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 2272 2273 2274 2275 2276 2277 2278 2279 2280 2281 2282 2283 2284 2285 2286 2287 2288 2289 2290 2291 2292 2293 2294 2295 2296 2297 2298 2299 2300 2301 2302 2303 2304 2305 2306 2307 2308 2309 2310 2311 2312 2313 2314 2315 2316 2317 2318 2319 2320 2321 2322 2323 2324 2325 2326 2327 2328 2329 2330 2331 2332 2333 2334 2335 2336 2337 2338 2339 2340 2341 2342 2343 2344 2345 2346 2347 2348 2349 2350 2351 2352 2353 2354 2355 2356 2357 2358 2359 2360 2361 2362 2363 2364 2365 2366 2367 2368 2369 2370 2371 2372 2373 2374 2375 2376 2377 2378 2379 2380 2381 2382 2383 2384 2385 2386 2387 2388 2389 2390 2391 2392 2393 2394 2395 2396 2397 2398 2399 2400 2401 2402 2403 2404 2405 2406 2407 2408 2409 2410 2411 2412 2413 2414 2415 2416 2417 2418 2419 2420 2421 2422 2423 2424 2425 2426 2427 2428 2429 2430 2431 2432 2433 2434 2435 2436 2437 2438 2439 2440 2441 2442 2443 2444 2445 2446 2447 2448 2449
/// Containers to hold repeated fundamental values. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct BytesList { #[prost(bytes, repeated, tag="1")] pub value: ::std::vec::Vec<std::vec::Vec<u8>>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FloatList { #[prost(float, repeated, tag="1")] pub value: ::std::vec::Vec<f32>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Int64List { #[prost(int64, repeated, tag="1")] pub value: ::std::vec::Vec<i64>, } /// Containers for non-sequential data. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Feature { /// Each feature can be exactly one kind. #[prost(oneof="feature::Kind", tags="1, 2, 3")] pub kind: ::std::option::Option<feature::Kind>, } pub mod feature { /// Each feature can be exactly one kind. #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Kind { #[prost(message, tag="1")] BytesList(super::BytesList), #[prost(message, tag="2")] FloatList(super::FloatList), #[prost(message, tag="3")] Int64List(super::Int64List), } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Features { /// Map from feature name to feature. #[prost(map="string, message", tag="1")] pub feature: ::std::collections::HashMap<std::string::String, Feature>, } /// Containers for sequential data. /// /// A FeatureList contains lists of Features. These may hold zero or more /// Feature values. /// /// FeatureLists are organized into categories by name. The FeatureLists message /// contains the mapping from name to FeatureList. /// #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FeatureList { #[prost(message, repeated, tag="1")] pub feature: ::std::vec::Vec<Feature>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FeatureLists { /// Map from feature name to feature list. #[prost(map="string, message", tag="1")] pub feature_list: ::std::collections::HashMap<std::string::String, FeatureList>, } // An Example is a mostly-normalized data format for storing data for // training and inference. It contains a key-value store (features); where // each key (string) maps to a Feature message (which is oneof packed BytesList, // FloatList, or Int64List). This flexible and compact format allows the // storage of large amounts of typed data, but requires that the data shape // and use be determined by the configuration files and parsers that are used to // read and write this format. That is, the Example is mostly *not* a // self-describing format. In TensorFlow, Examples are read in row-major // format, so any configuration that describes data with rank-2 or above // should keep this in mind. For example, to store an M x N matrix of Bytes, // the BytesList must contain M*N bytes, with M rows of N contiguous values // each. That is, the BytesList value must store the matrix as: // .... row 0 .... .... row 1 .... // ........... // ... row M-1 .... // // An Example for a movie recommendation application: // features { // feature { // key: "age" // value { float_list { // value: 29.0 // }} // } // feature { // key: "movie" // value { bytes_list { // value: "The Shawshank Redemption" // value: "Fight Club" // }} // } // feature { // key: "movie_ratings" // value { float_list { // value: 9.0 // value: 9.7 // }} // } // feature { // key: "suggestion" // value { bytes_list { // value: "Inception" // }} // } // # Note that this feature exists to be used as a label in training. // # E.g., if training a logistic regression model to predict purchase // # probability in our learning tool we would set the label feature to // # "suggestion_purchased". // feature { // key: "suggestion_purchased" // value { float_list { // value: 1.0 // }} // } // # Similar to "suggestion_purchased" above this feature exists to be used // # as a label in training. // # E.g., if training a linear regression model to predict purchase // # price in our learning tool we would set the label feature to // # "purchase_price". // feature { // key: "purchase_price" // value { float_list { // value: 9.99 // }} // } // } // // A conformant Example data set obeys the following conventions: // - If a Feature K exists in one example with data type T, it must be of // type T in all other examples when present. It may be omitted. // - The number of instances of Feature K list data may vary across examples, // depending on the requirements of the model. // - If a Feature K doesn't exist in an example, a K-specific default will be // used, if configured. // - If a Feature K exists in an example but contains no items, the intent // is considered to be an empty tensor and no default will be used. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Example { #[prost(message, optional, tag="1")] pub features: ::std::option::Option<Features>, } // A SequenceExample is an Example representing one or more sequences, and // some context. The context contains features which apply to the entire // example. The feature_lists contain a key, value map where each key is // associated with a repeated set of Features (a FeatureList). // A FeatureList thus represents the values of a feature identified by its key // over time / frames. // // Below is a SequenceExample for a movie recommendation application recording a // sequence of ratings by a user. The time-independent features ("locale", // "age", "favorites") describing the user are part of the context. The sequence // of movies the user rated are part of the feature_lists. For each movie in the // sequence we have information on its name and actors and the user's rating. // This information is recorded in three separate feature_list(s). // In the example below there are only two movies. All three feature_list(s), // namely "movie_ratings", "movie_names", and "actors" have a feature value for // both movies. Note, that "actors" is itself a bytes_list with multiple // strings per movie. // // context: { // feature: { // key : "locale" // value: { // bytes_list: { // value: [ "pt_BR" ] // } // } // } // feature: { // key : "age" // value: { // float_list: { // value: [ 19.0 ] // } // } // } // feature: { // key : "favorites" // value: { // bytes_list: { // value: [ "Majesty Rose", "Savannah Outen", "One Direction" ] // } // } // } // } // feature_lists: { // feature_list: { // key : "movie_ratings" // value: { // feature: { // float_list: { // value: [ 4.5 ] // } // } // feature: { // float_list: { // value: [ 5.0 ] // } // } // } // } // feature_list: { // key : "movie_names" // value: { // feature: { // bytes_list: { // value: [ "The Shawshank Redemption" ] // } // } // feature: { // bytes_list: { // value: [ "Fight Club" ] // } // } // } // } // feature_list: { // key : "actors" // value: { // feature: { // bytes_list: { // value: [ "Tim Robbins", "Morgan Freeman" ] // } // } // feature: { // bytes_list: { // value: [ "Brad Pitt", "Edward Norton", "Helena Bonham Carter" ] // } // } // } // } // } // // A conformant SequenceExample data set obeys the following conventions: // // Context: // - All conformant context features K must obey the same conventions as // a conformant Example's features (see above). // Feature lists: // - A FeatureList L may be missing in an example; it is up to the // parser configuration to determine if this is allowed or considered // an empty list (zero length). // - If a FeatureList L exists, it may be empty (zero length). // - If a FeatureList L is non-empty, all features within the FeatureList // must have the same data type T. Even across SequenceExamples, the type T // of the FeatureList identified by the same key must be the same. An entry // without any values may serve as an empty feature. // - If a FeatureList L is non-empty, it is up to the parser configuration // to determine if all features within the FeatureList must // have the same size. The same holds for this FeatureList across multiple // examples. // - For sequence modeling, e.g.: // http://colah.github.io/posts/2015-08-Understanding-LSTMs/ // https://github.com/tensorflow/nmt // the feature lists represent a sequence of frames. // In this scenario, all FeatureLists in a SequenceExample have the same // number of Feature messages, so that the ith element in each FeatureList // is part of the ith frame (or time step). // Examples of conformant and non-conformant examples' FeatureLists: // // Conformant FeatureLists: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // // Non-conformant FeatureLists (mismatched types): // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { int64_list: { value: [ 5 ] } } } // } } // // Conditionally conformant FeatureLists, the parser configuration determines // if the feature sizes must match: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0, 6.0 ] } } } // } } // // Conformant pair of SequenceExample // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // and: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } // feature: { float_list: { value: [ 2.0 ] } } } // } } // // Conformant pair of SequenceExample // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // and: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { } // } } // // Conditionally conformant pair of SequenceExample, the parser configuration // determines if the second feature_lists is consistent (zero-length) or // invalid (missing "movie_ratings"): // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // and: // feature_lists: { } // // Non-conformant pair of SequenceExample (mismatched types) // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // and: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { int64_list: { value: [ 4 ] } } // feature: { int64_list: { value: [ 5 ] } } // feature: { int64_list: { value: [ 2 ] } } } // } } // // Conditionally conformant pair of SequenceExample; the parser configuration // determines if the feature sizes must match: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.5 ] } } // feature: { float_list: { value: [ 5.0 ] } } } // } } // and: // feature_lists: { feature_list: { // key: "movie_ratings" // value: { feature: { float_list: { value: [ 4.0 ] } } // feature: { float_list: { value: [ 5.0, 3.0 ] } } // } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct SequenceExample { #[prost(message, optional, tag="1")] pub context: ::std::option::Option<Features>, #[prost(message, optional, tag="2")] pub feature_lists: ::std::option::Option<FeatureLists>, } /// Dimensions of a tensor. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TensorShapeProto { /// Dimensions of the tensor, such as {"input", 30}, {"output", 40} /// for a 30 x 40 2D tensor. If an entry has size -1, this /// corresponds to a dimension of unknown size. The names are /// optional. /// /// The order of entries in "dim" matters: It indicates the layout of the /// values in the tensor in-memory representation. /// /// The first entry in "dim" is the outermost dimension used to layout the /// values, the last entry is the innermost dimension. This matches the /// in-memory layout of RowMajor Eigen tensors. /// /// If "dim.size()" > 0, "unknown_rank" must be false. #[prost(message, repeated, tag="2")] pub dim: ::std::vec::Vec<tensor_shape_proto::Dim>, /// If true, the number of dimensions in the shape is unknown. /// /// If true, "dim.size()" must be 0. #[prost(bool, tag="3")] pub unknown_rank: bool, } pub mod tensor_shape_proto { /// One dimension of the tensor. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Dim { /// Size of the tensor in that dimension. /// This value must be >= -1, but values of -1 are reserved for "unknown" /// shapes (values of -1 mean "unknown" dimension). Certain wrappers /// that work with TensorShapeProto may fail at runtime when deserializing /// a TensorShapeProto containing a dim value of -1. #[prost(int64, tag="1")] pub size: i64, /// Optional name of the tensor dimension. #[prost(string, tag="2")] pub name: std::string::String, } } /// (== suppress_warning documentation-presence ==) /// LINT.IfChange #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum DataType { /// Not a legal value for DataType. Used to indicate a DataType field /// has not been set. DtInvalid = 0, /// Data types that all computation devices are expected to be /// capable to support. DtFloat = 1, DtDouble = 2, DtInt32 = 3, DtUint8 = 4, DtInt16 = 5, DtInt8 = 6, DtString = 7, /// Single-precision complex DtComplex64 = 8, DtInt64 = 9, DtBool = 10, /// Quantized int8 DtQint8 = 11, /// Quantized uint8 DtQuint8 = 12, /// Quantized int32 DtQint32 = 13, /// Float32 truncated to 16 bits. Only for cast ops. DtBfloat16 = 14, /// Quantized int16 DtQint16 = 15, /// Quantized uint16 DtQuint16 = 16, DtUint16 = 17, /// Double-precision complex DtComplex128 = 18, DtHalf = 19, DtResource = 20, /// Arbitrary C++ data types DtVariant = 21, DtUint32 = 22, DtUint64 = 23, /// Do not use! These are only for parameters. Every enum above /// should have a corresponding value below (verified by types_test). DtFloatRef = 101, DtDoubleRef = 102, DtInt32Ref = 103, DtUint8Ref = 104, DtInt16Ref = 105, DtInt8Ref = 106, DtStringRef = 107, DtComplex64Ref = 108, DtInt64Ref = 109, DtBoolRef = 110, DtQint8Ref = 111, DtQuint8Ref = 112, DtQint32Ref = 113, DtBfloat16Ref = 114, DtQint16Ref = 115, DtQuint16Ref = 116, DtUint16Ref = 117, DtComplex128Ref = 118, DtHalfRef = 119, DtResourceRef = 120, DtVariantRef = 121, DtUint32Ref = 122, DtUint64Ref = 123, } /// Protocol buffer representing a handle to a tensorflow resource. Handles are /// not valid across executions, but can be serialized back and forth from within /// a single run. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ResourceHandleProto { /// Unique name for the device containing the resource. #[prost(string, tag="1")] pub device: std::string::String, /// Container in which this resource is placed. #[prost(string, tag="2")] pub container: std::string::String, /// Unique name of this resource. #[prost(string, tag="3")] pub name: std::string::String, /// Hash code for the type of the resource. Is only valid in the same device /// and in the same execution. #[prost(uint64, tag="4")] pub hash_code: u64, /// For debug-only, the name of the type pointed to by this handle, if /// available. #[prost(string, tag="5")] pub maybe_type_name: std::string::String, /// Data types and shapes for the underlying resource. #[prost(message, repeated, tag="6")] pub dtypes_and_shapes: ::std::vec::Vec<resource_handle_proto::DtypeAndShape>, /// A set of devices containing the resource. If empty, the resource only /// exists on `device`. #[prost(string, repeated, tag="7")] pub allowed_devices: ::std::vec::Vec<std::string::String>, } pub mod resource_handle_proto { /// Protocol buffer representing a pair of (data type, tensor shape). #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct DtypeAndShape { #[prost(enumeration="super::DataType", tag="1")] pub dtype: i32, #[prost(message, optional, tag="2")] pub shape: ::std::option::Option<super::TensorShapeProto>, } } /// Protocol buffer representing a tensor. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TensorProto { #[prost(enumeration="DataType", tag="1")] pub dtype: i32, /// Shape of the tensor. TODO(touts): sort out the 0-rank issues. #[prost(message, optional, tag="2")] pub tensor_shape: ::std::option::Option<TensorShapeProto>, // Only one of the representations below is set, one of "tensor_contents" and // the "xxx_val" attributes. We are not using oneof because as oneofs cannot // contain repeated fields it would require another extra set of messages. /// Version number. /// /// In version 0, if the "repeated xxx" representations contain only one /// element, that element is repeated to fill the shape. This makes it easy /// to represent a constant Tensor with a single value. #[prost(int32, tag="3")] pub version_number: i32, /// Serialized raw tensor content from either Tensor::AsProtoTensorContent or /// memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation /// can be used for all tensor types. The purpose of this representation is to /// reduce serialization overhead during RPC call by avoiding serialization of /// many repeated small items. #[prost(bytes, tag="4")] pub tensor_content: std::vec::Vec<u8>, // Type specific representations that make it easy to create tensor protos in // all languages. Only the representation corresponding to "dtype" can // be set. The values hold the flattened representation of the tensor in // row major order. /// DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll /// have some pointless zero padding for each value here. #[prost(int32, repeated, tag="13")] pub half_val: ::std::vec::Vec<i32>, /// DT_FLOAT. #[prost(float, repeated, tag="5")] pub float_val: ::std::vec::Vec<f32>, /// DT_DOUBLE. #[prost(double, repeated, tag="6")] pub double_val: ::std::vec::Vec<f64>, /// DT_INT32, DT_INT16, DT_INT8, DT_UINT8. #[prost(int32, repeated, tag="7")] pub int_val: ::std::vec::Vec<i32>, /// DT_STRING #[prost(bytes, repeated, tag="8")] pub string_val: ::std::vec::Vec<std::vec::Vec<u8>>, /// DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real /// and imaginary parts of i-th single precision complex. #[prost(float, repeated, tag="9")] pub scomplex_val: ::std::vec::Vec<f32>, /// DT_INT64 #[prost(int64, repeated, tag="10")] pub int64_val: ::std::vec::Vec<i64>, /// DT_BOOL #[prost(bool, repeated, tag="11")] pub bool_val: ::std::vec::Vec<bool>, /// DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real /// and imaginary parts of i-th double precision complex. #[prost(double, repeated, tag="12")] pub dcomplex_val: ::std::vec::Vec<f64>, /// DT_RESOURCE #[prost(message, repeated, tag="14")] pub resource_handle_val: ::std::vec::Vec<ResourceHandleProto>, /// DT_VARIANT #[prost(message, repeated, tag="15")] pub variant_val: ::std::vec::Vec<VariantTensorDataProto>, /// DT_UINT32 #[prost(uint32, repeated, tag="16")] pub uint32_val: ::std::vec::Vec<u32>, /// DT_UINT64 #[prost(uint64, repeated, tag="17")] pub uint64_val: ::std::vec::Vec<u64>, } /// Protocol buffer representing the serialization format of DT_VARIANT tensors. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct VariantTensorDataProto { /// Name of the type of objects being serialized. #[prost(string, tag="1")] pub type_name: std::string::String, /// Portions of the object that are not Tensors. #[prost(bytes, tag="2")] pub metadata: std::vec::Vec<u8>, /// Tensors contained within objects being serialized. #[prost(message, repeated, tag="3")] pub tensors: ::std::vec::Vec<TensorProto>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct VarLenFeatureProto { #[prost(enumeration="DataType", tag="1")] pub dtype: i32, #[prost(string, tag="2")] pub values_output_tensor_name: std::string::String, #[prost(string, tag="3")] pub indices_output_tensor_name: std::string::String, #[prost(string, tag="4")] pub shapes_output_tensor_name: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FixedLenFeatureProto { #[prost(enumeration="DataType", tag="1")] pub dtype: i32, #[prost(message, optional, tag="2")] pub shape: ::std::option::Option<TensorShapeProto>, #[prost(message, optional, tag="3")] pub default_value: ::std::option::Option<TensorProto>, #[prost(string, tag="4")] pub values_output_tensor_name: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FeatureConfiguration { #[prost(oneof="feature_configuration::Config", tags="1, 2")] pub config: ::std::option::Option<feature_configuration::Config>, } pub mod feature_configuration { #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Config { #[prost(message, tag="1")] FixedLenFeature(super::FixedLenFeatureProto), #[prost(message, tag="2")] VarLenFeature(super::VarLenFeatureProto), } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ExampleParserConfiguration { #[prost(map="string, message", tag="1")] pub feature_map: ::std::collections::HashMap<std::string::String, FeatureConfiguration>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AllocationDescription { /// Total number of bytes requested #[prost(int64, tag="1")] pub requested_bytes: i64, /// Total number of bytes allocated if known #[prost(int64, tag="2")] pub allocated_bytes: i64, /// Name of the allocator used #[prost(string, tag="3")] pub allocator_name: std::string::String, /// Identifier of the allocated buffer if known #[prost(int64, tag="4")] pub allocation_id: i64, /// Set if this tensor only has one remaining reference #[prost(bool, tag="5")] pub has_single_reference: bool, /// Address of the allocation. #[prost(uint64, tag="6")] pub ptr: u64, } /// Protocol buffer representing the value for an attr used to configure an Op. /// Comment indicates the corresponding attr type. Only the field matching the /// attr type may be filled. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AttrValue { #[prost(oneof="attr_value::Value", tags="2, 3, 4, 5, 6, 7, 8, 1, 10, 9")] pub value: ::std::option::Option<attr_value::Value>, } pub mod attr_value { /// LINT.IfChange #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ListValue { /// "list(string)" #[prost(bytes, repeated, tag="2")] pub s: ::std::vec::Vec<std::vec::Vec<u8>>, /// "list(int)" #[prost(int64, repeated, tag="3")] pub i: ::std::vec::Vec<i64>, /// "list(float)" #[prost(float, repeated, tag="4")] pub f: ::std::vec::Vec<f32>, /// "list(bool)" #[prost(bool, repeated, tag="5")] pub b: ::std::vec::Vec<bool>, /// "list(type)" #[prost(enumeration="super::DataType", repeated, tag="6")] pub r#type: ::std::vec::Vec<i32>, /// "list(shape)" #[prost(message, repeated, tag="7")] pub shape: ::std::vec::Vec<super::TensorShapeProto>, /// "list(tensor)" #[prost(message, repeated, tag="8")] pub tensor: ::std::vec::Vec<super::TensorProto>, /// "list(attr)" #[prost(message, repeated, tag="9")] pub func: ::std::vec::Vec<super::NameAttrList>, } #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Value { /// "string" #[prost(bytes, tag="2")] S(std::vec::Vec<u8>), /// "int" #[prost(int64, tag="3")] I(i64), /// "float" #[prost(float, tag="4")] F(f32), /// "bool" #[prost(bool, tag="5")] B(bool), /// "type" #[prost(enumeration="super::DataType", tag="6")] Type(i32), /// "shape" #[prost(message, tag="7")] Shape(super::TensorShapeProto), /// "tensor" #[prost(message, tag="8")] Tensor(super::TensorProto), /// any "list(...)" #[prost(message, tag="1")] List(ListValue), /// "func" represents a function. func.name is a function's name or /// a primitive op's name. func.attr.first is the name of an attr /// defined for that function. func.attr.second is the value for /// that attr in the instantiation. #[prost(message, tag="10")] Func(super::NameAttrList), /// This is a placeholder only used in nodes defined inside a /// function. It indicates the attr value will be supplied when /// the function is instantiated. For example, let us suppose a /// node "N" in function "FN". "N" has an attr "A" with value /// placeholder = "foo". When FN is instantiated with attr "foo" /// set to "bar", the instantiated node N's attr A will have been /// given the value "bar". #[prost(string, tag="9")] Placeholder(std::string::String), } } /// A list of attr names and their values. The whole list is attached /// with a string name. E.g., MatMul[T=float]. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct NameAttrList { #[prost(string, tag="1")] pub name: std::string::String, #[prost(map="string, message", tag="2")] pub attr: ::std::collections::HashMap<std::string::String, AttrValue>, } /// Used to specify and override the default API & behavior in the /// generated code for client languages, from what you would get from /// the OpDef alone. There will be a set of ApiDefs that are common /// to all client languages, and another set per client language. /// The per-client-language ApiDefs will inherit values from the /// common ApiDefs which it can either replace or modify. /// /// We separate the API definition from the OpDef so we can evolve the /// API while remaining backwards compatible when interpretting old /// graphs. Overrides go in an "api_def.pbtxt" file with a text-format /// ApiDefs message. /// /// WARNING: Be *very* careful changing the API for any existing op -- /// you can change the semantics of existing code. These changes may /// need to wait until a major release of TensorFlow to avoid breaking /// our compatibility promises. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ApiDef { /// Name of the op (in the OpDef) to specify the API for. #[prost(string, tag="1")] pub graph_op_name: std::string::String, /// If this op is deprecated, set deprecation message to the message /// that should be logged when this op is used. /// The message should indicate alternative op to use, if any. #[prost(string, tag="12")] pub deprecation_message: std::string::String, /// Major version when the op will be deleted. For e.g. set this /// value to 2 if op API should be removed in TensorFlow 2.0 and /// deprecated in versions before that. #[prost(int32, tag="13")] pub deprecation_version: i32, #[prost(enumeration="api_def::Visibility", tag="2")] pub visibility: i32, #[prost(message, repeated, tag="3")] pub endpoint: ::std::vec::Vec<api_def::Endpoint>, #[prost(message, repeated, tag="4")] pub in_arg: ::std::vec::Vec<api_def::Arg>, #[prost(message, repeated, tag="5")] pub out_arg: ::std::vec::Vec<api_def::Arg>, /// List of original in_arg names to specify new argument order. /// Length of arg_order should be either empty to keep current order /// or match size of in_arg. #[prost(string, repeated, tag="11")] pub arg_order: ::std::vec::Vec<std::string::String>, #[prost(message, repeated, tag="6")] pub attr: ::std::vec::Vec<api_def::Attr>, /// One-line human-readable description of what the Op does. #[prost(string, tag="7")] pub summary: std::string::String, /// Additional, longer human-readable description of what the Op does. #[prost(string, tag="8")] pub description: std::string::String, /// Modify an existing/inherited description by adding text to the beginning /// or end. #[prost(string, tag="9")] pub description_prefix: std::string::String, #[prost(string, tag="10")] pub description_suffix: std::string::String, } pub mod api_def { /// If you specify any endpoint, this will replace all of the /// inherited endpoints. The first endpoint should be the /// "canonical" endpoint, and should not be deprecated (unless all /// endpoints are deprecated). #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Endpoint { /// Name should be either like "CamelCaseName" or /// "Package.CamelCaseName". Client-language-specific ApiDefs may /// use a snake_case convention instead of CamelCase. #[prost(string, tag="1")] pub name: std::string::String, /// Set if this endpoint is deprecated. If set to true, a message suggesting /// to use a non-deprecated endpoint instead will be printed. If all /// endpoints are deprecated, set deprecation_message in ApiDef instead. #[prost(bool, tag="3")] pub deprecated: bool, /// Major version when an endpoint will be deleted. For e.g. set this /// value to 2 if endpoint should be removed in TensorFlow 2.0 and /// deprecated in versions before that. #[prost(int32, tag="4")] pub deprecation_version: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Arg { #[prost(string, tag="1")] pub name: std::string::String, /// Change the name used to access this arg in the API from what /// is used in the GraphDef. Note that these names in `backticks` /// will also be replaced in the summary & description fields. #[prost(string, tag="2")] pub rename_to: std::string::String, /// Note: this will replace any inherited arg doc. There is no /// current way of modifying arg descriptions (other than replacing /// them entirely) as can be done with op descriptions. #[prost(string, tag="3")] pub description: std::string::String, } /// Description of the graph-construction-time configuration of this /// Op. That is to say, this describes the attr fields that will /// be specified in the NodeDef. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Attr { #[prost(string, tag="1")] pub name: std::string::String, /// Change the name used to access this attr in the API from what /// is used in the GraphDef. Note that these names in `backticks` /// will also be replaced in the summary & description fields. #[prost(string, tag="2")] pub rename_to: std::string::String, /// Specify a new default value to use for this attr. This default /// will be used when creating new graphs, as opposed to the /// default in the OpDef, which will be used when interpreting old /// GraphDefs. #[prost(message, optional, tag="3")] pub default_value: ::std::option::Option<super::AttrValue>, /// Note: this will replace any inherited attr doc, there is no current /// way of modifying attr descriptions as can be done with op descriptions. #[prost(string, tag="4")] pub description: std::string::String, } #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Visibility { /// Normally this is "VISIBLE" unless you are inheriting a /// different value from another ApiDef. DefaultVisibility = 0, /// Publicly visible in the API. Visible = 1, /// Do not include this op in the generated API. If visibility is /// set to 'SKIP', other fields are ignored for this op. Skip = 2, /// Hide this op by putting it into an internal namespace (or whatever /// is appropriate in the target language). Hidden = 3, } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ApiDefs { #[prost(message, repeated, tag="1")] pub op: ::std::vec::Vec<ApiDef>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct CostGraphDef { #[prost(message, repeated, tag="1")] pub node: ::std::vec::Vec<cost_graph_def::Node>, #[prost(message, repeated, tag="2")] pub cost: ::std::vec::Vec<cost_graph_def::AggregatedCost>, } pub mod cost_graph_def { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Node { /// The name of the node. Names are globally unique. #[prost(string, tag="1")] pub name: std::string::String, /// The device of the node. Can be empty if the node is mapped to the /// default partition or partitioning hasn't been run yet. #[prost(string, tag="2")] pub device: std::string::String, /// The id of the node. Node ids are only unique inside a partition. #[prost(int32, tag="3")] pub id: i32, #[prost(message, repeated, tag="4")] pub input_info: ::std::vec::Vec<node::InputInfo>, #[prost(message, repeated, tag="5")] pub output_info: ::std::vec::Vec<node::OutputInfo>, /// Temporary memory used by this node. #[prost(int64, tag="6")] pub temporary_memory_size: i64, /// Persistent memory used by this node. #[prost(int64, tag="12")] pub persistent_memory_size: i64, #[prost(int64, tag="10")] pub host_temp_memory_size: i64, #[prost(int64, tag="11")] pub device_temp_memory_size: i64, #[prost(int64, tag="16")] pub device_persistent_memory_size: i64, /// Estimate of the computational cost of this node, in microseconds. #[prost(int64, tag="9")] pub compute_cost: i64, /// Analytical estimate of the computational cost of this node, in /// microseconds. #[prost(int64, tag="14")] pub compute_time: i64, /// Analytical estimate of the memory access cost of this node, in /// microseconds. #[prost(int64, tag="15")] pub memory_time: i64, /// If true, the output is permanent: it can't be discarded, because this /// node is part of the "final output". Nodes may depend on final nodes. #[prost(bool, tag="7")] pub is_final: bool, /// Ids of the control inputs for this node. #[prost(int32, repeated, tag="8")] pub control_input: ::std::vec::Vec<i32>, /// Are the costs inaccurate? #[prost(bool, tag="17")] pub inaccurate: bool, } pub mod node { /// Inputs of this node. They must be executed before this node can be /// executed. An input is a particular output of another node, specified /// by the node id and the output index. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct InputInfo { #[prost(int32, tag="1")] pub preceding_node: i32, #[prost(int32, tag="2")] pub preceding_port: i32, } /// Outputs of this node. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct OutputInfo { #[prost(int64, tag="1")] pub size: i64, /// If >= 0, the output is an alias of an input. Note that an alias input /// may itself be an alias. The algorithm will therefore need to follow /// those pointers. #[prost(int64, tag="2")] pub alias_input_port: i64, #[prost(message, optional, tag="3")] pub shape: ::std::option::Option<super::super::TensorShapeProto>, #[prost(enumeration="super::super::DataType", tag="4")] pub dtype: i32, } } /// Total cost of this graph, typically used for balancing decisions. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AggregatedCost { /// Aggregated cost value. #[prost(float, tag="1")] pub cost: f32, /// Aggregated cost dimension (e.g. 'memory', 'compute', 'network'). #[prost(string, tag="2")] pub dimension: std::string::String, } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct InterconnectLink { #[prost(int32, tag="1")] pub device_id: i32, #[prost(string, tag="2")] pub r#type: std::string::String, #[prost(int32, tag="3")] pub strength: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct LocalLinks { #[prost(message, repeated, tag="1")] pub link: ::std::vec::Vec<InterconnectLink>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct DeviceLocality { /// Optional bus locality of device. Default value of 0 means /// no specific locality. Specific localities are indexed from 1. #[prost(int32, tag="1")] pub bus_id: i32, /// Optional NUMA locality of device. #[prost(int32, tag="2")] pub numa_node: i32, /// Optional local interconnect links to other devices. #[prost(message, optional, tag="3")] pub links: ::std::option::Option<LocalLinks>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct DeviceAttributes { /// Fully specified name of the device within a cluster. #[prost(string, tag="1")] pub name: std::string::String, /// String representation of device_type. #[prost(string, tag="2")] pub device_type: std::string::String, /// Memory capacity of device in bytes. #[prost(int64, tag="4")] pub memory_limit: i64, /// Platform-specific data about device that may be useful /// for supporting efficient data transfers. #[prost(message, optional, tag="5")] pub locality: ::std::option::Option<DeviceLocality>, /// A device is assigned a global unique number each time it is /// initialized. "incarnation" should never be 0. #[prost(fixed64, tag="6")] pub incarnation: u64, /// String representation of the physical device that this device maps to. #[prost(string, tag="7")] pub physical_device_desc: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct NodeDef { /// The name given to this operator. Used for naming inputs, /// logging, visualization, etc. Unique within a single GraphDef. /// Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_>./]*". #[prost(string, tag="1")] pub name: std::string::String, /// The operation name. There may be custom parameters in attrs. /// Op names starting with an underscore are reserved for internal use. #[prost(string, tag="2")] pub op: std::string::String, /// Each input is "node:src_output" with "node" being a string name and /// "src_output" indicating which output tensor to use from "node". If /// "src_output" is 0 the ":0" suffix can be omitted. Regular inputs /// may optionally be followed by control inputs that have the format /// "^node". #[prost(string, repeated, tag="3")] pub input: ::std::vec::Vec<std::string::String>, /// A (possibly partial) specification for the device on which this /// node should be placed. /// The expected syntax for this string is as follows: /// /// DEVICE_SPEC ::= PARTIAL_SPEC /// /// PARTIAL_SPEC ::= ("/" CONSTRAINT) * /// CONSTRAINT ::= ("job:" JOB_NAME) /// | ("replica:" [1-9][0-9]*) /// | ("task:" [1-9][0-9]*) /// | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") ) /// /// Valid values for this string include: /// * "/job:worker/replica:0/task:1/device:GPU:3" (full specification) /// * "/job:worker/device:GPU:3" (partial specification) /// * "" (no specification) /// /// If the constraints do not resolve to a single device (or if this /// field is empty or not present), the runtime will attempt to /// choose a device automatically. #[prost(string, tag="4")] pub device: std::string::String, /// Operation-specific graph-construction-time configuration. /// Note that this should include all attrs defined in the /// corresponding OpDef, including those with a value matching /// the default -- this allows the default to change and makes /// NodeDefs easier to interpret on their own. However, if /// an attr with a default is not specified in this list, the /// default will be used. /// The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and /// one of the names from the corresponding OpDef's attr field). /// The values must have a type matching the corresponding OpDef /// attr's type field. /// TODO(josh11b): Add some examples here showing best practices. #[prost(map="string, message", tag="5")] pub attr: ::std::collections::HashMap<std::string::String, AttrValue>, /// This stores debug information associated with the node. #[prost(message, optional, tag="6")] pub experimental_debug_info: ::std::option::Option<node_def::ExperimentalDebugInfo>, } pub mod node_def { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ExperimentalDebugInfo { /// Opaque string inserted into error messages created by the runtime. /// /// This is intended to store the list of names of the nodes from the /// original graph that this node was derived. For example if this node, say /// C, was result of a fusion of 2 nodes A and B, then 'original_node' would /// be {A, B}. This information can be used to map errors originating at the /// current node to some top level source code. #[prost(string, repeated, tag="1")] pub original_node_names: ::std::vec::Vec<std::string::String>, /// This is intended to store the list of names of the functions from the /// original graph that this node was derived. For example if this node, say /// C, was result of a fusion of node A in function FA and node B in function /// FB, then `original_funcs` would be {FA, FB}. If the node is in the top /// level graph, the `original_func` is empty. This information, with the /// `original_node_names` can be used to map errors originating at the /// current ndoe to some top level source code. #[prost(string, repeated, tag="2")] pub original_func_names: ::std::vec::Vec<std::string::String>, } } /// Defines an operation. A NodeDef in a GraphDef specifies an Op by /// using the "op" field which should match the name of a OpDef. /// LINT.IfChange #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct OpDef { /// Op names starting with an underscore are reserved for internal use. /// Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9>_]*". #[prost(string, tag="1")] pub name: std::string::String, /// Description of the input(s). #[prost(message, repeated, tag="2")] pub input_arg: ::std::vec::Vec<op_def::ArgDef>, /// Description of the output(s). #[prost(message, repeated, tag="3")] pub output_arg: ::std::vec::Vec<op_def::ArgDef>, /// Named control outputs for this operation. Useful only for composite /// operations (i.e. functions) which want to name different control outputs. #[prost(string, repeated, tag="20")] pub control_output: ::std::vec::Vec<std::string::String>, #[prost(message, repeated, tag="4")] pub attr: ::std::vec::Vec<op_def::AttrDef>, /// Optional deprecation based on GraphDef versions. #[prost(message, optional, tag="8")] pub deprecation: ::std::option::Option<OpDeprecation>, /// One-line human-readable description of what the Op does. #[prost(string, tag="5")] pub summary: std::string::String, /// Additional, longer human-readable description of what the Op does. #[prost(string, tag="6")] pub description: std::string::String, // ------------------------------------------------------------------------- // Which optimizations this operation can participate in. /// True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs) #[prost(bool, tag="18")] pub is_commutative: bool, /// If is_aggregate is true, then this operation accepts N >= 2 /// inputs and produces 1 output all of the same type. Should be /// associative and commutative, and produce output with the same /// shape as the input. The optimizer may replace an aggregate op /// taking input from multiple devices with a tree of aggregate ops /// that aggregate locally within each device (and possibly within /// groups of nearby devices) before communicating. /// TODO(josh11b): Implement that optimization. /// /// for things like add #[prost(bool, tag="16")] pub is_aggregate: bool, // Other optimizations go here, like // can_alias_input, rewrite_when_output_unused, partitioning_strategy, etc. // ------------------------------------------------------------------------- // Optimization constraints. /// Ops are marked as stateful if their behavior depends on some state beyond /// their input tensors (e.g. variable reading op) or if they have /// a side-effect (e.g. printing or asserting ops). Equivalently, stateless ops /// must always produce the same output for the same input and have /// no side-effects. /// /// By default Ops may be moved between devices. Stateful ops should /// either not be moved, or should only be moved if that state can also /// be moved (e.g. via some sort of save / restore). /// Stateful ops are guaranteed to never be optimized away by Common /// Subexpression Elimination (CSE). /// /// for things like variables, queue #[prost(bool, tag="17")] pub is_stateful: bool, // ------------------------------------------------------------------------- // Non-standard options. /// By default, all inputs to an Op must be initialized Tensors. Ops /// that may initialize tensors for the first time should set this /// field to true, to allow the Op to take an uninitialized Tensor as /// input. /// /// for Assign, etc. #[prost(bool, tag="19")] pub allows_uninitialized_input: bool, } pub mod op_def { /// For describing inputs and outputs. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ArgDef { /// Name for the input/output. Should match the regexp "[a-z][a-z0-9_]*". #[prost(string, tag="1")] pub name: std::string::String, /// Human readable description. #[prost(string, tag="2")] pub description: std::string::String, /// Describes the type of one or more tensors that are accepted/produced /// by this input/output arg. The only legal combinations are: /// * For a single tensor: either the "type" field is set or the /// "type_attr" field is set to the name of an attr with type "type". /// * For a sequence of tensors with the same type: the "number_attr" /// field will be set to the name of an attr with type "int", and /// either the "type" or "type_attr" field will be set as for /// single tensors. /// * For a sequence of tensors, the "type_list_attr" field will be set /// to the name of an attr with type "list(type)". #[prost(enumeration="super::DataType", tag="3")] pub r#type: i32, /// if specified, attr must have type "type" #[prost(string, tag="4")] pub type_attr: std::string::String, /// if specified, attr must have type "int" #[prost(string, tag="5")] pub number_attr: std::string::String, /// If specified, attr must have type "list(type)", and none of /// type, type_attr, and number_attr may be specified. #[prost(string, tag="6")] pub type_list_attr: std::string::String, /// For inputs: if true, the inputs are required to be refs. /// By default, inputs can be either refs or non-refs. /// For outputs: if true, outputs are refs, otherwise they are not. #[prost(bool, tag="16")] pub is_ref: bool, } /// Description of the graph-construction-time configuration of this /// Op. That is to say, this describes the attr fields that will /// be specified in the NodeDef. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AttrDef { /// A descriptive name for the argument. May be used, e.g. by the /// Python client, as a keyword argument name, and so should match /// the regexp "[a-z][a-z0-9_]+". #[prost(string, tag="1")] pub name: std::string::String, /// One of the type names from attr_value.proto ("string", "list(string)", /// "int", etc.). #[prost(string, tag="2")] pub r#type: std::string::String, /// A reasonable default for this attribute if the user does not supply /// a value. If not specified, the user must supply a value. #[prost(message, optional, tag="3")] pub default_value: ::std::option::Option<super::AttrValue>, /// Human-readable description. #[prost(string, tag="4")] pub description: std::string::String, // TODO(josh11b): bool is_optional? // --- Constraints --- // These constraints are only in effect if specified. Default is no // constraints. /// For type == "int", this is a minimum value. For "list(___)" /// types, this is the minimum length. #[prost(bool, tag="5")] pub has_minimum: bool, #[prost(int64, tag="6")] pub minimum: i64, /// The set of allowed values. Has type that is the "list" version /// of the "type" field above (uses the "list" field of AttrValue). /// If type == "type" or "list(type)" above, then the "type" field /// of "allowed_values.list" has the set of allowed DataTypes. /// If type == "string" or "list(string)", then the "s" field of /// "allowed_values.list" has the set of allowed strings. #[prost(message, optional, tag="7")] pub allowed_values: ::std::option::Option<super::AttrValue>, } } /// Information about version-dependent deprecation of an op #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct OpDeprecation { /// First GraphDef version at which the op is disallowed. #[prost(int32, tag="1")] pub version: i32, /// Explanation of why it was deprecated and what to use instead. #[prost(string, tag="2")] pub explanation: std::string::String, } /// A collection of OpDefs #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct OpList { #[prost(message, repeated, tag="1")] pub op: ::std::vec::Vec<OpDef>, } /// A library is a set of named functions. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FunctionDefLibrary { #[prost(message, repeated, tag="1")] pub function: ::std::vec::Vec<FunctionDef>, #[prost(message, repeated, tag="2")] pub gradient: ::std::vec::Vec<GradientDef>, } /// A function can be instantiated when the runtime can bind every attr /// with a value. When a GraphDef has a call to a function, it must /// have binding for every attr defined in the signature. /// /// TODO(zhifengc): /// * device spec, etc. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct FunctionDef { /// The definition of the function's name, arguments, return values, /// attrs etc. #[prost(message, optional, tag="1")] pub signature: ::std::option::Option<OpDef>, /// Attributes specific to this function definition. #[prost(map="string, message", tag="5")] pub attr: ::std::collections::HashMap<std::string::String, AttrValue>, #[prost(map="uint32, message", tag="7")] pub arg_attr: ::std::collections::HashMap<u32, function_def::ArgAttrs>, /// Unique IDs for each resource argument, used to track aliasing resources. If /// Argument A and Argument B alias each other, then /// resource_arg_unique_ids[A.index] == resource_arg_unique_ids[B.index]. /// /// If this field is empty, none of the arguments could alias; otherwise, every /// resource argument should have an entry in this field. /// /// When instantiated, the unique IDs will be attached to the _Arg nodes' /// "_resource_arg_unique_id" attribute. #[prost(map="uint32, uint32", tag="8")] pub resource_arg_unique_id: ::std::collections::HashMap<u32, u32>, // In both of the following fields, there is the need to specify an // output that is used as either the input to another node (in // `node_def`) or as a return value of the function (in `ret`). // Unlike the NodeDefs in GraphDef, we need to be able to specify a // list in some cases (instead of just single outputs). Also, we // need to be able to deal with lists of unknown length (so the // output index may not be known at function definition time). So // we use the following format instead: // * "fun_in" where "fun_in" is the name of a function input arg in // the `signature` field above. This represents that input, whether // it is a single tensor or a list. // * "fun_in:0" gives the first element of a function input arg (a // non-list input is considered a list of length 1 for these // purposes). // * "node:out" where "node" is the name of a node in `node_def` and // "out" is the name one of its op's output arguments (the name // comes from the OpDef of the node's op). This represents that // node's output, whether it is a single tensor or a list. // Note: We enforce that an op's output arguments are never // renamed in the backwards-compatibility test. // * "node:out:0" gives the first element of a node output arg (a // non-list output is considered a list of length 1 for these // purposes). // // NOT CURRENTLY SUPPORTED (but may be in the future): // * "node:out:-1" gives last element in a node output list // * "node:out:1:" gives a list with all but the first element in a // node output list // * "node:out::-1" gives a list with all but the last element in a // node output list // The body of the function. Unlike the NodeDefs in a GraphDef, attrs // may have values of type `placeholder` and the `input` field uses // the "output" format above. /// By convention, "op" in node_def is resolved by consulting with a /// user-defined library first. If not resolved, "func" is assumed to /// be a builtin op. #[prost(message, repeated, tag="3")] pub node_def: ::std::vec::Vec<NodeDef>, /// A mapping from the output arg names from `signature` to the /// outputs from `node_def` that should be returned by the function. #[prost(map="string, string", tag="4")] pub ret: ::std::collections::HashMap<std::string::String, std::string::String>, /// A mapping from control output names from `signature` to node names in /// `node_def` which should be control outputs of this function. #[prost(map="string, string", tag="6")] pub control_ret: ::std::collections::HashMap<std::string::String, std::string::String>, } pub mod function_def { /// Attributes for function arguments. These attributes are the same set of /// valid attributes as to _Arg nodes. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ArgAttrs { #[prost(map="string, message", tag="1")] pub attr: ::std::collections::HashMap<std::string::String, super::AttrValue>, } } /// GradientDef defines the gradient function of a function defined in /// a function library. /// /// A gradient function g (specified by gradient_func) for a function f /// (specified by function_name) must follow the following: /// /// The function 'f' must be a numerical function which takes N inputs /// and produces M outputs. Its gradient function 'g', which is a /// function taking N + M inputs and produces N outputs. /// /// I.e. if we have /// (y1, y2, ..., y_M) = f(x1, x2, ..., x_N), /// then, g is /// (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N, /// dL/dy1, dL/dy2, ..., dL/dy_M), /// where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the /// loss function). dL/dx_i is the partial derivative of L with respect /// to x_i. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GradientDef { /// The function name. #[prost(string, tag="1")] pub function_name: std::string::String, /// The gradient function's name. #[prost(string, tag="2")] pub gradient_func: std::string::String, } /// Version information for a piece of serialized data /// /// There are different types of versions for each type of data /// (GraphDef, etc.), but they all have the same common shape /// described here. /// /// Each consumer has "consumer" and "min_producer" versions (specified /// elsewhere). A consumer is allowed to consume this data if /// /// producer >= min_producer /// consumer >= min_consumer /// consumer not in bad_consumers /// #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct VersionDef { /// The version of the code that produced this data. #[prost(int32, tag="1")] pub producer: i32, /// Any consumer below this version is not allowed to consume this data. #[prost(int32, tag="2")] pub min_consumer: i32, /// Specific consumer versions which are disallowed (e.g. due to bugs). #[prost(int32, repeated, tag="3")] pub bad_consumers: ::std::vec::Vec<i32>, } /// Represents the graph of operations #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphDef { #[prost(message, repeated, tag="1")] pub node: ::std::vec::Vec<NodeDef>, /// Compatibility versions of the graph. See core/public/version.h for version /// history. The GraphDef version is distinct from the TensorFlow version, and /// each release of TensorFlow will support a range of GraphDef versions. #[prost(message, optional, tag="4")] pub versions: ::std::option::Option<VersionDef>, /// Deprecated single version field; use versions above instead. Since all /// GraphDef changes before "versions" was introduced were forward /// compatible, this field is entirely ignored. #[prost(int32, tag="3")] pub version: i32, /// EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET. /// /// "library" provides user-defined functions. /// /// Naming: /// * library.function.name are in a flat namespace. /// NOTE: We may need to change it to be hierarchical to support /// different orgs. E.g., /// { "/google/nn", { ... }}, /// { "/google/vision", { ... }} /// { "/org_foo/module_bar", { ... }} /// map<string, FunctionDefLib> named_lib; /// * If node[i].op is the name of one function in "library", /// node[i] is deemed as a function call. Otherwise, node[i].op /// must be a primitive operation supported by the runtime. /// /// /// Function call semantics: /// /// * The callee may start execution as soon as some of its inputs /// are ready. The caller may want to use Tuple() mechanism to /// ensure all inputs are ready in the same time. /// /// * The consumer of return values may start executing as soon as /// the return values the consumer depends on are ready. The /// consumer may want to use Tuple() mechanism to ensure the /// consumer does not start until all return values of the callee /// function are ready. #[prost(message, optional, tag="2")] pub library: ::std::option::Option<FunctionDefLibrary>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferNodeInput { #[prost(int32, tag="1")] pub node_id: i32, #[prost(int32, tag="2")] pub output_port: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferNodeInfo { #[prost(string, tag="1")] pub name: std::string::String, #[prost(int32, tag="2")] pub node_id: i32, #[prost(string, tag="3")] pub type_name: std::string::String, #[prost(int32, tag="4")] pub soc_op_id: i32, #[prost(int32, tag="5")] pub padding_id: i32, #[prost(int32, tag="6")] pub input_count: i32, #[prost(int32, tag="7")] pub output_count: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferConstNodeInfo { #[prost(string, tag="1")] pub name: std::string::String, #[prost(int32, tag="2")] pub node_id: i32, #[prost(int64, repeated, tag="3")] pub shape: ::std::vec::Vec<i64>, #[prost(bytes, tag="4")] pub data: std::vec::Vec<u8>, #[prost(enumeration="DataType", tag="5")] pub dtype: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferNodeInputInfo { #[prost(int32, tag="1")] pub node_id: i32, #[prost(message, repeated, tag="2")] pub node_input: ::std::vec::Vec<GraphTransferNodeInput>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferNodeOutputInfo { #[prost(int32, tag="1")] pub node_id: i32, #[prost(int32, repeated, tag="2")] pub max_byte_size: ::std::vec::Vec<i32>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferGraphInputNodeInfo { #[prost(string, tag="1")] pub name: std::string::String, #[prost(int64, repeated, tag="2")] pub shape: ::std::vec::Vec<i64>, #[prost(enumeration="DataType", tag="3")] pub dtype: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferGraphOutputNodeInfo { #[prost(string, tag="1")] pub name: std::string::String, #[prost(int64, repeated, tag="2")] pub shape: ::std::vec::Vec<i64>, #[prost(enumeration="DataType", tag="3")] pub dtype: i32, } /// Protocol buffer representing a handle to a tensorflow resource. Handles are /// not valid across executions, but can be serialized back and forth from within /// a single run. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct GraphTransferInfo { #[prost(message, repeated, tag="1")] pub node_info: ::std::vec::Vec<GraphTransferNodeInfo>, #[prost(message, repeated, tag="2")] pub const_node_info: ::std::vec::Vec<GraphTransferConstNodeInfo>, #[prost(message, repeated, tag="3")] pub node_input_info: ::std::vec::Vec<GraphTransferNodeInputInfo>, #[prost(message, repeated, tag="4")] pub node_output_info: ::std::vec::Vec<GraphTransferNodeOutputInfo>, /// Input Node parameters of transferred graph #[prost(message, repeated, tag="5")] pub graph_input_node_info: ::std::vec::Vec<GraphTransferGraphInputNodeInfo>, #[prost(message, repeated, tag="6")] pub graph_output_node_info: ::std::vec::Vec<GraphTransferGraphOutputNodeInfo>, /// Destination of graph transfer #[prost(enumeration="graph_transfer_info::Destination", tag="7")] pub destination: i32, } pub mod graph_transfer_info { #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Destination { Nop = 0, Hexagon = 1, } } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct KernelDef { /// Must match the name of an Op. #[prost(string, tag="1")] pub op: std::string::String, /// Type of device this kernel runs on. #[prost(string, tag="2")] pub device_type: std::string::String, #[prost(message, repeated, tag="3")] pub constraint: ::std::vec::Vec<kernel_def::AttrConstraint>, /// Names of the Op's input_/output_args that reside in host memory /// instead of device memory. #[prost(string, repeated, tag="4")] pub host_memory_arg: ::std::vec::Vec<std::string::String>, /// This allows experimental kernels to be registered for an op that /// won't be used unless the user specifies a "_kernel" attr with /// value matching this. #[prost(string, tag="5")] pub label: std::string::String, /// Prioritization of kernel amongst different devices. By default we assume /// priority is 0. The higher the priority the better. By default (i.e. if /// this is not set), we prefer GPU kernels over CPU. #[prost(int32, tag="6")] pub priority: i32, } pub mod kernel_def { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AttrConstraint { /// Name of an attr from the Op. #[prost(string, tag="1")] pub name: std::string::String, /// A list of values that this kernel supports for this attr. /// Like OpDef.AttrDef.allowed_values, except for kernels instead of Ops. #[prost(message, optional, tag="2")] pub allowed_values: ::std::option::Option<super::AttrValue>, } } /// A collection of KernelDefs #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct KernelList { #[prost(message, repeated, tag="1")] pub kernel: ::std::vec::Vec<KernelDef>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TensorDescription { /// Data type of tensor elements #[prost(enumeration="DataType", tag="1")] pub dtype: i32, /// Shape of the tensor. #[prost(message, optional, tag="2")] pub shape: ::std::option::Option<TensorShapeProto>, /// Information about the size and allocator used for the data #[prost(message, optional, tag="4")] pub allocation_description: ::std::option::Option<AllocationDescription>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogStep { /// Process-unique step id. #[prost(int64, tag="1")] pub step_id: i64, /// Handle describing the feeds and fetches of the step. #[prost(string, tag="2")] pub handle: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogTensorAllocation { /// Process-unique step id. #[prost(int64, tag="1")] pub step_id: i64, /// Name of the kernel making the allocation as set in GraphDef, /// e.g., "affine2/weights/Assign". #[prost(string, tag="2")] pub kernel_name: std::string::String, /// Allocated tensor details. #[prost(message, optional, tag="3")] pub tensor: ::std::option::Option<TensorDescription>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogTensorDeallocation { /// Id of the tensor buffer being deallocated, used to match to a /// corresponding allocation. #[prost(int64, tag="1")] pub allocation_id: i64, /// Name of the allocator used. #[prost(string, tag="2")] pub allocator_name: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogTensorOutput { /// Process-unique step id. #[prost(int64, tag="1")] pub step_id: i64, /// Name of the kernel producing an output as set in GraphDef, e.g., /// "affine2/weights/Assign". #[prost(string, tag="2")] pub kernel_name: std::string::String, /// Index of the output being set. #[prost(int32, tag="3")] pub index: i32, /// Output tensor details. #[prost(message, optional, tag="4")] pub tensor: ::std::option::Option<TensorDescription>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogRawAllocation { /// Process-unique step id. #[prost(int64, tag="1")] pub step_id: i64, /// Name of the operation making the allocation. #[prost(string, tag="2")] pub operation: std::string::String, /// Number of bytes in the allocation. #[prost(int64, tag="3")] pub num_bytes: i64, /// Address of the allocation. #[prost(uint64, tag="4")] pub ptr: u64, /// Id of the tensor buffer being allocated, used to match to a /// corresponding deallocation. #[prost(int64, tag="5")] pub allocation_id: i64, /// Name of the allocator used. #[prost(string, tag="6")] pub allocator_name: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryLogRawDeallocation { /// Process-unique step id. #[prost(int64, tag="1")] pub step_id: i64, /// Name of the operation making the deallocation. #[prost(string, tag="2")] pub operation: std::string::String, /// Id of the tensor buffer being deallocated, used to match to a /// corresponding allocation. #[prost(int64, tag="3")] pub allocation_id: i64, /// Name of the allocator used. #[prost(string, tag="4")] pub allocator_name: std::string::String, /// True if the deallocation is queued and will be performed later, /// e.g. for GPU lazy freeing of buffers. #[prost(bool, tag="5")] pub deferred: bool, } /// For serializing and restoring the state of ReaderBase, see /// reader_base.h for details. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct ReaderBaseState { #[prost(int64, tag="1")] pub work_started: i64, #[prost(int64, tag="2")] pub work_finished: i64, #[prost(int64, tag="3")] pub num_records_produced: i64, #[prost(bytes, tag="4")] pub current_work: std::vec::Vec<u8>, } /// Protocol buffer representing a handle to a tensorflow resource. Handles are /// not valid across executions, but can be serialized back and forth from within /// a single run. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct RemoteFusedGraphExecuteInfo { /// Definition of remote graph #[prost(message, optional, tag="1")] pub remote_graph: ::std::option::Option<GraphDef>, /// Remote fused graph input node name #[prost(string, repeated, tag="2")] pub graph_input_node_name: ::std::vec::Vec<std::string::String>, /// Remote fused graph output node name #[prost(string, repeated, tag="3")] pub graph_output_node_name: ::std::vec::Vec<std::string::String>, /// Executor's name #[prost(string, tag="4")] pub executor_name: std::string::String, /// Optional: Parameters given to the executor #[prost(bytes, tag="5")] pub serialized_executor_parameters: std::vec::Vec<u8>, /// Optional: Default graph input tensor shape used to allocate memory /// before executing op #[prost(message, repeated, tag="6")] pub default_graph_input_tensor_shape: ::std::vec::Vec<remote_fused_graph_execute_info::TensorShapeTypeProto>, /// Optional: Default graph input tensor shape used to allocate memory /// before executing op /// TODO(satok): Remote output tensor shape once shape information is stored /// in NodeDef #[prost(message, repeated, tag="7")] pub default_graph_output_tensor_shape: ::std::vec::Vec<remote_fused_graph_execute_info::TensorShapeTypeProto>, } pub mod remote_fused_graph_execute_info { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TensorShapeTypeProto { #[prost(enumeration="super::DataType", tag="1")] pub dtype: i32, #[prost(message, optional, tag="2")] pub shape: ::std::option::Option<super::TensorShapeProto>, } } /// An allocation/de-allocation operation performed by the allocator. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AllocationRecord { /// The timestamp of the operation. #[prost(int64, tag="1")] pub alloc_micros: i64, /// Number of bytes allocated, or de-allocated if negative. #[prost(int64, tag="2")] pub alloc_bytes: i64, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct AllocatorMemoryUsed { #[prost(string, tag="1")] pub allocator_name: std::string::String, /// These are per-node allocator memory stats. #[prost(int64, tag="2")] pub total_bytes: i64, #[prost(int64, tag="3")] pub peak_bytes: i64, /// The bytes that are not deallocated. #[prost(int64, tag="4")] pub live_bytes: i64, /// The allocation and deallocation timeline. #[prost(message, repeated, tag="6")] pub allocation_records: ::std::vec::Vec<AllocationRecord>, /// These are snapshots of the overall allocator memory stats. /// The number of live bytes currently allocated by the allocator. #[prost(int64, tag="5")] pub allocator_bytes_in_use: i64, } /// Output sizes recorded for a single execution of a graph node. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct NodeOutput { #[prost(int32, tag="1")] pub slot: i32, #[prost(message, optional, tag="3")] pub tensor_description: ::std::option::Option<TensorDescription>, } /// For memory tracking. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct MemoryStats { #[prost(int64, tag="1")] pub temp_memory_size: i64, #[prost(int64, tag="3")] pub persistent_memory_size: i64, #[prost(int64, repeated, tag="5")] pub persistent_tensor_alloc_ids: ::std::vec::Vec<i64>, #[prost(int64, tag="2")] pub device_temp_memory_size: i64, #[prost(int64, tag="4")] pub device_persistent_memory_size: i64, #[prost(int64, repeated, packed="false", tag="6")] pub device_persistent_tensor_alloc_ids: ::std::vec::Vec<i64>, } /// Time/size stats recorded for a single execution of a graph node. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct NodeExecStats { /// TODO(tucker): Use some more compact form of node identity than /// the full string name. Either all processes should agree on a /// global id (cost_id?) for each node, or we should use a hash of /// the name. #[prost(string, tag="1")] pub node_name: std::string::String, #[prost(int64, tag="2")] pub all_start_micros: i64, #[prost(int64, tag="3")] pub op_start_rel_micros: i64, #[prost(int64, tag="4")] pub op_end_rel_micros: i64, #[prost(int64, tag="5")] pub all_end_rel_micros: i64, #[prost(message, repeated, tag="6")] pub memory: ::std::vec::Vec<AllocatorMemoryUsed>, #[prost(message, repeated, tag="7")] pub output: ::std::vec::Vec<NodeOutput>, #[prost(string, tag="8")] pub timeline_label: std::string::String, #[prost(int64, tag="9")] pub scheduled_micros: i64, #[prost(uint32, tag="10")] pub thread_id: u32, #[prost(message, repeated, tag="11")] pub referenced_tensor: ::std::vec::Vec<AllocationDescription>, #[prost(message, optional, tag="12")] pub memory_stats: ::std::option::Option<MemoryStats>, #[prost(int64, tag="13")] pub all_start_nanos: i64, #[prost(int64, tag="14")] pub op_start_rel_nanos: i64, #[prost(int64, tag="15")] pub op_end_rel_nanos: i64, #[prost(int64, tag="16")] pub all_end_rel_nanos: i64, #[prost(int64, tag="17")] pub scheduled_nanos: i64, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct DeviceStepStats { #[prost(string, tag="1")] pub device: std::string::String, #[prost(message, repeated, tag="2")] pub node_stats: ::std::vec::Vec<NodeExecStats>, /// Its key is thread id. #[prost(map="uint32, string", tag="3")] pub thread_names: ::std::collections::HashMap<u32, std::string::String>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct StepStats { #[prost(message, repeated, tag="1")] pub dev_stats: ::std::vec::Vec<DeviceStepStats>, } /// Metadata associated with a series of Summary data #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct SummaryDescription { /// Hint on how plugins should process the data in this series. /// Supported values include "scalar", "histogram", "image", "audio" #[prost(string, tag="1")] pub type_hint: std::string::String, } /// Serialization format for histogram module in /// core/lib/histogram/histogram.h #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct HistogramProto { #[prost(double, tag="1")] pub min: f64, #[prost(double, tag="2")] pub max: f64, #[prost(double, tag="3")] pub num: f64, #[prost(double, tag="4")] pub sum: f64, #[prost(double, tag="5")] pub sum_squares: f64, /// Parallel arrays encoding the bucket boundaries and the bucket values. /// bucket(i) is the count for the bucket i. The range for /// a bucket is: /// i == 0: -DBL_MAX .. bucket_limit(0) /// i != 0: bucket_limit(i-1) .. bucket_limit(i) #[prost(double, repeated, tag="6")] pub bucket_limit: ::std::vec::Vec<f64>, #[prost(double, repeated, tag="7")] pub bucket: ::std::vec::Vec<f64>, } /// A SummaryMetadata encapsulates information on which plugins are able to make /// use of a certain summary value. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct SummaryMetadata { /// Data that associates a summary with a certain plugin. #[prost(message, optional, tag="1")] pub plugin_data: ::std::option::Option<summary_metadata::PluginData>, /// Display name for viewing in TensorBoard. #[prost(string, tag="2")] pub display_name: std::string::String, /// Longform readable description of the summary sequence. Markdown supported. #[prost(string, tag="3")] pub summary_description: std::string::String, /// Class of data stored in this time series. Required for compatibility with /// TensorBoard's generic data facilities (`DataProvider`, et al.). This value /// imposes constraints on the dtype and shape of the corresponding tensor /// values. See `DataClass` docs for details. #[prost(enumeration="DataClass", tag="4")] pub data_class: i32, } pub mod summary_metadata { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct PluginData { /// The name of the plugin this data pertains to. #[prost(string, tag="1")] pub plugin_name: std::string::String, /// The content to store for the plugin. The best practice is for this to be /// a binary serialized protocol buffer. #[prost(bytes, tag="2")] pub content: std::vec::Vec<u8>, } } /// A Summary is a set of named values to be displayed by the /// visualizer. /// /// Summaries are produced regularly during training, as controlled by /// the "summary_interval_secs" attribute of the training operation. /// Summaries are also produced at the end of an evaluation. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Summary { /// Set of values for the summary. #[prost(message, repeated, tag="1")] pub value: ::std::vec::Vec<summary::Value>, } pub mod summary { #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Image { /// Dimensions of the image. #[prost(int32, tag="1")] pub height: i32, #[prost(int32, tag="2")] pub width: i32, /// Valid colorspace values are /// 1 - grayscale /// 2 - grayscale + alpha /// 3 - RGB /// 4 - RGBA /// 5 - DIGITAL_YUV /// 6 - BGRA #[prost(int32, tag="3")] pub colorspace: i32, /// Image data in encoded format. All image formats supported by /// image_codec::CoderUtil can be stored here. #[prost(bytes, tag="4")] pub encoded_image_string: std::vec::Vec<u8>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Audio { /// Sample rate of the audio in Hz. #[prost(float, tag="1")] pub sample_rate: f32, /// Number of channels of audio. #[prost(int64, tag="2")] pub num_channels: i64, /// Length of the audio in frames (samples per channel). #[prost(int64, tag="3")] pub length_frames: i64, /// Encoded audio data and its associated RFC 2045 content type (e.g. /// "audio/wav"). #[prost(bytes, tag="4")] pub encoded_audio_string: std::vec::Vec<u8>, #[prost(string, tag="5")] pub content_type: std::string::String, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Value { /// This field is deprecated and will not be set. #[prost(string, tag="7")] pub node_name: std::string::String, /// Tag name for the data. Used by TensorBoard plugins to organize data. Tags /// are often organized by scope (which contains slashes to convey /// hierarchy). For example: foo/bar/0 #[prost(string, tag="1")] pub tag: std::string::String, /// Contains metadata on the summary value such as which plugins may use it. /// Take note that many summary values may lack a metadata field. This is /// because the FileWriter only keeps a metadata object on the first summary /// value with a certain tag for each tag. TensorBoard then remembers which /// tags are associated with which plugins. This saves space. #[prost(message, optional, tag="9")] pub metadata: ::std::option::Option<super::SummaryMetadata>, /// Value associated with the tag. #[prost(oneof="value::Value", tags="2, 3, 4, 5, 6, 8")] pub value: ::std::option::Option<value::Value>, } pub mod value { /// Value associated with the tag. #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Value { #[prost(float, tag="2")] SimpleValue(f32), #[prost(bytes, tag="3")] ObsoleteOldStyleHistogram(std::vec::Vec<u8>), #[prost(message, tag="4")] Image(super::Image), #[prost(message, tag="5")] Histo(super::super::HistogramProto), #[prost(message, tag="6")] Audio(super::Audio), #[prost(message, tag="8")] Tensor(super::super::TensorProto), } } } #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum DataClass { /// Unknown data class, used (implicitly) for legacy data. Will not be /// processed by data ingestion pipelines. Unknown = 0, /// Scalar time series. Each `Value` for the corresponding tag must have /// `tensor` set to a rank-0 tensor of floating-point dtype, which will be /// converted to float64. Scalar = 1, /// Tensor time series. Each `Value` for the corresponding tag must have /// `tensor` set. The tensor value is arbitrary, but should be small to /// accommodate direct storage in database backends: an upper bound of a few /// kilobytes is a reasonable rule of thumb. Tensor = 2, /// Blob sequence time series. Each `Value` for the corresponding tag must /// have `tensor` set to a rank-1 tensor of bytestring dtype. BlobSequence = 3, } /// Can only be interpreted if you know the corresponding TensorShape. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TensorSliceProto { /// Extent of the slice in all tensor dimensions. /// /// Must have one entry for each of the dimension of the tensor that this /// slice belongs to. The order of sizes is the same as the order of /// dimensions in the TensorShape. #[prost(message, repeated, tag="1")] pub extent: ::std::vec::Vec<tensor_slice_proto::Extent>, } pub mod tensor_slice_proto { /// Extent of the slice in one dimension. /// /// Either both or no attributes must be set. When no attribute is set /// means: All data in that dimension. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Extent { /// Start index of the slice, starting at 0. #[prost(int64, tag="1")] pub start: i64, /// Length of the slice: if the length is missing or -1 we will /// interpret this as "everything in this dimension". We use /// "oneof" to preserve information about whether the length is /// present without changing the serialization format from the /// prior proto2 version of this proto. #[prost(oneof="extent::HasLength", tags="2")] pub has_length: ::std::option::Option<extent::HasLength>, } pub mod extent { /// Length of the slice: if the length is missing or -1 we will /// interpret this as "everything in this dimension". We use /// "oneof" to preserve information about whether the length is /// present without changing the serialization format from the /// prior proto2 version of this proto. #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum HasLength { #[prost(int64, tag="2")] Length(i64), } } } /// Protocol buffer representing a Variable. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct VariableDef { /// Name of the variable tensor. #[prost(string, tag="1")] pub variable_name: std::string::String, /// Name of the tensor holding the variable's initial value. #[prost(string, tag="6")] pub initial_value_name: std::string::String, /// Name of the initializer op. #[prost(string, tag="2")] pub initializer_name: std::string::String, /// Name of the snapshot tensor. #[prost(string, tag="3")] pub snapshot_name: std::string::String, /// Support for saving variables as slices of a larger variable. #[prost(message, optional, tag="4")] pub save_slice_info_def: ::std::option::Option<SaveSliceInfoDef>, /// Whether to represent this as a ResourceVariable. #[prost(bool, tag="5")] pub is_resource: bool, /// Whether this variable should be trained. #[prost(bool, tag="7")] pub trainable: bool, /// Indicates when a distributed variable will be synced. #[prost(enumeration="VariableSynchronization", tag="8")] pub synchronization: i32, /// Indicates how a distributed variable will be aggregated. #[prost(enumeration="VariableAggregation", tag="9")] pub aggregation: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct SaveSliceInfoDef { /// Name of the full variable of which this is a slice. #[prost(string, tag="1")] pub full_name: std::string::String, /// Shape of the full variable. #[prost(int64, repeated, tag="2")] pub full_shape: ::std::vec::Vec<i64>, /// Offset of this variable into the full variable. #[prost(int64, repeated, tag="3")] pub var_offset: ::std::vec::Vec<i64>, /// Shape of this variable. #[prost(int64, repeated, tag="4")] pub var_shape: ::std::vec::Vec<i64>, } /// Indicates when a distributed variable will be synced. #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum VariableSynchronization { /// `AUTO`: Indicates that the synchronization will be determined by the /// current `DistributionStrategy` (eg. With `MirroredStrategy` this would be /// `ON_WRITE`). Auto = 0, /// `NONE`: Indicates that there will only be one copy of the variable, so /// there is no need to sync. None = 1, /// `ON_WRITE`: Indicates that the variable will be updated across devices /// every time it is written. OnWrite = 2, /// `ON_READ`: Indicates that the variable will be aggregated across devices /// when it is read (eg. when checkpointing or when evaluating an op that uses /// the variable). OnRead = 3, } /// Indicates how a distributed variable will be aggregated. #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum VariableAggregation { /// `NONE`: This is the default, giving an error if you use a /// variable-update operation with multiple replicas. None = 0, /// `SUM`: Add the updates across replicas. Sum = 1, /// `MEAN`: Take the arithmetic mean ("average") of the updates across /// replicas. Mean = 2, /// `ONLY_FIRST_REPLICA`: This is for when every replica is performing the same /// update, but we only want to perform the update once. Used, e.g., for the /// global step counter. OnlyFirstReplica = 3, } /// Protocol buffer representing an event that happened during /// the execution of a Brain model. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct Event { /// Timestamp of the event. #[prost(double, tag="1")] pub wall_time: f64, /// Global step of the event. #[prost(int64, tag="2")] pub step: i64, #[prost(oneof="event::What", tags="3, 4, 5, 6, 7, 8, 9")] pub what: ::std::option::Option<event::What>, } pub mod event { #[derive(Clone, PartialEq, ::prost::Oneof)] #[derive(serde::Serialize, serde::Deserialize)] pub enum What { /// An event file was started, with the specified version. /// This is use to identify the contents of the record IO files /// easily. Current version is "brain.Event:2". All versions /// start with "brain.Event:". #[prost(string, tag="3")] FileVersion(std::string::String), /// An encoded version of a GraphDef. #[prost(bytes, tag="4")] GraphDef(std::vec::Vec<u8>), /// A summary was generated. #[prost(message, tag="5")] Summary(super::Summary), /// The user output a log message. Not all messages are logged, only ones /// generated via the Python tensorboard_logging module. #[prost(message, tag="6")] LogMessage(super::LogMessage), /// The state of the session which can be used for restarting after crashes. #[prost(message, tag="7")] SessionLog(super::SessionLog), /// The metadata returned by running a session.run() call. #[prost(message, tag="8")] TaggedRunMetadata(super::TaggedRunMetadata), /// An encoded version of a MetaGraphDef. #[prost(bytes, tag="9")] MetaGraphDef(std::vec::Vec<u8>), } } /// Protocol buffer used for logging messages to the events file. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct LogMessage { #[prost(enumeration="log_message::Level", tag="1")] pub level: i32, #[prost(string, tag="2")] pub message: std::string::String, } pub mod log_message { #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum Level { Unknown = 0, /// Note: The logging level 10 cannot be named DEBUG. Some software /// projects compile their C/C++ code with -DDEBUG in debug builds. So the /// C++ code generated from this file should not have an identifier named /// DEBUG. Debugging = 10, Info = 20, Warn = 30, Error = 40, Fatal = 50, } } /// Protocol buffer used for logging session state. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct SessionLog { #[prost(enumeration="session_log::SessionStatus", tag="1")] pub status: i32, /// This checkpoint_path contains both the path and filename. #[prost(string, tag="2")] pub checkpoint_path: std::string::String, #[prost(string, tag="3")] pub msg: std::string::String, } pub mod session_log { #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum SessionStatus { StatusUnspecified = 0, Start = 1, Stop = 2, Checkpoint = 3, } } /// For logging the metadata output for a single session.run() call. #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct TaggedRunMetadata { /// Tag name associated with this metadata. #[prost(string, tag="1")] pub tag: std::string::String, /// Byte-encoded version of the `RunMetadata` proto in order to allow lazy /// deserialization. #[prost(bytes, tag="2")] pub run_metadata: std::vec::Vec<u8>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct WatchdogConfig { #[prost(int64, tag="1")] pub timeout_ms: i64, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct RequestedExitCode { #[prost(int32, tag="1")] pub exit_code: i32, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct WorkerHeartbeatRequest { #[prost(enumeration="WorkerShutdownMode", tag="1")] pub shutdown_mode: i32, #[prost(message, optional, tag="2")] pub watchdog_config: ::std::option::Option<WatchdogConfig>, #[prost(message, optional, tag="3")] pub exit_code: ::std::option::Option<RequestedExitCode>, } #[derive(Clone, PartialEq, ::prost::Message)] #[derive(serde::Serialize, serde::Deserialize)] pub struct WorkerHeartbeatResponse { #[prost(enumeration="WorkerHealth", tag="1")] pub health_status: i32, #[prost(message, repeated, tag="2")] pub worker_log: ::std::vec::Vec<Event>, #[prost(string, tag="3")] pub hostname: std::string::String, } // Worker heartbeat messages. Support for these operations is currently // internal and expected to change. /// Current health status of a worker. #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum WorkerHealth { /// By default a worker is healthy. Ok = 0, ReceivedShutdownSignal = 1, InternalError = 2, /// Worker has been instructed to shutdown after a timeout. ShuttingDown = 3, } /// Indicates the behavior of the worker when an internal error or shutdown /// signal is received. #[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)] #[repr(i32)] #[derive(serde::Serialize, serde::Deserialize)] pub enum WorkerShutdownMode { Default = 0, NotConfigured = 1, WaitForCoordinator = 2, ShutdownAfterTimeout = 3, }