensor<fp16, [1, 77, 1280]> input_153_cast = reshape(shape = var_980, x = transpose_111)[name = tensor<string, []>("input_153_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(490740608)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494017472)))];
tensor<fp16, [1, 77, 1280]> hidden_states_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16, x = input_153_cast)[name = tensor<string, []>("hidden_states_57_cast")];
tensor<fp16, [1, 77, 1280]> input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor<string, []>("input_155_cast")];
tensor<int32, [1]> input_157_axes_0 = const()[name = tensor<string, []>("input_157_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494020096)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494022720)))];
tensor<fp16, [1, 77, 1280]> input_157_cast = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast)[name = tensor<string, []>("input_157_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(494025344)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507132608)))];
tensor<fp16, [1, 77, 5120]> input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16, x = input_157_cast)[name = tensor<string, []>("input_159_cast")];
tensor<string, []> input_161_mode_0 = const()[name = tensor<string, []>("input_161_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_161_cast = gelu(mode = input_161_mode_0, x = input_159_cast)[name = tensor<string, []>("input_161_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507142912)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520250176)))];
tensor<fp16, [1, 77, 1280]> hidden_states_59_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16, x = input_161_cast)[name = tensor<string, []>("hidden_states_59_cast")];
tensor<fp16, [1, 77, 1280]> input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor<string, []>("input_163_cast")];
tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = tensor<string, []>("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520252800)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520255424)))];
tensor<fp16, [1, 77, 1280]> hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast)[name = tensor<string, []>("hidden_states_61_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520258048)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523534912)))];
tensor<fp16, [1, 77, 1280]> var_1018_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("op_1018_cast")];
tensor<fp16, []> var_1019_to_fp16 = const()[name = tensor<string, []>("op_1019_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_65_cast = mul(x = var_1018_cast, y = var_1019_to_fp16)[name = tensor<string, []>("tensor_65_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523537536)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526814400)))];
tensor<fp16, [1, 77, 1280]> tensor_61_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_61_cast")];
tensor<int32, [4]> var_1024 = const()[name = tensor<string, []>("op_1024"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1025_cast = reshape(shape = var_1024, x = tensor_61_cast)[name = tensor<string, []>("op_1025_cast")];
tensor<int32, [4]> var_1026_perm_0 = const()[name = tensor<string, []>("op_1026_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526817024)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530093888)))];
tensor<fp16, [1, 77, 1280]> tensor_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16, x = hidden_states_61_cast)[name = tensor<string, []>("tensor_63_cast")];
tensor<int32, [4]> var_1031 = const()[name = tensor<string, []>("op_1031"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1032_cast = reshape(shape = var_1031, x = tensor_63_cast)[name = tensor<string, []>("op_1032_cast")];
tensor<int32, [4]> var_1033_perm_0 = const()[name = tensor<string, []>("op_1033_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1040 = const()[name = tensor<string, []>("op_1040"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1041_cast = reshape(shape = var_1040, x = tensor_65_cast)[name = tensor<string, []>("op_1041_cast")];
tensor<int32, [4]> var_1042_perm_0 = const()[name = tensor<string, []>("op_1042_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1044 = const()[name = tensor<string, []>("op_1044"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_108 = transpose(perm = var_1042_perm_0, x = var_1041_cast)[name = tensor<string, []>("transpose_108")];
tensor<fp16, [20, 77, 64]> query_states_21_cast = reshape(shape = var_1044, x = transpose_108)[name = tensor<string, []>("query_states_21_cast")];
tensor<int32, [3]> var_1046 = const()[name = tensor<string, []>("op_1046"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_110 = transpose(perm = var_1026_perm_0, x = var_1025_cast)[name = tensor<string, []>("transpose_110")];
tensor<fp16, [20, 77, 64]> key_states_43_cast = reshape(shape = var_1046, x = transpose_110)[name = tensor<string, []>("key_states_43_cast")];
tensor<int32, [3]> var_1048 = const()[name = tensor<string, []>("op_1048"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_109 = transpose(perm = var_1033_perm_0, x = var_1032_cast)[name = tensor<string, []>("transpose_109")];
tensor<fp16, [20, 77, 64]> value_states_43_cast = reshape(shape = var_1048, x = transpose_109)[name = tensor<string, []>("value_states_43_cast")];
tensor<int32, [3]> var_1051_perm_0 = const()[name = tensor<string, []>("op_1051_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_61_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_61_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_61_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_107 = transpose(perm = var_1051_perm_0, x = key_states_43_cast)[name = tensor<string, []>("transpose_107")];
tensor<fp16, [20, 77, 77]> attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_107)[name = tensor<string, []>("attn_weights_61_cast")];
tensor<int32, [4]> var_1053 = const()[name = tensor<string, []>("op_1053"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1054_cast = reshape(shape = var_1053, x = attn_weights_61_cast)[name = tensor<string, []>("op_1054_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_63_cast = add(x = var_1054_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_63_cast")];
tensor<int32, [3]> var_1059 = const()[name = tensor<string, []>("op_1059"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_165_cast = reshape(shape = var_1059, x = attn_weights_63_cast)[name = tensor<string, []>("input_165_cast")];
tensor<fp16, [20, 77, 77]> input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor<string, []>("input_167_cast")];
tensor<bool, []> attn_output_61_transpose_x_0 = const()[name = tensor<string, []>("attn_output_61_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_61_transpose_y_0 = const()[name = tensor<string, []>("attn_output_61_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor<string, []>("attn_output_61_cast")];
tensor<int32, [4]> var_1064 = const()[name = tensor<string, []>("op_1064"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_63_cast = reshape(shape = var_1064, x = attn_output_61_cast)[name = tensor<string, []>("attn_output_63_cast")];
tensor<int32, [4]> attn_output_65_perm_0 = const()[name = tensor<string, []>("attn_output_65_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1067 = const()[name = tensor<string, []>("op_1067"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_106 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor<string, []>("transpose_106")];
tensor<fp16, [1, 77, 1280]> input_169_cast = reshape(shape = var_1067, x = transpose_106)[name = tensor<string, []>("input_169_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(530096512)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533373376)))];
tensor<fp16, [1, 77, 1280]> hidden_states_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16, x = input_169_cast)[name = tensor<string, []>("hidden_states_63_cast")];
tensor<fp16, [1, 77, 1280]> input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor<string, []>("input_171_cast")];
tensor<int32, [1]> input_173_axes_0 = const()[name = tensor<string, []>("input_173_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533376000)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533378624)))];
tensor<fp16, [1, 77, 1280]> input_173_cast = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast)[name = tensor<string, []>("input_173_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(533381248)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(546488512)))];
tensor<fp16, [1, 77, 5120]> input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16, x = input_173_cast)[name = tensor<string, []>("input_175_cast")];
tensor<string, []> input_177_mode_0 = const()[name = tensor<string, []>("input_177_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_177_cast = gelu(mode = input_177_mode_0, x = input_175_cast)[name = tensor<string, []>("input_177_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(546498816)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559606080)))];
tensor<fp16, [1, 77, 1280]> hidden_states_65_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16, x = input_177_cast)[name = tensor<string, []>("hidden_states_65_cast")];
tensor<fp16, [1, 77, 1280]> input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor<string, []>("input_179_cast")];
tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = tensor<string, []>("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559608704)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559611328)))];
tensor<fp16, [1, 77, 1280]> hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast)[name = tensor<string, []>("hidden_states_67_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(559613952)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(562890816)))];
tensor<fp16, [1, 77, 1280]> var_1105_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("op_1105_cast")];
tensor<fp16, []> var_1106_to_fp16 = const()[name = tensor<string, []>("op_1106_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_71_cast = mul(x = var_1105_cast, y = var_1106_to_fp16)[name = tensor<string, []>("tensor_71_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(562893440)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(566170304)))];
tensor<fp16, [1, 77, 1280]> tensor_67_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_67_cast")];
tensor<int32, [4]> var_1111 = const()[name = tensor<string, []>("op_1111"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1112_cast = reshape(shape = var_1111, x = tensor_67_cast)[name = tensor<string, []>("op_1112_cast")];
tensor<int32, [4]> var_1113_perm_0 = const()[name = tensor<string, []>("op_1113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(566172928)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569449792)))];
tensor<fp16, [1, 77, 1280]> tensor_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16, x = hidden_states_67_cast)[name = tensor<string, []>("tensor_69_cast")];
tensor<int32, [4]> var_1118 = const()[name = tensor<string, []>("op_1118"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1119_cast = reshape(shape = var_1118, x = tensor_69_cast)[name = tensor<string, []>("op_1119_cast")];
tensor<int32, [4]> var_1120_perm_0 = const()[name = tensor<string, []>("op_1120_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1127 = const()[name = tensor<string, []>("op_1127"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1128_cast = reshape(shape = var_1127, x = tensor_71_cast)[name = tensor<string, []>("op_1128_cast")];
tensor<int32, [4]> var_1129_perm_0 = const()[name = tensor<string, []>("op_1129_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1131 = const()[name = tensor<string, []>("op_1131"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_103 = transpose(perm = var_1129_perm_0, x = var_1128_cast)[name = tensor<string, []>("transpose_103")];
tensor<fp16, [20, 77, 64]> query_states_23_cast = reshape(shape = var_1131, x = transpose_103)[name = tensor<string, []>("query_states_23_cast")];
tensor<int32, [3]> var_1133 = const()[name = tensor<string, []>("op_1133"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_105 = transpose(perm = var_1113_perm_0, x = var_1112_cast)[name = tensor<string, []>("transpose_105")];
tensor<fp16, [20, 77, 64]> key_states_47_cast = reshape(shape = var_1133, x = transpose_105)[name = tensor<string, []>("key_states_47_cast")];
tensor<int32, [3]> var_1135 = const()[name = tensor<string, []>("op_1135"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_104 = transpose(perm = var_1120_perm_0, x = var_1119_cast)[name = tensor<string, []>("transpose_104")];
tensor<fp16, [20, 77, 64]> value_states_47_cast = reshape(shape = var_1135, x = transpose_104)[name = tensor<string, []>("value_states_47_cast")];
tensor<int32, [3]> var_1138_perm_0 = const()[name = tensor<string, []>("op_1138_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_67_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_67_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_67_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_102 = transpose(perm = var_1138_perm_0, x = key_states_47_cast)[name = tensor<string, []>("transpose_102")];
tensor<fp16, [20, 77, 77]> attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_23_cast, y = transpose_102)[name = tensor<string, []>("attn_weights_67_cast")];
tensor<int32, [4]> var_1140 = const()[name = tensor<string, []>("op_1140"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1141_cast = reshape(shape = var_1140, x = attn_weights_67_cast)[name = tensor<string, []>("op_1141_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_69_cast = add(x = var_1141_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_69_cast")];
tensor<int32, [3]> var_1146 = const()[name = tensor<string, []>("op_1146"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_181_cast = reshape(shape = var_1146, x = attn_weights_69_cast)[name = tensor<string, []>("input_181_cast")];
tensor<fp16, [20, 77, 77]> input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor<string, []>("input_183_cast")];
tensor<bool, []> attn_output_67_transpose_x_0 = const()[name = tensor<string, []>("attn_output_67_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_67_transpose_y_0 = const()[name = tensor<string, []>("attn_output_67_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_47_cast)[name = tensor<string, []>("attn_output_67_cast")];
tensor<int32, [4]> var_1151 = const()[name = tensor<string, []>("op_1151"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_69_cast = reshape(shape = var_1151, x = attn_output_67_cast)[name = tensor<string, []>("attn_output_69_cast")];
tensor<int32, [4]> attn_output_71_perm_0 = const()[name = tensor<string, []>("attn_output_71_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1154 = const()[name = tensor<string, []>("op_1154"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_101 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor<string, []>("transpose_101")];
tensor<fp16, [1, 77, 1280]> input_185_cast = reshape(shape = var_1154, x = transpose_101)[name = tensor<string, []>("input_185_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569452416)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572729280)))];
tensor<fp16, [1, 77, 1280]> hidden_states_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16, x = input_185_cast)[name = tensor<string, []>("hidden_states_69_cast")];
tensor<fp16, [1, 77, 1280]> input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor<string, []>("input_187_cast")];
tensor<int32, [1]> input_189_axes_0 = const()[name = tensor<string, []>("input_189_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572731904)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572734528)))];
tensor<fp16, [1, 77, 1280]> input_189_cast = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast)[name = tensor<string, []>("input_189_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572737152)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(585844416)))];
tensor<fp16, [1, 77, 5120]> input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16, x = input_189_cast)[name = tensor<string, []>("input_191_cast")];
tensor<string, []> input_193_mode_0 = const()[name = tensor<string, []>("input_193_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_193_cast = gelu(mode = input_193_mode_0, x = input_191_cast)[name = tensor<string, []>("input_193_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(585854720)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598961984)))];
tensor<fp16, [1, 77, 1280]> hidden_states_71_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16, x = input_193_cast)[name = tensor<string, []>("hidden_states_71_cast")];
tensor<fp16, [1, 77, 1280]> input_195_cast = add(x = input_187_cast, y = hidden_states_71_cast)[name = tensor<string, []>("input_195_cast")];
tensor<int32, [1]> hidden_states_73_axes_0 = const()[name = tensor<string, []>("hidden_states_73_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598964608)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598967232)))];
tensor<fp16, [1, 77, 1280]> hidden_states_73_cast = layer_norm(axes = hidden_states_73_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_195_cast)[name = tensor<string, []>("hidden_states_73_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(598969856)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(602246720)))];
tensor<fp16, [1, 77, 1280]> var_1192_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("op_1192_cast")];
tensor<fp16, []> var_1193_to_fp16 = const()[name = tensor<string, []>("op_1193_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_77_cast = mul(x = var_1192_cast, y = var_1193_to_fp16)[name = tensor<string, []>("tensor_77_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(602249344)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(605526208)))];
tensor<fp16, [1, 77, 1280]> tensor_73_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_73_cast")];
tensor<int32, [4]> var_1198 = const()[name = tensor<string, []>("op_1198"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1199_cast = reshape(shape = var_1198, x = tensor_73_cast)[name = tensor<string, []>("op_1199_cast")];
tensor<int32, [4]> var_1200_perm_0 = const()[name = tensor<string, []>("op_1200_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(605528832)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608805696)))];
tensor<fp16, [1, 77, 1280]> tensor_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16, x = hidden_states_73_cast)[name = tensor<string, []>("tensor_75_cast")];
tensor<int32, [4]> var_1205 = const()[name = tensor<string, []>("op_1205"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1206_cast = reshape(shape = var_1205, x = tensor_75_cast)[name = tensor<string, []>("op_1206_cast")];
tensor<int32, [4]> var_1207_perm_0 = const()[name = tensor<string, []>("op_1207_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1214 = const()[name = tensor<string, []>("op_1214"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1215_cast = reshape(shape = var_1214, x = tensor_77_cast)[name = tensor<string, []>("op_1215_cast")];
tensor<int32, [4]> var_1216_perm_0 = const()[name = tensor<string, []>("op_1216_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1218 = const()[name = tensor<string, []>("op_1218"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_98 = transpose(perm = var_1216_perm_0, x = var_1215_cast)[name = tensor<string, []>("transpose_98")];
tensor<fp16, [20, 77, 64]> query_states_25_cast = reshape(shape = var_1218, x = transpose_98)[name = tensor<string, []>("query_states_25_cast")];
tensor<int32, [3]> var_1220 = const()[name = tensor<string, []>("op_1220"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_100 = transpose(perm = var_1200_perm_0, x = var_1199_cast)[name = tensor<string, []>("transpose_100")];
tensor<fp16, [20, 77, 64]> key_states_51_cast = reshape(shape = var_1220, x = transpose_100)[name = tensor<string, []>("key_states_51_cast")];
tensor<int32, [3]> var_1222 = const()[name = tensor<string, []>("op_1222"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_99 = transpose(perm = var_1207_perm_0, x = var_1206_cast)[name = tensor<string, []>("transpose_99")];
tensor<fp16, [20, 77, 64]> value_states_51_cast = reshape(shape = var_1222, x = transpose_99)[name = tensor<string, []>("value_states_51_cast")];
tensor<int32, [3]> var_1225_perm_0 = const()[name = tensor<string, []>("op_1225_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_73_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_73_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_73_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_97 = transpose(perm = var_1225_perm_0, x = key_states_51_cast)[name = tensor<string, []>("transpose_97")];
tensor<fp16, [20, 77, 77]> attn_weights_73_cast = matmul(transpose_x = attn_weights_73_transpose_x_0, transpose_y = attn_weights_73_transpose_y_0, x = query_states_25_cast, y = transpose_97)[name = tensor<string, []>("attn_weights_73_cast")];
tensor<int32, [4]> var_1227 = const()[name = tensor<string, []>("op_1227"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1228_cast = reshape(shape = var_1227, x = attn_weights_73_cast)[name = tensor<string, []>("op_1228_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_75_cast = add(x = var_1228_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_75_cast")];
tensor<int32, [3]> var_1233 = const()[name = tensor<string, []>("op_1233"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_197_cast = reshape(shape = var_1233, x = attn_weights_75_cast)[name = tensor<string, []>("input_197_cast")];
tensor<fp16, [20, 77, 77]> input_199_cast = softmax(axis = var_5, x = input_197_cast)[name = tensor<string, []>("input_199_cast")];
tensor<bool, []> attn_output_73_transpose_x_0 = const()[name = tensor<string, []>("attn_output_73_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_73_transpose_y_0 = const()[name = tensor<string, []>("attn_output_73_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_73_cast = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast, y = value_states_51_cast)[name = tensor<string, []>("attn_output_73_cast")];
tensor<int32, [4]> var_1238 = const()[name = tensor<string, []>("op_1238"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_75_cast = reshape(shape = var_1238, x = attn_output_73_cast)[name = tensor<string, []>("attn_output_75_cast")];
tensor<int32, [4]> attn_output_77_perm_0 = const()[name = tensor<string, []>("attn_output_77_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1241 = const()[name = tensor<string, []>("op_1241"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_96 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor<string, []>("transpose_96")];
tensor<fp16, [1, 77, 1280]> input_201_cast = reshape(shape = var_1241, x = transpose_96)[name = tensor<string, []>("input_201_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(608808320)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612085184)))];
tensor<fp16, [1, 77, 1280]> hidden_states_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16, x = input_201_cast)[name = tensor<string, []>("hidden_states_75_cast")];
tensor<fp16, [1, 77, 1280]> input_203_cast = add(x = input_195_cast, y = hidden_states_75_cast)[name = tensor<string, []>("input_203_cast")];
tensor<int32, [1]> input_205_axes_0 = const()[name = tensor<string, []>("input_205_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612087808)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612090432)))];
tensor<fp16, [1, 77, 1280]> input_205_cast = layer_norm(axes = input_205_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_203_cast)[name = tensor<string, []>("input_205_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(612093056)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(625200320)))];
tensor<fp16, [1, 77, 5120]> input_207_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16, x = input_205_cast)[name = tensor<string, []>("input_207_cast")];
tensor<string, []> input_209_mode_0 = const()[name = tensor<string, []>("input_209_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_209_cast = gelu(mode = input_209_mode_0, x = input_207_cast)[name = tensor<string, []>("input_209_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(625210624)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638317888)))];
tensor<fp16, [1, 77, 1280]> hidden_states_77_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16, x = input_209_cast)[name = tensor<string, []>("hidden_states_77_cast")];
tensor<fp16, [1, 77, 1280]> input_211_cast = add(x = input_203_cast, y = hidden_states_77_cast)[name = tensor<string, []>("input_211_cast")];
tensor<int32, [1]> hidden_states_79_axes_0 = const()[name = tensor<string, []>("hidden_states_79_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638320512)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638323136)))];
tensor<fp16, [1, 77, 1280]> hidden_states_79_cast = layer_norm(axes = hidden_states_79_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_211_cast)[name = tensor<string, []>("hidden_states_79_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638325760)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641602624)))];
tensor<fp16, [1, 77, 1280]> var_1279_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("op_1279_cast")];
tensor<fp16, []> var_1280_to_fp16 = const()[name = tensor<string, []>("op_1280_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_83_cast = mul(x = var_1279_cast, y = var_1280_to_fp16)[name = tensor<string, []>("tensor_83_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641605248)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644882112)))];
tensor<fp16, [1, 77, 1280]> tensor_79_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_79_cast")];
tensor<int32, [4]> var_1285 = const()[name = tensor<string, []>("op_1285"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1286_cast = reshape(shape = var_1285, x = tensor_79_cast)[name = tensor<string, []>("op_1286_cast")];
tensor<int32, [4]> var_1287_perm_0 = const()[name = tensor<string, []>("op_1287_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644884736)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648161600)))];
tensor<fp16, [1, 77, 1280]> tensor_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16, x = hidden_states_79_cast)[name = tensor<string, []>("tensor_81_cast")];
tensor<int32, [4]> var_1292 = const()[name = tensor<string, []>("op_1292"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1293_cast = reshape(shape = var_1292, x = tensor_81_cast)[name = tensor<string, []>("op_1293_cast")];
tensor<int32, [4]> var_1294_perm_0 = const()[name = tensor<string, []>("op_1294_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1301 = const()[name = tensor<string, []>("op_1301"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1302_cast = reshape(shape = var_1301, x = tensor_83_cast)[name = tensor<string, []>("op_1302_cast")];
tensor<int32, [4]> var_1303_perm_0 = const()[name = tensor<string, []>("op_1303_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1305 = const()[name = tensor<string, []>("op_1305"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_93 = transpose(perm = var_1303_perm_0, x = var_1302_cast)[name = tensor<string, []>("transpose_93")];
tensor<fp16, [20, 77, 64]> query_states_27_cast = reshape(shape = var_1305, x = transpose_93)[name = tensor<string, []>("query_states_27_cast")];
tensor<int32, [3]> var_1307 = const()[name = tensor<string, []>("op_1307"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_95 = transpose(perm = var_1287_perm_0, x = var_1286_cast)[name = tensor<string, []>("transpose_95")];
tensor<fp16, [20, 77, 64]> key_states_55_cast = reshape(shape = var_1307, x = transpose_95)[name = tensor<string, []>("key_states_55_cast")];
tensor<int32, [3]> var_1309 = const()[name = tensor<string, []>("op_1309"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_94 = transpose(perm = var_1294_perm_0, x = var_1293_cast)[name = tensor<string, []>("transpose_94")];
tensor<fp16, [20, 77, 64]> value_states_55_cast = reshape(shape = var_1309, x = transpose_94)[name = tensor<string, []>("value_states_55_cast")];
tensor<int32, [3]> var_1312_perm_0 = const()[name = tensor<string, []>("op_1312_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_79_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_79_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_79_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_92 = transpose(perm = var_1312_perm_0, x = key_states_55_cast)[name = tensor<string, []>("transpose_92")];
tensor<fp16, [20, 77, 77]> attn_weights_79_cast = matmul(transpose_x = attn_weights_79_transpose_x_0, transpose_y = attn_weights_79_transpose_y_0, x = query_states_27_cast, y = transpose_92)[name = tensor<string, []>("attn_weights_79_cast")];
tensor<int32, [4]> var_1314 = const()[name = tensor<string, []>("op_1314"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1315_cast = reshape(shape = var_1314, x = attn_weights_79_cast)[name = tensor<string, []>("op_1315_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_81_cast = add(x = var_1315_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_81_cast")];
tensor<int32, [3]> var_1320 = const()[name = tensor<string, []>("op_1320"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_213_cast = reshape(shape = var_1320, x = attn_weights_81_cast)[name = tensor<string, []>("input_213_cast")];
tensor<fp16, [20, 77, 77]> input_215_cast = softmax(axis = var_5, x = input_213_cast)[name = tensor<string, []>("input_215_cast")];
tensor<bool, []> attn_output_79_transpose_x_0 = const()[name = tensor<string, []>("attn_output_79_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_79_transpose_y_0 = const()[name = tensor<string, []>("attn_output_79_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_79_cast = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast, y = value_states_55_cast)[name = tensor<string, []>("attn_output_79_cast")];
tensor<int32, [4]> var_1325 = const()[name = tensor<string, []>("op_1325"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_81_cast = reshape(shape = var_1325, x = attn_output_79_cast)[name = tensor<string, []>("attn_output_81_cast")];
tensor<int32, [4]> attn_output_83_perm_0 = const()[name = tensor<string, []>("attn_output_83_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1328 = const()[name = tensor<string, []>("op_1328"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_91 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor<string, []>("transpose_91")];
tensor<fp16, [1, 77, 1280]> input_217_cast = reshape(shape = var_1328, x = transpose_91)[name = tensor<string, []>("input_217_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(648164224)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651441088)))];
tensor<fp16, [1, 77, 1280]> hidden_states_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16, x = input_217_cast)[name = tensor<string, []>("hidden_states_81_cast")];
tensor<fp16, [1, 77, 1280]> input_219_cast = add(x = input_211_cast, y = hidden_states_81_cast)[name = tensor<string, []>("input_219_cast")];
tensor<int32, [1]> input_221_axes_0 = const()[name = tensor<string, []>("input_221_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651443712)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651446336)))];
tensor<fp16, [1, 77, 1280]> input_221_cast = layer_norm(axes = input_221_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_219_cast)[name = tensor<string, []>("input_221_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(651448960)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664556224)))];
tensor<fp16, [1, 77, 5120]> input_223_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16, x = input_221_cast)[name = tensor<string, []>("input_223_cast")];
tensor<string, []> input_225_mode_0 = const()[name = tensor<string, []>("input_225_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_225_cast = gelu(mode = input_225_mode_0, x = input_223_cast)[name = tensor<string, []>("input_225_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(664566528)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677673792)))];
tensor<fp16, [1, 77, 1280]> hidden_states_83_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16, x = input_225_cast)[name = tensor<string, []>("hidden_states_83_cast")];
tensor<fp16, [1, 77, 1280]> input_227_cast = add(x = input_219_cast, y = hidden_states_83_cast)[name = tensor<string, []>("input_227_cast")];
tensor<int32, [1]> hidden_states_85_axes_0 = const()[name = tensor<string, []>("hidden_states_85_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677676416)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677679040)))];
tensor<fp16, [1, 77, 1280]> hidden_states_85_cast = layer_norm(axes = hidden_states_85_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_227_cast)[name = tensor<string, []>("hidden_states_85_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(677681664)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680958528)))];
tensor<fp16, [1, 77, 1280]> var_1366_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("op_1366_cast")];
tensor<fp16, []> var_1367_to_fp16 = const()[name = tensor<string, []>("op_1367_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_89_cast = mul(x = var_1366_cast, y = var_1367_to_fp16)[name = tensor<string, []>("tensor_89_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(680961152)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684238016)))];
tensor<fp16, [1, 77, 1280]> tensor_85_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_85_cast")];
tensor<int32, [4]> var_1372 = const()[name = tensor<string, []>("op_1372"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1373_cast = reshape(shape = var_1372, x = tensor_85_cast)[name = tensor<string, []>("op_1373_cast")];
tensor<int32, [4]> var_1374_perm_0 = const()[name = tensor<string, []>("op_1374_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(684240640)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687517504)))];
tensor<fp16, [1, 77, 1280]> tensor_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16, x = hidden_states_85_cast)[name = tensor<string, []>("tensor_87_cast")];
tensor<int32, [4]> var_1379 = const()[name = tensor<string, []>("op_1379"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1380_cast = reshape(shape = var_1379, x = tensor_87_cast)[name = tensor<string, []>("op_1380_cast")];
tensor<int32, [4]> var_1381_perm_0 = const()[name = tensor<string, []>("op_1381_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1388 = const()[name = tensor<string, []>("op_1388"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1389_cast = reshape(shape = var_1388, x = tensor_89_cast)[name = tensor<string, []>("op_1389_cast")];
tensor<int32, [4]> var_1390_perm_0 = const()[name = tensor<string, []>("op_1390_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1392 = const()[name = tensor<string, []>("op_1392"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_88 = transpose(perm = var_1390_perm_0, x = var_1389_cast)[name = tensor<string, []>("transpose_88")];
tensor<fp16, [20, 77, 64]> query_states_29_cast = reshape(shape = var_1392, x = transpose_88)[name = tensor<string, []>("query_states_29_cast")];
tensor<int32, [3]> var_1394 = const()[name = tensor<string, []>("op_1394"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_90 = transpose(perm = var_1374_perm_0, x = var_1373_cast)[name = tensor<string, []>("transpose_90")];
tensor<fp16, [20, 77, 64]> key_states_59_cast = reshape(shape = var_1394, x = transpose_90)[name = tensor<string, []>("key_states_59_cast")];
tensor<int32, [3]> var_1396 = const()[name = tensor<string, []>("op_1396"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_89 = transpose(perm = var_1381_perm_0, x = var_1380_cast)[name = tensor<string, []>("transpose_89")];
tensor<fp16, [20, 77, 64]> value_states_59_cast = reshape(shape = var_1396, x = transpose_89)[name = tensor<string, []>("value_states_59_cast")];
tensor<int32, [3]> var_1399_perm_0 = const()[name = tensor<string, []>("op_1399_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_85_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_85_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_85_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_87 = transpose(perm = var_1399_perm_0, x = key_states_59_cast)[name = tensor<string, []>("transpose_87")];
tensor<fp16, [20, 77, 77]> attn_weights_85_cast = matmul(transpose_x = attn_weights_85_transpose_x_0, transpose_y = attn_weights_85_transpose_y_0, x = query_states_29_cast, y = transpose_87)[name = tensor<string, []>("attn_weights_85_cast")];
tensor<int32, [4]> var_1401 = const()[name = tensor<string, []>("op_1401"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1402_cast = reshape(shape = var_1401, x = attn_weights_85_cast)[name = tensor<string, []>("op_1402_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_87_cast = add(x = var_1402_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_87_cast")];
tensor<int32, [3]> var_1407 = const()[name = tensor<string, []>("op_1407"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_229_cast = reshape(shape = var_1407, x = attn_weights_87_cast)[name = tensor<string, []>("input_229_cast")];
tensor<fp16, [20, 77, 77]> input_231_cast = softmax(axis = var_5, x = input_229_cast)[name = tensor<string, []>("input_231_cast")];
tensor<bool, []> attn_output_85_transpose_x_0 = const()[name = tensor<string, []>("attn_output_85_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_85_transpose_y_0 = const()[name = tensor<string, []>("attn_output_85_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_85_cast = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast, y = value_states_59_cast)[name = tensor<string, []>("attn_output_85_cast")];
tensor<int32, [4]> var_1412 = const()[name = tensor<string, []>("op_1412"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_87_cast = reshape(shape = var_1412, x = attn_output_85_cast)[name = tensor<string, []>("attn_output_87_cast")];
tensor<int32, [4]> attn_output_89_perm_0 = const()[name = tensor<string, []>("attn_output_89_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1415 = const()[name = tensor<string, []>("op_1415"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_86 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor<string, []>("transpose_86")];
tensor<fp16, [1, 77, 1280]> input_233_cast = reshape(shape = var_1415, x = transpose_86)[name = tensor<string, []>("input_233_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687520128)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690796992)))];
tensor<fp16, [1, 77, 1280]> hidden_states_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16, x = input_233_cast)[name = tensor<string, []>("hidden_states_87_cast")];
tensor<fp16, [1, 77, 1280]> input_235_cast = add(x = input_227_cast, y = hidden_states_87_cast)[name = tensor<string, []>("input_235_cast")];
tensor<int32, [1]> input_237_axes_0 = const()[name = tensor<string, []>("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690799616)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690802240)))];
tensor<fp16, [1, 77, 1280]> input_237_cast = layer_norm(axes = input_237_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_235_cast)[name = tensor<string, []>("input_237_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(690804864)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(703912128)))];
tensor<fp16, [1, 77, 5120]> input_239_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16, x = input_237_cast)[name = tensor<string, []>("input_239_cast")];
tensor<string, []> input_241_mode_0 = const()[name = tensor<string, []>("input_241_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_241_cast = gelu(mode = input_241_mode_0, x = input_239_cast)[name = tensor<string, []>("input_241_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(703922432)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717029696)))];
tensor<fp16, [1, 77, 1280]> hidden_states_89_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16, x = input_241_cast)[name = tensor<string, []>("hidden_states_89_cast")];
tensor<fp16, [1, 77, 1280]> input_243_cast = add(x = input_235_cast, y = hidden_states_89_cast)[name = tensor<string, []>("input_243_cast")];
tensor<int32, [1]> hidden_states_91_axes_0 = const()[name = tensor<string, []>("hidden_states_91_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717032320)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717034944)))];
tensor<fp16, [1, 77, 1280]> hidden_states_91_cast = layer_norm(axes = hidden_states_91_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_243_cast)[name = tensor<string, []>("hidden_states_91_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(717037568)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(720314432)))];
tensor<fp16, [1, 77, 1280]> var_1453_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("op_1453_cast")];
tensor<fp16, []> var_1454_to_fp16 = const()[name = tensor<string, []>("op_1454_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_95_cast = mul(x = var_1453_cast, y = var_1454_to_fp16)[name = tensor<string, []>("tensor_95_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(720317056)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(723593920)))];
tensor<fp16, [1, 77, 1280]> tensor_91_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_91_cast")];
tensor<int32, [4]> var_1459 = const()[name = tensor<string, []>("op_1459"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1460_cast = reshape(shape = var_1459, x = tensor_91_cast)[name = tensor<string, []>("op_1460_cast")];
tensor<int32, [4]> var_1461_perm_0 = const()[name = tensor<string, []>("op_1461_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(723596544)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726873408)))];
tensor<fp16, [1, 77, 1280]> tensor_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16, x = hidden_states_91_cast)[name = tensor<string, []>("tensor_93_cast")];
tensor<int32, [4]> var_1466 = const()[name = tensor<string, []>("op_1466"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1467_cast = reshape(shape = var_1466, x = tensor_93_cast)[name = tensor<string, []>("op_1467_cast")];
tensor<int32, [4]> var_1468_perm_0 = const()[name = tensor<string, []>("op_1468_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1475 = const()[name = tensor<string, []>("op_1475"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1476_cast = reshape(shape = var_1475, x = tensor_95_cast)[name = tensor<string, []>("op_1476_cast")];
tensor<int32, [4]> var_1477_perm_0 = const()[name = tensor<string, []>("op_1477_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1479 = const()[name = tensor<string, []>("op_1479"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_83 = transpose(perm = var_1477_perm_0, x = var_1476_cast)[name = tensor<string, []>("transpose_83")];
tensor<fp16, [20, 77, 64]> query_states_31_cast = reshape(shape = var_1479, x = transpose_83)[name = tensor<string, []>("query_states_31_cast")];
tensor<int32, [3]> var_1481 = const()[name = tensor<string, []>("op_1481"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_85 = transpose(perm = var_1461_perm_0, x = var_1460_cast)[name = tensor<string, []>("transpose_85")];
tensor<fp16, [20, 77, 64]> key_states_63_cast = reshape(shape = var_1481, x = transpose_85)[name = tensor<string, []>("key_states_63_cast")];
tensor<int32, [3]> var_1483 = const()[name = tensor<string, []>("op_1483"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_84 = transpose(perm = var_1468_perm_0, x = var_1467_cast)[name = tensor<string, []>("transpose_84")];
tensor<fp16, [20, 77, 64]> value_states_63_cast = reshape(shape = var_1483, x = transpose_84)[name = tensor<string, []>("value_states_63_cast")];
tensor<int32, [3]> var_1486_perm_0 = const()[name = tensor<string, []>("op_1486_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_91_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_91_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_91_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_82 = transpose(perm = var_1486_perm_0, x = key_states_63_cast)[name = tensor<string, []>("transpose_82")];
tensor<fp16, [20, 77, 77]> attn_weights_91_cast = matmul(transpose_x = attn_weights_91_transpose_x_0, transpose_y = attn_weights_91_transpose_y_0, x = query_states_31_cast, y = transpose_82)[name = tensor<string, []>("attn_weights_91_cast")];
tensor<int32, [4]> var_1488 = const()[name = tensor<string, []>("op_1488"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1489_cast = reshape(shape = var_1488, x = attn_weights_91_cast)[name = tensor<string, []>("op_1489_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_93_cast = add(x = var_1489_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_93_cast")];
tensor<int32, [3]> var_1494 = const()[name = tensor<string, []>("op_1494"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_245_cast = reshape(shape = var_1494, x = attn_weights_93_cast)[name = tensor<string, []>("input_245_cast")];
tensor<fp16, [20, 77, 77]> input_247_cast = softmax(axis = var_5, x = input_245_cast)[name = tensor<string, []>("input_247_cast")];
tensor<bool, []> attn_output_91_transpose_x_0 = const()[name = tensor<string, []>("attn_output_91_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_91_transpose_y_0 = const()[name = tensor<string, []>("attn_output_91_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_91_cast = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast, y = value_states_63_cast)[name = tensor<string, []>("attn_output_91_cast")];
tensor<int32, [4]> var_1499 = const()[name = tensor<string, []>("op_1499"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_93_cast = reshape(shape = var_1499, x = attn_output_91_cast)[name = tensor<string, []>("attn_output_93_cast")];
tensor<int32, [4]> attn_output_95_perm_0 = const()[name = tensor<string, []>("attn_output_95_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1502 = const()[name = tensor<string, []>("op_1502"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_81 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor<string, []>("transpose_81")];
tensor<fp16, [1, 77, 1280]> input_249_cast = reshape(shape = var_1502, x = transpose_81)[name = tensor<string, []>("input_249_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726876032)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730152896)))];
tensor<fp16, [1, 77, 1280]> hidden_states_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16, x = input_249_cast)[name = tensor<string, []>("hidden_states_93_cast")];
tensor<fp16, [1, 77, 1280]> input_251_cast = add(x = input_243_cast, y = hidden_states_93_cast)[name = tensor<string, []>("input_251_cast")];
tensor<int32, [1]> input_253_axes_0 = const()[name = tensor<string, []>("input_253_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730155520)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730158144)))];
tensor<fp16, [1, 77, 1280]> input_253_cast = layer_norm(axes = input_253_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_251_cast)[name = tensor<string, []>("input_253_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(730160768)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(743268032)))];
tensor<fp16, [1, 77, 5120]> input_255_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16, x = input_253_cast)[name = tensor<string, []>("input_255_cast")];
tensor<string, []> input_257_mode_0 = const()[name = tensor<string, []>("input_257_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_257_cast = gelu(mode = input_257_mode_0, x = input_255_cast)[name = tensor<string, []>("input_257_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(743278336)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756385600)))];
tensor<fp16, [1, 77, 1280]> hidden_states_95_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16, x = input_257_cast)[name = tensor<string, []>("hidden_states_95_cast")];
tensor<fp16, [1, 77, 1280]> input_259_cast = add(x = input_251_cast, y = hidden_states_95_cast)[name = tensor<string, []>("input_259_cast")];
tensor<int32, [1]> hidden_states_97_axes_0 = const()[name = tensor<string, []>("hidden_states_97_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756388224)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756390848)))];
tensor<fp16, [1, 77, 1280]> hidden_states_97_cast = layer_norm(axes = hidden_states_97_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_259_cast)[name = tensor<string, []>("hidden_states_97_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(756393472)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(759670336)))];
tensor<fp16, [1, 77, 1280]> var_1540_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("op_1540_cast")];
tensor<fp16, []> var_1541_to_fp16 = const()[name = tensor<string, []>("op_1541_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_101_cast = mul(x = var_1540_cast, y = var_1541_to_fp16)[name = tensor<string, []>("tensor_101_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(759672960)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(762949824)))];
tensor<fp16, [1, 77, 1280]> tensor_97_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_97_cast")];
tensor<int32, [4]> var_1546 = const()[name = tensor<string, []>("op_1546"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1547_cast = reshape(shape = var_1546, x = tensor_97_cast)[name = tensor<string, []>("op_1547_cast")];
tensor<int32, [4]> var_1548_perm_0 = const()[name = tensor<string, []>("op_1548_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(762952448)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766229312)))];
tensor<fp16, [1, 77, 1280]> tensor_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16, x = hidden_states_97_cast)[name = tensor<string, []>("tensor_99_cast")];
tensor<int32, [4]> var_1553 = const()[name = tensor<string, []>("op_1553"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1554_cast = reshape(shape = var_1553, x = tensor_99_cast)[name = tensor<string, []>("op_1554_cast")];
tensor<int32, [4]> var_1555_perm_0 = const()[name = tensor<string, []>("op_1555_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1562 = const()[name = tensor<string, []>("op_1562"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1563_cast = reshape(shape = var_1562, x = tensor_101_cast)[name = tensor<string, []>("op_1563_cast")];
tensor<int32, [4]> var_1564_perm_0 = const()[name = tensor<string, []>("op_1564_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1566 = const()[name = tensor<string, []>("op_1566"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_78 = transpose(perm = var_1564_perm_0, x = var_1563_cast)[name = tensor<string, []>("transpose_78")];
tensor<fp16, [20, 77, 64]> query_states_33_cast = reshape(shape = var_1566, x = transpose_78)[name = tensor<string, []>("query_states_33_cast")];
tensor<int32, [3]> var_1568 = const()[name = tensor<string, []>("op_1568"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_80 = transpose(perm = var_1548_perm_0, x = var_1547_cast)[name = tensor<string, []>("transpose_80")];
tensor<fp16, [20, 77, 64]> key_states_67_cast = reshape(shape = var_1568, x = transpose_80)[name = tensor<string, []>("key_states_67_cast")];
tensor<int32, [3]> var_1570 = const()[name = tensor<string, []>("op_1570"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_79 = transpose(perm = var_1555_perm_0, x = var_1554_cast)[name = tensor<string, []>("transpose_79")];
tensor<fp16, [20, 77, 64]> value_states_67_cast = reshape(shape = var_1570, x = transpose_79)[name = tensor<string, []>("value_states_67_cast")];
tensor<int32, [3]> var_1573_perm_0 = const()[name = tensor<string, []>("op_1573_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_97_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_97_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_97_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_77 = transpose(perm = var_1573_perm_0, x = key_states_67_cast)[name = tensor<string, []>("transpose_77")];
tensor<fp16, [20, 77, 77]> attn_weights_97_cast = matmul(transpose_x = attn_weights_97_transpose_x_0, transpose_y = attn_weights_97_transpose_y_0, x = query_states_33_cast, y = transpose_77)[name = tensor<string, []>("attn_weights_97_cast")];
tensor<int32, [4]> var_1575 = const()[name = tensor<string, []>("op_1575"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1576_cast = reshape(shape = var_1575, x = attn_weights_97_cast)[name = tensor<string, []>("op_1576_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_99_cast = add(x = var_1576_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_99_cast")];
tensor<int32, [3]> var_1581 = const()[name = tensor<string, []>("op_1581"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_261_cast = reshape(shape = var_1581, x = attn_weights_99_cast)[name = tensor<string, []>("input_261_cast")];
tensor<fp16, [20, 77, 77]> input_263_cast = softmax(axis = var_5, x = input_261_cast)[name = tensor<string, []>("input_263_cast")];
tensor<bool, []> attn_output_97_transpose_x_0 = const()[name = tensor<string, []>("attn_output_97_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_97_transpose_y_0 = const()[name = tensor<string, []>("attn_output_97_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_97_cast = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast, y = value_states_67_cast)[name = tensor<string, []>("attn_output_97_cast")];
tensor<int32, [4]> var_1586 = const()[name = tensor<string, []>("op_1586"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_99_cast = reshape(shape = var_1586, x = attn_output_97_cast)[name = tensor<string, []>("attn_output_99_cast")];
tensor<int32, [4]> attn_output_101_perm_0 = const()[name = tensor<string, []>("attn_output_101_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1589 = const()[name = tensor<string, []>("op_1589"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_76 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor<string, []>("transpose_76")];
tensor<fp16, [1, 77, 1280]> input_265_cast = reshape(shape = var_1589, x = transpose_76)[name = tensor<string, []>("input_265_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766231936)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769508800)))];
tensor<fp16, [1, 77, 1280]> hidden_states_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16, x = input_265_cast)[name = tensor<string, []>("hidden_states_99_cast")];
tensor<fp16, [1, 77, 1280]> input_267_cast = add(x = input_259_cast, y = hidden_states_99_cast)[name = tensor<string, []>("input_267_cast")];
tensor<int32, [1]> input_269_axes_0 = const()[name = tensor<string, []>("input_269_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769511424)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769514048)))];
tensor<fp16, [1, 77, 1280]> input_269_cast = layer_norm(axes = input_269_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_267_cast)[name = tensor<string, []>("input_269_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(769516672)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(782623936)))];
tensor<fp16, [1, 77, 5120]> input_271_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16, x = input_269_cast)[name = tensor<string, []>("input_271_cast")];
tensor<string, []> input_273_mode_0 = const()[name = tensor<string, []>("input_273_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_273_cast = gelu(mode = input_273_mode_0, x = input_271_cast)[name = tensor<string, []>("input_273_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(782634240)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795741504)))];
tensor<fp16, [1, 77, 1280]> hidden_states_101_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16, x = input_273_cast)[name = tensor<string, []>("hidden_states_101_cast")];
tensor<fp16, [1, 77, 1280]> input_275_cast = add(x = input_267_cast, y = hidden_states_101_cast)[name = tensor<string, []>("input_275_cast")];
tensor<int32, [1]> hidden_states_103_axes_0 = const()[name = tensor<string, []>("hidden_states_103_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795744128)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795746752)))];
tensor<fp16, [1, 77, 1280]> hidden_states_103_cast = layer_norm(axes = hidden_states_103_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_275_cast)[name = tensor<string, []>("hidden_states_103_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(795749376)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(799026240)))];
tensor<fp16, [1, 77, 1280]> var_1627_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("op_1627_cast")];
tensor<fp16, []> var_1628_to_fp16 = const()[name = tensor<string, []>("op_1628_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_107_cast = mul(x = var_1627_cast, y = var_1628_to_fp16)[name = tensor<string, []>("tensor_107_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(799028864)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802305728)))];
tensor<fp16, [1, 77, 1280]> tensor_103_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_103_cast")];
tensor<int32, [4]> var_1633 = const()[name = tensor<string, []>("op_1633"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1634_cast = reshape(shape = var_1633, x = tensor_103_cast)[name = tensor<string, []>("op_1634_cast")];
tensor<int32, [4]> var_1635_perm_0 = const()[name = tensor<string, []>("op_1635_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802308352)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(805585216)))];
tensor<fp16, [1, 77, 1280]> tensor_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16, x = hidden_states_103_cast)[name = tensor<string, []>("tensor_105_cast")];
tensor<int32, [4]> var_1640 = const()[name = tensor<string, []>("op_1640"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1641_cast = reshape(shape = var_1640, x = tensor_105_cast)[name = tensor<string, []>("op_1641_cast")];
tensor<int32, [4]> var_1642_perm_0 = const()[name = tensor<string, []>("op_1642_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1649 = const()[name = tensor<string, []>("op_1649"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1650_cast = reshape(shape = var_1649, x = tensor_107_cast)[name = tensor<string, []>("op_1650_cast")];
tensor<int32, [4]> var_1651_perm_0 = const()[name = tensor<string, []>("op_1651_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1653 = const()[name = tensor<string, []>("op_1653"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_73 = transpose(perm = var_1651_perm_0, x = var_1650_cast)[name = tensor<string, []>("transpose_73")];
tensor<fp16, [20, 77, 64]> query_states_35_cast = reshape(shape = var_1653, x = transpose_73)[name = tensor<string, []>("query_states_35_cast")];
tensor<int32, [3]> var_1655 = const()[name = tensor<string, []>("op_1655"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_75 = transpose(perm = var_1635_perm_0, x = var_1634_cast)[name = tensor<string, []>("transpose_75")];
tensor<fp16, [20, 77, 64]> key_states_71_cast = reshape(shape = var_1655, x = transpose_75)[name = tensor<string, []>("key_states_71_cast")];
tensor<int32, [3]> var_1657 = const()[name = tensor<string, []>("op_1657"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_74 = transpose(perm = var_1642_perm_0, x = var_1641_cast)[name = tensor<string, []>("transpose_74")];
tensor<fp16, [20, 77, 64]> value_states_71_cast = reshape(shape = var_1657, x = transpose_74)[name = tensor<string, []>("value_states_71_cast")];
tensor<int32, [3]> var_1660_perm_0 = const()[name = tensor<string, []>("op_1660_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_103_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_103_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_103_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_72 = transpose(perm = var_1660_perm_0, x = key_states_71_cast)[name = tensor<string, []>("transpose_72")];
tensor<fp16, [20, 77, 77]> attn_weights_103_cast = matmul(transpose_x = attn_weights_103_transpose_x_0, transpose_y = attn_weights_103_transpose_y_0, x = query_states_35_cast, y = transpose_72)[name = tensor<string, []>("attn_weights_103_cast")];
tensor<int32, [4]> var_1662 = const()[name = tensor<string, []>("op_1662"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1663_cast = reshape(shape = var_1662, x = attn_weights_103_cast)[name = tensor<string, []>("op_1663_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_105_cast = add(x = var_1663_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_105_cast")];
tensor<int32, [3]> var_1668 = const()[name = tensor<string, []>("op_1668"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_277_cast = reshape(shape = var_1668, x = attn_weights_105_cast)[name = tensor<string, []>("input_277_cast")];
tensor<fp16, [20, 77, 77]> input_279_cast = softmax(axis = var_5, x = input_277_cast)[name = tensor<string, []>("input_279_cast")];
tensor<bool, []> attn_output_103_transpose_x_0 = const()[name = tensor<string, []>("attn_output_103_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_103_transpose_y_0 = const()[name = tensor<string, []>("attn_output_103_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_103_cast = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast, y = value_states_71_cast)[name = tensor<string, []>("attn_output_103_cast")];
tensor<int32, [4]> var_1673 = const()[name = tensor<string, []>("op_1673"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_105_cast = reshape(shape = var_1673, x = attn_output_103_cast)[name = tensor<string, []>("attn_output_105_cast")];
tensor<int32, [4]> attn_output_107_perm_0 = const()[name = tensor<string, []>("attn_output_107_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1676 = const()[name = tensor<string, []>("op_1676"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_71 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor<string, []>("transpose_71")];
tensor<fp16, [1, 77, 1280]> input_281_cast = reshape(shape = var_1676, x = transpose_71)[name = tensor<string, []>("input_281_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(805587840)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808864704)))];
tensor<fp16, [1, 77, 1280]> hidden_states_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16, x = input_281_cast)[name = tensor<string, []>("hidden_states_105_cast")];
tensor<fp16, [1, 77, 1280]> input_283_cast = add(x = input_275_cast, y = hidden_states_105_cast)[name = tensor<string, []>("input_283_cast")];
tensor<int32, [1]> input_285_axes_0 = const()[name = tensor<string, []>("input_285_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808867328)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808869952)))];
tensor<fp16, [1, 77, 1280]> input_285_cast = layer_norm(axes = input_285_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_283_cast)[name = tensor<string, []>("input_285_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(808872576)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(821979840)))];
tensor<fp16, [1, 77, 5120]> input_287_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16, x = input_285_cast)[name = tensor<string, []>("input_287_cast")];
tensor<string, []> input_289_mode_0 = const()[name = tensor<string, []>("input_289_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_289_cast = gelu(mode = input_289_mode_0, x = input_287_cast)[name = tensor<string, []>("input_289_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(821990144)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835097408)))];
tensor<fp16, [1, 77, 1280]> hidden_states_107_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16, x = input_289_cast)[name = tensor<string, []>("hidden_states_107_cast")];
tensor<fp16, [1, 77, 1280]> input_291_cast = add(x = input_283_cast, y = hidden_states_107_cast)[name = tensor<string, []>("input_291_cast")];
tensor<int32, [1]> hidden_states_109_axes_0 = const()[name = tensor<string, []>("hidden_states_109_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835100032)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835102656)))];
tensor<fp16, [1, 77, 1280]> hidden_states_109_cast = layer_norm(axes = hidden_states_109_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_291_cast)[name = tensor<string, []>("hidden_states_109_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(835105280)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(838382144)))];
tensor<fp16, [1, 77, 1280]> var_1714_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("op_1714_cast")];
tensor<fp16, []> var_1715_to_fp16 = const()[name = tensor<string, []>("op_1715_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_113_cast = mul(x = var_1714_cast, y = var_1715_to_fp16)[name = tensor<string, []>("tensor_113_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(838384768)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(841661632)))];
tensor<fp16, [1, 77, 1280]> tensor_109_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_109_cast")];
tensor<int32, [4]> var_1720 = const()[name = tensor<string, []>("op_1720"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1721_cast = reshape(shape = var_1720, x = tensor_109_cast)[name = tensor<string, []>("op_1721_cast")];
tensor<int32, [4]> var_1722_perm_0 = const()[name = tensor<string, []>("op_1722_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(841664256)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(844941120)))];
tensor<fp16, [1, 77, 1280]> tensor_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16, x = hidden_states_109_cast)[name = tensor<string, []>("tensor_111_cast")];
tensor<int32, [4]> var_1727 = const()[name = tensor<string, []>("op_1727"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1728_cast = reshape(shape = var_1727, x = tensor_111_cast)[name = tensor<string, []>("op_1728_cast")];
tensor<int32, [4]> var_1729_perm_0 = const()[name = tensor<string, []>("op_1729_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1736 = const()[name = tensor<string, []>("op_1736"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1737_cast = reshape(shape = var_1736, x = tensor_113_cast)[name = tensor<string, []>("op_1737_cast")];
tensor<int32, [4]> var_1738_perm_0 = const()[name = tensor<string, []>("op_1738_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1740 = const()[name = tensor<string, []>("op_1740"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_68 = transpose(perm = var_1738_perm_0, x = var_1737_cast)[name = tensor<string, []>("transpose_68")];
tensor<fp16, [20, 77, 64]> query_states_37_cast = reshape(shape = var_1740, x = transpose_68)[name = tensor<string, []>("query_states_37_cast")];
tensor<int32, [3]> var_1742 = const()[name = tensor<string, []>("op_1742"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_70 = transpose(perm = var_1722_perm_0, x = var_1721_cast)[name = tensor<string, []>("transpose_70")];
tensor<fp16, [20, 77, 64]> key_states_75_cast = reshape(shape = var_1742, x = transpose_70)[name = tensor<string, []>("key_states_75_cast")];
tensor<int32, [3]> var_1744 = const()[name = tensor<string, []>("op_1744"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_69 = transpose(perm = var_1729_perm_0, x = var_1728_cast)[name = tensor<string, []>("transpose_69")];
tensor<fp16, [20, 77, 64]> value_states_75_cast = reshape(shape = var_1744, x = transpose_69)[name = tensor<string, []>("value_states_75_cast")];
tensor<int32, [3]> var_1747_perm_0 = const()[name = tensor<string, []>("op_1747_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_109_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_109_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_109_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_67 = transpose(perm = var_1747_perm_0, x = key_states_75_cast)[name = tensor<string, []>("transpose_67")];
tensor<fp16, [20, 77, 77]> attn_weights_109_cast = matmul(transpose_x = attn_weights_109_transpose_x_0, transpose_y = attn_weights_109_transpose_y_0, x = query_states_37_cast, y = transpose_67)[name = tensor<string, []>("attn_weights_109_cast")];
tensor<int32, [4]> var_1749 = const()[name = tensor<string, []>("op_1749"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1750_cast = reshape(shape = var_1749, x = attn_weights_109_cast)[name = tensor<string, []>("op_1750_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_111_cast = add(x = var_1750_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_111_cast")];
tensor<int32, [3]> var_1755 = const()[name = tensor<string, []>("op_1755"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_293_cast = reshape(shape = var_1755, x = attn_weights_111_cast)[name = tensor<string, []>("input_293_cast")];
tensor<fp16, [20, 77, 77]> input_295_cast = softmax(axis = var_5, x = input_293_cast)[name = tensor<string, []>("input_295_cast")];
tensor<bool, []> attn_output_109_transpose_x_0 = const()[name = tensor<string, []>("attn_output_109_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_109_transpose_y_0 = const()[name = tensor<string, []>("attn_output_109_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_109_cast = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast, y = value_states_75_cast)[name = tensor<string, []>("attn_output_109_cast")];
tensor<int32, [4]> var_1760 = const()[name = tensor<string, []>("op_1760"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_111_cast = reshape(shape = var_1760, x = attn_output_109_cast)[name = tensor<string, []>("attn_output_111_cast")];
tensor<int32, [4]> attn_output_113_perm_0 = const()[name = tensor<string, []>("attn_output_113_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1763 = const()[name = tensor<string, []>("op_1763"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_66 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor<string, []>("transpose_66")];
tensor<fp16, [1, 77, 1280]> input_297_cast = reshape(shape = var_1763, x = transpose_66)[name = tensor<string, []>("input_297_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(844943744)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848220608)))];
tensor<fp16, [1, 77, 1280]> hidden_states_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16, x = input_297_cast)[name = tensor<string, []>("hidden_states_111_cast")];
tensor<fp16, [1, 77, 1280]> input_299_cast = add(x = input_291_cast, y = hidden_states_111_cast)[name = tensor<string, []>("input_299_cast")];
tensor<int32, [1]> input_301_axes_0 = const()[name = tensor<string, []>("input_301_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848223232)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848225856)))];
tensor<fp16, [1, 77, 1280]> input_301_cast = layer_norm(axes = input_301_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_299_cast)[name = tensor<string, []>("input_301_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(848228480)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(861335744)))];
tensor<fp16, [1, 77, 5120]> input_303_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16, x = input_301_cast)[name = tensor<string, []>("input_303_cast")];
tensor<string, []> input_305_mode_0 = const()[name = tensor<string, []>("input_305_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_305_cast = gelu(mode = input_305_mode_0, x = input_303_cast)[name = tensor<string, []>("input_305_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(861346048)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874453312)))];
tensor<fp16, [1, 77, 1280]> hidden_states_113_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16, x = input_305_cast)[name = tensor<string, []>("hidden_states_113_cast")];
tensor<fp16, [1, 77, 1280]> input_307_cast = add(x = input_299_cast, y = hidden_states_113_cast)[name = tensor<string, []>("input_307_cast")];
tensor<int32, [1]> hidden_states_115_axes_0 = const()[name = tensor<string, []>("hidden_states_115_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874455936)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874458560)))];
tensor<fp16, [1, 77, 1280]> hidden_states_115_cast = layer_norm(axes = hidden_states_115_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_307_cast)[name = tensor<string, []>("hidden_states_115_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(874461184)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877738048)))];
tensor<fp16, [1, 77, 1280]> var_1801_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("op_1801_cast")];
tensor<fp16, []> var_1802_to_fp16 = const()[name = tensor<string, []>("op_1802_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_119_cast = mul(x = var_1801_cast, y = var_1802_to_fp16)[name = tensor<string, []>("tensor_119_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877740672)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(881017536)))];
tensor<fp16, [1, 77, 1280]> tensor_115_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_115_cast")];
tensor<int32, [4]> var_1807 = const()[name = tensor<string, []>("op_1807"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1808_cast = reshape(shape = var_1807, x = tensor_115_cast)[name = tensor<string, []>("op_1808_cast")];
tensor<int32, [4]> var_1809_perm_0 = const()[name = tensor<string, []>("op_1809_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(881020160)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(884297024)))];
tensor<fp16, [1, 77, 1280]> tensor_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16, x = hidden_states_115_cast)[name = tensor<string, []>("tensor_117_cast")];
tensor<int32, [4]> var_1814 = const()[name = tensor<string, []>("op_1814"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1815_cast = reshape(shape = var_1814, x = tensor_117_cast)[name = tensor<string, []>("op_1815_cast")];
tensor<int32, [4]> var_1816_perm_0 = const()[name = tensor<string, []>("op_1816_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1823 = const()[name = tensor<string, []>("op_1823"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1824_cast = reshape(shape = var_1823, x = tensor_119_cast)[name = tensor<string, []>("op_1824_cast")];
tensor<int32, [4]> var_1825_perm_0 = const()[name = tensor<string, []>("op_1825_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1827 = const()[name = tensor<string, []>("op_1827"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_63 = transpose(perm = var_1825_perm_0, x = var_1824_cast)[name = tensor<string, []>("transpose_63")];
tensor<fp16, [20, 77, 64]> query_states_39_cast = reshape(shape = var_1827, x = transpose_63)[name = tensor<string, []>("query_states_39_cast")];
tensor<int32, [3]> var_1829 = const()[name = tensor<string, []>("op_1829"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_65 = transpose(perm = var_1809_perm_0, x = var_1808_cast)[name = tensor<string, []>("transpose_65")];
tensor<fp16, [20, 77, 64]> key_states_79_cast = reshape(shape = var_1829, x = transpose_65)[name = tensor<string, []>("key_states_79_cast")];
tensor<int32, [3]> var_1831 = const()[name = tensor<string, []>("op_1831"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_64 = transpose(perm = var_1816_perm_0, x = var_1815_cast)[name = tensor<string, []>("transpose_64")];
tensor<fp16, [20, 77, 64]> value_states_79_cast = reshape(shape = var_1831, x = transpose_64)[name = tensor<string, []>("value_states_79_cast")];
tensor<int32, [3]> var_1834_perm_0 = const()[name = tensor<string, []>("op_1834_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_115_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_115_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_115_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_62 = transpose(perm = var_1834_perm_0, x = key_states_79_cast)[name = tensor<string, []>("transpose_62")];
tensor<fp16, [20, 77, 77]> attn_weights_115_cast = matmul(transpose_x = attn_weights_115_transpose_x_0, transpose_y = attn_weights_115_transpose_y_0, x = query_states_39_cast, y = transpose_62)[name = tensor<string, []>("attn_weights_115_cast")];
tensor<int32, [4]> var_1836 = const()[name = tensor<string, []>("op_1836"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1837_cast = reshape(shape = var_1836, x = attn_weights_115_cast)[name = tensor<string, []>("op_1837_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_117_cast = add(x = var_1837_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_117_cast")];
tensor<int32, [3]> var_1842 = const()[name = tensor<string, []>("op_1842"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_309_cast = reshape(shape = var_1842, x = attn_weights_117_cast)[name = tensor<string, []>("input_309_cast")];
tensor<fp16, [20, 77, 77]> input_311_cast = softmax(axis = var_5, x = input_309_cast)[name = tensor<string, []>("input_311_cast")];
tensor<bool, []> attn_output_115_transpose_x_0 = const()[name = tensor<string, []>("attn_output_115_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_115_transpose_y_0 = const()[name = tensor<string, []>("attn_output_115_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_115_cast = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast, y = value_states_79_cast)[name = tensor<string, []>("attn_output_115_cast")];
tensor<int32, [4]> var_1847 = const()[name = tensor<string, []>("op_1847"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_117_cast = reshape(shape = var_1847, x = attn_output_115_cast)[name = tensor<string, []>("attn_output_117_cast")];
tensor<int32, [4]> attn_output_119_perm_0 = const()[name = tensor<string, []>("attn_output_119_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1850 = const()[name = tensor<string, []>("op_1850"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_61 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor<string, []>("transpose_61")];
tensor<fp16, [1, 77, 1280]> input_313_cast = reshape(shape = var_1850, x = transpose_61)[name = tensor<string, []>("input_313_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(884299648)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887576512)))];
tensor<fp16, [1, 77, 1280]> hidden_states_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16, x = input_313_cast)[name = tensor<string, []>("hidden_states_117_cast")];
tensor<fp16, [1, 77, 1280]> input_315_cast = add(x = input_307_cast, y = hidden_states_117_cast)[name = tensor<string, []>("input_315_cast")];
tensor<int32, [1]> input_317_axes_0 = const()[name = tensor<string, []>("input_317_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887579136)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887581760)))];
tensor<fp16, [1, 77, 1280]> input_317_cast = layer_norm(axes = input_317_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_315_cast)[name = tensor<string, []>("input_317_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(887584384)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900691648)))];
tensor<fp16, [1, 77, 5120]> input_319_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16, x = input_317_cast)[name = tensor<string, []>("input_319_cast")];
tensor<string, []> input_321_mode_0 = const()[name = tensor<string, []>("input_321_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_321_cast = gelu(mode = input_321_mode_0, x = input_319_cast)[name = tensor<string, []>("input_321_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900701952)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913809216)))];
tensor<fp16, [1, 77, 1280]> hidden_states_119_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16, x = input_321_cast)[name = tensor<string, []>("hidden_states_119_cast")];
tensor<fp16, [1, 77, 1280]> input_323_cast = add(x = input_315_cast, y = hidden_states_119_cast)[name = tensor<string, []>("input_323_cast")];
tensor<int32, [1]> hidden_states_121_axes_0 = const()[name = tensor<string, []>("hidden_states_121_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913811840)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913814464)))];
tensor<fp16, [1, 77, 1280]> hidden_states_121_cast = layer_norm(axes = hidden_states_121_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_323_cast)[name = tensor<string, []>("hidden_states_121_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913817088)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(917093952)))];
tensor<fp16, [1, 77, 1280]> var_1888_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("op_1888_cast")];
tensor<fp16, []> var_1889_to_fp16 = const()[name = tensor<string, []>("op_1889_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_125_cast = mul(x = var_1888_cast, y = var_1889_to_fp16)[name = tensor<string, []>("tensor_125_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(917096576)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920373440)))];
tensor<fp16, [1, 77, 1280]> tensor_121_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_121_cast")];
tensor<int32, [4]> var_1894 = const()[name = tensor<string, []>("op_1894"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1895_cast = reshape(shape = var_1894, x = tensor_121_cast)[name = tensor<string, []>("op_1895_cast")];
tensor<int32, [4]> var_1896_perm_0 = const()[name = tensor<string, []>("op_1896_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(920376064)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(923652928)))];
tensor<fp16, [1, 77, 1280]> tensor_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16, x = hidden_states_121_cast)[name = tensor<string, []>("tensor_123_cast")];
tensor<int32, [4]> var_1901 = const()[name = tensor<string, []>("op_1901"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1902_cast = reshape(shape = var_1901, x = tensor_123_cast)[name = tensor<string, []>("op_1902_cast")];
tensor<int32, [4]> var_1903_perm_0 = const()[name = tensor<string, []>("op_1903_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1910 = const()[name = tensor<string, []>("op_1910"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1911_cast = reshape(shape = var_1910, x = tensor_125_cast)[name = tensor<string, []>("op_1911_cast")];
tensor<int32, [4]> var_1912_perm_0 = const()[name = tensor<string, []>("op_1912_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1914 = const()[name = tensor<string, []>("op_1914"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_58 = transpose(perm = var_1912_perm_0, x = var_1911_cast)[name = tensor<string, []>("transpose_58")];
tensor<fp16, [20, 77, 64]> query_states_41_cast = reshape(shape = var_1914, x = transpose_58)[name = tensor<string, []>("query_states_41_cast")];
tensor<int32, [3]> var_1916 = const()[name = tensor<string, []>("op_1916"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_60 = transpose(perm = var_1896_perm_0, x = var_1895_cast)[name = tensor<string, []>("transpose_60")];
tensor<fp16, [20, 77, 64]> key_states_83_cast = reshape(shape = var_1916, x = transpose_60)[name = tensor<string, []>("key_states_83_cast")];
tensor<int32, [3]> var_1918 = const()[name = tensor<string, []>("op_1918"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_59 = transpose(perm = var_1903_perm_0, x = var_1902_cast)[name = tensor<string, []>("transpose_59")];
tensor<fp16, [20, 77, 64]> value_states_83_cast = reshape(shape = var_1918, x = transpose_59)[name = tensor<string, []>("value_states_83_cast")];
tensor<int32, [3]> var_1921_perm_0 = const()[name = tensor<string, []>("op_1921_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_121_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_121_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_121_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_57 = transpose(perm = var_1921_perm_0, x = key_states_83_cast)[name = tensor<string, []>("transpose_57")];
tensor<fp16, [20, 77, 77]> attn_weights_121_cast = matmul(transpose_x = attn_weights_121_transpose_x_0, transpose_y = attn_weights_121_transpose_y_0, x = query_states_41_cast, y = transpose_57)[name = tensor<string, []>("attn_weights_121_cast")];
tensor<int32, [4]> var_1923 = const()[name = tensor<string, []>("op_1923"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_1924_cast = reshape(shape = var_1923, x = attn_weights_121_cast)[name = tensor<string, []>("op_1924_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_123_cast = add(x = var_1924_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_123_cast")];
tensor<int32, [3]> var_1929 = const()[name = tensor<string, []>("op_1929"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_325_cast = reshape(shape = var_1929, x = attn_weights_123_cast)[name = tensor<string, []>("input_325_cast")];
tensor<fp16, [20, 77, 77]> input_327_cast = softmax(axis = var_5, x = input_325_cast)[name = tensor<string, []>("input_327_cast")];
tensor<bool, []> attn_output_121_transpose_x_0 = const()[name = tensor<string, []>("attn_output_121_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_121_transpose_y_0 = const()[name = tensor<string, []>("attn_output_121_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_121_cast = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast, y = value_states_83_cast)[name = tensor<string, []>("attn_output_121_cast")];
tensor<int32, [4]> var_1934 = const()[name = tensor<string, []>("op_1934"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_123_cast = reshape(shape = var_1934, x = attn_output_121_cast)[name = tensor<string, []>("attn_output_123_cast")];
tensor<int32, [4]> attn_output_125_perm_0 = const()[name = tensor<string, []>("attn_output_125_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_1937 = const()[name = tensor<string, []>("op_1937"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_56 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor<string, []>("transpose_56")];
tensor<fp16, [1, 77, 1280]> input_329_cast = reshape(shape = var_1937, x = transpose_56)[name = tensor<string, []>("input_329_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(923655552)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926932416)))];
tensor<fp16, [1, 77, 1280]> hidden_states_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16, x = input_329_cast)[name = tensor<string, []>("hidden_states_123_cast")];
tensor<fp16, [1, 77, 1280]> input_331_cast = add(x = input_323_cast, y = hidden_states_123_cast)[name = tensor<string, []>("input_331_cast")];
tensor<int32, [1]> input_333_axes_0 = const()[name = tensor<string, []>("input_333_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926935040)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926937664)))];
tensor<fp16, [1, 77, 1280]> input_333_cast = layer_norm(axes = input_333_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_331_cast)[name = tensor<string, []>("input_333_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(926940288)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940047552)))];
tensor<fp16, [1, 77, 5120]> input_335_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16, x = input_333_cast)[name = tensor<string, []>("input_335_cast")];
tensor<string, []> input_337_mode_0 = const()[name = tensor<string, []>("input_337_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_337_cast = gelu(mode = input_337_mode_0, x = input_335_cast)[name = tensor<string, []>("input_337_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(940057856)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953165120)))];
tensor<fp16, [1, 77, 1280]> hidden_states_125_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16, x = input_337_cast)[name = tensor<string, []>("hidden_states_125_cast")];
tensor<fp16, [1, 77, 1280]> input_339_cast = add(x = input_331_cast, y = hidden_states_125_cast)[name = tensor<string, []>("input_339_cast")];
tensor<int32, [1]> hidden_states_127_axes_0 = const()[name = tensor<string, []>("hidden_states_127_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953167744)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953170368)))];
tensor<fp16, [1, 77, 1280]> hidden_states_127_cast = layer_norm(axes = hidden_states_127_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_339_cast)[name = tensor<string, []>("hidden_states_127_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(953172992)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(956449856)))];
tensor<fp16, [1, 77, 1280]> var_1975_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("op_1975_cast")];
tensor<fp16, []> var_1976_to_fp16 = const()[name = tensor<string, []>("op_1976_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_131_cast = mul(x = var_1975_cast, y = var_1976_to_fp16)[name = tensor<string, []>("tensor_131_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(956452480)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(959729344)))];
tensor<fp16, [1, 77, 1280]> tensor_127_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_127_cast")];
tensor<int32, [4]> var_1981 = const()[name = tensor<string, []>("op_1981"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1982_cast = reshape(shape = var_1981, x = tensor_127_cast)[name = tensor<string, []>("op_1982_cast")];
tensor<int32, [4]> var_1983_perm_0 = const()[name = tensor<string, []>("op_1983_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(959731968)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(963008832)))];
tensor<fp16, [1, 77, 1280]> tensor_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16, x = hidden_states_127_cast)[name = tensor<string, []>("tensor_129_cast")];
tensor<int32, [4]> var_1988 = const()[name = tensor<string, []>("op_1988"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1989_cast = reshape(shape = var_1988, x = tensor_129_cast)[name = tensor<string, []>("op_1989_cast")];
tensor<int32, [4]> var_1990_perm_0 = const()[name = tensor<string, []>("op_1990_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_1997 = const()[name = tensor<string, []>("op_1997"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_1998_cast = reshape(shape = var_1997, x = tensor_131_cast)[name = tensor<string, []>("op_1998_cast")];
tensor<int32, [4]> var_1999_perm_0 = const()[name = tensor<string, []>("op_1999_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2001 = const()[name = tensor<string, []>("op_2001"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_53 = transpose(perm = var_1999_perm_0, x = var_1998_cast)[name = tensor<string, []>("transpose_53")];
tensor<fp16, [20, 77, 64]> query_states_43_cast = reshape(shape = var_2001, x = transpose_53)[name = tensor<string, []>("query_states_43_cast")];
tensor<int32, [3]> var_2003 = const()[name = tensor<string, []>("op_2003"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_55 = transpose(perm = var_1983_perm_0, x = var_1982_cast)[name = tensor<string, []>("transpose_55")];
tensor<fp16, [20, 77, 64]> key_states_87_cast = reshape(shape = var_2003, x = transpose_55)[name = tensor<string, []>("key_states_87_cast")];
tensor<int32, [3]> var_2005 = const()[name = tensor<string, []>("op_2005"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_54 = transpose(perm = var_1990_perm_0, x = var_1989_cast)[name = tensor<string, []>("transpose_54")];
tensor<fp16, [20, 77, 64]> value_states_87_cast = reshape(shape = var_2005, x = transpose_54)[name = tensor<string, []>("value_states_87_cast")];
tensor<int32, [3]> var_2008_perm_0 = const()[name = tensor<string, []>("op_2008_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_127_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_127_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_127_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_52 = transpose(perm = var_2008_perm_0, x = key_states_87_cast)[name = tensor<string, []>("transpose_52")];
tensor<fp16, [20, 77, 77]> attn_weights_127_cast = matmul(transpose_x = attn_weights_127_transpose_x_0, transpose_y = attn_weights_127_transpose_y_0, x = query_states_43_cast, y = transpose_52)[name = tensor<string, []>("attn_weights_127_cast")];
tensor<int32, [4]> var_2010 = const()[name = tensor<string, []>("op_2010"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2011_cast = reshape(shape = var_2010, x = attn_weights_127_cast)[name = tensor<string, []>("op_2011_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_129_cast = add(x = var_2011_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_129_cast")];
tensor<int32, [3]> var_2016 = const()[name = tensor<string, []>("op_2016"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_341_cast = reshape(shape = var_2016, x = attn_weights_129_cast)[name = tensor<string, []>("input_341_cast")];
tensor<fp16, [20, 77, 77]> input_343_cast = softmax(axis = var_5, x = input_341_cast)[name = tensor<string, []>("input_343_cast")];
tensor<bool, []> attn_output_127_transpose_x_0 = const()[name = tensor<string, []>("attn_output_127_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_127_transpose_y_0 = const()[name = tensor<string, []>("attn_output_127_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_127_cast = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast, y = value_states_87_cast)[name = tensor<string, []>("attn_output_127_cast")];
tensor<int32, [4]> var_2021 = const()[name = tensor<string, []>("op_2021"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_129_cast = reshape(shape = var_2021, x = attn_output_127_cast)[name = tensor<string, []>("attn_output_129_cast")];
tensor<int32, [4]> attn_output_131_perm_0 = const()[name = tensor<string, []>("attn_output_131_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2024 = const()[name = tensor<string, []>("op_2024"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_51 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor<string, []>("transpose_51")];
tensor<fp16, [1, 77, 1280]> input_345_cast = reshape(shape = var_2024, x = transpose_51)[name = tensor<string, []>("input_345_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(963011456)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966288320)))];
tensor<fp16, [1, 77, 1280]> hidden_states_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16, x = input_345_cast)[name = tensor<string, []>("hidden_states_129_cast")];
tensor<fp16, [1, 77, 1280]> input_347_cast = add(x = input_339_cast, y = hidden_states_129_cast)[name = tensor<string, []>("input_347_cast")];
tensor<int32, [1]> input_349_axes_0 = const()[name = tensor<string, []>("input_349_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966290944)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966293568)))];
tensor<fp16, [1, 77, 1280]> input_349_cast = layer_norm(axes = input_349_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_347_cast)[name = tensor<string, []>("input_349_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966296192)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(979403456)))];
tensor<fp16, [1, 77, 5120]> input_351_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16, x = input_349_cast)[name = tensor<string, []>("input_351_cast")];
tensor<string, []> input_353_mode_0 = const()[name = tensor<string, []>("input_353_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_353_cast = gelu(mode = input_353_mode_0, x = input_351_cast)[name = tensor<string, []>("input_353_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(979413760)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992521024)))];
tensor<fp16, [1, 77, 1280]> hidden_states_131_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16, x = input_353_cast)[name = tensor<string, []>("hidden_states_131_cast")];
tensor<fp16, [1, 77, 1280]> input_355_cast = add(x = input_347_cast, y = hidden_states_131_cast)[name = tensor<string, []>("input_355_cast")];
tensor<int32, [1]> hidden_states_133_axes_0 = const()[name = tensor<string, []>("hidden_states_133_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992523648)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992526272)))];
tensor<fp16, [1, 77, 1280]> hidden_states_133_cast = layer_norm(axes = hidden_states_133_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_355_cast)[name = tensor<string, []>("hidden_states_133_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(992528896)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(995805760)))];
tensor<fp16, [1, 77, 1280]> var_2062_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("op_2062_cast")];
tensor<fp16, []> var_2063_to_fp16 = const()[name = tensor<string, []>("op_2063_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_137_cast = mul(x = var_2062_cast, y = var_2063_to_fp16)[name = tensor<string, []>("tensor_137_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(995808384)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(999085248)))];
tensor<fp16, [1, 77, 1280]> tensor_133_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_133_cast")];
tensor<int32, [4]> var_2068 = const()[name = tensor<string, []>("op_2068"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2069_cast = reshape(shape = var_2068, x = tensor_133_cast)[name = tensor<string, []>("op_2069_cast")];
tensor<int32, [4]> var_2070_perm_0 = const()[name = tensor<string, []>("op_2070_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(999087872)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1002364736)))];
tensor<fp16, [1, 77, 1280]> tensor_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16, x = hidden_states_133_cast)[name = tensor<string, []>("tensor_135_cast")];
tensor<int32, [4]> var_2075 = const()[name = tensor<string, []>("op_2075"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2076_cast = reshape(shape = var_2075, x = tensor_135_cast)[name = tensor<string, []>("op_2076_cast")];
tensor<int32, [4]> var_2077_perm_0 = const()[name = tensor<string, []>("op_2077_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2084 = const()[name = tensor<string, []>("op_2084"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2085_cast = reshape(shape = var_2084, x = tensor_137_cast)[name = tensor<string, []>("op_2085_cast")];
tensor<int32, [4]> var_2086_perm_0 = const()[name = tensor<string, []>("op_2086_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2088 = const()[name = tensor<string, []>("op_2088"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_48 = transpose(perm = var_2086_perm_0, x = var_2085_cast)[name = tensor<string, []>("transpose_48")];
tensor<fp16, [20, 77, 64]> query_states_45_cast = reshape(shape = var_2088, x = transpose_48)[name = tensor<string, []>("query_states_45_cast")];
tensor<int32, [3]> var_2090 = const()[name = tensor<string, []>("op_2090"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_50 = transpose(perm = var_2070_perm_0, x = var_2069_cast)[name = tensor<string, []>("transpose_50")];
tensor<fp16, [20, 77, 64]> key_states_91_cast = reshape(shape = var_2090, x = transpose_50)[name = tensor<string, []>("key_states_91_cast")];
tensor<int32, [3]> var_2092 = const()[name = tensor<string, []>("op_2092"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_49 = transpose(perm = var_2077_perm_0, x = var_2076_cast)[name = tensor<string, []>("transpose_49")];
tensor<fp16, [20, 77, 64]> value_states_91_cast = reshape(shape = var_2092, x = transpose_49)[name = tensor<string, []>("value_states_91_cast")];
tensor<int32, [3]> var_2095_perm_0 = const()[name = tensor<string, []>("op_2095_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_133_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_133_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_133_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_47 = transpose(perm = var_2095_perm_0, x = key_states_91_cast)[name = tensor<string, []>("transpose_47")];
tensor<fp16, [20, 77, 77]> attn_weights_133_cast = matmul(transpose_x = attn_weights_133_transpose_x_0, transpose_y = attn_weights_133_transpose_y_0, x = query_states_45_cast, y = transpose_47)[name = tensor<string, []>("attn_weights_133_cast")];
tensor<int32, [4]> var_2097 = const()[name = tensor<string, []>("op_2097"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2098_cast = reshape(shape = var_2097, x = attn_weights_133_cast)[name = tensor<string, []>("op_2098_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_135_cast = add(x = var_2098_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_135_cast")];
tensor<int32, [3]> var_2103 = const()[name = tensor<string, []>("op_2103"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_357_cast = reshape(shape = var_2103, x = attn_weights_135_cast)[name = tensor<string, []>("input_357_cast")];
tensor<fp16, [20, 77, 77]> input_359_cast = softmax(axis = var_5, x = input_357_cast)[name = tensor<string, []>("input_359_cast")];
tensor<bool, []> attn_output_133_transpose_x_0 = const()[name = tensor<string, []>("attn_output_133_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_133_transpose_y_0 = const()[name = tensor<string, []>("attn_output_133_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_133_cast = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast, y = value_states_91_cast)[name = tensor<string, []>("attn_output_133_cast")];
tensor<int32, [4]> var_2108 = const()[name = tensor<string, []>("op_2108"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_135_cast = reshape(shape = var_2108, x = attn_output_133_cast)[name = tensor<string, []>("attn_output_135_cast")];
tensor<int32, [4]> attn_output_137_perm_0 = const()[name = tensor<string, []>("attn_output_137_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2111 = const()[name = tensor<string, []>("op_2111"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_46 = transpose(perm = attn_output_137_perm_0, x = attn_output_135_cast)[name = tensor<string, []>("transpose_46")];
tensor<fp16, [1, 77, 1280]> input_361_cast = reshape(shape = var_2111, x = transpose_46)[name = tensor<string, []>("input_361_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1002367360)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005644224)))];
tensor<fp16, [1, 77, 1280]> hidden_states_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16, x = input_361_cast)[name = tensor<string, []>("hidden_states_135_cast")];
tensor<fp16, [1, 77, 1280]> input_363_cast = add(x = input_355_cast, y = hidden_states_135_cast)[name = tensor<string, []>("input_363_cast")];
tensor<int32, [1]> input_365_axes_0 = const()[name = tensor<string, []>("input_365_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005646848)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005649472)))];
tensor<fp16, [1, 77, 1280]> input_365_cast = layer_norm(axes = input_365_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_363_cast)[name = tensor<string, []>("input_365_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1005652096)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1018759360)))];
tensor<fp16, [1, 77, 5120]> input_367_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16, x = input_365_cast)[name = tensor<string, []>("input_367_cast")];
tensor<string, []> input_369_mode_0 = const()[name = tensor<string, []>("input_369_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_369_cast = gelu(mode = input_369_mode_0, x = input_367_cast)[name = tensor<string, []>("input_369_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1018769664)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031876928)))];
tensor<fp16, [1, 77, 1280]> hidden_states_137_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16, x = input_369_cast)[name = tensor<string, []>("hidden_states_137_cast")];
tensor<fp16, [1, 77, 1280]> input_371_cast = add(x = input_363_cast, y = hidden_states_137_cast)[name = tensor<string, []>("input_371_cast")];
tensor<int32, [1]> hidden_states_139_axes_0 = const()[name = tensor<string, []>("hidden_states_139_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031879552)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031882176)))];
tensor<fp16, [1, 77, 1280]> hidden_states_139_cast = layer_norm(axes = hidden_states_139_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm1_weight_to_fp16, x = input_371_cast)[name = tensor<string, []>("hidden_states_139_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031884800)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1035161664)))];
tensor<fp16, [1, 77, 1280]> var_2149_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_q_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("op_2149_cast")];
tensor<fp16, []> var_2150_to_fp16 = const()[name = tensor<string, []>("op_2150_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_143_cast = mul(x = var_2149_cast, y = var_2150_to_fp16)[name = tensor<string, []>("tensor_143_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1035164288)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1038441152)))];
tensor<fp16, [1, 77, 1280]> tensor_139_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_k_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_139_cast")];
tensor<int32, [4]> var_2155 = const()[name = tensor<string, []>("op_2155"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2156_cast = reshape(shape = var_2155, x = tensor_139_cast)[name = tensor<string, []>("op_2156_cast")];
tensor<int32, [4]> var_2157_perm_0 = const()[name = tensor<string, []>("op_2157_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1038443776)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1041720640)))];
tensor<fp16, [1, 77, 1280]> tensor_141_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_v_proj_weight_to_fp16, x = hidden_states_139_cast)[name = tensor<string, []>("tensor_141_cast")];
tensor<int32, [4]> var_2162 = const()[name = tensor<string, []>("op_2162"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2163_cast = reshape(shape = var_2162, x = tensor_141_cast)[name = tensor<string, []>("op_2163_cast")];
tensor<int32, [4]> var_2164_perm_0 = const()[name = tensor<string, []>("op_2164_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2171 = const()[name = tensor<string, []>("op_2171"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2172_cast = reshape(shape = var_2171, x = tensor_143_cast)[name = tensor<string, []>("op_2172_cast")];
tensor<int32, [4]> var_2173_perm_0 = const()[name = tensor<string, []>("op_2173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2175 = const()[name = tensor<string, []>("op_2175"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_43 = transpose(perm = var_2173_perm_0, x = var_2172_cast)[name = tensor<string, []>("transpose_43")];
tensor<fp16, [20, 77, 64]> query_states_47_cast = reshape(shape = var_2175, x = transpose_43)[name = tensor<string, []>("query_states_47_cast")];
tensor<int32, [3]> var_2177 = const()[name = tensor<string, []>("op_2177"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_45 = transpose(perm = var_2157_perm_0, x = var_2156_cast)[name = tensor<string, []>("transpose_45")];
tensor<fp16, [20, 77, 64]> key_states_95_cast = reshape(shape = var_2177, x = transpose_45)[name = tensor<string, []>("key_states_95_cast")];
tensor<int32, [3]> var_2179 = const()[name = tensor<string, []>("op_2179"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_44 = transpose(perm = var_2164_perm_0, x = var_2163_cast)[name = tensor<string, []>("transpose_44")];
tensor<fp16, [20, 77, 64]> value_states_95_cast = reshape(shape = var_2179, x = transpose_44)[name = tensor<string, []>("value_states_95_cast")];
tensor<int32, [3]> var_2182_perm_0 = const()[name = tensor<string, []>("op_2182_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_139_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_139_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_139_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_42 = transpose(perm = var_2182_perm_0, x = key_states_95_cast)[name = tensor<string, []>("transpose_42")];
tensor<fp16, [20, 77, 77]> attn_weights_139_cast = matmul(transpose_x = attn_weights_139_transpose_x_0, transpose_y = attn_weights_139_transpose_y_0, x = query_states_47_cast, y = transpose_42)[name = tensor<string, []>("attn_weights_139_cast")];
tensor<int32, [4]> var_2184 = const()[name = tensor<string, []>("op_2184"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2185_cast = reshape(shape = var_2184, x = attn_weights_139_cast)[name = tensor<string, []>("op_2185_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_141_cast = add(x = var_2185_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_141_cast")];
tensor<int32, [3]> var_2190 = const()[name = tensor<string, []>("op_2190"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_373_cast = reshape(shape = var_2190, x = attn_weights_141_cast)[name = tensor<string, []>("input_373_cast")];
tensor<fp16, [20, 77, 77]> input_375_cast = softmax(axis = var_5, x = input_373_cast)[name = tensor<string, []>("input_375_cast")];
tensor<bool, []> attn_output_139_transpose_x_0 = const()[name = tensor<string, []>("attn_output_139_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_139_transpose_y_0 = const()[name = tensor<string, []>("attn_output_139_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_139_cast = matmul(transpose_x = attn_output_139_transpose_x_0, transpose_y = attn_output_139_transpose_y_0, x = input_375_cast, y = value_states_95_cast)[name = tensor<string, []>("attn_output_139_cast")];
tensor<int32, [4]> var_2195 = const()[name = tensor<string, []>("op_2195"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_141_cast = reshape(shape = var_2195, x = attn_output_139_cast)[name = tensor<string, []>("attn_output_141_cast")];
tensor<int32, [4]> attn_output_143_perm_0 = const()[name = tensor<string, []>("attn_output_143_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2198 = const()[name = tensor<string, []>("op_2198"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_41 = transpose(perm = attn_output_143_perm_0, x = attn_output_141_cast)[name = tensor<string, []>("transpose_41")];
tensor<fp16, [1, 77, 1280]> input_377_cast = reshape(shape = var_2198, x = transpose_41)[name = tensor<string, []>("input_377_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1041723264)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045000128)))];
tensor<fp16, [1, 77, 1280]> hidden_states_141_cast = linear(bias = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_self_attn_out_proj_weight_to_fp16, x = input_377_cast)[name = tensor<string, []>("hidden_states_141_cast")];
tensor<fp16, [1, 77, 1280]> input_379_cast = add(x = input_371_cast, y = hidden_states_141_cast)[name = tensor<string, []>("input_379_cast")];
tensor<int32, [1]> input_381_axes_0 = const()[name = tensor<string, []>("input_381_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045002752)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045005376)))];
tensor<fp16, [1, 77, 1280]> input_381_cast = layer_norm(axes = input_381_axes_0, beta = text_encoder_text_model_encoder_layers_23_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_23_layer_norm2_weight_to_fp16, x = input_379_cast)[name = tensor<string, []>("input_381_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1045008000)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058115264)))];
tensor<fp16, [1, 77, 5120]> input_383_cast = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc1_weight_to_fp16, x = input_381_cast)[name = tensor<string, []>("input_383_cast")];
tensor<string, []> input_385_mode_0 = const()[name = tensor<string, []>("input_385_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_385_cast = gelu(mode = input_385_mode_0, x = input_383_cast)[name = tensor<string, []>("input_385_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058125568)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071232832)))];
tensor<fp16, [1, 77, 1280]> hidden_states_143_cast = linear(bias = text_encoder_text_model_encoder_layers_23_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_23_mlp_fc2_weight_to_fp16, x = input_385_cast)[name = tensor<string, []>("hidden_states_143_cast")];
tensor<fp16, [1, 77, 1280]> input_387_cast = add(x = input_379_cast, y = hidden_states_143_cast)[name = tensor<string, []>("input_387_cast")];
tensor<int32, [1]> hidden_states_145_axes_0 = const()[name = tensor<string, []>("hidden_states_145_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071235456)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071238080)))];
tensor<fp16, [1, 77, 1280]> hidden_states_145_cast = layer_norm(axes = hidden_states_145_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm1_weight_to_fp16, x = input_387_cast)[name = tensor<string, []>("hidden_states_145_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071240704)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1074517568)))];
tensor<fp16, [1, 77, 1280]> var_2236_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_q_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("op_2236_cast")];
tensor<fp16, []> var_2237_to_fp16 = const()[name = tensor<string, []>("op_2237_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_149_cast = mul(x = var_2236_cast, y = var_2237_to_fp16)[name = tensor<string, []>("tensor_149_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1074520192)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077797056)))];
tensor<fp16, [1, 77, 1280]> tensor_145_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_k_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_145_cast")];
tensor<int32, [4]> var_2242 = const()[name = tensor<string, []>("op_2242"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2243_cast = reshape(shape = var_2242, x = tensor_145_cast)[name = tensor<string, []>("op_2243_cast")];
tensor<int32, [4]> var_2244_perm_0 = const()[name = tensor<string, []>("op_2244_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1077799680)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1081076544)))];
tensor<fp16, [1, 77, 1280]> tensor_147_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_v_proj_weight_to_fp16, x = hidden_states_145_cast)[name = tensor<string, []>("tensor_147_cast")];
tensor<int32, [4]> var_2249 = const()[name = tensor<string, []>("op_2249"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2250_cast = reshape(shape = var_2249, x = tensor_147_cast)[name = tensor<string, []>("op_2250_cast")];
tensor<int32, [4]> var_2251_perm_0 = const()[name = tensor<string, []>("op_2251_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2258 = const()[name = tensor<string, []>("op_2258"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2259_cast = reshape(shape = var_2258, x = tensor_149_cast)[name = tensor<string, []>("op_2259_cast")];
tensor<int32, [4]> var_2260_perm_0 = const()[name = tensor<string, []>("op_2260_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2262 = const()[name = tensor<string, []>("op_2262"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_38 = transpose(perm = var_2260_perm_0, x = var_2259_cast)[name = tensor<string, []>("transpose_38")];
tensor<fp16, [20, 77, 64]> query_states_49_cast = reshape(shape = var_2262, x = transpose_38)[name = tensor<string, []>("query_states_49_cast")];
tensor<int32, [3]> var_2264 = const()[name = tensor<string, []>("op_2264"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_40 = transpose(perm = var_2244_perm_0, x = var_2243_cast)[name = tensor<string, []>("transpose_40")];
tensor<fp16, [20, 77, 64]> key_states_99_cast = reshape(shape = var_2264, x = transpose_40)[name = tensor<string, []>("key_states_99_cast")];
tensor<int32, [3]> var_2266 = const()[name = tensor<string, []>("op_2266"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_39 = transpose(perm = var_2251_perm_0, x = var_2250_cast)[name = tensor<string, []>("transpose_39")];
tensor<fp16, [20, 77, 64]> value_states_99_cast = reshape(shape = var_2266, x = transpose_39)[name = tensor<string, []>("value_states_99_cast")];
tensor<int32, [3]> var_2269_perm_0 = const()[name = tensor<string, []>("op_2269_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_145_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_145_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_145_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_37 = transpose(perm = var_2269_perm_0, x = key_states_99_cast)[name = tensor<string, []>("transpose_37")];
tensor<fp16, [20, 77, 77]> attn_weights_145_cast = matmul(transpose_x = attn_weights_145_transpose_x_0, transpose_y = attn_weights_145_transpose_y_0, x = query_states_49_cast, y = transpose_37)[name = tensor<string, []>("attn_weights_145_cast")];
tensor<int32, [4]> var_2271 = const()[name = tensor<string, []>("op_2271"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2272_cast = reshape(shape = var_2271, x = attn_weights_145_cast)[name = tensor<string, []>("op_2272_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_147_cast = add(x = var_2272_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_147_cast")];
tensor<int32, [3]> var_2277 = const()[name = tensor<string, []>("op_2277"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_389_cast = reshape(shape = var_2277, x = attn_weights_147_cast)[name = tensor<string, []>("input_389_cast")];
tensor<fp16, [20, 77, 77]> input_391_cast = softmax(axis = var_5, x = input_389_cast)[name = tensor<string, []>("input_391_cast")];
tensor<bool, []> attn_output_145_transpose_x_0 = const()[name = tensor<string, []>("attn_output_145_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_145_transpose_y_0 = const()[name = tensor<string, []>("attn_output_145_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_145_cast = matmul(transpose_x = attn_output_145_transpose_x_0, transpose_y = attn_output_145_transpose_y_0, x = input_391_cast, y = value_states_99_cast)[name = tensor<string, []>("attn_output_145_cast")];
tensor<int32, [4]> var_2282 = const()[name = tensor<string, []>("op_2282"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_147_cast = reshape(shape = var_2282, x = attn_output_145_cast)[name = tensor<string, []>("attn_output_147_cast")];
tensor<int32, [4]> attn_output_149_perm_0 = const()[name = tensor<string, []>("attn_output_149_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2285 = const()[name = tensor<string, []>("op_2285"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_36 = transpose(perm = attn_output_149_perm_0, x = attn_output_147_cast)[name = tensor<string, []>("transpose_36")];
tensor<fp16, [1, 77, 1280]> input_393_cast = reshape(shape = var_2285, x = transpose_36)[name = tensor<string, []>("input_393_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1081079168)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084356032)))];
tensor<fp16, [1, 77, 1280]> hidden_states_147_cast = linear(bias = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_self_attn_out_proj_weight_to_fp16, x = input_393_cast)[name = tensor<string, []>("hidden_states_147_cast")];
tensor<fp16, [1, 77, 1280]> input_395_cast = add(x = input_387_cast, y = hidden_states_147_cast)[name = tensor<string, []>("input_395_cast")];
tensor<int32, [1]> input_397_axes_0 = const()[name = tensor<string, []>("input_397_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084358656)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084361280)))];
tensor<fp16, [1, 77, 1280]> input_397_cast = layer_norm(axes = input_397_axes_0, beta = text_encoder_text_model_encoder_layers_24_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_24_layer_norm2_weight_to_fp16, x = input_395_cast)[name = tensor<string, []>("input_397_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1084363904)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097471168)))];
tensor<fp16, [1, 77, 5120]> input_399_cast = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc1_weight_to_fp16, x = input_397_cast)[name = tensor<string, []>("input_399_cast")];
tensor<string, []> input_401_mode_0 = const()[name = tensor<string, []>("input_401_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_401_cast = gelu(mode = input_401_mode_0, x = input_399_cast)[name = tensor<string, []>("input_401_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1097481472)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110588736)))];
tensor<fp16, [1, 77, 1280]> hidden_states_149_cast = linear(bias = text_encoder_text_model_encoder_layers_24_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_24_mlp_fc2_weight_to_fp16, x = input_401_cast)[name = tensor<string, []>("hidden_states_149_cast")];
tensor<fp16, [1, 77, 1280]> input_403_cast = add(x = input_395_cast, y = hidden_states_149_cast)[name = tensor<string, []>("input_403_cast")];
tensor<int32, [1]> hidden_states_151_axes_0 = const()[name = tensor<string, []>("hidden_states_151_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110591360)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110593984)))];
tensor<fp16, [1, 77, 1280]> hidden_states_151_cast = layer_norm(axes = hidden_states_151_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm1_weight_to_fp16, x = input_403_cast)[name = tensor<string, []>("hidden_states_151_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1110596608)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113873472)))];
tensor<fp16, [1, 77, 1280]> var_2323_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_q_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("op_2323_cast")];
tensor<fp16, []> var_2324_to_fp16 = const()[name = tensor<string, []>("op_2324_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_155_cast = mul(x = var_2323_cast, y = var_2324_to_fp16)[name = tensor<string, []>("tensor_155_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113876096)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1117152960)))];
tensor<fp16, [1, 77, 1280]> tensor_151_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_k_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_151_cast")];
tensor<int32, [4]> var_2329 = const()[name = tensor<string, []>("op_2329"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2330_cast = reshape(shape = var_2329, x = tensor_151_cast)[name = tensor<string, []>("op_2330_cast")];
tensor<int32, [4]> var_2331_perm_0 = const()[name = tensor<string, []>("op_2331_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1117155584)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120432448)))];
tensor<fp16, [1, 77, 1280]> tensor_153_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_v_proj_weight_to_fp16, x = hidden_states_151_cast)[name = tensor<string, []>("tensor_153_cast")];
tensor<int32, [4]> var_2336 = const()[name = tensor<string, []>("op_2336"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2337_cast = reshape(shape = var_2336, x = tensor_153_cast)[name = tensor<string, []>("op_2337_cast")];
tensor<int32, [4]> var_2338_perm_0 = const()[name = tensor<string, []>("op_2338_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2345 = const()[name = tensor<string, []>("op_2345"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2346_cast = reshape(shape = var_2345, x = tensor_155_cast)[name = tensor<string, []>("op_2346_cast")];
tensor<int32, [4]> var_2347_perm_0 = const()[name = tensor<string, []>("op_2347_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2349 = const()[name = tensor<string, []>("op_2349"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_33 = transpose(perm = var_2347_perm_0, x = var_2346_cast)[name = tensor<string, []>("transpose_33")];
tensor<fp16, [20, 77, 64]> query_states_51_cast = reshape(shape = var_2349, x = transpose_33)[name = tensor<string, []>("query_states_51_cast")];
tensor<int32, [3]> var_2351 = const()[name = tensor<string, []>("op_2351"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_35 = transpose(perm = var_2331_perm_0, x = var_2330_cast)[name = tensor<string, []>("transpose_35")];
tensor<fp16, [20, 77, 64]> key_states_103_cast = reshape(shape = var_2351, x = transpose_35)[name = tensor<string, []>("key_states_103_cast")];
tensor<int32, [3]> var_2353 = const()[name = tensor<string, []>("op_2353"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_34 = transpose(perm = var_2338_perm_0, x = var_2337_cast)[name = tensor<string, []>("transpose_34")];
tensor<fp16, [20, 77, 64]> value_states_103_cast = reshape(shape = var_2353, x = transpose_34)[name = tensor<string, []>("value_states_103_cast")];
tensor<int32, [3]> var_2356_perm_0 = const()[name = tensor<string, []>("op_2356_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_151_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_151_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_151_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_32 = transpose(perm = var_2356_perm_0, x = key_states_103_cast)[name = tensor<string, []>("transpose_32")];
tensor<fp16, [20, 77, 77]> attn_weights_151_cast = matmul(transpose_x = attn_weights_151_transpose_x_0, transpose_y = attn_weights_151_transpose_y_0, x = query_states_51_cast, y = transpose_32)[name = tensor<string, []>("attn_weights_151_cast")];
tensor<int32, [4]> var_2358 = const()[name = tensor<string, []>("op_2358"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2359_cast = reshape(shape = var_2358, x = attn_weights_151_cast)[name = tensor<string, []>("op_2359_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_153_cast = add(x = var_2359_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_153_cast")];
tensor<int32, [3]> var_2364 = const()[name = tensor<string, []>("op_2364"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_405_cast = reshape(shape = var_2364, x = attn_weights_153_cast)[name = tensor<string, []>("input_405_cast")];
tensor<fp16, [20, 77, 77]> input_407_cast = softmax(axis = var_5, x = input_405_cast)[name = tensor<string, []>("input_407_cast")];
tensor<bool, []> attn_output_151_transpose_x_0 = const()[name = tensor<string, []>("attn_output_151_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_151_transpose_y_0 = const()[name = tensor<string, []>("attn_output_151_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_151_cast = matmul(transpose_x = attn_output_151_transpose_x_0, transpose_y = attn_output_151_transpose_y_0, x = input_407_cast, y = value_states_103_cast)[name = tensor<string, []>("attn_output_151_cast")];
tensor<int32, [4]> var_2369 = const()[name = tensor<string, []>("op_2369"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_153_cast = reshape(shape = var_2369, x = attn_output_151_cast)[name = tensor<string, []>("attn_output_153_cast")];
tensor<int32, [4]> attn_output_155_perm_0 = const()[name = tensor<string, []>("attn_output_155_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2372 = const()[name = tensor<string, []>("op_2372"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_31 = transpose(perm = attn_output_155_perm_0, x = attn_output_153_cast)[name = tensor<string, []>("transpose_31")];
tensor<fp16, [1, 77, 1280]> input_409_cast = reshape(shape = var_2372, x = transpose_31)[name = tensor<string, []>("input_409_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120435072)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123711936)))];
tensor<fp16, [1, 77, 1280]> hidden_states_153_cast = linear(bias = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_self_attn_out_proj_weight_to_fp16, x = input_409_cast)[name = tensor<string, []>("hidden_states_153_cast")];
tensor<fp16, [1, 77, 1280]> input_411_cast = add(x = input_403_cast, y = hidden_states_153_cast)[name = tensor<string, []>("input_411_cast")];
tensor<int32, [1]> input_413_axes_0 = const()[name = tensor<string, []>("input_413_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123714560)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123717184)))];
tensor<fp16, [1, 77, 1280]> input_413_cast = layer_norm(axes = input_413_axes_0, beta = text_encoder_text_model_encoder_layers_25_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_25_layer_norm2_weight_to_fp16, x = input_411_cast)[name = tensor<string, []>("input_413_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1123719808)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1136827072)))];
tensor<fp16, [1, 77, 5120]> input_415_cast = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc1_weight_to_fp16, x = input_413_cast)[name = tensor<string, []>("input_415_cast")];
tensor<string, []> input_417_mode_0 = const()[name = tensor<string, []>("input_417_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_417_cast = gelu(mode = input_417_mode_0, x = input_415_cast)[name = tensor<string, []>("input_417_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1136837376)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149944640)))];
tensor<fp16, [1, 77, 1280]> hidden_states_155_cast = linear(bias = text_encoder_text_model_encoder_layers_25_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_25_mlp_fc2_weight_to_fp16, x = input_417_cast)[name = tensor<string, []>("hidden_states_155_cast")];
tensor<fp16, [1, 77, 1280]> input_419_cast = add(x = input_411_cast, y = hidden_states_155_cast)[name = tensor<string, []>("input_419_cast")];
tensor<int32, [1]> hidden_states_157_axes_0 = const()[name = tensor<string, []>("hidden_states_157_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149947264)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149949888)))];
tensor<fp16, [1, 77, 1280]> hidden_states_157_cast = layer_norm(axes = hidden_states_157_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm1_weight_to_fp16, x = input_419_cast)[name = tensor<string, []>("hidden_states_157_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1149952512)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1153229376)))];
tensor<fp16, [1, 77, 1280]> var_2410_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_q_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("op_2410_cast")];
tensor<fp16, []> var_2411_to_fp16 = const()[name = tensor<string, []>("op_2411_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_161_cast = mul(x = var_2410_cast, y = var_2411_to_fp16)[name = tensor<string, []>("tensor_161_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1153232000)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156508864)))];
tensor<fp16, [1, 77, 1280]> tensor_157_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_k_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_157_cast")];
tensor<int32, [4]> var_2416 = const()[name = tensor<string, []>("op_2416"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2417_cast = reshape(shape = var_2416, x = tensor_157_cast)[name = tensor<string, []>("op_2417_cast")];
tensor<int32, [4]> var_2418_perm_0 = const()[name = tensor<string, []>("op_2418_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156511488)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1159788352)))];
tensor<fp16, [1, 77, 1280]> tensor_159_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_v_proj_weight_to_fp16, x = hidden_states_157_cast)[name = tensor<string, []>("tensor_159_cast")];
tensor<int32, [4]> var_2423 = const()[name = tensor<string, []>("op_2423"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2424_cast = reshape(shape = var_2423, x = tensor_159_cast)[name = tensor<string, []>("op_2424_cast")];
tensor<int32, [4]> var_2425_perm_0 = const()[name = tensor<string, []>("op_2425_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2432 = const()[name = tensor<string, []>("op_2432"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2433_cast = reshape(shape = var_2432, x = tensor_161_cast)[name = tensor<string, []>("op_2433_cast")];
tensor<int32, [4]> var_2434_perm_0 = const()[name = tensor<string, []>("op_2434_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2436 = const()[name = tensor<string, []>("op_2436"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_28 = transpose(perm = var_2434_perm_0, x = var_2433_cast)[name = tensor<string, []>("transpose_28")];
tensor<fp16, [20, 77, 64]> query_states_53_cast = reshape(shape = var_2436, x = transpose_28)[name = tensor<string, []>("query_states_53_cast")];
tensor<int32, [3]> var_2438 = const()[name = tensor<string, []>("op_2438"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_30 = transpose(perm = var_2418_perm_0, x = var_2417_cast)[name = tensor<string, []>("transpose_30")];
tensor<fp16, [20, 77, 64]> key_states_107_cast = reshape(shape = var_2438, x = transpose_30)[name = tensor<string, []>("key_states_107_cast")];
tensor<int32, [3]> var_2440 = const()[name = tensor<string, []>("op_2440"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_29 = transpose(perm = var_2425_perm_0, x = var_2424_cast)[name = tensor<string, []>("transpose_29")];
tensor<fp16, [20, 77, 64]> value_states_107_cast = reshape(shape = var_2440, x = transpose_29)[name = tensor<string, []>("value_states_107_cast")];
tensor<int32, [3]> var_2443_perm_0 = const()[name = tensor<string, []>("op_2443_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_157_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_157_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_157_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_27 = transpose(perm = var_2443_perm_0, x = key_states_107_cast)[name = tensor<string, []>("transpose_27")];
tensor<fp16, [20, 77, 77]> attn_weights_157_cast = matmul(transpose_x = attn_weights_157_transpose_x_0, transpose_y = attn_weights_157_transpose_y_0, x = query_states_53_cast, y = transpose_27)[name = tensor<string, []>("attn_weights_157_cast")];
tensor<int32, [4]> var_2445 = const()[name = tensor<string, []>("op_2445"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2446_cast = reshape(shape = var_2445, x = attn_weights_157_cast)[name = tensor<string, []>("op_2446_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_159_cast = add(x = var_2446_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_159_cast")];
tensor<int32, [3]> var_2451 = const()[name = tensor<string, []>("op_2451"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_421_cast = reshape(shape = var_2451, x = attn_weights_159_cast)[name = tensor<string, []>("input_421_cast")];
tensor<fp16, [20, 77, 77]> input_423_cast = softmax(axis = var_5, x = input_421_cast)[name = tensor<string, []>("input_423_cast")];
tensor<bool, []> attn_output_157_transpose_x_0 = const()[name = tensor<string, []>("attn_output_157_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_157_transpose_y_0 = const()[name = tensor<string, []>("attn_output_157_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_157_cast = matmul(transpose_x = attn_output_157_transpose_x_0, transpose_y = attn_output_157_transpose_y_0, x = input_423_cast, y = value_states_107_cast)[name = tensor<string, []>("attn_output_157_cast")];
tensor<int32, [4]> var_2456 = const()[name = tensor<string, []>("op_2456"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_159_cast = reshape(shape = var_2456, x = attn_output_157_cast)[name = tensor<string, []>("attn_output_159_cast")];
tensor<int32, [4]> attn_output_161_perm_0 = const()[name = tensor<string, []>("attn_output_161_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2459 = const()[name = tensor<string, []>("op_2459"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_26 = transpose(perm = attn_output_161_perm_0, x = attn_output_159_cast)[name = tensor<string, []>("transpose_26")];
tensor<fp16, [1, 77, 1280]> input_425_cast = reshape(shape = var_2459, x = transpose_26)[name = tensor<string, []>("input_425_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1159790976)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163067840)))];
tensor<fp16, [1, 77, 1280]> hidden_states_159_cast = linear(bias = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_self_attn_out_proj_weight_to_fp16, x = input_425_cast)[name = tensor<string, []>("hidden_states_159_cast")];
tensor<fp16, [1, 77, 1280]> input_427_cast = add(x = input_419_cast, y = hidden_states_159_cast)[name = tensor<string, []>("input_427_cast")];
tensor<int32, [1]> input_429_axes_0 = const()[name = tensor<string, []>("input_429_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163070464)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163073088)))];
tensor<fp16, [1, 77, 1280]> input_429_cast = layer_norm(axes = input_429_axes_0, beta = text_encoder_text_model_encoder_layers_26_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_26_layer_norm2_weight_to_fp16, x = input_427_cast)[name = tensor<string, []>("input_429_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163075712)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1176182976)))];
tensor<fp16, [1, 77, 5120]> input_431_cast = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc1_weight_to_fp16, x = input_429_cast)[name = tensor<string, []>("input_431_cast")];
tensor<string, []> input_433_mode_0 = const()[name = tensor<string, []>("input_433_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_433_cast = gelu(mode = input_433_mode_0, x = input_431_cast)[name = tensor<string, []>("input_433_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1176193280)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189300544)))];
tensor<fp16, [1, 77, 1280]> hidden_states_161_cast = linear(bias = text_encoder_text_model_encoder_layers_26_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_26_mlp_fc2_weight_to_fp16, x = input_433_cast)[name = tensor<string, []>("hidden_states_161_cast")];
tensor<fp16, [1, 77, 1280]> input_435_cast = add(x = input_427_cast, y = hidden_states_161_cast)[name = tensor<string, []>("input_435_cast")];
tensor<int32, [1]> hidden_states_163_axes_0 = const()[name = tensor<string, []>("hidden_states_163_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189303168)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189305792)))];
tensor<fp16, [1, 77, 1280]> hidden_states_163_cast = layer_norm(axes = hidden_states_163_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm1_weight_to_fp16, x = input_435_cast)[name = tensor<string, []>("hidden_states_163_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1189308416)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192585280)))];
tensor<fp16, [1, 77, 1280]> var_2497_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_q_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("op_2497_cast")];
tensor<fp16, []> var_2498_to_fp16 = const()[name = tensor<string, []>("op_2498_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_167_cast = mul(x = var_2497_cast, y = var_2498_to_fp16)[name = tensor<string, []>("tensor_167_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1192587904)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195864768)))];
tensor<fp16, [1, 77, 1280]> tensor_163_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_k_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_163_cast")];
tensor<int32, [4]> var_2503 = const()[name = tensor<string, []>("op_2503"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2504_cast = reshape(shape = var_2503, x = tensor_163_cast)[name = tensor<string, []>("op_2504_cast")];
tensor<int32, [4]> var_2505_perm_0 = const()[name = tensor<string, []>("op_2505_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195867392)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1199144256)))];
tensor<fp16, [1, 77, 1280]> tensor_165_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_v_proj_weight_to_fp16, x = hidden_states_163_cast)[name = tensor<string, []>("tensor_165_cast")];
tensor<int32, [4]> var_2510 = const()[name = tensor<string, []>("op_2510"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2511_cast = reshape(shape = var_2510, x = tensor_165_cast)[name = tensor<string, []>("op_2511_cast")];
tensor<int32, [4]> var_2512_perm_0 = const()[name = tensor<string, []>("op_2512_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2519 = const()[name = tensor<string, []>("op_2519"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2520_cast = reshape(shape = var_2519, x = tensor_167_cast)[name = tensor<string, []>("op_2520_cast")];
tensor<int32, [4]> var_2521_perm_0 = const()[name = tensor<string, []>("op_2521_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2523 = const()[name = tensor<string, []>("op_2523"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_23 = transpose(perm = var_2521_perm_0, x = var_2520_cast)[name = tensor<string, []>("transpose_23")];
tensor<fp16, [20, 77, 64]> query_states_55_cast = reshape(shape = var_2523, x = transpose_23)[name = tensor<string, []>("query_states_55_cast")];
tensor<int32, [3]> var_2525 = const()[name = tensor<string, []>("op_2525"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_25 = transpose(perm = var_2505_perm_0, x = var_2504_cast)[name = tensor<string, []>("transpose_25")];
tensor<fp16, [20, 77, 64]> key_states_111_cast = reshape(shape = var_2525, x = transpose_25)[name = tensor<string, []>("key_states_111_cast")];
tensor<int32, [3]> var_2527 = const()[name = tensor<string, []>("op_2527"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_24 = transpose(perm = var_2512_perm_0, x = var_2511_cast)[name = tensor<string, []>("transpose_24")];
tensor<fp16, [20, 77, 64]> value_states_111_cast = reshape(shape = var_2527, x = transpose_24)[name = tensor<string, []>("value_states_111_cast")];
tensor<int32, [3]> var_2530_perm_0 = const()[name = tensor<string, []>("op_2530_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_163_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_163_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_163_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_22 = transpose(perm = var_2530_perm_0, x = key_states_111_cast)[name = tensor<string, []>("transpose_22")];
tensor<fp16, [20, 77, 77]> attn_weights_163_cast = matmul(transpose_x = attn_weights_163_transpose_x_0, transpose_y = attn_weights_163_transpose_y_0, x = query_states_55_cast, y = transpose_22)[name = tensor<string, []>("attn_weights_163_cast")];
tensor<int32, [4]> var_2532 = const()[name = tensor<string, []>("op_2532"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2533_cast = reshape(shape = var_2532, x = attn_weights_163_cast)[name = tensor<string, []>("op_2533_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_165_cast = add(x = var_2533_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_165_cast")];
tensor<int32, [3]> var_2538 = const()[name = tensor<string, []>("op_2538"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_437_cast = reshape(shape = var_2538, x = attn_weights_165_cast)[name = tensor<string, []>("input_437_cast")];
tensor<fp16, [20, 77, 77]> input_439_cast = softmax(axis = var_5, x = input_437_cast)[name = tensor<string, []>("input_439_cast")];
tensor<bool, []> attn_output_163_transpose_x_0 = const()[name = tensor<string, []>("attn_output_163_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_163_transpose_y_0 = const()[name = tensor<string, []>("attn_output_163_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_163_cast = matmul(transpose_x = attn_output_163_transpose_x_0, transpose_y = attn_output_163_transpose_y_0, x = input_439_cast, y = value_states_111_cast)[name = tensor<string, []>("attn_output_163_cast")];
tensor<int32, [4]> var_2543 = const()[name = tensor<string, []>("op_2543"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_165_cast = reshape(shape = var_2543, x = attn_output_163_cast)[name = tensor<string, []>("attn_output_165_cast")];
tensor<int32, [4]> attn_output_167_perm_0 = const()[name = tensor<string, []>("attn_output_167_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2546 = const()[name = tensor<string, []>("op_2546"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_21 = transpose(perm = attn_output_167_perm_0, x = attn_output_165_cast)[name = tensor<string, []>("transpose_21")];
tensor<fp16, [1, 77, 1280]> input_441_cast = reshape(shape = var_2546, x = transpose_21)[name = tensor<string, []>("input_441_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1199146880)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202423744)))];
tensor<fp16, [1, 77, 1280]> hidden_states_165_cast = linear(bias = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_self_attn_out_proj_weight_to_fp16, x = input_441_cast)[name = tensor<string, []>("hidden_states_165_cast")];
tensor<fp16, [1, 77, 1280]> input_443_cast = add(x = input_435_cast, y = hidden_states_165_cast)[name = tensor<string, []>("input_443_cast")];
tensor<int32, [1]> input_445_axes_0 = const()[name = tensor<string, []>("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202426368)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202428992)))];
tensor<fp16, [1, 77, 1280]> input_445_cast = layer_norm(axes = input_445_axes_0, beta = text_encoder_text_model_encoder_layers_27_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_27_layer_norm2_weight_to_fp16, x = input_443_cast)[name = tensor<string, []>("input_445_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1202431616)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1215538880)))];
tensor<fp16, [1, 77, 5120]> input_447_cast = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc1_weight_to_fp16, x = input_445_cast)[name = tensor<string, []>("input_447_cast")];
tensor<string, []> input_449_mode_0 = const()[name = tensor<string, []>("input_449_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_449_cast = gelu(mode = input_449_mode_0, x = input_447_cast)[name = tensor<string, []>("input_449_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1215549184)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228656448)))];
tensor<fp16, [1, 77, 1280]> hidden_states_167_cast = linear(bias = text_encoder_text_model_encoder_layers_27_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_27_mlp_fc2_weight_to_fp16, x = input_449_cast)[name = tensor<string, []>("hidden_states_167_cast")];
tensor<fp16, [1, 77, 1280]> input_451_cast = add(x = input_443_cast, y = hidden_states_167_cast)[name = tensor<string, []>("input_451_cast")];
tensor<int32, [1]> hidden_states_169_axes_0 = const()[name = tensor<string, []>("hidden_states_169_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228659072)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228661696)))];
tensor<fp16, [1, 77, 1280]> hidden_states_169_cast = layer_norm(axes = hidden_states_169_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm1_weight_to_fp16, x = input_451_cast)[name = tensor<string, []>("hidden_states_169_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1228664320)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1231941184)))];
tensor<fp16, [1, 77, 1280]> var_2584_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_q_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("op_2584_cast")];
tensor<fp16, []> var_2585_to_fp16 = const()[name = tensor<string, []>("op_2585_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_173_cast = mul(x = var_2584_cast, y = var_2585_to_fp16)[name = tensor<string, []>("tensor_173_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1231943808)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235220672)))];
tensor<fp16, [1, 77, 1280]> tensor_169_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_k_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_169_cast")];
tensor<int32, [4]> var_2590 = const()[name = tensor<string, []>("op_2590"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2591_cast = reshape(shape = var_2590, x = tensor_169_cast)[name = tensor<string, []>("op_2591_cast")];
tensor<int32, [4]> var_2592_perm_0 = const()[name = tensor<string, []>("op_2592_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235223296)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1238500160)))];
tensor<fp16, [1, 77, 1280]> tensor_171_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_v_proj_weight_to_fp16, x = hidden_states_169_cast)[name = tensor<string, []>("tensor_171_cast")];
tensor<int32, [4]> var_2597 = const()[name = tensor<string, []>("op_2597"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2598_cast = reshape(shape = var_2597, x = tensor_171_cast)[name = tensor<string, []>("op_2598_cast")];
tensor<int32, [4]> var_2599_perm_0 = const()[name = tensor<string, []>("op_2599_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2606 = const()[name = tensor<string, []>("op_2606"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2607_cast = reshape(shape = var_2606, x = tensor_173_cast)[name = tensor<string, []>("op_2607_cast")];
tensor<int32, [4]> var_2608_perm_0 = const()[name = tensor<string, []>("op_2608_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2610 = const()[name = tensor<string, []>("op_2610"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_18 = transpose(perm = var_2608_perm_0, x = var_2607_cast)[name = tensor<string, []>("transpose_18")];
tensor<fp16, [20, 77, 64]> query_states_57_cast = reshape(shape = var_2610, x = transpose_18)[name = tensor<string, []>("query_states_57_cast")];
tensor<int32, [3]> var_2612 = const()[name = tensor<string, []>("op_2612"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_20 = transpose(perm = var_2592_perm_0, x = var_2591_cast)[name = tensor<string, []>("transpose_20")];
tensor<fp16, [20, 77, 64]> key_states_115_cast = reshape(shape = var_2612, x = transpose_20)[name = tensor<string, []>("key_states_115_cast")];
tensor<int32, [3]> var_2614 = const()[name = tensor<string, []>("op_2614"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_19 = transpose(perm = var_2599_perm_0, x = var_2598_cast)[name = tensor<string, []>("transpose_19")];
tensor<fp16, [20, 77, 64]> value_states_115_cast = reshape(shape = var_2614, x = transpose_19)[name = tensor<string, []>("value_states_115_cast")];
tensor<int32, [3]> var_2617_perm_0 = const()[name = tensor<string, []>("op_2617_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_169_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_169_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_169_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_17 = transpose(perm = var_2617_perm_0, x = key_states_115_cast)[name = tensor<string, []>("transpose_17")];
tensor<fp16, [20, 77, 77]> attn_weights_169_cast = matmul(transpose_x = attn_weights_169_transpose_x_0, transpose_y = attn_weights_169_transpose_y_0, x = query_states_57_cast, y = transpose_17)[name = tensor<string, []>("attn_weights_169_cast")];
tensor<int32, [4]> var_2619 = const()[name = tensor<string, []>("op_2619"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2620_cast = reshape(shape = var_2619, x = attn_weights_169_cast)[name = tensor<string, []>("op_2620_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_171_cast = add(x = var_2620_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_171_cast")];
tensor<int32, [3]> var_2625 = const()[name = tensor<string, []>("op_2625"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_453_cast = reshape(shape = var_2625, x = attn_weights_171_cast)[name = tensor<string, []>("input_453_cast")];
tensor<fp16, [20, 77, 77]> input_455_cast = softmax(axis = var_5, x = input_453_cast)[name = tensor<string, []>("input_455_cast")];
tensor<bool, []> attn_output_169_transpose_x_0 = const()[name = tensor<string, []>("attn_output_169_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_169_transpose_y_0 = const()[name = tensor<string, []>("attn_output_169_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_169_cast = matmul(transpose_x = attn_output_169_transpose_x_0, transpose_y = attn_output_169_transpose_y_0, x = input_455_cast, y = value_states_115_cast)[name = tensor<string, []>("attn_output_169_cast")];
tensor<int32, [4]> var_2630 = const()[name = tensor<string, []>("op_2630"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_171_cast = reshape(shape = var_2630, x = attn_output_169_cast)[name = tensor<string, []>("attn_output_171_cast")];
tensor<int32, [4]> attn_output_173_perm_0 = const()[name = tensor<string, []>("attn_output_173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2633 = const()[name = tensor<string, []>("op_2633"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_16 = transpose(perm = attn_output_173_perm_0, x = attn_output_171_cast)[name = tensor<string, []>("transpose_16")];
tensor<fp16, [1, 77, 1280]> input_457_cast = reshape(shape = var_2633, x = transpose_16)[name = tensor<string, []>("input_457_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1238502784)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241779648)))];
tensor<fp16, [1, 77, 1280]> hidden_states_171_cast = linear(bias = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_self_attn_out_proj_weight_to_fp16, x = input_457_cast)[name = tensor<string, []>("hidden_states_171_cast")];
tensor<fp16, [1, 77, 1280]> input_459_cast = add(x = input_451_cast, y = hidden_states_171_cast)[name = tensor<string, []>("input_459_cast")];
tensor<int32, [1]> input_461_axes_0 = const()[name = tensor<string, []>("input_461_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241782272)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241784896)))];
tensor<fp16, [1, 77, 1280]> input_461_cast = layer_norm(axes = input_461_axes_0, beta = text_encoder_text_model_encoder_layers_28_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_28_layer_norm2_weight_to_fp16, x = input_459_cast)[name = tensor<string, []>("input_461_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1241787520)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254894784)))];
tensor<fp16, [1, 77, 5120]> input_463_cast = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc1_weight_to_fp16, x = input_461_cast)[name = tensor<string, []>("input_463_cast")];
tensor<string, []> input_465_mode_0 = const()[name = tensor<string, []>("input_465_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_465_cast = gelu(mode = input_465_mode_0, x = input_463_cast)[name = tensor<string, []>("input_465_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254905088)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268012352)))];
tensor<fp16, [1, 77, 1280]> hidden_states_173_cast = linear(bias = text_encoder_text_model_encoder_layers_28_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_28_mlp_fc2_weight_to_fp16, x = input_465_cast)[name = tensor<string, []>("hidden_states_173_cast")];
tensor<fp16, [1, 77, 1280]> input_467_cast = add(x = input_459_cast, y = hidden_states_173_cast)[name = tensor<string, []>("input_467_cast")];
tensor<int32, [1]> hidden_states_175_axes_0 = const()[name = tensor<string, []>("hidden_states_175_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268014976)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268017600)))];
tensor<fp16, [1, 77, 1280]> hidden_states_175_cast = layer_norm(axes = hidden_states_175_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm1_weight_to_fp16, x = input_467_cast)[name = tensor<string, []>("hidden_states_175_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268020224)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1271297088)))];
tensor<fp16, [1, 77, 1280]> var_2671_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_q_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("op_2671_cast")];
tensor<fp16, []> var_2672_to_fp16 = const()[name = tensor<string, []>("op_2672_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_179_cast = mul(x = var_2671_cast, y = var_2672_to_fp16)[name = tensor<string, []>("tensor_179_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1271299712)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274576576)))];
tensor<fp16, [1, 77, 1280]> tensor_175_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_k_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_175_cast")];
tensor<int32, [4]> var_2677 = const()[name = tensor<string, []>("op_2677"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2678_cast = reshape(shape = var_2677, x = tensor_175_cast)[name = tensor<string, []>("op_2678_cast")];
tensor<int32, [4]> var_2679_perm_0 = const()[name = tensor<string, []>("op_2679_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1274579200)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1277856064)))];
tensor<fp16, [1, 77, 1280]> tensor_177_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_v_proj_weight_to_fp16, x = hidden_states_175_cast)[name = tensor<string, []>("tensor_177_cast")];
tensor<int32, [4]> var_2684 = const()[name = tensor<string, []>("op_2684"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2685_cast = reshape(shape = var_2684, x = tensor_177_cast)[name = tensor<string, []>("op_2685_cast")];
tensor<int32, [4]> var_2686_perm_0 = const()[name = tensor<string, []>("op_2686_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2693 = const()[name = tensor<string, []>("op_2693"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2694_cast = reshape(shape = var_2693, x = tensor_179_cast)[name = tensor<string, []>("op_2694_cast")];
tensor<int32, [4]> var_2695_perm_0 = const()[name = tensor<string, []>("op_2695_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2697 = const()[name = tensor<string, []>("op_2697"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_13 = transpose(perm = var_2695_perm_0, x = var_2694_cast)[name = tensor<string, []>("transpose_13")];
tensor<fp16, [20, 77, 64]> query_states_59_cast = reshape(shape = var_2697, x = transpose_13)[name = tensor<string, []>("query_states_59_cast")];
tensor<int32, [3]> var_2699 = const()[name = tensor<string, []>("op_2699"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_15 = transpose(perm = var_2679_perm_0, x = var_2678_cast)[name = tensor<string, []>("transpose_15")];
tensor<fp16, [20, 77, 64]> key_states_119_cast = reshape(shape = var_2699, x = transpose_15)[name = tensor<string, []>("key_states_119_cast")];
tensor<int32, [3]> var_2701 = const()[name = tensor<string, []>("op_2701"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_14 = transpose(perm = var_2686_perm_0, x = var_2685_cast)[name = tensor<string, []>("transpose_14")];
tensor<fp16, [20, 77, 64]> value_states_119_cast = reshape(shape = var_2701, x = transpose_14)[name = tensor<string, []>("value_states_119_cast")];
tensor<int32, [3]> var_2704_perm_0 = const()[name = tensor<string, []>("op_2704_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_175_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_175_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_175_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_12 = transpose(perm = var_2704_perm_0, x = key_states_119_cast)[name = tensor<string, []>("transpose_12")];
tensor<fp16, [20, 77, 77]> attn_weights_175_cast = matmul(transpose_x = attn_weights_175_transpose_x_0, transpose_y = attn_weights_175_transpose_y_0, x = query_states_59_cast, y = transpose_12)[name = tensor<string, []>("attn_weights_175_cast")];
tensor<int32, [4]> var_2706 = const()[name = tensor<string, []>("op_2706"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2707_cast = reshape(shape = var_2706, x = attn_weights_175_cast)[name = tensor<string, []>("op_2707_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_177_cast = add(x = var_2707_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_177_cast")];
tensor<int32, [3]> var_2712 = const()[name = tensor<string, []>("op_2712"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_469_cast = reshape(shape = var_2712, x = attn_weights_177_cast)[name = tensor<string, []>("input_469_cast")];
tensor<fp16, [20, 77, 77]> input_471_cast = softmax(axis = var_5, x = input_469_cast)[name = tensor<string, []>("input_471_cast")];
tensor<bool, []> attn_output_175_transpose_x_0 = const()[name = tensor<string, []>("attn_output_175_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_175_transpose_y_0 = const()[name = tensor<string, []>("attn_output_175_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_175_cast = matmul(transpose_x = attn_output_175_transpose_x_0, transpose_y = attn_output_175_transpose_y_0, x = input_471_cast, y = value_states_119_cast)[name = tensor<string, []>("attn_output_175_cast")];
tensor<int32, [4]> var_2717 = const()[name = tensor<string, []>("op_2717"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_177_cast = reshape(shape = var_2717, x = attn_output_175_cast)[name = tensor<string, []>("attn_output_177_cast")];
tensor<int32, [4]> attn_output_179_perm_0 = const()[name = tensor<string, []>("attn_output_179_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2720 = const()[name = tensor<string, []>("op_2720"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_11 = transpose(perm = attn_output_179_perm_0, x = attn_output_177_cast)[name = tensor<string, []>("transpose_11")];
tensor<fp16, [1, 77, 1280]> input_473_cast = reshape(shape = var_2720, x = transpose_11)[name = tensor<string, []>("input_473_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1277858688)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281135552)))];
tensor<fp16, [1, 77, 1280]> hidden_states_177_cast = linear(bias = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_self_attn_out_proj_weight_to_fp16, x = input_473_cast)[name = tensor<string, []>("hidden_states_177_cast")];
tensor<fp16, [1, 77, 1280]> input_475_cast = add(x = input_467_cast, y = hidden_states_177_cast)[name = tensor<string, []>("input_475_cast")];
tensor<int32, [1]> input_477_axes_0 = const()[name = tensor<string, []>("input_477_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281138176)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281140800)))];
tensor<fp16, [1, 77, 1280]> input_477_cast = layer_norm(axes = input_477_axes_0, beta = text_encoder_text_model_encoder_layers_29_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_29_layer_norm2_weight_to_fp16, x = input_475_cast)[name = tensor<string, []>("input_477_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1281143424)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1294250688)))];
tensor<fp16, [1, 77, 5120]> input_479_cast = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc1_weight_to_fp16, x = input_477_cast)[name = tensor<string, []>("input_479_cast")];
tensor<string, []> input_481_mode_0 = const()[name = tensor<string, []>("input_481_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_481_cast = gelu(mode = input_481_mode_0, x = input_479_cast)[name = tensor<string, []>("input_481_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1294260992)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307368256)))];
tensor<fp16, [1, 77, 1280]> hidden_states_179_cast = linear(bias = text_encoder_text_model_encoder_layers_29_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_29_mlp_fc2_weight_to_fp16, x = input_481_cast)[name = tensor<string, []>("hidden_states_179_cast")];
tensor<fp16, [1, 77, 1280]> input_483_cast = add(x = input_475_cast, y = hidden_states_179_cast)[name = tensor<string, []>("input_483_cast")];
tensor<int32, [1]> hidden_states_181_axes_0 = const()[name = tensor<string, []>("hidden_states_181_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307370880)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307373504)))];
tensor<fp16, [1, 77, 1280]> hidden_states_181_cast = layer_norm(axes = hidden_states_181_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm1_weight_to_fp16, x = input_483_cast)[name = tensor<string, []>("hidden_states_181_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307376128)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310652992)))];
tensor<fp16, [1, 77, 1280]> var_2758_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_q_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("op_2758_cast")];
tensor<fp16, []> var_2759_to_fp16 = const()[name = tensor<string, []>("op_2759_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_185_cast = mul(x = var_2758_cast, y = var_2759_to_fp16)[name = tensor<string, []>("tensor_185_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310655616)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1313932480)))];
tensor<fp16, [1, 77, 1280]> tensor_181_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_k_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_181_cast")];
tensor<int32, [4]> var_2764 = const()[name = tensor<string, []>("op_2764"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2765_cast = reshape(shape = var_2764, x = tensor_181_cast)[name = tensor<string, []>("op_2765_cast")];
tensor<int32, [4]> var_2766_perm_0 = const()[name = tensor<string, []>("op_2766_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1313935104)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317211968)))];
tensor<fp16, [1, 77, 1280]> tensor_183_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_v_proj_weight_to_fp16, x = hidden_states_181_cast)[name = tensor<string, []>("tensor_183_cast")];
tensor<int32, [4]> var_2771 = const()[name = tensor<string, []>("op_2771"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2772_cast = reshape(shape = var_2771, x = tensor_183_cast)[name = tensor<string, []>("op_2772_cast")];
tensor<int32, [4]> var_2773_perm_0 = const()[name = tensor<string, []>("op_2773_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2780 = const()[name = tensor<string, []>("op_2780"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2781_cast = reshape(shape = var_2780, x = tensor_185_cast)[name = tensor<string, []>("op_2781_cast")];
tensor<int32, [4]> var_2782_perm_0 = const()[name = tensor<string, []>("op_2782_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2784 = const()[name = tensor<string, []>("op_2784"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_8 = transpose(perm = var_2782_perm_0, x = var_2781_cast)[name = tensor<string, []>("transpose_8")];
tensor<fp16, [20, 77, 64]> query_states_61_cast = reshape(shape = var_2784, x = transpose_8)[name = tensor<string, []>("query_states_61_cast")];
tensor<int32, [3]> var_2786 = const()[name = tensor<string, []>("op_2786"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_10 = transpose(perm = var_2766_perm_0, x = var_2765_cast)[name = tensor<string, []>("transpose_10")];
tensor<fp16, [20, 77, 64]> key_states_123_cast = reshape(shape = var_2786, x = transpose_10)[name = tensor<string, []>("key_states_123_cast")];
tensor<int32, [3]> var_2788 = const()[name = tensor<string, []>("op_2788"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_9 = transpose(perm = var_2773_perm_0, x = var_2772_cast)[name = tensor<string, []>("transpose_9")];
tensor<fp16, [20, 77, 64]> value_states_123_cast = reshape(shape = var_2788, x = transpose_9)[name = tensor<string, []>("value_states_123_cast")];
tensor<int32, [3]> var_2791_perm_0 = const()[name = tensor<string, []>("op_2791_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_181_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_181_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_181_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_7 = transpose(perm = var_2791_perm_0, x = key_states_123_cast)[name = tensor<string, []>("transpose_7")];
tensor<fp16, [20, 77, 77]> attn_weights_181_cast = matmul(transpose_x = attn_weights_181_transpose_x_0, transpose_y = attn_weights_181_transpose_y_0, x = query_states_61_cast, y = transpose_7)[name = tensor<string, []>("attn_weights_181_cast")];
tensor<int32, [4]> var_2793 = const()[name = tensor<string, []>("op_2793"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2794_cast = reshape(shape = var_2793, x = attn_weights_181_cast)[name = tensor<string, []>("op_2794_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_183_cast = add(x = var_2794_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_183_cast")];
tensor<int32, [3]> var_2799 = const()[name = tensor<string, []>("op_2799"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_485_cast = reshape(shape = var_2799, x = attn_weights_183_cast)[name = tensor<string, []>("input_485_cast")];
tensor<fp16, [20, 77, 77]> input_487_cast = softmax(axis = var_5, x = input_485_cast)[name = tensor<string, []>("input_487_cast")];
tensor<bool, []> attn_output_181_transpose_x_0 = const()[name = tensor<string, []>("attn_output_181_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_181_transpose_y_0 = const()[name = tensor<string, []>("attn_output_181_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_181_cast = matmul(transpose_x = attn_output_181_transpose_x_0, transpose_y = attn_output_181_transpose_y_0, x = input_487_cast, y = value_states_123_cast)[name = tensor<string, []>("attn_output_181_cast")];
tensor<int32, [4]> var_2804 = const()[name = tensor<string, []>("op_2804"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_183_cast = reshape(shape = var_2804, x = attn_output_181_cast)[name = tensor<string, []>("attn_output_183_cast")];
tensor<int32, [4]> attn_output_185_perm_0 = const()[name = tensor<string, []>("attn_output_185_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2807 = const()[name = tensor<string, []>("op_2807"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_6 = transpose(perm = attn_output_185_perm_0, x = attn_output_183_cast)[name = tensor<string, []>("transpose_6")];
tensor<fp16, [1, 77, 1280]> input_489_cast = reshape(shape = var_2807, x = transpose_6)[name = tensor<string, []>("input_489_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317214592)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320491456)))];
tensor<fp16, [1, 77, 1280]> hidden_states_183_cast = linear(bias = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_self_attn_out_proj_weight_to_fp16, x = input_489_cast)[name = tensor<string, []>("hidden_states_183_cast")];
tensor<fp16, [1, 77, 1280]> input_491_cast = add(x = input_483_cast, y = hidden_states_183_cast)[name = tensor<string, []>("input_491_cast")];
tensor<int32, [1]> input_493_axes_0 = const()[name = tensor<string, []>("input_493_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320494080)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320496704)))];
tensor<fp16, [1, 77, 1280]> input_493_cast = layer_norm(axes = input_493_axes_0, beta = text_encoder_text_model_encoder_layers_30_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_30_layer_norm2_weight_to_fp16, x = input_491_cast)[name = tensor<string, []>("input_493_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1320499328)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333606592)))];
tensor<fp16, [1, 77, 5120]> input_495_cast = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc1_weight_to_fp16, x = input_493_cast)[name = tensor<string, []>("input_495_cast")];
tensor<string, []> input_497_mode_0 = const()[name = tensor<string, []>("input_497_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_497_cast = gelu(mode = input_497_mode_0, x = input_495_cast)[name = tensor<string, []>("input_497_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333616896)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346724160)))];
tensor<fp16, [1, 77, 1280]> hidden_states_185_cast = linear(bias = text_encoder_text_model_encoder_layers_30_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_30_mlp_fc2_weight_to_fp16, x = input_497_cast)[name = tensor<string, []>("hidden_states_185_cast")];
tensor<fp16, [1, 77, 1280]> hidden_embeds = add(x = input_491_cast, y = hidden_states_185_cast)[name = tensor<string, []>("input_499_cast")];
tensor<int32, [1]> hidden_states_187_axes_0 = const()[name = tensor<string, []>("hidden_states_187_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346726784)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346729408)))];
tensor<fp16, [1, 77, 1280]> hidden_states_187_cast = layer_norm(axes = hidden_states_187_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm1_weight_to_fp16, x = hidden_embeds)[name = tensor<string, []>("hidden_states_187_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1346732032)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350008896)))];
tensor<fp16, [1, 77, 1280]> var_2845_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_q_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("op_2845_cast")];
tensor<fp16, []> var_2846_to_fp16 = const()[name = tensor<string, []>("op_2846_to_fp16"), val = tensor<fp16, []>(0x1p-3)];
tensor<fp16, [1, 77, 1280]> tensor_cast = mul(x = var_2845_cast, y = var_2846_to_fp16)[name = tensor<string, []>("tensor_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350011520)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1353288384)))];
tensor<fp16, [1, 77, 1280]> tensor_187_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_k_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_187_cast")];
tensor<int32, [4]> var_2851 = const()[name = tensor<string, []>("op_2851"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2852_cast = reshape(shape = var_2851, x = tensor_187_cast)[name = tensor<string, []>("op_2852_cast")];
tensor<int32, [4]> var_2853_perm_0 = const()[name = tensor<string, []>("op_2853_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1353291008)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1356567872)))];
tensor<fp16, [1, 77, 1280]> tensor_189_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_v_proj_weight_to_fp16, x = hidden_states_187_cast)[name = tensor<string, []>("tensor_189_cast")];
tensor<int32, [4]> var_2858 = const()[name = tensor<string, []>("op_2858"), val = tensor<int32, [4]>([1, -1, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2859_cast = reshape(shape = var_2858, x = tensor_189_cast)[name = tensor<string, []>("op_2859_cast")];
tensor<int32, [4]> var_2860_perm_0 = const()[name = tensor<string, []>("op_2860_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [4]> var_2867 = const()[name = tensor<string, []>("op_2867"), val = tensor<int32, [4]>([1, 77, 20, 64])];
tensor<fp16, [1, 77, 20, 64]> var_2868_cast = reshape(shape = var_2867, x = tensor_cast)[name = tensor<string, []>("op_2868_cast")];
tensor<int32, [4]> var_2869_perm_0 = const()[name = tensor<string, []>("op_2869_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2871 = const()[name = tensor<string, []>("op_2871"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_3 = transpose(perm = var_2869_perm_0, x = var_2868_cast)[name = tensor<string, []>("transpose_3")];
tensor<fp16, [20, 77, 64]> query_states_cast = reshape(shape = var_2871, x = transpose_3)[name = tensor<string, []>("query_states_cast")];
tensor<int32, [3]> var_2873 = const()[name = tensor<string, []>("op_2873"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_5 = transpose(perm = var_2853_perm_0, x = var_2852_cast)[name = tensor<string, []>("transpose_5")];
tensor<fp16, [20, 77, 64]> key_states_cast = reshape(shape = var_2873, x = transpose_5)[name = tensor<string, []>("key_states_cast")];
tensor<int32, [3]> var_2875 = const()[name = tensor<string, []>("op_2875"), val = tensor<int32, [3]>([20, -1, 64])];
tensor<fp16, [1, 20, 77, 64]> transpose_4 = transpose(perm = var_2860_perm_0, x = var_2859_cast)[name = tensor<string, []>("transpose_4")];
tensor<fp16, [20, 77, 64]> value_states_cast = reshape(shape = var_2875, x = transpose_4)[name = tensor<string, []>("value_states_cast")];
tensor<int32, [3]> var_2878_perm_0 = const()[name = tensor<string, []>("op_2878_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<bool, []> attn_weights_187_transpose_x_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_weights_187_transpose_y_0 = const()[name = tensor<string, []>("attn_weights_187_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 64, 77]> transpose_2 = transpose(perm = var_2878_perm_0, x = key_states_cast)[name = tensor<string, []>("transpose_2")];
tensor<fp16, [20, 77, 77]> attn_weights_187_cast = matmul(transpose_x = attn_weights_187_transpose_x_0, transpose_y = attn_weights_187_transpose_y_0, x = query_states_cast, y = transpose_2)[name = tensor<string, []>("attn_weights_187_cast")];
tensor<int32, [4]> var_2880 = const()[name = tensor<string, []>("op_2880"), val = tensor<int32, [4]>([1, 20, 77, 77])];
tensor<fp16, [1, 20, 77, 77]> var_2881_cast = reshape(shape = var_2880, x = attn_weights_187_cast)[name = tensor<string, []>("op_2881_cast")];
tensor<fp16, [1, 20, 77, 77]> attn_weights_189_cast = add(x = var_2881_cast, y = var_58_to_fp16)[name = tensor<string, []>("attn_weights_189_cast")];
tensor<int32, [3]> var_2886 = const()[name = tensor<string, []>("op_2886"), val = tensor<int32, [3]>([20, 77, 77])];
tensor<fp16, [20, 77, 77]> input_501_cast = reshape(shape = var_2886, x = attn_weights_189_cast)[name = tensor<string, []>("input_501_cast")];
tensor<fp16, [20, 77, 77]> input_503_cast = softmax(axis = var_5, x = input_501_cast)[name = tensor<string, []>("input_503_cast")];
tensor<bool, []> attn_output_187_transpose_x_0 = const()[name = tensor<string, []>("attn_output_187_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> attn_output_187_transpose_y_0 = const()[name = tensor<string, []>("attn_output_187_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [20, 77, 64]> attn_output_187_cast = matmul(transpose_x = attn_output_187_transpose_x_0, transpose_y = attn_output_187_transpose_y_0, x = input_503_cast, y = value_states_cast)[name = tensor<string, []>("attn_output_187_cast")];
tensor<int32, [4]> var_2891 = const()[name = tensor<string, []>("op_2891"), val = tensor<int32, [4]>([1, 20, 77, 64])];
tensor<fp16, [1, 20, 77, 64]> attn_output_189_cast = reshape(shape = var_2891, x = attn_output_187_cast)[name = tensor<string, []>("attn_output_189_cast")];
tensor<int32, [4]> attn_output_perm_0 = const()[name = tensor<string, []>("attn_output_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> var_2894 = const()[name = tensor<string, []>("op_2894"), val = tensor<int32, [3]>([1, 77, 1280])];
tensor<fp16, [1, 77, 20, 64]> transpose_1 = transpose(perm = attn_output_perm_0, x = attn_output_189_cast)[name = tensor<string, []>("transpose_1")];
tensor<fp16, [1, 77, 1280]> input_505_cast = reshape(shape = var_2894, x = transpose_1)[name = tensor<string, []>("input_505_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1356570496)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359847360)))];
tensor<fp16, [1, 77, 1280]> hidden_states_189_cast = linear(bias = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_self_attn_out_proj_weight_to_fp16, x = input_505_cast)[name = tensor<string, []>("hidden_states_189_cast")];
tensor<fp16, [1, 77, 1280]> input_507_cast = add(x = hidden_embeds, y = hidden_states_189_cast)[name = tensor<string, []>("input_507_cast")];
tensor<int32, [1]> input_509_axes_0 = const()[name = tensor<string, []>("input_509_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359849984)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359852608)))];
tensor<fp16, [1, 77, 1280]> input_509_cast = layer_norm(axes = input_509_axes_0, beta = text_encoder_text_model_encoder_layers_31_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_31_layer_norm2_weight_to_fp16, x = input_507_cast)[name = tensor<string, []>("input_509_cast")];
tensor<fp16, [5120, 1280]> text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [5120, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359855232)))];
tensor<fp16, [5120]> text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1372962496)))];
tensor<fp16, [1, 77, 5120]> input_511_cast = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc1_weight_to_fp16, x = input_509_cast)[name = tensor<string, []>("input_511_cast")];
tensor<string, []> input_513_mode_0 = const()[name = tensor<string, []>("input_513_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 77, 5120]> input_513_cast = gelu(mode = input_513_mode_0, x = input_511_cast)[name = tensor<string, []>("input_513_cast")];
tensor<fp16, [1280, 5120]> text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [1280, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1372972800)))];
tensor<fp16, [1280]> text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386080064)))];
tensor<fp16, [1, 77, 1280]> hidden_states_cast = linear(bias = text_encoder_text_model_encoder_layers_31_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_31_mlp_fc2_weight_to_fp16, x = input_513_cast)[name = tensor<string, []>("hidden_states_cast")];
tensor<fp16, [1, 77, 1280]> input_515_cast = add(x = input_507_cast, y = hidden_states_cast)[name = tensor<string, []>("input_515_cast")];
tensor<int32, [1]> last_hidden_state_axes_0 = const()[name = tensor<string, []>("last_hidden_state_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386082688)))];
tensor<fp16, [1280]> text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386085312)))];
tensor<fp16, [1, 77, 1280]> last_hidden_state_cast = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_515_cast)[name = tensor<string, []>("last_hidden_state_cast")];
tensor<int32, [1]> var_2922 = const()[name = tensor<string, []>("op_2922"), val = tensor<int32, [1]>([0])];
tensor<int32, [1]> var_2924 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_1326)[name = tensor<string, []>("op_2924")];
tensor<int32, []> stack_0_axis_0 = const()[name = tensor<string, []>("stack_0_axis_0"), val = tensor<int32, []>(1)];
tensor<int32, [1, 2]> stack_0 = stack(axis = stack_0_axis_0, values = (var_2922, var_2924))[name = tensor<string, []>("stack_0")];
tensor<int32, []> input_transpose_batch_dims_0 = const()[name = tensor<string, []>("input_transpose_batch_dims_0"), val = tensor<int32, []>(0)];
tensor<fp16, [1, 1280]> input_transpose_cast = gather_nd(batch_dims = input_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor<string, []>("input_transpose_cast")];
tensor<fp16, [1280, 1280]> text_encoder_text_projection_weight_to_fp16 = const()[name = tensor<string, []>("text_encoder_text_projection_weight_to_fp16"), val = tensor<fp16, [1280, 1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1386087936)))];
tensor<fp16, [1280]> var_2931_bias_0_to_fp16 = const()[name = tensor<string, []>("op_2931_bias_0_to_fp16"), val = tensor<fp16, [1280]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1389364800)))];
tensor<fp16, [1, 1280]> pooled_outputs = linear(bias = var_2931_bias_0_to_fp16, weight = text_encoder_text_projection_weight_to_fp16, x = input_transpose_cast)[name = tensor<string, []>("op_2931_cast")];
} -> (hidden_embeds, pooled_outputs);
} |