Performance library for Deep Learning
2.0.0
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20 #ifndef ONEAPI_DNNL_DNNL_HPP
21 #define ONEAPI_DNNL_DNNL_HPP
23 #include "oneapi/dnnl/dnnl_config.h"
32 #include <unordered_map>
42 #ifndef DNNL_ENABLE_EXCEPTIONS
43 #if __cpp_exceptions || __EXCEPTIONS \
44 || (defined(_MSC_VER) && !defined(__clang__))
45 #define DNNL_ENABLE_EXCEPTIONS 1
47 #define DNNL_ENABLE_EXCEPTIONS 0
51 #if defined(__GNUC__) || defined(__clang__)
52 #define DNNL_TRAP() __builtin_trap()
53 #elif defined(__INTEL_COMPILER) || defined(_MSC_VER)
54 #define DNNL_TRAP() __debugbreak()
56 #error "unknown compiler"
59 #if DNNL_ENABLE_EXCEPTIONS
60 #define DNNL_THROW_ERROR(status, msg) throw error(status, msg)
63 #define DNNL_THROW_ERROR(status, msg) \
84 struct error :
public std::exception {
96 const char *
what() const noexcept
override {
return message; }
109 template <
typename T>
110 void validate_container_size(
const T &v,
const char *error_message,
111 int min_size = 1,
int max_size = -1) {
112 const int size = (int)v.size();
113 if (size < min_size || (max_size >= 0 && size > max_size))
119 template <
typename T>
135 template <
typename T,
typename traits = handle_traits<T>>
139 std::shared_ptr<typename std::remove_pointer<T>::type> data_ {0};
142 bool operator==(
const T other)
const {
return other == data_.get(); }
143 bool operator!=(
const T other)
const {
return !(*
this == other); }
176 void reset(T t,
bool weak =
false) {
177 data_.reset(t, weak ? &dummy_destructor : traits::destructor);
185 T
get(
bool allow_empty =
false)
const {
186 T result = data_.get();
187 if (allow_empty ==
false && result ==
nullptr)
197 explicit operator T()
const {
return get(
true); }
202 explicit operator bool()
const {
return get(
true) !=
nullptr; }
211 return other.data_.get() == data_.get();
257 struct primitive_desc;
355 const std::unordered_map<int, memory> &args)
const;
369 "could not get a primitive descriptor from a primitive");
380 "could not get a primitive kind from a primitive descriptor");
470 undef = dnnl_alg_kind_undef,
660 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
661 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
662 return static_cast<enum_name>( \
663 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
666 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
667 return static_cast<enum_name>( \
668 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
671 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
672 return static_cast<enum_name>( \
673 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
676 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
677 lhs = static_cast<enum_name>( \
678 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
682 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
683 lhs = static_cast<enum_name>( \
684 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
688 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
689 lhs = static_cast<enum_name>( \
690 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
694 inline enum_name operator~(enum_name rhs) { \
695 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
896 "could not create an engine");
909 "could not get an engine from a primitive_desc");
910 reset(c_engine,
true);
918 "could not get kind of an engine");
927 template <
typename primitive_desc>
937 template <
typename primitive_desc>
942 "could not get an engine from a primitive_desc");
943 return engine(c_engine,
true);
1001 "could not create a stream");
1009 "could not get an engine from a stream object");
1010 return engine(c_engine,
true);
1113 template <
typename T>
1115 validate_container_size(
1406 Abc16a = dnnl_Abc16a,
1407 ABc16a16b = dnnl_ABc16a16b,
1408 ABc4a4b = dnnl_ABc4a4b,
1411 ABc16b16a = dnnl_ABc16b16a,
1414 ABc4b16a4b = dnnl_ABc4b16a4b,
1415 ABc2b8a4b = dnnl_ABc2b8a4b,
1416 ABc16b16a4b = dnnl_ABc16b16a4b,
1417 ABc16b16a2b = dnnl_ABc16b16a2b,
1418 ABc4b4a = dnnl_ABc4b4a,
1419 ABc8a16b2a = dnnl_ABc8a16b2a,
1420 ABc8a8b = dnnl_ABc8a8b,
1421 ABc8a4b = dnnl_ABc8a4b,
1423 ABc8b16a2b = dnnl_ABc8b16a2b,
1424 ABc8b8a = dnnl_ABc8b8a,
1425 Abcd8a = dnnl_Abcd8a,
1426 Abcd16a = dnnl_Abcd16a,
1427 Abcd32a = dnnl_Abcd32a,
1428 ABcd16a16b = dnnl_ABcd16a16b,
1431 ABcd16b16a = dnnl_ABcd16b16a,
1432 aBCd16b16c = dnnl_aBCd16b16c,
1433 aBCd16c16b = dnnl_aBCd16c16b,
1434 Abcd4a = dnnl_Abcd4a,
1436 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1437 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1438 ABcd4b4a = dnnl_ABcd4b4a,
1439 ABcd4a4b = dnnl_ABcd4a4b,
1440 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1441 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1442 ABcd16b16a4b = dnnl_ABcd16b16a4b,
1443 ABcd16b16a2b = dnnl_ABcd16b16a2b,
1444 aBCd16c16b4c = dnnl_aBCd16c16b4c,
1445 aBCd16c16b2c = dnnl_aBCd16c16b2c,
1446 aBCd4c4b = dnnl_aBCd4c4b,
1447 aBCd4b4c = dnnl_aBCd4b4c,
1448 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1449 ABcd8a8b = dnnl_ABcd8a8b,
1450 ABcd8a4b = dnnl_ABcd8a4b,
1453 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1454 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1457 aBCd8b8c = dnnl_aBCd8b8c,
1458 aBCd8b4c = dnnl_aBCd8b4c,
1459 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1460 aBCd8c8b = dnnl_aBCd8c8b,
1461 Abcde16a = dnnl_Abcde16a,
1462 Abcde32a = dnnl_Abcde32a,
1463 ABcde16a16b = dnnl_ABcde16a16b,
1466 ABcde16b16a = dnnl_ABcde16b16a,
1467 aBCde16b16c = dnnl_aBCde16b16c,
1468 aBCde16c16b = dnnl_aBCde16c16b,
1469 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1470 Abcde4a = dnnl_Abcde4a,
1472 ABcde4b4a = dnnl_ABcde4b4a,
1473 ABcde4a4b = dnnl_ABcde4a4b,
1474 aBCde4b4c = dnnl_aBCde4b4c,
1475 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1476 aBCde16c16b4c = dnnl_aBCde16c16b4c,
1477 aBCde16c16b2c = dnnl_aBCde16c16b2c,
1478 aBCde4c4b = dnnl_aBCde4c4b,
1479 Abcde8a = dnnl_Abcde8a,
1480 ABcde8a8b = dnnl_ABcde8a8b,
1481 ABcde8a4b = dnnl_ABcde8a4b,
1483 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1486 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1487 ABcde8b8a = dnnl_ABcde8b8a,
1488 aBCde8b8c = dnnl_aBCde8b8c,
1489 aBCde8b4c = dnnl_aBCde8b4c,
1490 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1491 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1492 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1493 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1494 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1495 aBCde8c8b = dnnl_aBCde8c8b,
1497 aBCdef16b16c = dnnl_aBCdef16b16c,
1498 aBCdef16c16b = dnnl_aBCdef16c16b,
1501 aBCdef4c4b = dnnl_aBCdef4c4b,
1502 aBCdef4b4c = dnnl_aBCdef4b4c,
1503 aBCdef8b8c = dnnl_aBCdef8b8c,
1504 aBCdef8b4c = dnnl_aBCdef8b4c,
1505 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1506 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1507 aBCdef8c8b = dnnl_aBCdef8c8b,
1508 aBdc16b = dnnl_aBdc16b,
1509 aBdc4b = dnnl_aBdc4b,
1510 aBdc8b = dnnl_aBdc8b,
1511 aBdec16b = dnnl_aBdec16b,
1512 aBdec4b = dnnl_aBdec4b,
1513 aBdec8b = dnnl_aBdec8b,
1514 aBdefc16b = dnnl_aBdefc16b,
1515 aCBdef16c16b = dnnl_aCBdef16c16b,
1516 aCBdef16b16c = dnnl_aCBdef16b16c,
1517 aBdefc4b = dnnl_aBdefc4b,
1518 aBdefc8b = dnnl_aBdefc8b,
1519 Acb16a = dnnl_Acb16a,
1522 aCBd16b16c = dnnl_aCBd16b16c,
1523 aCBd16c16b = dnnl_aCBd16c16b,
1524 aCBde16b16c = dnnl_aCBde16b16c,
1525 aCBde16c16b = dnnl_aCBde16c16b,
1526 Acdb16a = dnnl_Acdb16a,
1527 Acdb4a = dnnl_Acdb4a,
1528 Acdb8a = dnnl_Acdb8a,
1529 Acdeb16a = dnnl_Acdeb16a,
1530 Acdeb4a = dnnl_Acdeb4a,
1531 Acdeb8a = dnnl_Acdeb8a,
1532 BAc16a16b = dnnl_BAc16a16b,
1533 BAc16b16a = dnnl_BAc16b16a,
1534 BAcd16a16b = dnnl_BAcd16a16b,
1535 BAcd16b16a = dnnl_BAcd16b16a,
1536 ABcd32a32b = dnnl_ABcd32a32b,
1537 BAcde16b16a = dnnl_BAcde16b16a,
1538 BAcde16a16b = dnnl_BAcde16a16b,
1539 aBdec32b = dnnl_aBdec32b,
1540 Abcdef16a = dnnl_Abcdef16a,
1541 Abcdef32a = dnnl_Abcdef32a,
1542 Acdb32a = dnnl_Acdb32a,
1546 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1547 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1548 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1549 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1550 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1551 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1552 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1553 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1554 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1567 NCw16n16c = dnnl_NCw16n16c,
1568 NChw16n16c = dnnl_NChw16n16c,
1569 NCdhw16n16c = dnnl_NCdhw16n16c,
1570 NCdhw32n32c = dnnl_NCdhw32n32c,
1571 NChw32n32c = dnnl_NChw32n32c,
1572 IOhw16i16o = dnnl_IOhw16i16o,
1573 Ohwi32o = dnnl_Ohwi32o,
1574 IOdhw16i16o = dnnl_IOdhw16i16o,
1575 gIOhw16i16o = dnnl_gIOhw16i16o,
1576 gOhwi32o = dnnl_gOhwi32o,
1577 Goidhw16g = dnnl_Goidhw16g,
1578 IOw16o16i = dnnl_IOw16o16i,
1579 OIw16i16o = dnnl_OIw16i16o,
1580 IOw16i16o = dnnl_IOw16i16o,
1581 gIOw16i16o = dnnl_gIOw16i16o,
1582 OIw16o16i = dnnl_OIw16o16i,
1583 Oiw16o = dnnl_Oiw16o,
1584 OIw4i16o4i = dnnl_OIw4i16o4i,
1585 OIw2i8o4i = dnnl_OIw2i8o4i,
1586 OIw4i4o = dnnl_OIw4i4o,
1587 OIw4o4i = dnnl_OIw4o4i,
1589 OIw8i16o2i = dnnl_OIw8i16o2i,
1590 OIw8i8o = dnnl_OIw8i8o,
1591 OIw8o16i2o = dnnl_OIw8o16i2o,
1592 OIw8o8i = dnnl_OIw8o8i,
1593 OIw8o4i = dnnl_OIw8o4i,
1594 Owi16o = dnnl_Owi16o,
1595 OwI16o2i = dnnl_OwI16o2i,
1598 IOhw16o16i = dnnl_IOhw16o16i,
1599 Ohwi16o = dnnl_Ohwi16o,
1600 OhwI16o2i = dnnl_OhwI16o2i,
1601 Ohwi4o = dnnl_Ohwi4o,
1602 Ohwi8o = dnnl_Ohwi8o,
1603 OIhw16i16o = dnnl_OIhw16i16o,
1604 OIhw16o16i = dnnl_OIhw16o16i,
1605 Oihw16o = dnnl_Oihw16o,
1606 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1607 OIhw4i4o = dnnl_OIhw4i4o,
1608 OIhw4o4i = dnnl_OIhw4o4i,
1609 Oihw4o = dnnl_Oihw4o,
1610 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1611 OIhw8i8o = dnnl_OIhw8i8o,
1612 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1613 OIhw8o8i = dnnl_OIhw8o8i,
1614 OIhw8o4i = dnnl_OIhw8o4i,
1615 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1616 IOdhw16o16i = dnnl_IOdhw16o16i,
1617 Odhwi16o = dnnl_Odhwi16o,
1618 OdhwI16o2i = dnnl_OdhwI16o2i,
1619 Odhwi4o = dnnl_Odhwi4o,
1620 Odhwi8o = dnnl_Odhwi8o,
1621 OIdhw16i16o = dnnl_OIdhw16i16o,
1622 OIdhw16o16i = dnnl_OIdhw16o16i,
1623 Oidhw16o = dnnl_Oidhw16o,
1624 OIdhw4i4o = dnnl_OIdhw4i4o,
1625 OIdhw4o4i = dnnl_OIdhw4o4i,
1626 Oidhw4o = dnnl_Oidhw4o,
1627 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1628 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1629 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1630 OIdhw8i8o = dnnl_OIdhw8i8o,
1631 OIdhw8o8i = dnnl_OIdhw8o8i,
1632 OIdhw8o4i = dnnl_OIdhw8o4i,
1633 gIOw16o16i = dnnl_gIOw16o16i,
1634 gOIw16i16o = dnnl_gOIw16i16o,
1635 gOIw16o16i = dnnl_gOIw16o16i,
1636 gOiw16o = dnnl_gOiw16o,
1637 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1638 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1639 gOIw4i4o = dnnl_gOIw4i4o,
1640 gOIw4o4i = dnnl_gOIw4o4i,
1641 gOiw4o = dnnl_gOiw4o,
1642 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1643 gOIw8i8o = dnnl_gOIw8i8o,
1644 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1645 gOIw8o8i = dnnl_gOIw8o8i,
1646 gOIw8o4i = dnnl_gOIw8o4i,
1647 gOwi16o = dnnl_gOwi16o,
1648 gOwI16o2i = dnnl_gOwI16o2i,
1649 gOwi4o = dnnl_gOwi4o,
1650 gOwi8o = dnnl_gOwi8o,
1651 Goiw8g = dnnl_Goiw8g,
1652 Goiw16g = dnnl_Goiw16g,
1653 gIOhw16o16i = dnnl_gIOhw16o16i,
1654 gOhwi16o = dnnl_gOhwi16o,
1655 gOhwI16o2i = dnnl_gOhwI16o2i,
1656 gOhwi4o = dnnl_gOhwi4o,
1657 gOhwi8o = dnnl_gOhwi8o,
1658 Goihw16g = dnnl_Goihw16g,
1659 gOIhw16i16o = dnnl_gOIhw16i16o,
1660 gOIhw16o16i = dnnl_gOIhw16o16i,
1661 gOihw16o = dnnl_gOihw16o,
1662 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1663 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1664 gOIhw4i4o = dnnl_gOIhw4i4o,
1665 gOIhw4o4i = dnnl_gOIhw4o4i,
1666 gOihw4o = dnnl_gOihw4o,
1667 Goihw8g = dnnl_Goihw8g,
1668 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1669 gOIhw8i8o = dnnl_gOIhw8i8o,
1670 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1671 OIw4o8i8o4i = dnnl_OIw4o8i8o4i,
1672 OIdhw4o8i8o4i = dnnl_OIdhw4o8i8o4i,
1673 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1674 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1675 gOIw4o8i8o4i = dnnl_gOIw4o8i8o4i,
1676 gOIdhw4o8i8o4i = dnnl_gOIdhw4o8i8o4i,
1677 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1678 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1679 OIhw16i16o4i = dnnl_OIhw16i16o4i,
1680 OIhw16i16o2i = dnnl_OIhw16i16o2i,
1681 gOIhw16i16o4i = dnnl_gOIhw16i16o4i,
1682 gOIhw16i16o2i = dnnl_gOIhw16i16o2i,
1683 gOIhw8o8i = dnnl_gOIhw8o8i,
1684 gOIhw8o4i = dnnl_gOIhw8o4i,
1685 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1686 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1687 gOdhwi16o = dnnl_gOdhwi16o,
1688 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1689 gOdhwi4o = dnnl_gOdhwi4o,
1690 gOdhwi8o = dnnl_gOdhwi8o,
1691 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1692 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1693 gOidhw16o = dnnl_gOidhw16o,
1694 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1695 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1696 gOidhw4o = dnnl_gOidhw4o,
1697 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1698 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1699 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1700 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1701 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1702 gOIdhw8o4i = dnnl_gOIdhw8o4i,
1703 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1704 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1705 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1706 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1707 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1708 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1709 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1710 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1711 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1712 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1713 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1714 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1743 bool allow_empty =
false)
1745 validate_dims(adims);
1747 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1751 "could not construct a memory descriptor using a "
1771 bool allow_empty =
false)
1773 validate_dims(adims);
1774 if (!strides.empty()) validate_dims(strides, (
int)adims.size());
1776 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1777 strides.empty() ?
nullptr : &strides[0]);
1780 "could not construct a memory descriptor using "
1801 bool allow_empty =
false)
const {
1802 validate_dims(adims, data.
ndims);
1803 validate_dims(offsets, data.
ndims);
1806 &sub_md, &data, adims.data(), offsets.data());
1809 return desc(sub_md);
1857 if (data.
ndims) validate_dims(adims, 1);
1860 &out_md, &data, (
int)adims.size(), adims.data());
1863 status,
"could not reshape a memory descriptor");
1864 return desc(out_md);
1905 bool allow_empty =
false)
const {
1906 validate_dims(permutation, data.
ndims);
1909 &out_md, &data, permutation.data());
1912 "could not permute axes of a memory descriptor");
1913 return desc(out_md);
1958 explicit operator bool()
const {
return data.
ndims != 0; }
1990 "could not create a memory object");
2007 "could not get a memory descriptor from a memory object");
2008 return desc(*cdesc);
2015 "could not get an engine from a memory object");
2016 return engine(c_engine,
true);
2026 "could not get a native handle from a memory object");
2061 "could not set native handle of a memory object");
2077 "could not set native handle of a memory object");
2101 template <
typename T =
void>
2105 "could not map memory object data");
2106 return static_cast<T *
>(mapped_ptr);
2121 "could not unmap memory object data");
2203 "post-ops index is out of range");
2240 "could not append a sum post-op");
2243 memory::convert_to_c(data_type)),
2244 "could not append a sum post-op");
2253 "could not get parameters of a sum post-op");
2265 get(), index, &scale, &c_data_type),
2266 "could not get parameters of a sum post-op");
2284 float scale,
algorithm aalgorithm,
float alpha,
float beta) {
2287 "could not append an elementwise post-op");
2298 float &alpha,
float &beta)
const {
2301 get(), index, &scale, &c_alg, &alpha, &beta),
2302 "could not get parameters of an elementwise post-op");
2336 int mask,
const std::vector<float> &scales) {
2339 memory::convert_to_c(weights_data_type),
2340 memory::convert_to_c(bias_data_type),
2341 memory::convert_to_c(dst_data_type),
2342 scales.size(), mask, &scales[0]),
2343 "could not append depthwise post-op");
2362 int &mask, std::vector<float> &scales)
const {
2369 const float *c_scales;
2371 &c_weights_data_type, &c_bias_data_type,
2372 &c_dst_data_type, &count, &c_mask, &c_scales),
2373 "could not get parameters of depthwise post-op");
2378 scales.resize(count);
2382 scales[c] = c_scales[c];
2421 int mask,
const std::vector<float> &scales) {
2424 memory::convert_to_c(weights_data_type),
2425 memory::convert_to_c(bias_data_type),
2426 memory::convert_to_c(dst_data_type),
2427 scales.size(), mask, &scales[0]),
2428 "could not append depthwise post-op");
2447 int &mask, std::vector<float> &scales)
const {
2454 const float *c_scales;
2456 &c_weights_data_type, &c_bias_data_type,
2457 &c_dst_data_type, &count, &c_mask, &c_scales),
2458 "could not get parameters of depthwise post-op");
2463 scales.resize(count);
2467 scales[c] = c_scales[c];
2488 "could not append a binary post-op");
2502 "could not get parameters of a binary post-op");
2504 src1_desc.
data = *data;
2527 "could not create primitive attribute");
2544 "could not get scratchpad mode primitive attribute");
2554 "could not set scratchpad mode primitive attribute");
2569 const float *c_scales;
2571 get(), &count, &c_mask, &c_scales),
2572 "could not get output scales primitive attribute");
2573 scales.resize(count);
2577 scales[c] = c_scales[c];
2626 "could not set output scales primitive attribute");
2640 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2643 const float *c_scales;
2645 get(), arg, &count, &c_mask, &c_scales),
2646 "could not get scales primitive attributes");
2647 scales.resize(count);
2651 scales[c] = c_scales[c];
2670 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
2673 (
dnnl_dim_t)scales.size(), mask, scales.data()),
2674 "could not set scales primitive attribute");
2688 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
2691 const int32_t *c_zero_points;
2693 get(), arg, &count, &c_mask, &c_zero_points),
2694 "could not get zero points primitive attribute");
2695 zero_points.resize(count);
2699 zero_points[c] = c_zero_points[c];
2723 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
2726 zero_points.data()),
2727 "could not set zero points primitive attribute");
2737 "could not get post-ops primitive attribute");
2752 "could not set post-ops primitive attribute");
2791 "could not set RNN data quantization parameters primitive "
2823 (
int)scales.size(), mask, scales.data()),
2824 "could not set RNN weights quantization parameters primitive "
2851 "could not retrieve implementation info string from a "
2852 "primitive descriptor");
2881 std::vector<query> valid_q {query::src_md, query::diff_src_md,
2882 query::weights_md, query::diff_weights_md, query::dst_md,
2883 query::diff_dst_md, query::workspace_md, query::scratchpad_md,
2885 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
2886 [=](
query q) { return what == q; }))
2888 "memory descriptor query is invalid");
2901 return query_md(query::src_md, idx);
2910 return query_md(query::dst_md, idx);
2919 return query_md(query::weights_md, idx);
2928 return query_md(query::diff_src_md, idx);
2937 return query_md(query::diff_dst_md, idx);
2946 return query_md(query::diff_weights_md, idx);
2993 return query_md(query::workspace_md, 0);
3002 return query_md(query::scratchpad_md, 0);
3012 "could not retrieve scratchpad engine from a primitive "
3014 return engine(c_engine,
true);
3022 "could not get attributes from a primitive descriptor");
3025 "could not clone primitive attributes");
3035 "could not get primitive kind from a primitive descriptor");
3046 "could not clone a primitive descriptor");
3099 if (pd ==
nullptr)
return;
3112 rc,
"could not get primitive kind from a primitive descriptor");
3113 if (pd_kind != c_prim_kind)
3115 "primitive descriptor operation kind mismatch");
3125 "could not get propagation kind from the primitive "
3131 && (pd_prop_kind == c_prop_kind1
3132 || pd_prop_kind == c_prop_kind2))) {
3139 "primitive descriptor propagation kind mismatch");
3185 bool allow_empty =
false) {
3189 dst_engine.
get(), attr.get());
3192 "could not create a primitive descriptor for a reorder "
3210 bool allow_empty =
false) {
3219 "could not create a primitive descriptor for a reorder "
3234 return engine::query(*
this, dnnl::query::reorder_src_engine);
3240 return engine::query(*
this, dnnl::query::reorder_dst_engine);
3293 const std::vector<memory::desc> &mems) {
3294 std::vector<dnnl_memory_desc_t> c_mems;
3295 c_mems.reserve(mems.size());
3296 for (
const auto &s : mems)
3297 c_mems.push_back(s.data);
3322 const std::vector<memory::desc> &srcs,
const engine &aengine,
3329 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3330 attr.get(), aengine.
get()),
3331 "could not create a primitive descriptor for a concat "
3349 const std::vector<memory::desc> &srcs,
const engine &aengine,
3356 (
int)c_api_srcs.size(), concat_dimension,
3357 c_api_srcs.data(), attr.get(), aengine.
get()),
3358 "could not create a primitive descriptor for a concat "
3413 const std::vector<float> &scales,
3414 const std::vector<memory::desc> &srcs,
const engine &aengine,
3416 validate_container_size(scales,
3417 "counts of scales and sources are not equal",
3418 (
int)srcs.size(), (
int)srcs.size());
3425 (
int)c_api_srcs.size(), scales.data(),
3426 c_api_srcs.data(), attr.get(), aengine.
get()),
3427 "could not create a primitive descriptor for a sum "
3443 const std::vector<memory::desc> &srcs,
const engine &aengine,
3445 validate_container_size(scales,
3446 "counts of scales and sources are not equal",
3447 (
int)srcs.size(), (
int)srcs.size());
3453 (
int)c_api_srcs.size(), scales.data(),
3454 c_api_srcs.data(), attr.get(), aengine.
get()),
3455 "could not create a primitive descriptor for a sum "
3518 bool allow_empty =
false)
3519 : allow_empty_(allow_empty) {
3522 desc, attr ? attr->
get() :
nullptr, aengine.
get(), hint_fwd_pd);
3525 status,
"could not create a primitive descriptor iterator");
3526 pd_iterator.reset(iterator);
3539 status,
"could not advance a primitive descriptor iterator");
3545 bool allow_empty_ =
false;
3549 pd_iterator.
get(allow_empty_));
3552 "could not fetch a primitive descriptor from a primitive "
3553 "descriptor iterator");
3619 &strides[0], &padding_l[0], &padding_r[0]),
3620 "could not create a descriptor for a convolution forward "
3621 "propagation primitive");
3663 &weights_desc.
data,
nullptr, &dst_desc.
data,
3664 &strides[0], &padding_l[0], &padding_r[0]),
3665 "could not create a descriptor for a convolution forward "
3666 "propagation primitive");
3713 &weights_desc.
data, &bias_desc.
data,
3714 &dst_desc.
data, &strides[0], &dilates[0],
3715 &padding_l[0], &padding_r[0]),
3716 "could not create a descriptor for a dilated convolution "
3717 "forward propagation primitive");
3762 &weights_desc.
data,
nullptr,
3763 &dst_desc.
data, &strides[0], &dilates[0],
3764 &padding_l[0], &padding_r[0]),
3765 "could not create a descriptor for a dilated convolution "
3766 "forward propagation primitive");
3786 bool allow_empty =
false)
3788 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
3802 const engine &aengine,
bool allow_empty =
false)
3804 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
3884 &weights_desc.
data, &diff_dst_desc.
data,
3885 &strides[0], &padding_l[0], &padding_r[0]),
3886 "could not create a descriptor for a convolution backward "
3887 "propagation primitive");
3929 &weights_desc.
data, &diff_dst_desc.
data,
3930 &strides[0], &dilates[0], &padding_l[0],
3932 "could not create a descriptor for a dilated convolution "
3933 "backward propagation primitive");
3957 bool allow_empty =
false)
3959 hint_fwd_pd.
get(), allow_empty) {}
3978 bool allow_empty =
false)
3980 hint_fwd_pd.
get(), allow_empty) {}
4055 &diff_weights_desc.
data, &diff_bias_desc.
data,
4056 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4058 "could not create a descriptor for a convolution weights "
4059 "update primitive");
4096 &diff_weights_desc.
data,
nullptr,
4097 &diff_dst_desc.
data, &strides[0],
4098 &padding_l[0], &padding_r[0]),
4099 "could not create a descriptor for a convolution weights "
4100 "update primitive");
4145 &diff_weights_desc.
data, &diff_bias_desc.
data,
4146 &diff_dst_desc.
data, &strides[0], &dilates[0],
4147 &padding_l[0], &padding_r[0]),
4148 "could not create a descriptor for a dilated convolution "
4149 "weights gradient primitive");
4191 &diff_weights_desc.
data,
nullptr,
4192 &diff_dst_desc.
data, &strides[0], &dilates[0],
4193 &padding_l[0], &padding_r[0]),
4194 "could not create a descriptor for a dilated convolution "
4195 "weights gradient primitive");
4218 bool allow_empty =
false)
4220 hint_fwd_pd.
get(), allow_empty) {}
4238 bool allow_empty =
false)
4240 hint_fwd_pd.
get(), allow_empty) {}
4339 &strides[0], &padding_l[0], &padding_r[0]),
4340 "could not create a descriptor for a deconvolution forward "
4341 "propagation primitive");
4382 &weights_desc.
data,
nullptr, &dst_desc.
data,
4383 &strides[0], &padding_l[0], &padding_r[0]),
4384 "could not create a descriptor for a deconvolution forward "
4385 "propagation primitive");
4431 &weights_desc.
data, &bias_desc.
data,
4432 &dst_desc.
data, &strides[0], &dilates[0],
4433 &padding_l[0], &padding_r[0]),
4434 "could not create a descriptor for a dilated deconvolution "
4435 "forward propagation primitive");
4479 &weights_desc.
data,
nullptr,
4480 &dst_desc.
data, &strides[0], &dilates[0],
4481 &padding_l[0], &padding_r[0]),
4482 "could not create a descriptor for a dilated deconvolution "
4483 "forward propagation primitive");
4503 bool allow_empty =
false)
4505 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4519 const engine &aengine,
bool allow_empty =
false)
4521 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4596 &weights_desc.
data, &diff_dst_desc.
data,
4597 &strides[0], &padding_l[0], &padding_r[0]),
4598 "could not create a descriptor for a deconvolution "
4599 "backward propagation primitive");
4640 &weights_desc.
data, &diff_dst_desc.
data,
4641 &strides[0], &dilates[0], &padding_l[0],
4643 "could not create a descriptor for a dilated deconvolution "
4644 "backward propagation primitive");
4668 bool allow_empty =
false)
4670 hint_fwd_pd.
get(), allow_empty) {}
4689 bool allow_empty =
false)
4691 hint_fwd_pd.
get(), allow_empty) {}
4765 &diff_weights_desc.
data, &diff_bias_desc.
data,
4766 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4768 "could not create a descriptor for a deconvolution weights "
4769 "update primitive");
4805 &src_desc.
data, &diff_weights_desc.
data,
4806 nullptr, &diff_dst_desc.
data, &strides[0],
4807 &padding_l[0], &padding_r[0]),
4808 "could not create a descriptor for a deconvolution weights "
4809 "update primitive");
4853 &diff_weights_desc.
data, &diff_bias_desc.
data,
4854 &diff_dst_desc.
data, &strides[0], &dilates[0],
4855 &padding_l[0], &padding_r[0]),
4856 "could not create a descriptor for a dilated deconvolution "
4857 "weights gradient primitive");
4898 &diff_weights_desc.
data,
nullptr,
4899 &diff_dst_desc.
data, &strides[0], &dilates[0],
4900 &padding_l[0], &padding_r[0]),
4901 "could not create a descriptor for a dilated deconvolution "
4902 "weights gradient primitive");
4926 bool allow_empty =
false)
4928 hint_fwd_pd.
get(), allow_empty) {}
4947 bool allow_empty =
false)
4949 hint_fwd_pd.
get(), allow_empty) {}
5019 float alpha,
float beta,
float k = 1.f) {
5023 local_size, alpha, beta, k),
5024 "could not create a descriptor for a lrn forward "
5025 "propagation primitive");
5044 bool allow_empty =
false)
5046 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5059 const engine &aengine,
bool allow_empty =
false)
5061 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5113 float alpha,
float beta,
float k = 1.f) {
5116 &diff_data_desc.
data, &data_desc.
data, local_size,
5118 "could not create a descriptor for a lrn backward "
5119 "propagation primitive");
5142 bool allow_empty =
false)
5144 hint_fwd_pd.
get(), allow_empty) {}
5162 bool allow_empty =
false)
5164 hint_fwd_pd.
get(), allow_empty) {}
5246 &dst_desc.
data, &strides[0], &kernel[0],
5247 &padding_l[0], &padding_r[0]),
5248 "could not create a descriptor for a pooling forward "
5249 "propagation primitive");
5268 bool allow_empty =
false)
5270 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5283 const engine &aengine,
bool allow_empty =
false)
5285 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5355 &diff_dst_desc.
data, &strides[0], &kernel[0],
5356 &padding_l[0], &padding_r[0]),
5357 "could not create a descriptor for a pooling backward "
5358 "propagation primitive");
5381 bool allow_empty =
false)
5383 hint_fwd_pd.
get(), allow_empty) {}
5401 bool allow_empty =
false)
5403 hint_fwd_pd.
get(), allow_empty) {}
5481 &data_desc.
data, alpha, beta),
5482 "could not create a descriptor for an eltwise forward "
5483 "propagation primitive");
5503 bool allow_empty =
false)
5505 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5519 const engine &aengine,
bool allow_empty =
false)
5521 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5573 &diff_data_desc.
data, &data_desc.
data, alpha, beta),
5574 "could not create a descriptor for an eltwise backward "
5575 "propagation primitive");
5599 bool allow_empty =
false)
5601 hint_fwd_pd.
get(), allow_empty) {}
5620 bool allow_empty =
false)
5622 hint_fwd_pd.
get(), allow_empty) {}
5684 &data_desc.
data, softmax_axis),
5685 "could not create a descriptor for a softmax forward "
5686 "propagation primitive");
5706 bool allow_empty =
false)
5708 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5722 const engine &aengine,
bool allow_empty =
false)
5724 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5773 &data_desc.
data, softmax_axis),
5774 "could not create a descriptor for a softmax backward "
5775 "propagation primitive");
5799 bool allow_empty =
false)
5801 hint_fwd_pd.
get(), allow_empty) {}
5820 bool allow_empty =
false)
5822 hint_fwd_pd.
get(), allow_empty) {}
5881 int logsoftmax_axis) {
5884 &data_desc.
data, logsoftmax_axis),
5885 "could not create a descriptor for a logsoftmax forward "
5886 "propagation primitive");
5906 bool allow_empty =
false)
5908 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5922 const engine &aengine,
bool allow_empty =
false)
5924 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5974 int logsoftmax_axis) {
5976 &diff_data_desc.
data, &data_desc.
data,
5978 "could not create a descriptor for a logsoftmax backward "
5979 "propagation primitive");
6003 bool allow_empty =
false)
6005 hint_fwd_pd.
get(), allow_empty) {}
6024 bool allow_empty =
false)
6026 hint_fwd_pd.
get(), allow_empty) {}
6109 "could not create a descriptor for a batch normalization "
6110 "forward propagation primitive");
6131 bool allow_empty =
false)
6133 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6147 const engine &aengine,
bool allow_empty =
false)
6149 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6194 "could not retrieve a descriptor from a primitive "
6195 "descriptor for batch normalization forward propagation "
6235 &diff_data_desc.
data, &data_desc.
data,
6237 "could not create a descriptor for a batch normalization "
6238 "backward propagation primitive");
6263 bool allow_empty =
false)
6265 hint_fwd_pd.
get(), allow_empty) {}
6284 bool allow_empty =
false)
6286 hint_fwd_pd.
get(), allow_empty) {}
6389 "could not create a descriptor for a layer normalization "
6390 "forward propagation primitive");
6409 "could not create a descriptor for a layer normalization "
6410 "forward propagation primitive");
6431 bool allow_empty =
false)
6433 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6447 const engine &aengine,
bool allow_empty =
false)
6449 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6492 "could not retrieve a descriptor from a primitive "
6493 "descriptor for layer normalization forward propagation "
6535 &diff_data_desc.
data, &data_desc.
data,
6537 "could not create a descriptor for a batch normalization "
6538 "backward propagation primitive");
6558 &diff_data_desc.
data, &data_desc.
data,
6560 "could not create a descriptor for a batch normalization "
6561 "backward propagation primitive");
6586 bool allow_empty =
false)
6588 hint_fwd_pd.
get(), allow_empty) {}
6607 bool allow_empty =
false)
6609 hint_fwd_pd.
get(), allow_empty) {}
6699 &src_desc.
data, &weights_desc.
data,
6701 "could not create a descriptor for an inner product "
6702 "forward propagation primitive");
6724 &weights_desc.
data,
nullptr, &dst_desc.
data),
6725 "could not create a descriptor for an inner product "
6726 "forward propagation primitive");
6746 bool allow_empty =
false)
6748 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6762 const engine &aengine,
bool allow_empty =
false)
6764 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6819 &diff_src_desc.
data, &weights_desc.
data,
6820 &diff_dst_desc.
data),
6821 "could not create a descriptor for an inner product "
6822 "backward propagation primitive");
6847 bool allow_empty =
false)
6849 hint_fwd_pd.
get(), allow_empty) {}
6868 bool allow_empty =
false)
6870 hint_fwd_pd.
get(), allow_empty) {}
6924 &src_desc.
data, &diff_weights_desc.
data,
6925 &diff_bias_desc.
data, &diff_dst_desc.
data),
6926 "could not create a descriptor for an inner product "
6927 "weights gradient primitive");
6945 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
6946 &diff_dst_desc.
data),
6947 "could not create a descriptor for an inner product "
6948 "weights gradient primitive");
6972 bool allow_empty =
false)
6974 hint_fwd_pd.
get(), allow_empty) {}
6993 bool allow_empty =
false)
6995 hint_fwd_pd.
get(), allow_empty) {}
7045 using primitive_desc::primitive_desc;
7229 "could not retrieve a descriptor from a primitive descriptor "
7230 "for an RNN primitive");
7243 "mismatch between expected and provided descriptors for an "
7305 float beta = 0.0f) {
7311 &src_iter_desc.
data, &weights_layer_desc.
data,
7312 &weights_iter_desc.
data, &bias_desc.
data,
7313 &dst_layer_desc.
data, &dst_iter_desc.
data,
7315 "could not create a descriptor for a vanilla RNN forward "
7316 "propagation primitive");
7336 bool allow_empty =
false)
7338 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7352 const engine &aengine,
bool allow_empty =
false)
7354 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7485 float beta = 0.0f) {
7491 &src_iter_desc.
data, &weights_layer_desc.
data,
7492 &weights_iter_desc.
data, &bias_desc.
data,
7493 &dst_layer_desc.
data, &dst_iter_desc.
data,
7494 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7495 &diff_weights_layer_desc.
data,
7496 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7497 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7499 "could not create a descriptor for a vanilla RNN backward "
7500 "propagation primitive");
7524 bool allow_empty =
false)
7526 hint_fwd_pd.
get(), allow_empty) {}
7545 bool allow_empty =
false)
7547 hint_fwd_pd.
get(), allow_empty) {}
7709 &src_iter_desc.
data, &src_iter_c_desc.
data,
7710 &weights_layer_desc.
data, &weights_iter_desc.
data,
7711 &weights_peephole_desc.
data,
7712 &weights_projection_desc.
data, &bias_desc.
data,
7713 &dst_layer_desc.
data, &dst_iter_desc.
data,
7715 "could not create a descriptor for an LSTM forward "
7716 "propagation primitive");
7776 &src_iter_desc.
data, &src_iter_c_desc.
data,
7777 &weights_layer_desc.
data, &weights_iter_desc.
data,
7778 &weights_peephole_desc.
data, &bias_desc.
data,
7779 &dst_layer_desc.
data, &dst_iter_desc.
data,
7781 "could not create a descriptor for an LSTM forward "
7782 "propagation primitive");
7836 &src_iter_desc.
data, &src_iter_c_desc.
data,
7837 &weights_layer_desc.
data, &weights_iter_desc.
data,
7838 &bias_desc.
data, &dst_layer_desc.
data,
7839 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
7841 "could not create a descriptor for an LSTM forward "
7842 "propagation primitive");
7861 bool allow_empty =
false)
7863 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7876 const engine &aengine,
bool allow_empty =
false)
7878 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8064 &src_iter_desc.
data, &src_iter_c_desc.
data,
8065 &weights_layer_desc.
data, &weights_iter_desc.
data,
8066 &weights_peephole_desc.
data,
8067 &weights_projection_desc.
data, &bias_desc.
data,
8068 &dst_layer_desc.
data, &dst_iter_desc.
data,
8069 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8070 &diff_src_iter_desc.
data,
8071 &diff_src_iter_c_desc.
data,
8072 &diff_weights_layer_desc.
data,
8073 &diff_weights_iter_desc.
data,
8074 &diff_weights_peephole_desc.
data,
8075 &diff_weights_projection_desc.
data,
8076 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8077 &diff_dst_iter_desc.
data,
8078 &diff_dst_iter_c_desc.
data,
8080 "could not create a descriptor for an LSTM backward "
8081 "propagation primitive");
8174 &src_iter_desc.
data, &src_iter_c_desc.
data,
8175 &weights_layer_desc.
data, &weights_iter_desc.
data,
8176 &weights_peephole_desc.
data, &bias_desc.
data,
8177 &dst_layer_desc.
data, &dst_iter_desc.
data,
8178 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8179 &diff_src_iter_desc.
data,
8180 &diff_src_iter_c_desc.
data,
8181 &diff_weights_layer_desc.
data,
8182 &diff_weights_iter_desc.
data,
8183 &diff_weights_peephole_desc.
data,
8184 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8185 &diff_dst_iter_desc.
data,
8186 &diff_dst_iter_c_desc.
data,
8188 "could not create a descriptor for an LSTM backward "
8189 "propagation primitive");
8271 &src_iter_desc.
data, &src_iter_c_desc.
data,
8272 &weights_layer_desc.
data, &weights_iter_desc.
data,
8273 &bias_desc.
data, &dst_layer_desc.
data,
8274 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8275 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8276 &diff_src_iter_c_desc.
data,
8277 &diff_weights_layer_desc.
data,
8278 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8279 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8280 &diff_dst_iter_c_desc.
data,
8282 "could not create a descriptor for an LSTM backward "
8283 "propagation primitive");
8306 bool allow_empty =
false)
8308 hint_fwd_pd.
get(), allow_empty) {}
8326 bool allow_empty =
false)
8328 hint_fwd_pd.
get(), allow_empty) {}
8510 &src_iter_desc.
data, &weights_layer_desc.
data,
8511 &weights_iter_desc.
data, &bias_desc.
data,
8512 &dst_layer_desc.
data, &dst_iter_desc.
data,
8514 "could not create a descriptor for a GRU forward "
8515 "propagation primitive");
8534 bool allow_empty =
false)
8536 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8549 const engine &aengine,
bool allow_empty =
false)
8551 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8678 &src_iter_desc.
data, &weights_layer_desc.
data,
8679 &weights_iter_desc.
data, &bias_desc.
data,
8680 &dst_layer_desc.
data, &dst_iter_desc.
data,
8681 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8682 &diff_weights_layer_desc.
data,
8683 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8684 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8686 "could not create a descriptor for a GRU backward "
8687 "propagation primitive");
8710 bool allow_empty =
false)
8712 hint_fwd_pd.
get(), allow_empty) {}
8730 bool allow_empty =
false)
8732 hint_fwd_pd.
get(), allow_empty) {}
8875 &src_iter_desc.
data, &weights_layer_desc.
data,
8876 &weights_iter_desc.
data, &bias_desc.
data,
8877 &dst_layer_desc.
data, &dst_iter_desc.
data,
8879 "could not create a descriptor for an LBR GRU forward "
8880 "propagation primitive");
8900 bool allow_empty =
false)
8902 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8916 const engine &aengine,
bool allow_empty =
false)
8918 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9046 &src_iter_desc.
data, &weights_layer_desc.
data,
9047 &weights_iter_desc.
data, &bias_desc.
data,
9048 &dst_layer_desc.
data, &dst_iter_desc.
data,
9049 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9050 &diff_weights_layer_desc.
data,
9051 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9052 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9054 "could not create a descriptor for an LBR GRU backward "
9055 "propagation primitive");
9079 bool allow_empty =
false)
9081 hint_fwd_pd.
get(), allow_empty) {}
9100 bool allow_empty =
false)
9102 hint_fwd_pd.
get(), allow_empty) {}
9222 &data_desc.
data, axis, group_size),
9223 "could not create a descriptor for a shuffle forward "
9224 "propagation primitive");
9246 bool allow_empty =
false)
9248 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9293 &diff_data_desc.
data, axis, group_size),
9294 "could not create a descriptor for a shuffle backward "
9295 "propagation primitive");
9321 bool allow_empty =
false)
9323 hint_fwd_pd.
get(), allow_empty) {}
9383 "could not create a descriptor for a binary operation "
9403 bool allow_empty =
false)
9405 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9418 const engine &aengine,
bool allow_empty =
false)
9420 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9478 &weights_desc.
data,
nullptr, &dst_desc.
data),
9479 "could not create a descriptor for a matmul primitive");
9491 &weights_desc.
data, &bias_desc.
data,
9493 "could not create a descriptor for a matmul primitive");
9511 bool allow_empty =
false)
9513 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9525 const engine &aengine,
bool allow_empty =
false)
9527 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9541 return query_md(query::weights_md, 0);
9546 return query_md(query::weights_md, 1);
9600 "could not create a resampling forward descriptor");
9615 const std::vector<float> &factors,
9621 &src_desc.
data,
nullptr),
9622 "could not create a resampling forward descriptor");
9642 const std::vector<float> &factors,
const memory::desc &src_desc,
9644 if (!factors.empty())
9650 "could not create a resampling forward descriptor");
9670 bool allow_empty =
false)
9672 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9686 const engine &aengine,
bool allow_empty =
false)
9688 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9735 &diff_src_desc.
data, &diff_dst_desc.
data),
9736 "could not create a resampling backward data descriptor");
9751 if (!factors.empty())
9755 &diff_src_desc.
data, &diff_dst_desc.
data),
9756 "could not create a resampling backward data descriptor");
9780 bool allow_empty =
false)
9782 hint_fwd_pd.
get(), allow_empty) {}
9801 bool allow_empty =
false)
9803 hint_fwd_pd.
get(), allow_empty) {}
9882 &dst_desc.
data, &strides[0], &kernel[0],
9883 &dilation[0], &padding_l[0], &padding_r[0]),
9884 "could not create a descriptor for a pooling forward "
9885 "propagation primitive");
9905 bool allow_empty =
false)
9907 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9921 const engine &aengine,
bool allow_empty =
false)
9923 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9998 &diff_dst_desc.
data, &strides[0], &kernel[0],
9999 &dilation[0], &padding_l[0], &padding_r[0]),
10000 "could not create a descriptor for a pooling backward "
10001 "propagation primitive");
10026 bool allow_empty =
false)
10028 hint_fwd_pd.
get(), allow_empty) {}
10047 bool allow_empty =
false)
10049 hint_fwd_pd.
get(), allow_empty) {}
10123 &src_desc.
data, &dst_desc.
data, p, eps),
10124 "could not create a reduction descriptor");
10142 bool allow_empty =
false)
10144 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10156 const engine &aengine,
bool allow_empty =
false)
10158 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10264 return static_cast<status>(
10286 "could not get primitive cache capacity");
10293 "could not set primitive cache capacity");
10310 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10317 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10319 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10326 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10328 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10339 "could not create a primitive");
10345 inline void primitive::execute(
const stream &astream,
10346 const std::unordered_map<int, memory> &args)
const {
10347 std::vector<dnnl_exec_arg_t> c_args;
10348 c_args.reserve(args.size());
10349 for (
const auto &a : args)
10350 c_args.push_back({a.first, a.second.get(
true)});
10353 (
int)c_args.size(), c_args.data()),
10354 "could not execute a primitive");
10358 #undef DNNL_DEFINE_BITMASK_OPS
10365 namespace dnnl = ::dnnl;
primitive_desc(const desc &adesc, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6845
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2235
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2247
void set_data_handle(void *handle) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2074
handle(handle< T, traits > &&)=default
Move constructor.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7594
primitive(const primitive_desc &pd)
Constructs a primitive from a primitive descriptor.
status gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
Definition: dnnl.hpp:10323
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_next(dnnl_primitive_desc_iterator_t iterator)
Advances the primitive descriptor iterator to point to the next available implementation.
Resampling backward propagation primitive.
Definition: dnnl.hpp:9718
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4719
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9430
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1930
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3824
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:2788
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6507
logsoftmax_backward()=default
Default constructor. Produces an empty object.
desc(prop_kind aprop_kind, algorithm activation, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, rnn_flags flags=rnn_flags::undef, float alpha=0.0f, float beta=0.0f)
Constructs a descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7469
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7641
@ softmax
A softmax primitive.
engine()=default
Constructs an empty engine.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7203
dnnl_status_t DNNL_API dnnl_inner_product_forward_desc_init(dnnl_inner_product_desc_t *ip_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes descriptor for inner product forward propagation.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7083
dnnl_status_t DNNL_API dnnl_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:5850
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5835
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:9960
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8583
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ success
The operation was successful.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution forward propagation primitive from a C API prim...
Definition: dnnl.hpp:4529
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:913
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5078
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9389
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:702
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:915
convolution_backward_data()=default
Default constructor. Produces an empty object.
void execute(const stream &astream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
@ all
Any ISA (excepting those listed as initial support)
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8462
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:1934
Reorder primitive.
Definition: dnnl.hpp:3157
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2259
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9278
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6677
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7578
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a LBR GRU forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:8926
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8445
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6647
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7586
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8809
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:96
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8794
dnnl_status_t DNNL_API dnnl_pooling_backward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling backward propagation primitive.
@ any
An unspecified engine.
void get_params_dw_k3s2p1(int index, memory::data_type &weights_data_type, memory::data_type &bias_data_type, memory::data_type &dst_data_type, int &mask, std::vector< float > &scales) const
Returns the parameters of an depthwise post-op with stride 2.
Definition: dnnl.hpp:2445
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:366
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8885
Convolution weights gradient primitive.
Definition: dnnl.hpp:4012
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:973
An execution stream.
Definition: dnnl.hpp:975
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:1787
void get_params_dw_k3s1p1(int index, memory::data_type &weights_data_type, memory::data_type &bias_data_type, memory::data_type &dst_data_type, int &mask, std::vector< float > &scales) const
Returns the parameters of an depthwise post-op with stride 1.
Definition: dnnl.hpp:2360
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4502
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution forward propagation primitive without bias.
Definition: dnnl.hpp:4371
primitive_desc(const desc &adesc, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4216
primitive_desc(const desc &adesc, const engine &aengine, const softmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5797
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Constructs a descriptor for an inner product forward propagation primitive with bias.
Definition: dnnl.hpp:6694
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2236
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
prop_kind
Propagation kind.
Definition: dnnl.hpp:433
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5302
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2196
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a matmul primitive from a C API primitive descriptor that must ...
Definition: dnnl.hpp:9533
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution forward propagation primitive.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9402
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:837
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
An opaque structure to describe a memory.
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:211
Softmax backward propagation primitive.
Definition: dnnl.hpp:5754
Primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10129
primitive_desc()=default
Default constructor. Produces an empty object.
An opaque structure to describe a primitive descriptor iterator.
pooling_v2_backward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10079
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:833
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7412
rnn_primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::prop_kind aprop_kind, dnnl::algorithm cell_kind)
Constructs an RNN primitive descriptor base from a C API primitive descriptor while checking that it ...
Definition: dnnl.hpp:7057
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2267
status gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
Definition: dnnl.hpp:10314
Descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7414
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5177
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8976
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:2036
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9537
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7847
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5192
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated convolution forward propagation primitive without bias.
Definition: dnnl.hpp:3750
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2054
primitive_desc(const desc &adesc, const engine &aengine, const eltwise_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5597
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for LSTM forward propagation primitive.
engine(const handle< dnnl_primitive_desc_t > &pd)
Constructs an engine based on a primitive from the primitive descriptor pd by querying its engine.
Definition: dnnl.hpp:904
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc)
Constructs a descriptor for an inner product forward propagation primitive without bias.
Definition: dnnl.hpp:6718
dnnl_cpu_isa_t DNNL_API dnnl_get_effective_cpu_isa(void)
Gets the maximal ISA the library can dispatch to on the CPU.
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7143
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2246
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3233
memory(const desc &md, const engine &aengine)
Constructs a memory object.
Definition: dnnl.hpp:2000
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8573
#define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:2066
An execution engine.
Definition: dnnl.hpp:859
desc(prop_kind aprop_kind, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a batch normalization descriptor for forward propagation.
Definition: dnnl.hpp:6103
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for sum primitive from a C API primitive descriptor which must have...
Definition: dnnl.hpp:3464
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5419
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an eltwise backward propagation primitive from a C API primitiv...
Definition: dnnl.hpp:5630
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:6796
desc()=default
Default constructor. Produces an empty object.
void get_zero_points(int arg, int &mask, std::vector< int32_t > &zero_points) const
Returns zero points correspondence mask and values.
Definition: dnnl.hpp:2687
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:827
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution backward propagation primitive from a C API pri...
Definition: dnnl.hpp:4699
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:996
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:4999
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7011
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5553
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s2p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 2.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a resampling backward propagation primitive from a C API primit...
Definition: dnnl.hpp:9811
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2264
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:2022
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &dilation, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9868
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1047
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1935
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8410
kind
Kinds of primitives supported by the library.
Definition: dnnl.hpp:271
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8565
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2188
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:10234
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5363
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8753
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6661
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:1721
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7933
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8611
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8899
primitive_desc(const memory &src, const memory &dst, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for reorder primitive.
Definition: dnnl.hpp:3208
An opaque structure to describe an engine.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6633
primitive_desc()=default
Default constructor. Produces an empty object.
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5547
Reduction.
Definition: dnnl.hpp:10094
logsoftmax_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_binary(const_dnnl_post_ops_t post_ops, int index, dnnl_alg_kind_t *alg_kind, const dnnl_memory_desc_t **src1_desc)
Returns the parameters of a binary post-op.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7397
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:9576
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5641
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1015
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:874
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1773
@ shuffle
A shuffle primitive.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8578
concat()=default
Default constructor. Produces an empty object.
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:7167
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:882
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5830
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3993
void append_sum(float scale=1.f, memory::data_type data_type=memory::data_type::undef)
Appends an accumulation (sum) post-op.
Definition: dnnl.hpp:2236
@ none
Use no normalization flags.
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:987
pooling_v2_forward()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8440
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9136
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:921
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9669
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2927
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5551
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &weights_peephole_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_src_iter_c_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_weights_peephole_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, const memory::desc &diff_dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs an LSTM (with or without peephole) descriptor for backward propagation using prop_kind,...
Definition: dnnl.hpp:8148
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:815
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2256
desc permute_axes(const std::vector< int > &permutation, bool allow_empty=false) const
Constructs a memory descriptor by permuting axes in an existing one.
Definition: dnnl.hpp:1904
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9464
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9816
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8359
desc()=default
Default constructor. Produces an empty object.
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7095
A descriptor of a convolution operation.
Definition: dnnl_types.h:1277
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3996
primitive_desc(const desc &adesc, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3955
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3818
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7155
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6301
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:809
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5458
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5422
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3975
dnnl_status_t DNNL_API dnnl_memory_desc_permute_axes(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, const int *permutation)
Initializes a memory descriptor by permuting axes in an existing one.
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4965
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1643
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:927
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
dnnl_status_t DNNL_API dnnl_memory_desc_reshape(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, int ndims, const dnnl_dims_t dims)
Initializes a memory descriptor by reshaping an existing one.
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2297
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2226
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a logsoftmax forward propagation primitive from a C API primiti...
Definition: dnnl.hpp:5932
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a resampling forward propagation primitive from a C API primiti...
Definition: dnnl.hpp:9696
void append_dw_k3s2p1(memory::data_type weights_data_type, memory::data_type bias_data_type, memory::data_type dst_data_type, int mask, const std::vector< float > &scales)
Appends a depthwise post-op convolution with stride 2.
Definition: dnnl.hpp:2419
dnnl_status_t DNNL_API dnnl_logsoftmax_forward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax forward propagation primitive.
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
desc submemory_desc(const dims &adims, const dims &offsets, bool allow_empty=false) const
Constructs a memory descriptor for a region inside an area described by this memory descriptor.
Definition: dnnl.hpp:1800
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:648
A descriptor for an RNN operation.
Definition: dnnl_types.h:1665
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1649
desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7897
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:10239
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5921
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:819
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:883
void set_data_handle(void *handle, const stream &astream) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2058
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a convolution weights gradient primitive from a C API primitive...
Definition: dnnl.hpp:4248
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9466
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7030
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8594
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a shuffle forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:9256
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5030
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a shuffle backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:9331
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:802
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2909
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3534
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:9179
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6467
A descriptor of an inner product operation.
Definition: dnnl_types.h:1609
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7928
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:6953
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s2p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 2.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a layer normalization forward propagation primitive from a C AP...
Definition: dnnl.hpp:6457
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1865
primitive()=default
Default constructor. Constructs an empty object.
dnnl_status_t DNNL_API dnnl_memory_unmap_data(const_dnnl_memory_t memory, void *mapped_ptr)
Unmaps a memory object and writes back any changes made to the previously mapped memory buffer.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5305
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5864
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8658
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &weights_peephole_desc, const memory::desc &weights_projection_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_src_iter_c_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_weights_peephole_desc, const memory::desc &diff_weights_projection_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, const memory::desc &diff_dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs an LSTM (with or without peephole and with or without projection) descriptor for backward ...
Definition: dnnl.hpp:8036
dnnl_status_t DNNL_API dnnl_layer_normalization_backward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for a layer normalization backward propagation primitive.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8779
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3471
desc(algorithm aalgorithm, const std::vector< float > &factors, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:9748
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7183
desc(prop_kind aprop_kind, algorithm aalgorithm, const std::vector< float > &factors, const memory::desc &src_desc, const memory::desc &dst_desc)
Constructs a descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9641
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5460
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:1920
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a vanilla RNN backward propagation primitive from a C API primi...
Definition: dnnl.hpp:7555
LSTM backward propagation primitive.
Definition: dnnl.hpp:7956
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6368
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5538
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2278
primitive_desc(const desc &adesc, const engine &aengine, const resampling_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9778
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:8605
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a layer normalization backward propagation primitive from a C A...
Definition: dnnl.hpp:6617
Descriptor for reduction.
Definition: dnnl.hpp:10096
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2249
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:892
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8945
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8354
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5314
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:825
GRU forward propagation primitive.
Definition: dnnl.hpp:8460
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:2299
kind
Kinds of engines.
Definition: dnnl.hpp:864
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9169
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6313
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7376
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a GRU forward propagation primitive from a C API primitive desc...
Definition: dnnl.hpp:8559
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &weights_peephole_desc, const memory::desc &weights_projection_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for an LSTM (with or without peephole and with or without projection) forward...
Definition: dnnl.hpp:7692
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8341
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6181
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:9839
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:6898
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:868
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9448
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:884
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2398
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8932
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:981
lstm_backward()=default
Default constructor. Produces an empty object.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:210
reduction(const primitive_desc &pd)
Constructs a reduction primitive.
Definition: dnnl.hpp:10179
stream()=default
Constructs an empty stream.
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:888
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9190
static void validate_dims(const std::vector< T > &v, int min_size=0)
Helper function that validates that an std::vector of dimensions can be safely converted to the C API...
Definition: dnnl.hpp:1114
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution forward propagation primitive without bias.
Definition: dnnl.hpp:3652
desc(algorithm aalgorithm, const memory::desc &src0, const memory::desc &src1, const memory::desc &dst)
Constructs a descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9378
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10263
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1668
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6043
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6146
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8288
@ pooling
A pooling primitive.
Primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10007
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6889
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:3019
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8763
desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for concat primitive from a C API primitive descriptor which must h...
Definition: dnnl.hpp:3367
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5043
primitive_desc(const desc &adesc, const engine &aengine, const lbr_gru_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9077
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:792
dnnl_status_t DNNL_API dnnl_pooling_v2_backward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) backward propagation primitiv...
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4586
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2244
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2279
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2269
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7135
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2551
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:399
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5416
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2263
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7373
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:2134
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1645
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:549
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2254
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8804
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9655
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8497
@ dnnl_cpu_isa_avx512_core_amx
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2413
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6177
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5075
primitive_desc()=default
Default constructor. Produces an empty object.
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:3007
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2146
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) backward propagation primitive.
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8425
sum()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7599
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7589
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5090
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const batch_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6281
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7386
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3398
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7821
deconvolution_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:899
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1656
reorder(const memory &src, const memory &dst, const primitive_attr &attr=primitive_attr())
Constructs a reorder primitive that would reorder data between memory objects having the same memory ...
Definition: dnnl.hpp:3264
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2962
A descriptor of a pooling operation.
Definition: dnnl_types.h:1435
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6366
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4253
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4962
primitive_desc_base()=default
Default constructor. Produces an empty object.
void set_zero_points(int arg, int mask, const std::vector< int32_t > &zero_points)
Sets zero points for primitive operations for a given memory argument.
Definition: dnnl.hpp:2722
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2122
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization backward propagation primitive.
Definition: dnnl.hpp:6553
primitive_desc(const engine &src_engine, const memory::desc &src_md, const engine &dst_engine, const memory::desc &dst_md, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for reorder primitive.
Definition: dnnl.hpp:3182
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:915
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7581
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3801
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated convolution forward propagation primitive with bias.
Definition: dnnl.hpp:3701
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product descriptor weights update primitive with bias.
Definition: dnnl.hpp:6918
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:937
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:9761
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2986
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:2750
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:979
dnnl_status_t DNNL_API dnnl_primitive_attr_create(dnnl_primitive_attr_t *attr)
Creates an empty (default) primitive attributes with all the parameters set to their default values.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9920
eltwise_backward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a GRU backward propagation primitive from a C API primitive des...
Definition: dnnl.hpp:8740
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_weights_projection_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or with out recurrent project...
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:955
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &dilation, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:9986
void append_dw_k3s1p1(memory::data_type weights_data_type, memory::data_type bias_data_type, memory::data_type dst_data_type, int mask, const std::vector< float > &scales)
Appends a depthwise post-op convolution with stride 1.
Definition: dnnl.hpp:2334
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5488
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:3031
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_zero_points(const_dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const int32_t **zero_points)
Returns count, correspondence zero point mask, and a pointer to a constant int32_t array of zero_poin...
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:959
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum_v2(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_data_type_t *data_type)
Returns the parameters of an accumulation (sum) post-op with a data type parameter.
@ resampling
A resampling primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_output_scales(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets output scaling factors correspondence mask and values.
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_create(dnnl_primitive_desc_iterator_t *iterator, const_dnnl_op_desc_t op_desc, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine, const_dnnl_primitive_desc_t hint_forward_primitive_desc)
Creates a primitive descriptor iterator.
desc(prop_kind aprop_kind, algorithm aalgorithm, const std::vector< float > &factors, const memory::desc &src_desc)
Constructs a descriptor for a resampling forward propagation primitive using source memory descriptor...
Definition: dnnl.hpp:9614
shuffle_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_softmax_forward_desc_init(dnnl_softmax_desc_t *softmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax forward propagation primitive.
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(dnnl_primitive_desc_t *primitive_desc, const_dnnl_primitive_desc_t existing_primitive_desc)
Clones a primitive descriptor.
const dnnl_version_t DNNL_API * dnnl_version(void)
Returns library version information.
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:1022
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:905
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9060
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5001
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5691
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2262
desc(prop_kind aprop_kind, algorithm activation, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, rnn_flags flags=rnn_flags::undef, float alpha=0.0f, float beta=0.0f)
Constructs a descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7296
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5180
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an LRN forward propagation primitive from a C API primitive des...
Definition: dnnl.hpp:5069
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution backward propagation primitive.
Definition: dnnl.hpp:4628
Pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9837
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6761
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3247
primitive_desc()=default
Default constructor. Produces an empty object.
int get_primitive_cache_capacity()
Returns the number of primitives that can be held in the primitive cache at the same time.
Definition: dnnl.hpp:10283
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3244
Post-ops.
Definition: dnnl.hpp:2184
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:965
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6883
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2968
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8799
lstm_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:2992
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6416
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:788
query
Primitive descriptor query specification.
Definition: dnnl.hpp:735
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8591
dnnl_status_t DNNL_API dnnl_primitive_desc_query(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index, void *result)
Queries a primitive descriptor for various pieces of information.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a reduction primitive from a C API primitive descriptor that mu...
Definition: dnnl.hpp:10164
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:880
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1035
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2140
dnnl_status_t DNNL_API dnnl_primitive_execute(const_dnnl_primitive_t primitive, dnnl_stream_t stream, int nargs, const dnnl_exec_arg_t *args)
Executes a primitive.
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2394
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8940
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6058
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:4723
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8958
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6778
desc(const memory::desc &diff_data_desc, const memory::desc &data_desc, int softmax_axis)
Constructs a descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5769
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
#define DNNL_ARG_DIFF_BIAS
Gradient (diff) of the bias tensor argument.
Definition: dnnl_types.h:2155
dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr)
Destroys primitive attributes.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum(dnnl_post_ops_t post_ops, float scale)
Appends an accumulation (sum) to post-ops.
primitive_desc(const desc &adesc, const engine &aengine, const lstm_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8304
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2060
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7071
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3303
dnnl_status_t DNNL_API dnnl_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU forward propagation primitive.
dnnl_status_t DNNL_API dnnl_gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5960
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:866
Convolution forward propagation primitive.
Definition: dnnl.hpp:3571
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6046
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6215
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:567
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6084
dnnl_status_t DNNL_API dnnl_memory_desc_init_submemory(dnnl_memory_desc_t *memory_desc, const dnnl_memory_desc_t *parent_memory_desc, const dnnl_dims_t dims, const dnnl_dims_t offsets)
Initializes a memory descriptor for a region inside an area described by an existing memory descripto...
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1859
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:843
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7609
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6644
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:876
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:92
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8766
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10063
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5299
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:182
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:579
desc(prop_kind aprop_kind, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization forward propagation primitive.
Definition: dnnl.hpp:6403
dnnl_status_t DNNL_API dnnl_post_ops_append_eltwise(dnnl_post_ops_t post_ops, float scale, dnnl_alg_kind_t alg_kind, float alpha, float beta)
Appends an elementwise post-op.
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:6904
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1205
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scratchpad_mode(const_dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t *mode)
Returns the primitive attributes scratchpad mode.
dnnl_status_t DNNL_API dnnl_concat_primitive_desc_create(dnnl_primitive_desc_t *concat_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, int concat_dimension, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an out-of-place concatenation primitive.
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
dnnl_status_t DNNL_API dnnl_eltwise_backward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Softmax forward propagation primitive.
Definition: dnnl.hpp:5664
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:829
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6213
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2260
dnnl_status_t DNNL_API dnnl_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution backward propagation primitive.
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:798
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6164
dnnl_status_t DNNL_API dnnl_reduction_desc_init(dnnl_reduction_desc_t *desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, float p, float eps)
Initializes a descriptor for a reduction primitive.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6886
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1405
@ undef
Undefined algorithm.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6446
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const lbr_gru_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9097
@ dnnl_cpu_isa_avx512_core_bf16
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2408
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling forward propagation primitive.
Definition: dnnl.hpp:5235
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7408
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:186
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling backward propagation primitive.
Definition: dnnl.hpp:5344
data_type
Data type specification.
Definition: dnnl.hpp:1120
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const gru_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8727
primitive_desc(const desc &adesc, const engine &aengine, const deconvolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4666
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an LRN backward propagation primitive from a C API primitive de...
Definition: dnnl.hpp:5172
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const lrn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5159
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8826
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const float *scales)
Sets primitive attributes scaling factors for primitive operations for a given memory argument.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7335
dnnl_status_t DNNL_API dnnl_stream_create(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags)
Creates an execution stream.
dnnl_status_t DNNL_API dnnl_sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const lstm_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8323
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4200
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6307
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7915
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9026
dnnl_status_t DNNL_API dnnl_stream_wait(dnnl_stream_t stream)
Waits for all primitives in the execution stream to finish computations.
dnnl_status_t DNNL_API dnnl_memory_set_data_handle_v2(dnnl_memory_t memory, void *handle, dnnl_stream_t stream)
Sets the underlying memory buffer.
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7161
An opaque structure to describe a primitive descriptor.
desc(const memory::desc &diff_data_desc, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5973
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:2013
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5254
dnnl_status_t DNNL_API dnnl_sum_primitive_desc_create(dnnl_primitive_desc_t *sum_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, const float *scales, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an (out-of-place) sum primitive.
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:928
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:555
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:933
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:5732
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const layer_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6604
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:939
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2095
dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(const_dnnl_primitive_desc_t primitive_desc, const_dnnl_primitive_attr_t *attr)
Returns a constant reference to the attributes of a primitive descriptor.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10168
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:983
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1661
@ inner_product
An inner product primitive.
#define DNNL_ARG_DIFF_DST_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2116
dnnl_status_t DNNL_API dnnl_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU backward propagation primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7941
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:909
void set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
Definition: dnnl.hpp:10291
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7936
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4488
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9524
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:967
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8390
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6636
@ undef
Undefined primitive.
Resampling forward propagation.
Definition: dnnl.hpp:9574
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for a resampling backward propagation primitive using source and destination ...
Definition: dnnl.hpp:9731
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2004
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9265
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7189
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
dnnl_engine_kind_t convert_to_c(engine::kind akind)
Converts engine kind enum value from C++ API to C API type.
Definition: dnnl.hpp:951
Inner product weights gradient primitive.
Definition: dnnl.hpp:6902
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6476
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:9828
@ layer_normalization
A layer normalization primitive.
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:975
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7077
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1195
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2268
void unmap_data(void *mapped_ptr) const
Unmaps a memory object and writes back any changes made to the previously mapped memory buffer.
Definition: dnnl.hpp:2119
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:2110
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8570
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:1998
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1902
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2266
#define DNNL_MEMORY_ALLOCATE
Special pointer value that indicates that the library needs to allocate an underlying buffer for a me...
Definition: dnnl_types.h:1253
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:951
dnnl_status_t DNNL_API dnnl_lbr_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:796
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9705
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:197
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &data_desc, memory::dim local_size, float alpha, float beta, float k=1.f)
Constructs a descriptor for a LRN forward propagation primitive.
Definition: dnnl.hpp:5017
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4235
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:605
Inner product backward propagation primitive.
Definition: dnnl.hpp:6800
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1009
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution forward propagation primitive with bias.
Definition: dnnl.hpp:3606
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:9558
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:935
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6321
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a batch normalization forward propagation primitive from a C AP...
Definition: dnnl.hpp:6157
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:817
Inner product forward propagation primitive.
Definition: dnnl.hpp:6675
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4707
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2280
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5958
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:835
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8692
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:9890
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4535
dnnl_status_t DNNL_API dnnl_set_max_cpu_isa(dnnl_cpu_isa_t isa)
Sets the maximal ISA the library can dispatch to on the CPU.
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9174
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1208
dnnl_status_t DNNL_API dnnl_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution weights gradient primitive.
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product descriptor weights update primitive without bias.
Definition: dnnl.hpp:6940
primitive_desc(const desc &adesc, const engine &aengine, const pooling_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5379
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7604
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a LBR GRU backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:9110
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:2069
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
An opaque structure to describe a primitive.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution weights gradient primitive from a C API primiti...
Definition: dnnl.hpp:4957
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4710
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an LSTM forward propagation primitive from a C API primitive de...
Definition: dnnl.hpp:7886
convolution_forward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6430
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5081
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2377
dnnl_status_t DNNL_API dnnl_reorder_primitive_desc_create(dnnl_primitive_desc_t *reorder_primitive_desc, const dnnl_memory_desc_t *src_desc, dnnl_engine_t src_engine, const dnnl_memory_desc_t *dst_desc, dnnl_engine_t dst_engine, const_dnnl_primitive_attr_t attr)
Creates a primitive descriptor for a reorder primitive.
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7920
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2253
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7560
primitive_desc(const desc &adesc, const engine &aengine, const shuffle_forward::primitive_desc &hint_fwd_pd, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9318
dnnl_status_t DNNL_API dnnl_softmax_backward_desc_init(dnnl_softmax_desc_t *softmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
void set_scales(int arg, int mask, const std::vector< float > &scales)
Sets scaling factors for primitive operations for a given memory argument.
Definition: dnnl.hpp:2670
dnnl_primitive_kind_t convert_to_c(primitive::kind akind)
Converts primitive kind enum value from C++ API to C API type.
Definition: dnnl.hpp:362
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3771
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7089
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1079
dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(const_dnnl_memory_t memory, const dnnl_memory_desc_t **memory_desc)
Returns the memory descriptor for a memory object.
primitive_desc(const desc &adesc, const engine &aengine, const layer_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6584
dnnl_status_t DNNL_API dnnl_vanilla_rnn_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN backward propagation primitive.
lbr_gru_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8774
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5535
dnnl_status_t DNNL_API dnnl_resampling_backward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes a descriptor for resampling backward propagation primitive.
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s1p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 1.
desc(prop_kind aprop_kind, const memory::desc &data_desc, int softmax_axis)
Constructs a descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5680
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(const_dnnl_primitive_t primitive, const_dnnl_primitive_desc_t *primitive_desc)
Retrieves a constant reference to the primitive descriptor of a given primitive.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7565
desc(const dims &adims, data_type adata_type, const dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:1770
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6513
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8758
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const logsoftmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6021
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2281
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7892
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9550
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5635
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:427
handle()=default
Constructs an empty handle object.
primitive_desc()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:9714
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2255
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2030
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7875
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:845
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a convolution forward propagation primitive from a C API primit...
Definition: dnnl.hpp:3812
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8862
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
A special mnemonic for diff of RNN weights applied to the projection weights.
Definition: dnnl_types.h:2152
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:870
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7129
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:169
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:813
void append_binary(algorithm aalgorithm, const memory::desc &src1_desc)
Appends a binary post-op.
Definition: dnnl.hpp:2485
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9498
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const pooling_v2_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10044
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6116
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:9545
dnnl_status_t DNNL_API dnnl_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution backward propagation primitive.
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1508
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2303
primitive_desc(const desc &adesc, const engine &aengine, const deconvolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution weights update primitive.
Definition: dnnl.hpp:4924
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:2048
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1330
primitive_desc(const desc &adesc, const engine &aengine, const logsoftmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6001
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10066
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8349
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated convolution weights gradient primitive with bias.
Definition: dnnl.hpp:4132
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6244
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5945
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2271
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3305
gru_backward()=default
Default constructor. Produces an empty object.
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:800
softmax_backward()=default
Default constructor. Produces an empty object.
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2345
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1539
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2980
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2974
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:925
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6511
@ library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
resampling_forward()=default
Default constructor. Produces an empty object.
Primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8520
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
Pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:9958
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive from a C API primit...
Definition: dnnl.hpp:6034
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7624
softmax_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum_v2(dnnl_post_ops_t post_ops, float scale, dnnl_data_type_t data_type)
Appends an accumulation v2 (sum) to post-ops.
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1352
dnnl_status_t DNNL_API dnnl_eltwise_forward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise forward propagation primitive.
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2936
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:963
layer_normalization_backward()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7123
primitive_desc(const desc &adesc, const engine &aengine, const batch_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6261
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6470
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:839
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7394
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4256
handle< T, traits > & operator=(handle< T, traits > &&)=default
Move assignment operator.
@ undef
Undefined data type (used for empty memory descriptors).
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4261
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8364
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:10229
desc(prop_kind aprop_kind, const memory::desc &data_desc, const memory::desc &stat_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization forward propagation primitive.
Definition: dnnl.hpp:6382
desc reshape(const dims &adims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:1856
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2233
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9436
Pooling forward propagation primitive.
Definition: dnnl.hpp:5206
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2380
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
status sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
Definition: dnnl.hpp:10306
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:2859
status
Status values returned by the library functions.
Definition: dnnl.hpp:10196
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8978
dnnl_status_t DNNL_API dnnl_memory_get_engine(const_dnnl_memory_t memory, dnnl_engine_t *engine)
Returns the engine of a memory object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6627
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:971
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2386
@ dnnl_cpu_isa_avx512_core_vnni
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2403
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s1p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 1.
primitive_desc(int concat_dimension, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3348
Convolution backward propagation primitive.
Definition: dnnl.hpp:3843
int ndims
Number of dimensions.
Definition: dnnl_types.h:1190
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7115
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:185
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:2956
primitive_desc()=default
Default constructor. Produces an empty object.
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1572
cpu_isa get_effective_cpu_isa()
Gets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10269
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3159
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9336
Elementwise binary operator primitive.
Definition: dnnl.hpp:9362
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5096
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution weights gradient primitive without bias.
Definition: dnnl.hpp:4796
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4544
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6802
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:907
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9141
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:923
oneDNN exception class.
Definition: dnnl.hpp:84
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6473
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9938
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc)
Constructs a descriptor for a resampling forward propagation primitive using source and destination m...
Definition: dnnl.hpp:9594
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:929
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6479
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8789
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:1926
@ pooling_v2
A pooling version 2 primitive.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
desc(const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Constructs a descriptor for a matmul primitive.
Definition: dnnl.hpp:9488
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1102
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const deconvolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4686
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive from a C API primit...
Definition: dnnl.hpp:7362
primitive_desc(const memory::desc &dst, int concat_dimension, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3321
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7016
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8382
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4907
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5282
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:823
dnnl_status_t DNNL_API dnnl_inner_product_backward_data_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product backward propagation.
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2566
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9941
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5058
dnnl_status_t DNNL_API dnnl_memory_map_data(const_dnnl_memory_t memory, void **mapped_ptr)
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6624
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution weights gradient primitive.
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8430
Pooling backward propagation primitive.
Definition: dnnl.hpp:5318
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4704
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2301
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6781
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3489
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8456
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization backward propagation primitive.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive fr...
Definition: dnnl.hpp:9932
dnnl_status_t DNNL_API dnnl_lbr_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU forward propagation primitive.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9439
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:176
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5741
primitive_desc(const desc &adesc, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product weights update primitive.
Definition: dnnl.hpp:6970
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9164
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7174
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:821
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7619
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:979
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7149
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9944
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6329
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an LSTM backward propagation primitive from a C API primitive d...
Definition: dnnl.hpp:8336
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5411
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9291
dnnl_status_t DNNL_API dnnl_inner_product_backward_weights_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5183
desc()=default
Default constructor. Produces an empty object.
resampling_backward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5638
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6639
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10069
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution weights gradient primitive with bias.
Definition: dnnl.hpp:4840
An opaque structure for primitive descriptor attributes.
dnnl_status_t DNNL_API dnnl_set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
oneAPI namespace
Definition: dnnl.hpp:10363
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:7019
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution forward propagation primitive with bias.
Definition: dnnl.hpp:4419
dnnl_status_t DNNL_API dnnl_stream_get_engine(const_dnnl_stream_t stream, dnnl_engine_t *engine)
Returns the engine of a stream object.
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:831
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7614
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes scaling factors correspondence mask and values for a given memory argume...
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2275
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_data_qparams(dnnl_primitive_attr_t attr, const float scale, const float shift)
Set quantization scale and shift parameters for RNN data tensors.
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for dilated convolution backward propagation primitive.
Definition: dnnl.hpp:3917
@ convolution
A convolution primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_post_ops(const_dnnl_primitive_attr_t attr, const_dnnl_post_ops_t *post_ops)
Returns primitive attributes post-ops.
void get_params_sum(int index, float &scale, memory::data_type &data_type) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2261
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9159
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8784
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6049
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2536
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5431
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9206
void execute(const stream &astream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3276
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9262
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3374
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1913
Primitive attributes.
Definition: dnnl.hpp:2520
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:5750
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9144
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product weights update primitive.
Definition: dnnl.hpp:6990
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6784
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9120
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10141
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9348
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6828
dnnl_status_t DNNL_API dnnl_get_primitive_cache_capacity(int *capacity)
Returns the number of primitives that can be held in the primitive cache at the same time.
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2229
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution backward propagation primitive.
#define DNNL_ARG_DIFF_SRC_LAYER
A special mnemonic for gradient (diff) of RNN input vector.
Definition: dnnl_types.h:2089
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2258
A descriptor of resampling operation.
Definition: dnnl_types.h:1795
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8961
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3846
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:919
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9281
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5738
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1863
Memory object.
Definition: dnnl.hpp:1098
An opaque structure for a chain of post operations.
pooling_v2_backward()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7197
void get_scales(int arg, int &mask, std::vector< float > &scales) const
Returns scaling factors correspondence mask and values for a given memory argument.
Definition: dnnl.hpp:2640
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution weights gradient primitive with bias.
Definition: dnnl.hpp:4754
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2227
@ undef
Undefined RNN flags.
eltwise_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:903
static void wrap_c_api(dnnl_status_t status, const char *message)
A convenience function for wrapping calls to C API functions.
Definition: dnnl.hpp:103
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:5650
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9417
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8548
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2945
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8377
@ undef
Undefined propagation kind.
inner_product_forward()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6324
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution weights gradient primitive.
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
primitive(const_dnnl_primitive_desc_t c_pd)
Constructs a primitive from a C API primitive descriptor.
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:10214
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2101
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6167
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6731
oneDNN C API handle wrapper class.
Definition: dnnl.hpp:136
desc(algorithm aalgorithm, const memory::desc &data_desc, const memory::desc &diff_data_desc, memory::dim local_size, float alpha, float beta, float k=1.f)
Constructs a descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5111
pooling_backward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9244
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8420
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:2900
reduction()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
primitive_desc(const memory::desc &dst, const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3412
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7905
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:961
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an inner product weights update primitive from a C API primitiv...
Definition: dnnl.hpp:7003
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6086
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a binary primitive from a C API primitive descriptor that must ...
Definition: dnnl.hpp:9426
dnnl_status_t DNNL_API dnnl_memory_create(dnnl_memory_t *memory, const dnnl_memory_desc_t *memory_desc, dnnl_engine_t engine, void *handle)
Creates a memory object.
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:911
dnnl_status_t DNNL_API dnnl_pooling_forward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7568
inner_product_backward_data()=default
Default constructor. Produces an empty object.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9123
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution weights gradient primitive without bias.
Definition: dnnl.hpp:4886
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7063
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:4008
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const resampling_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9798
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6310
dnnl_status_t DNNL_API dnnl_shuffle_forward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle forward propagation primitive.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4518
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8824
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9819
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6338
Memory descriptor.
Definition: dnnl_types.h:1188
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:804
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10155
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7381
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7900
memory(const desc &md, const engine &aengine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:1986
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:847
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7101
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2622
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4278
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const softmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5817
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5954
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:220
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:3830
desc(prop_kind aprop_kind, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5880
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2375
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2007
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:6787
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:1953
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5320
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9229
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution weights gradient primitive without bias.
Definition: dnnl.hpp:4087
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution weights gradient primitive with bias.
Definition: dnnl.hpp:4044
batch_normalization_forward()=default
Default constructor. Produces an empty object.
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, float p, float eps)
Constructs a descriptor for a reduction primitive using algorithm specific parameters,...
Definition: dnnl.hpp:10119
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6865
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4541
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7253
dnnl_status_t DNNL_API dnnl_lrn_forward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN forward propagation primitive.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:9366
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8533
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:564
@ scratchpad_engine
scratchpad engine
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8395
dnnl_status_t DNNL_API dnnl_pooling_v2_forward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) forward propagation primitive...
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9133
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7008
dnnl_status_t DNNL_API dnnl_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
void reset_with_clone(const_dnnl_primitive_desc_t pd)
Resets the value of the handle to a clone of a C API primitive descriptor.
Definition: dnnl.hpp:3043
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6567
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:3001
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization forward propagation primitive.
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:561
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9300
dnnl_status_t DNNL_API dnnl_shuffle_backward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, const dnnl_memory_desc_t *diff_data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle backward propagation primitive.
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4649
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2251
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2257
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4267
engine(kind akind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:892
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9364
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4725
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:957
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive f...
Definition: dnnl.hpp:10058
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3371
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7109
A descriptor of reduction operation.
Definition: dnnl_types.h:1823
dnnl_status_t DNNL_API dnnl_lrn_backward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN backward propagation primitive.
A class that provides the destructor for a oneDNN C API handle.
Definition: dnnl.hpp:120
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2918
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9149
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2232
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1105
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5780
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4557
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6173
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8435
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum(const_dnnl_post_ops_t post_ops, int index, float *scale)
Returns the parameters of an accumulation (sum) post-op.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5721
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scratchpad_mode(dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t mode)
Sets primitive attributes scratchpad mode.
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:2733
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7368
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6745
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8586
A memory descriptor.
Definition: dnnl.hpp:1718
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3821
Base class for all computational primitives.
Definition: dnnl.hpp:269
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7860
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:861
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:872
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1265
@ dnnl_cpu_isa_avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2390
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6630
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:1006
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5267
batch_normalization_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_strides(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, const dnnl_dims_t strides)
Initializes a memory descriptor using dimensions and strides.
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2012
format_kind
Memory format kind.
Definition: dnnl.hpp:1139
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:894
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:3839
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:1945
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9204
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8972
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9685
dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const int32_t *zero_points)
Sets primitive attributes zero points for primitive operations for a given memory argument.
matmul()=default
Default constructor. Produces an empty object.
lbr_gru_forward()=default
Default constructor. Produces an empty object.
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or without recurrent projecti...
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3573
desc(const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc)
Constructs a descriptor for a matmul primitive.
Definition: dnnl.hpp:9474
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:1939
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1659
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:7952
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8415
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7925
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:886
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:573
oneDNN namespace
Definition: dnnl.hpp:74
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:943
@ logsoftmax
A logsoftmax primitive.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8950
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
An opaque structure to describe an execution stream.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:9540
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4014
@ impl_info_str
implementation name
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4559
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8953
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5518
A descriptor of a binary operation.
Definition: dnnl_types.h:1747
pooling_forward()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9128
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3239
@ batch_normalization
A batch normalization primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
primitive_desc(const desc &adesc, const engine &aengine, const vanilla_rnn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7522
dnnl_status_t DNNL_API dnnl_post_ops_append_binary(dnnl_post_ops_t post_ops, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src1_desc)
Appends a binary post-op.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const pooling_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5398
primitive_desc()=default
Default constructor. Produces an empty object.
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2023
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:864
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3785
dnnl_primitive_kind_t DNNL_API dnnl_post_ops_get_kind(const_dnnl_post_ops_t post_ops, int index)
Returns the kind of a post-op entry.
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:969
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3479
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3382
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2276
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
void get_params_eltwise(int index, float &scale, algorithm &aalgorithm, float &alpha, float &beta) const
Returns parameters of an elementwise post-op.
Definition: dnnl.hpp:2297
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7251
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9115
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8915
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7635
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9339
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &data_desc, float alpha=0, float beta=0)
Constructs a descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5475
void get_params_binary(int index, algorithm &aalgorithm, memory::desc &src1_desc) const
Returns the parameters of a binary post-op.
Definition: dnnl.hpp:2496
A descriptor of a pooling (version 2) operation.
Definition: dnnl_types.h:1468
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4553
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:10219
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:794
binary()=default
Default constructor. Produces an empty object.
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3255
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an inner product forward propagation primitive from a C API pri...
Definition: dnnl.hpp:6772
desc(const dims &adims, data_type adata_type, format_tag aformat_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:1742
desc(const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6815
dnnl_status_t DNNL_API dnnl_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution forward propagation primitive.
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:2201
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8937
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:468
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3938
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8385
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:785
dnnl_status_t DNNL_API dnnl_resampling_forward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a resampling forward propagation primitive.
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, const memory::desc &stat_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization backward propagation primitive.
Definition: dnnl.hpp:6529
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6304
primitive_desc()=default
Default constructor. Produces an empty object.
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:373
dnnl_status_t DNNL_API dnnl_matmul_desc_init(dnnl_matmul_desc_t *matmul_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a matrix multiplication descriptor.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4973
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10171
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5705
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1671
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &weights_peephole_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs a descriptor for an LSTM (with or without peephole) forward propagation primitive.
Definition: dnnl.hpp:7760
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9154
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_tag(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, dnnl_format_tag_t tag)
Initializes a memory descriptor using dimensions and memory format tag.
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2230
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1651
dnnl_primitive_desc_t DNNL_API dnnl_primitive_desc_iterator_fetch(const_dnnl_primitive_desc_iterator_t iterator)
Fetches the current primitive descriptor from a primitive descriptor iterator.
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5208
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for reorder primitive from a C API primitive descriptor which must ...
Definition: dnnl.hpp:3228
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5580
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5866
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:878
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9433
@ in_order
In-order execution.
T * map_data() const
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents.
Definition: dnnl.hpp:2102
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3999
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:853
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6209
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8400
primitive_desc()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9274
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution backward propagation primitive.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3468
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const vanilla_rnn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7542
dnnl_status_t DNNL_API dnnl_layer_normalization_forward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for layer normalization forward propagation primitive.
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:576
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2540
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN weights tensors.
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(dnnl_primitive_attr_t attr, const_dnnl_post_ops_t post_ops)
Sets primitive attributes post-ops.
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:1725
@ out_of_order
Out-of-order execution.
convolution_backward_weights()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
void append_eltwise(float scale, algorithm aalgorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2283
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7351
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:941
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1861
lrn_backward()=default
Default constructor. Produces an empty object.
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7044
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2524
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:552
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5124
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:849
LSTM forward propagation primitive.
Definition: dnnl.hpp:7639
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an inner product backward propagation primitive from a C API pr...
Definition: dnnl.hpp:6878
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2383
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:2843
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:977
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:782
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8745
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:2847
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2282
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution forward propagation primitive with bias.
Definition: dnnl.hpp:4326
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7910
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6170
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:2880
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5502
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6316
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a batch normalization descriptor for backward propagation.
Definition: dnnl.hpp:6230
dnnl_status_t DNNL_API dnnl_dilated_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution forward propagation primitive.
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:901
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4538
stream(const engine &aengine, flags aflags=flags::default_flags)
Constructs a stream for the specified engine and with behavior controlled by the specified flags.
Definition: dnnl.hpp:997
dnnl_status_t DNNL_API dnnl_primitive_attr_get_output_scales(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes output scaling factors correspondence mask and values.
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2277
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9904
primitive_desc(const desc &adesc, const engine &aengine, const pooling_v2_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10024
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6652
primitive_desc(const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3442
@ default_flags
Default stream configuration.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4984
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9510
primitive_desc(const desc &adesc, const engine &aengine, const lrn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5140
Base class for all primitive descriptors.
Definition: dnnl.hpp:2835
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5756
reorder()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution forward propagation primitive without bias.
Definition: dnnl.hpp:4467
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6130
const dnnl_memory_desc_t DNNL_API * dnnl_primitive_desc_query_md(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index)
Queries primitive descriptor for a memory descriptor.
dnnl_status_t DNNL_API dnnl_gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2261
primitive_desc(const desc &adesc, const engine &aengine, const gru_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8708
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:917
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9702
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a convolution backward propagation primitive from a C API primi...
Definition: dnnl.hpp:3988
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:7958
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
pooling_v2_forward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9954
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:10224
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8771
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5841
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7389
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4292
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5094
@ eltwise
An element-wise primitive.
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_src_iter_c_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, const memory::desc &diff_dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs an LSTM descriptor for backward propagation using prop_kind, direction,...
Definition: dnnl.hpp:8247
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5942
primitive_desc()=default
Default constructor. Produces an empty object.
gru_forward()=default
Default constructor. Produces an empty object.
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1674
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5838
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5666
shuffle_backward()=default
Default constructor. Produces an empty object.
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:811
desc(prop_kind aprop_kind, const memory::desc &data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9218
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:8405
Primitive descriptor for an RNN backward propagation primitive.
Definition: dnnl.hpp:7505
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3396
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5891
dnnl_status_t DNNL_API dnnl_vanilla_rnn_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN forward propagation primitive.
@ deconvolution
A deconvolution primitive.
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8369
layer_normalization_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:890
handle(const handle< T, traits > &)=default
Copy constructor.
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8750
desc(algorithm aalgorithm, const memory::desc &diff_data_desc, const memory::desc &data_desc, float alpha=0, float beta=0)
Constructs a descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5567
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7321
lrn_forward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:5293
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:2001
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1653
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5905
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:8820
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4970
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6464
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5984
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2241
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3874
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:851
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:2821
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_alg_kind_t *alg_kind, float *alpha, float *beta)
Returns the parameters of an elementwise post-op.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:2024
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated convolution weights gradient primitive without bias.
Definition: dnnl.hpp:4179
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9720
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const deconvolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution weights update primitive.
Definition: dnnl.hpp:4944
GRU backward propagation primitive.
Definition: dnnl.hpp:8609
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const eltwise_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5617
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2283
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8374
memory()=default
Default constructor.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8346
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4294
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a batch normalization backward propagation primitive from a C A...
Definition: dnnl.hpp:6294
@ primitive_kind
primitive kind
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:931
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:953
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an eltwise forward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5529
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7573
dnnl_status_t DNNL_API dnnl_binary_desc_init(dnnl_binary_desc_t *binary_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src0_desc, const dnnl_memory_desc_t *src1_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a binary primitive.