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;
357 const std::unordered_map<int, memory> &args)
const;
371 "could not get a primitive descriptor from a primitive");
382 "could not get a primitive kind from a primitive descriptor");
472 undef = dnnl_alg_kind_undef,
686 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
687 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
688 return static_cast<enum_name>( \
689 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
692 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
693 return static_cast<enum_name>( \
694 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
697 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
698 return static_cast<enum_name>( \
699 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
702 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
703 lhs = static_cast<enum_name>( \
704 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
708 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
709 lhs = static_cast<enum_name>( \
710 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
714 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
715 lhs = static_cast<enum_name>( \
716 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
720 inline enum_name operator~(enum_name rhs) { \
721 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
922 "could not create an engine");
935 "could not get an engine from a primitive_desc");
936 reset(c_engine,
true);
944 "could not get kind of an engine");
953 template <
typename primitive_desc>
963 template <
typename primitive_desc>
968 "could not get an engine from a primitive_desc");
969 return engine(c_engine,
true);
1027 "could not create a stream");
1035 "could not get an engine from a stream object");
1036 return engine(c_engine,
true);
1139 template <
typename T>
1141 validate_container_size(
1455 AB16b16a = dnnl_AB16b16a,
1456 AB16b32a = dnnl_AB16b32a,
1457 AB16b64a = dnnl_AB16b64a,
1458 AB8b16a2b = dnnl_AB8b16a2b,
1459 AB8b32a2b = dnnl_AB8b32a2b,
1460 AB8b64a2b = dnnl_AB8b64a2b,
1461 AB4b16a4b = dnnl_AB4b16a4b,
1462 AB4b32a4b = dnnl_AB4b32a4b,
1463 AB4b64a4b = dnnl_AB4b64a4b,
1464 AB16b16a4b = dnnl_AB16b16a4b,
1465 AB16b32a4b = dnnl_AB16b32a4b,
1466 AB16b48a4b = dnnl_AB16b48a4b,
1467 AB16b64a4b = dnnl_AB16b64a4b,
1468 AB16b16a2b = dnnl_AB16b16a2b,
1469 AB16b32a2b = dnnl_AB16b32a2b,
1470 AB16b48a2b = dnnl_AB16b48a2b,
1471 AB16b64a2b = dnnl_AB16b64a2b,
1472 Abc16a = dnnl_Abc16a,
1473 ABc16a16b = dnnl_ABc16a16b,
1474 ABc4a4b = dnnl_ABc4a4b,
1477 ABc16b16a = dnnl_ABc16b16a,
1478 ABc16b32a = dnnl_ABc16b32a,
1479 ABc16b64a = dnnl_ABc16b64a,
1482 ABc4b16a4b = dnnl_ABc4b16a4b,
1483 ABc4b32a4b = dnnl_ABc4b32a4b,
1484 ABc4b64a4b = dnnl_ABc4b64a4b,
1485 ABc2b8a4b = dnnl_ABc2b8a4b,
1486 ABc16a16b2a = dnnl_ABc16a16b2a,
1487 ABc16b16a4b = dnnl_ABc16b16a4b,
1488 ABc16b32a4b = dnnl_ABc16b32a4b,
1489 ABc16b48a4b = dnnl_ABc16b48a4b,
1490 ABc16b64a4b = dnnl_ABc16b64a4b,
1491 ABc16b16a2b = dnnl_ABc16b16a2b,
1492 ABc16b32a2b = dnnl_ABc16b32a2b,
1493 ABc16b48a2b = dnnl_ABc16b48a2b,
1494 ABc16b64a2b = dnnl_ABc16b64a2b,
1495 ABc4b4a = dnnl_ABc4b4a,
1496 ABc8a16b2a = dnnl_ABc8a16b2a,
1497 ABc8a8b = dnnl_ABc8a8b,
1498 ABc8a4b = dnnl_ABc8a4b,
1500 ABc8b16a2b = dnnl_ABc8b16a2b,
1501 ABc8b32a2b = dnnl_ABc8b32a2b,
1502 ABc8b64a2b = dnnl_ABc8b64a2b,
1503 ABc8b8a = dnnl_ABc8b8a,
1504 Abcd8a = dnnl_Abcd8a,
1505 Abcd16a = dnnl_Abcd16a,
1506 Abcd32a = dnnl_Abcd32a,
1507 ABcd16a16b = dnnl_ABcd16a16b,
1510 ABcd16b16a = dnnl_ABcd16b16a,
1511 ABcd16b32a = dnnl_ABcd16b32a,
1512 ABcd16b64a = dnnl_ABcd16b64a,
1513 aBCd16b16c = dnnl_aBCd16b16c,
1514 aBCd16c16b = dnnl_aBCd16c16b,
1515 Abcd4a = dnnl_Abcd4a,
1517 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1518 ABcd4b32a4b = dnnl_ABcd4b32a4b,
1519 ABcd4b64a4b = dnnl_ABcd4b64a4b,
1520 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1521 ABcd4b4a = dnnl_ABcd4b4a,
1522 ABcd4a4b = dnnl_ABcd4a4b,
1523 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1524 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1525 ABcd16a16b2a = dnnl_ABcd16a16b2a,
1526 ABcd16b16a4b = dnnl_ABcd16b16a4b,
1527 ABcd16b32a4b = dnnl_ABcd16b32a4b,
1528 ABcd16b48a4b = dnnl_ABcd16b48a4b,
1529 ABcd16b64a4b = dnnl_ABcd16b64a4b,
1530 ABcd16b16a2b = dnnl_ABcd16b16a2b,
1531 ABcd16b32a2b = dnnl_ABcd16b32a2b,
1532 ABcd16b48a2b = dnnl_ABcd16b48a2b,
1533 ABcd16b64a2b = dnnl_ABcd16b64a2b,
1534 aBCd16b16c2b = dnnl_aBCd16b16c2b,
1535 aBCd16c16b4c = dnnl_aBCd16c16b4c,
1536 aBCd16c16b2c = dnnl_aBCd16c16b2c,
1537 aBCd4c4b = dnnl_aBCd4c4b,
1538 aBCd4b4c = dnnl_aBCd4b4c,
1539 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1540 ABcd8a8b = dnnl_ABcd8a8b,
1541 ABcd8a4b = dnnl_ABcd8a4b,
1544 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1545 ABcd8b32a2b = dnnl_ABcd8b32a2b,
1546 ABcd8b64a2b = dnnl_ABcd8b64a2b,
1547 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1550 aBCd8b8c = dnnl_aBCd8b8c,
1551 aBCd8b4c = dnnl_aBCd8b4c,
1552 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1553 aBCd8c8b = dnnl_aBCd8c8b,
1554 Abcde16a = dnnl_Abcde16a,
1555 Abcde32a = dnnl_Abcde32a,
1556 ABcde16a16b = dnnl_ABcde16a16b,
1559 ABcde16b16a = dnnl_ABcde16b16a,
1560 ABcde16b32a = dnnl_ABcde16b32a,
1561 ABcde16b64a = dnnl_ABcde16b64a,
1562 aBCde16b16c = dnnl_aBCde16b16c,
1563 aBCde16c16b = dnnl_aBCde16c16b,
1564 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1565 Abcde4a = dnnl_Abcde4a,
1567 ABcde4b4a = dnnl_ABcde4b4a,
1568 ABcde4a4b = dnnl_ABcde4a4b,
1569 aBCde4b4c = dnnl_aBCde4b4c,
1570 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1571 aBCde16b16c2b = dnnl_aBCde16b16c2b,
1572 aBCde16c16b4c = dnnl_aBCde16c16b4c,
1573 aBCde16c16b2c = dnnl_aBCde16c16b2c,
1574 aBCdef16c16b2c = dnnl_aBCdef16c16b2c,
1575 aBCde4c4b = dnnl_aBCde4c4b,
1576 Abcde8a = dnnl_Abcde8a,
1577 ABcde8a8b = dnnl_ABcde8a8b,
1578 ABcde8a4b = dnnl_ABcde8a4b,
1580 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1581 ABcde8b32a2b = dnnl_ABcde8b32a2b,
1582 ABcde8b64a2b = dnnl_ABcde8b64a2b,
1584 ABcde4b32a4b = dnnl_ABcde4b32a4b,
1585 ABcde4b64a4b = dnnl_ABcde4b64a4b,
1586 ABcde16b16a4b = dnnl_ABcde16b16a4b,
1587 ABcde16b32a4b = dnnl_ABcde16b32a4b,
1588 ABcde16b48a4b = dnnl_ABcde16b48a4b,
1589 ABcde16b64a4b = dnnl_ABcde16b64a4b,
1590 ABcde16b16a2b = dnnl_ABcde16b16a2b,
1591 ABcde16b32a2b = dnnl_ABcde16b32a2b,
1592 ABcde16b48a2b = dnnl_ABcde16b48a2b,
1593 ABcde16b64a2b = dnnl_ABcde16b64a2b,
1595 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1596 ABcde8b8a = dnnl_ABcde8b8a,
1597 aBCde8b8c = dnnl_aBCde8b8c,
1598 aBCde8b4c = dnnl_aBCde8b4c,
1599 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1600 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1601 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1602 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1603 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1604 aBCde8c8b = dnnl_aBCde8c8b,
1606 aBCdef16b16c = dnnl_aBCdef16b16c,
1607 aBCdef16c16b = dnnl_aBCdef16c16b,
1610 aBCdef4c4b = dnnl_aBCdef4c4b,
1611 aBCdef4b4c = dnnl_aBCdef4b4c,
1612 aBCdef8b8c = dnnl_aBCdef8b8c,
1613 aBCdef8b4c = dnnl_aBCdef8b4c,
1614 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1615 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1616 aBCdef8c8b = dnnl_aBCdef8c8b,
1617 aBdc16b = dnnl_aBdc16b,
1618 aBdc4b = dnnl_aBdc4b,
1619 aBdc8b = dnnl_aBdc8b,
1620 aBdec16b = dnnl_aBdec16b,
1621 aBdec4b = dnnl_aBdec4b,
1622 aBdec8b = dnnl_aBdec8b,
1623 aBdefc16b = dnnl_aBdefc16b,
1624 aCBdef16c16b = dnnl_aCBdef16c16b,
1625 aCBdef16b16c = dnnl_aCBdef16b16c,
1626 aBdefc4b = dnnl_aBdefc4b,
1627 aBdefc8b = dnnl_aBdefc8b,
1628 Acb16a = dnnl_Acb16a,
1631 aCBd16b16c = dnnl_aCBd16b16c,
1632 aCBd16c16b = dnnl_aCBd16c16b,
1633 aCBde16b16c = dnnl_aCBde16b16c,
1634 aCBde16c16b = dnnl_aCBde16c16b,
1635 Acdb16a = dnnl_Acdb16a,
1636 Acdb4a = dnnl_Acdb4a,
1637 Acdb8a = dnnl_Acdb8a,
1638 Acdeb16a = dnnl_Acdeb16a,
1639 Acdeb4a = dnnl_Acdeb4a,
1640 Acdeb8a = dnnl_Acdeb8a,
1641 BAc16a16b = dnnl_BAc16a16b,
1642 BAc16b16a = dnnl_BAc16b16a,
1643 BAcd16a16b = dnnl_BAcd16a16b,
1644 BAcd16b16a = dnnl_BAcd16b16a,
1645 ABcd32a32b = dnnl_ABcd32a32b,
1646 BAcde16b16a = dnnl_BAcde16b16a,
1647 BAcde16a16b = dnnl_BAcde16a16b,
1648 aBdec32b = dnnl_aBdec32b,
1649 Abcdef16a = dnnl_Abcdef16a,
1650 Abcdef32a = dnnl_Abcdef32a,
1651 Acdb32a = dnnl_Acdb32a,
1655 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1656 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1657 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1658 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1659 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1660 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1661 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1662 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1663 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1664 AB32a32b8a4b = dnnl_AB32a32b8a4b,
1665 AB32a32b8a2b = dnnl_AB32a32b8a2b,
1666 AB8a4b = dnnl_AB8a4b,
1667 AB8a2b = dnnl_AB8a2b,
1668 abDc32d = dnnl_abDc32d,
1669 abDC32d4c = dnnl_abDC32d4c,
1670 abdEc32e = dnnl_abdEc32e,
1671 abdEC32e2c = dnnl_abdEC32e2c,
1672 abdEC32e4c = dnnl_abdEC32e4c,
1673 aBCdef16c16b4c = dnnl_aBCdef16c16b4c,
1674 aBdC16b4c = dnnl_aBdC16b4c,
1675 aBdeC16b4c = dnnl_aBdeC16b4c,
1676 AcB16a4b = dnnl_AcB16a4b,
1677 AcdB16a2b = dnnl_AcdB16a2b,
1678 aBdefC16b4c = dnnl_aBdefC16b4c,
1679 AcdeB16a4b = dnnl_AcdeB16a4b,
1681 Acb32a = dnnl_Acb32a,
1682 AcB32a2b = dnnl_AcB32a2b,
1683 AcB32a4b = dnnl_AcB32a4b,
1684 Acb48a = dnnl_Acb48a,
1685 AcB48a2b = dnnl_AcB48a2b,
1686 AcB48a4b = dnnl_AcB48a4b,
1687 Acb64a = dnnl_Acb64a,
1688 AcB64a2b = dnnl_AcB64a2b,
1689 AcB64a4b = dnnl_AcB64a4b,
1692 aBdc32b = dnnl_aBdc32b,
1693 aBdC32b2c = dnnl_aBdC32b2c,
1694 aBdC32b4c = dnnl_aBdC32b4c,
1695 aBdc48b = dnnl_aBdc48b,
1696 aBdC48b2c = dnnl_aBdC48b2c,
1697 aBdC48b4c = dnnl_aBdC48b4c,
1698 aBdc64b = dnnl_aBdc64b,
1699 aBdC64b2c = dnnl_aBdC64b2c,
1700 aBdC64b4c = dnnl_aBdC64b4c,
1702 adCb2c = dnnl_adCb2c,
1703 adCb4c = dnnl_adCb4c,
1704 AcdB32a2b = dnnl_AcdB32a2b,
1705 AcdB32a4b = dnnl_AcdB32a4b,
1706 Acdb48a = dnnl_Acdb48a,
1707 AcdB48a2b = dnnl_AcdB48a2b,
1708 AcdB48a4b = dnnl_AcdB48a4b,
1709 Acdb64a = dnnl_Acdb64a,
1710 AcdB64a2b = dnnl_AcdB64a2b,
1711 AcdB64a4b = dnnl_AcdB64a4b,
1712 cdBa2b = dnnl_cdBa2b,
1713 cdBa4b = dnnl_cdBa4b,
1714 aBdeC32b2c = dnnl_aBdeC32b2c,
1715 aBdeC32b4c = dnnl_aBdeC32b4c,
1716 aBdec48b = dnnl_aBdec48b,
1717 aBdeC48b2c = dnnl_aBdeC48b2c,
1718 aBdeC48b4c = dnnl_aBdeC48b4c,
1719 aBdec64b = dnnl_aBdec64b,
1720 aBdeC64b2c = dnnl_aBdeC64b2c,
1721 aBdeC64b4c = dnnl_aBdeC64b4c,
1723 adeCb2c = dnnl_adeCb2c,
1724 adeCb4c = dnnl_adeCb4c,
1725 Acdeb32a = dnnl_Acdeb32a,
1726 AcdeB32a2b = dnnl_AcdeB32a2b,
1727 AcdeB32a4b = dnnl_AcdeB32a4b,
1728 Acdeb48a = dnnl_Acdeb48a,
1729 AcdeB48a2b = dnnl_AcdeB48a2b,
1730 AcdeB48a4b = dnnl_AcdeB48a4b,
1731 Acdeb64a = dnnl_Acdeb64a,
1732 AcdeB64a2b = dnnl_AcdeB64a2b,
1733 AcdeB64a4b = dnnl_AcdeB64a4b,
1734 cdeBa2b = dnnl_cdeBa2b,
1735 cdeBa4b = dnnl_cdeBa4b,
1736 aBdefc32b = dnnl_aBdefc32b,
1737 aBdefC32b2c = dnnl_aBdefC32b2c,
1738 aBdefC32b4c = dnnl_aBdefC32b4c,
1739 aBdefc48b = dnnl_aBdefc48b,
1740 aBdefC48b2c = dnnl_aBdefC48b2c,
1741 aBdefC48b4c = dnnl_aBdefC48b4c,
1742 aBdefc64b = dnnl_aBdefc64b,
1743 aBdefC64b2c = dnnl_aBdefC64b2c,
1744 aBdefC64b4c = dnnl_aBdefC64b4c,
1745 adefcb = dnnl_adefcb,
1746 adefCb2c = dnnl_adefCb2c,
1747 adefCb4c = dnnl_adefCb4c,
1760 NCw16n16c = dnnl_NCw16n16c,
1761 NChw16n16c = dnnl_NChw16n16c,
1762 NCdhw16n16c = dnnl_NCdhw16n16c,
1763 NCdhw32n32c = dnnl_NCdhw32n32c,
1764 NChw32n32c = dnnl_NChw32n32c,
1765 IOhw16i16o = dnnl_IOhw16i16o,
1766 OI16i16o = dnnl_OI16i16o,
1767 OI16i32o = dnnl_OI16i32o,
1768 OI16i64o = dnnl_OI16i64o,
1769 OI8i16o2i = dnnl_OI8i16o2i,
1770 OI8i32o2i = dnnl_OI8i32o2i,
1771 OI8i64o2i = dnnl_OI8i64o2i,
1772 OI4i16o4i = dnnl_OI4i16o4i,
1773 OI4i32o4i = dnnl_OI4i32o4i,
1774 OI4i64o4i = dnnl_OI4i64o4i,
1775 Ohwi32o = dnnl_Ohwi32o,
1776 IOdhw16i16o = dnnl_IOdhw16i16o,
1777 gIOhw16i16o = dnnl_gIOhw16i16o,
1778 gOhwi32o = dnnl_gOhwi32o,
1779 Goidhw16g = dnnl_Goidhw16g,
1780 IOw16o16i = dnnl_IOw16o16i,
1781 OIw16i16o = dnnl_OIw16i16o,
1782 OIw16i32o = dnnl_OIw16i32o,
1783 OIw16i64o = dnnl_OIw16i64o,
1784 IOw16i16o = dnnl_IOw16i16o,
1785 gIOw16i16o = dnnl_gIOw16i16o,
1786 OIw16o16i = dnnl_OIw16o16i,
1787 Oiw16o = dnnl_Oiw16o,
1788 OIw4i16o4i = dnnl_OIw4i16o4i,
1789 OIw4i32o4i = dnnl_OIw4i32o4i,
1790 OIw4i64o4i = dnnl_OIw4i64o4i,
1791 OIw2i8o4i = dnnl_OIw2i8o4i,
1792 OIw4i4o = dnnl_OIw4i4o,
1793 OIw4o4i = dnnl_OIw4o4i,
1795 OIw8i16o2i = dnnl_OIw8i16o2i,
1796 OIw8i32o2i = dnnl_OIw8i32o2i,
1797 OIw8i64o2i = dnnl_OIw8i64o2i,
1798 OIw8i8o = dnnl_OIw8i8o,
1799 OIw8o16i2o = dnnl_OIw8o16i2o,
1800 OIw8o8i = dnnl_OIw8o8i,
1801 OIw8o4i = dnnl_OIw8o4i,
1802 OIw16i16o4i = dnnl_OIw16i16o4i,
1803 OIw16i32o4i = dnnl_OIw16i32o4i,
1804 OIw16i48o4i = dnnl_OIw16i48o4i,
1805 OIw16i64o4i = dnnl_OIw16i64o4i,
1806 OIw16i16o2i = dnnl_OIw16i16o2i,
1807 OIw16i32o2i = dnnl_OIw16i32o2i,
1808 OIw16i48o2i = dnnl_OIw16i48o2i,
1809 OIw16i64o2i = dnnl_OIw16i64o2i,
1810 OIw16o16i2o = dnnl_OIw16o16i2o,
1811 Owi16o = dnnl_Owi16o,
1812 OwI16o2i = dnnl_OwI16o2i,
1815 IOhw16o16i = dnnl_IOhw16o16i,
1816 Ohwi16o = dnnl_Ohwi16o,
1817 OhwI16o2i = dnnl_OhwI16o2i,
1818 Ohwi4o = dnnl_Ohwi4o,
1819 Ohwi8o = dnnl_Ohwi8o,
1820 OIhw16i16o = dnnl_OIhw16i16o,
1821 OIhw16i32o = dnnl_OIhw16i32o,
1822 OIhw16i64o = dnnl_OIhw16i64o,
1823 OIhw16o16i = dnnl_OIhw16o16i,
1824 Oihw16o = dnnl_Oihw16o,
1825 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1826 OIhw4i32o4i = dnnl_OIhw4i32o4i,
1827 OIhw4i64o4i = dnnl_OIhw4i64o4i,
1828 OIhw4i4o = dnnl_OIhw4i4o,
1829 OIhw4o4i = dnnl_OIhw4o4i,
1830 Oihw4o = dnnl_Oihw4o,
1831 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1832 OIhw8i32o2i = dnnl_OIhw8i32o2i,
1833 OIhw8i64o2i = dnnl_OIhw8i64o2i,
1834 OIhw8i8o = dnnl_OIhw8i8o,
1835 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1836 OIhw8o8i = dnnl_OIhw8o8i,
1837 OIhw8o4i = dnnl_OIhw8o4i,
1838 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1839 IOdhw16o16i = dnnl_IOdhw16o16i,
1840 Odhwi16o = dnnl_Odhwi16o,
1841 OdhwI16o2i = dnnl_OdhwI16o2i,
1842 Odhwi4o = dnnl_Odhwi4o,
1843 Odhwi8o = dnnl_Odhwi8o,
1844 OIdhw16i16o = dnnl_OIdhw16i16o,
1845 OIdhw16i32o = dnnl_OIdhw16i32o,
1846 OIdhw16i64o = dnnl_OIdhw16i64o,
1847 OIdhw16o16i = dnnl_OIdhw16o16i,
1848 Oidhw16o = dnnl_Oidhw16o,
1849 OIdhw4i4o = dnnl_OIdhw4i4o,
1850 OIdhw4o4i = dnnl_OIdhw4o4i,
1851 Oidhw4o = dnnl_Oidhw4o,
1852 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1853 OIdhw8i32o2i = dnnl_OIdhw8i32o2i,
1854 OIdhw8i64o2i = dnnl_OIdhw8i64o2i,
1855 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1856 OIdhw16i16o4i = dnnl_OIdhw16i16o4i,
1857 OIdhw16i32o4i = dnnl_OIdhw16i32o4i,
1858 OIdhw16i48o4i = dnnl_OIdhw16i48o4i,
1859 OIdhw16i64o4i = dnnl_OIdhw16i64o4i,
1860 OIdhw16i16o2i = dnnl_OIdhw16i16o2i,
1861 OIdhw16i32o2i = dnnl_OIdhw16i32o2i,
1862 OIdhw16i48o2i = dnnl_OIdhw16i48o2i,
1863 OIdhw16i64o2i = dnnl_OIdhw16i64o2i,
1864 OIdhw4i32o4i = dnnl_OIdhw4i32o4i,
1865 OIdhw4i64o4i = dnnl_OIdhw4i64o4i,
1866 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1867 OIdhw8i8o = dnnl_OIdhw8i8o,
1868 OIdhw8o8i = dnnl_OIdhw8o8i,
1869 OIdhw8o4i = dnnl_OIdhw8o4i,
1870 gIOw16o16i = dnnl_gIOw16o16i,
1871 gOIw16i16o = dnnl_gOIw16i16o,
1872 gOIw16o16i = dnnl_gOIw16o16i,
1873 gOiw16o = dnnl_gOiw16o,
1874 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1875 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1876 gOIw4i4o = dnnl_gOIw4i4o,
1877 gOIw4o4i = dnnl_gOIw4o4i,
1878 gOiw4o = dnnl_gOiw4o,
1879 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1880 gOIw8i8o = dnnl_gOIw8i8o,
1881 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1882 gOIw8o8i = dnnl_gOIw8o8i,
1883 gOIw8o4i = dnnl_gOIw8o4i,
1884 gOIw16i16o4i = dnnl_gOIw16i16o4i,
1885 gOIw16i16o2i = dnnl_gOIw16i16o2i,
1886 gOIw16o16i2o = dnnl_gOIw16o16i2o,
1887 gOwi16o = dnnl_gOwi16o,
1888 gOwI16o2i = dnnl_gOwI16o2i,
1889 gOwi4o = dnnl_gOwi4o,
1890 gOwi8o = dnnl_gOwi8o,
1891 Goiw8g = dnnl_Goiw8g,
1892 Goiw16g = dnnl_Goiw16g,
1893 gIOhw16o16i = dnnl_gIOhw16o16i,
1894 gOhwi16o = dnnl_gOhwi16o,
1895 gOhwI16o2i = dnnl_gOhwI16o2i,
1896 gOhwi4o = dnnl_gOhwi4o,
1897 gOhwi8o = dnnl_gOhwi8o,
1898 Goihw16g = dnnl_Goihw16g,
1899 gOIhw16i16o = dnnl_gOIhw16i16o,
1900 gOIhw16o16i = dnnl_gOIhw16o16i,
1901 gOihw16o = dnnl_gOihw16o,
1902 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1903 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1904 gOIhw4i4o = dnnl_gOIhw4i4o,
1905 gOIhw4o4i = dnnl_gOIhw4o4i,
1906 gOihw4o = dnnl_gOihw4o,
1907 Goihw8g = dnnl_Goihw8g,
1908 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1909 gOIhw8i8o = dnnl_gOIhw8i8o,
1910 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1911 OIw4o8i8o4i = dnnl_OIw4o8i8o4i,
1912 OIdhw4o8i8o4i = dnnl_OIdhw4o8i8o4i,
1913 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1914 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1915 gOIw4o8i8o4i = dnnl_gOIw4o8i8o4i,
1916 gOIdhw4o8i8o4i = dnnl_gOIdhw4o8i8o4i,
1917 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1918 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1919 OIhw16i16o4i = dnnl_OIhw16i16o4i,
1920 OIhw16i32o4i = dnnl_OIhw16i32o4i,
1921 OIhw16i48o4i = dnnl_OIhw16i48o4i,
1922 OIhw16i64o4i = dnnl_OIhw16i64o4i,
1923 OIhw16i16o2i = dnnl_OIhw16i16o2i,
1924 OIhw16i32o2i = dnnl_OIhw16i32o2i,
1925 OIhw16i48o2i = dnnl_OIhw16i48o2i,
1926 OIhw16i64o2i = dnnl_OIhw16i64o2i,
1927 OIhw16o16i2o = dnnl_OIhw16o16i2o,
1928 gOIhw16i16o4i = dnnl_gOIhw16i16o4i,
1929 gOIhw16i16o2i = dnnl_gOIhw16i16o2i,
1930 gOIhw16o16i2o = dnnl_gOIhw16o16i2o,
1931 gOIhw8o8i = dnnl_gOIhw8o8i,
1932 gOIhw8o4i = dnnl_gOIhw8o4i,
1933 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1934 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1935 gOdhwi16o = dnnl_gOdhwi16o,
1936 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1937 gOdhwi4o = dnnl_gOdhwi4o,
1938 gOdhwi8o = dnnl_gOdhwi8o,
1939 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1940 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1941 gOidhw16o = dnnl_gOidhw16o,
1942 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1943 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1944 gOidhw4o = dnnl_gOidhw4o,
1945 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1946 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1947 gOIdhw16i16o4i = dnnl_gOIdhw16i16o4i,
1948 gOIdhw16i16o2i = dnnl_gOIdhw16i16o2i,
1949 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1950 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1951 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1952 gOIdhw8o4i = dnnl_gOIdhw8o4i,
1953 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1954 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1955 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1956 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1957 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1958 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1959 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1960 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1961 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1962 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1963 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1964 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1966 ldOI32o4i = abDC32d4c,
1967 ldgOi32o = abdEc32e,
1968 ldgOI32o2i = abdEC32e2c,
1969 ldgOI32o4i = abdEC32e4c,
1970 OwI16o4i = dnnl_OwI16o4i,
1971 OhwI16o4i = dnnl_OhwI16o4i,
1972 gOwI16o4i = dnnl_gOwI16o4i,
1973 gOhwI16o4i = dnnl_gOhwI16o4i,
1974 OdhwI16o4i = dnnl_OdhwI16o4i,
1975 gOdhwI16o4i = dnnl_gOdhwI16o4i,
1977 Owi32o = dnnl_Owi32o,
1978 OwI32o2i = dnnl_OwI32o2i,
1979 OwI32o4i = dnnl_OwI32o4i,
1980 Owi48o = dnnl_Owi48o,
1981 OwI48o2i = dnnl_OwI48o2i,
1982 OwI48o4i = dnnl_OwI48o4i,
1983 Owi64o = dnnl_Owi64o,
1984 OwI64o2i = dnnl_OwI64o2i,
1985 OwI64o4i = dnnl_OwI64o4i,
1988 gOwi32o = dnnl_gOwi32o,
1989 gOwI32o2i = dnnl_gOwI32o2i,
1990 gOwI32o4i = dnnl_gOwI32o4i,
1991 gOwi48o = dnnl_gOwi48o,
1992 gOwI48o2i = dnnl_gOwI48o2i,
1993 gOwI48o4i = dnnl_gOwI48o4i,
1994 gOwi64o = dnnl_gOwi64o,
1995 gOwI64o2i = dnnl_gOwI64o2i,
1996 gOwI64o4i = dnnl_gOwI64o4i,
1998 gwIo2i = dnnl_gwIo2i,
1999 gwIo4i = dnnl_gwIo4i,
2000 OhwI32o = dnnl_OhwI32o,
2001 OhwI32o2i = dnnl_OhwI32o2i,
2002 OhwI32o4i = dnnl_OhwI32o4i,
2003 Ohwi48o = dnnl_Ohwi48o,
2004 OhwI48o2i = dnnl_OhwI48o2i,
2005 OhwI48o4i = dnnl_OhwI48o4i,
2006 Ohwi64o = dnnl_Ohwi64o,
2007 OhwI64o2i = dnnl_OhwI64o2i,
2008 OhwI64o4i = dnnl_OhwI64o4i,
2009 hwIo2i = dnnl_hwIo2i,
2010 hwIo4i = dnnl_hwIo4i,
2011 gOhwI32o = dnnl_gOhwI32o,
2012 gOhwI32o2i = dnnl_gOhwI32o2i,
2013 gOhwI32o4i = dnnl_gOhwI32o4i,
2014 gOhwi48o = dnnl_gOhwi48o,
2015 gOhwI48o2i = dnnl_gOhwI48o2i,
2016 gOhwI48o4i = dnnl_gOhwI48o4i,
2017 gOhwi64o = dnnl_gOhwi64o,
2018 gOhwI64o2i = dnnl_gOhwI64o2i,
2019 gOhwI64o4i = dnnl_gOhwI64o4i,
2021 ghwIo2i = dnnl_ghwIo2i,
2022 ghwIo4i = dnnl_ghwIo4i,
2023 Odhwi32o = dnnl_Odhwi32o,
2024 OdhwI32o2i = dnnl_OdhwI32o2i,
2025 OdhwI32o4i = dnnl_OdhwI32o4i,
2026 Odhwi48o = dnnl_Odhwi48o,
2027 OdhwI48o2i = dnnl_OdhwI48o2i,
2028 OdhwI48o4i = dnnl_OdhwI48o4i,
2029 Odhwi64o = dnnl_Odhwi64o,
2030 OdhwI64o2i = dnnl_OdhwI64o2i,
2031 OdhwI64o4i = dnnl_OdhwI64o4i,
2032 dhwIo2i = dnnl_dhwIo2i,
2033 dhwIo4i = dnnl_dhwIo4i,
2034 gOdhwi32o = dnnl_gOdhwi32o,
2035 gOdhwI32o2i = dnnl_gOdhwI32o2i,
2036 gOdhwI32o4i = dnnl_gOdhwI32o4i,
2037 gOdhwi48o = dnnl_gOdhwi48o,
2038 gOdhwI48o2i = dnnl_gOdhwI48o2i,
2039 gOdhwI48o4i = dnnl_gOdhwI48o4i,
2040 gOdhwi64o = dnnl_gOdhwi64o,
2041 gOdhwI64o2i = dnnl_gOdhwI64o2i,
2042 gOdhwI64o4i = dnnl_gOdhwI64o4i,
2043 gdhwio = dnnl_gdhwio,
2044 gdhwIo2i = dnnl_gdhwIo2i,
2045 gdhwIo4i = dnnl_gdhwIo4i,
2074 bool allow_empty =
false)
2076 validate_dims(adims);
2078 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
2082 "could not construct a memory descriptor using a "
2102 bool allow_empty =
false)
2104 validate_dims(adims);
2105 if (!strides.empty()) validate_dims(strides, (
int)adims.size());
2107 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
2108 strides.empty() ?
nullptr : &strides[0]);
2111 "could not construct a memory descriptor using "
2132 bool allow_empty =
false)
const {
2133 validate_dims(adims, data.
ndims);
2134 validate_dims(offsets, data.
ndims);
2137 &sub_md, &data, adims.data(), offsets.data());
2140 return desc(sub_md);
2188 if (data.
ndims) validate_dims(adims, 1);
2191 &out_md, &data, (
int)adims.size(), adims.data());
2194 status,
"could not reshape a memory descriptor");
2195 return desc(out_md);
2236 bool allow_empty =
false)
const {
2237 validate_dims(permutation, data.
ndims);
2240 &out_md, &data, permutation.data());
2243 "could not permute axes of a memory descriptor");
2244 return desc(out_md);
2289 explicit operator bool()
const {
return data.
ndims != 0; }
2321 "could not create a memory object");
2338 "could not get a memory descriptor from a memory object");
2339 return desc(*cdesc);
2346 "could not get an engine from a memory object");
2347 return engine(c_engine,
true);
2357 "could not get a native handle from a memory object");
2392 "could not set native handle of a memory object");
2408 "could not set native handle of a memory object");
2432 template <
typename T =
void>
2436 "could not map memory object data");
2437 return static_cast<T *
>(mapped_ptr);
2452 "could not unmap memory object data");
2534 "post-ops index is out of range");
2571 "could not append a sum post-op");
2574 memory::convert_to_c(data_type)),
2575 "could not append a sum post-op");
2584 "could not get parameters of a sum post-op");
2596 get(), index, &scale, &c_data_type),
2597 "could not get parameters of a sum post-op");
2615 float scale,
algorithm aalgorithm,
float alpha,
float beta) {
2618 "could not append an elementwise post-op");
2629 float &alpha,
float &beta)
const {
2632 get(), index, &scale, &c_alg, &alpha, &beta),
2633 "could not get parameters of an elementwise post-op");
2667 int mask,
const std::vector<float> &scales) {
2670 memory::convert_to_c(weights_data_type),
2671 memory::convert_to_c(bias_data_type),
2672 memory::convert_to_c(dst_data_type),
2673 scales.size(), mask, &scales[0]),
2674 "could not append depthwise post-op");
2693 int &mask, std::vector<float> &scales)
const {
2700 const float *c_scales;
2702 &c_weights_data_type, &c_bias_data_type,
2703 &c_dst_data_type, &count, &c_mask, &c_scales),
2704 "could not get parameters of depthwise post-op");
2709 scales.resize(count);
2713 scales[c] = c_scales[c];
2752 int mask,
const std::vector<float> &scales) {
2755 memory::convert_to_c(weights_data_type),
2756 memory::convert_to_c(bias_data_type),
2757 memory::convert_to_c(dst_data_type),
2758 scales.size(), mask, &scales[0]),
2759 "could not append depthwise post-op");
2778 int &mask, std::vector<float> &scales)
const {
2785 const float *c_scales;
2787 &c_weights_data_type, &c_bias_data_type,
2788 &c_dst_data_type, &count, &c_mask, &c_scales),
2789 "could not get parameters of depthwise post-op");
2794 scales.resize(count);
2798 scales[c] = c_scales[c];
2819 "could not append a binary post-op");
2833 "could not get parameters of a binary post-op");
2835 src1_desc.
data = *data;
2858 "could not create primitive attribute");
2875 "could not get scratchpad mode primitive attribute");
2885 "could not set scratchpad mode primitive attribute");
2900 const float *c_scales;
2902 get(), &count, &c_mask, &c_scales),
2903 "could not get output scales primitive attribute");
2904 scales.resize(count);
2908 scales[c] = c_scales[c];
2957 "could not set output scales primitive attribute");
2971 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2974 const float *c_scales;
2976 get(), arg, &count, &c_mask, &c_scales),
2977 "could not get scales primitive attributes");
2978 scales.resize(count);
2982 scales[c] = c_scales[c];
3001 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
3004 (
dnnl_dim_t)scales.size(), mask, scales.data()),
3005 "could not set scales primitive attribute");
3019 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
3022 const int32_t *c_zero_points;
3024 get(), arg, &count, &c_mask, &c_zero_points),
3025 "could not get zero points primitive attribute");
3026 zero_points.resize(count);
3030 zero_points[c] = c_zero_points[c];
3054 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
3057 zero_points.data()),
3058 "could not set zero points primitive attribute");
3068 "could not get post-ops primitive attribute");
3083 "could not set post-ops primitive attribute");
3122 "could not set RNN data quantization parameters primitive "
3136 float c_scale, c_shift;
3138 get(), &c_scale, &c_shift),
3139 "could not set RNN data quantization parameters primitive "
3173 (
int)scales.size(), mask, scales.data()),
3174 "could not set RNN weights quantization parameters primitive "
3200 const float *c_scales;
3202 get(), &count, &c_mask, &c_scales),
3203 "could not get primitive RNN weights quantization "
3204 "parameters attributes");
3205 scales.resize(count);
3209 scales[c] = c_scales[c];
3239 int mask,
const std::vector<float> &scales) {
3242 get(), (
int)scales.size(), mask, scales.data()),
3243 "could not set primitive RNN weights projection quantization "
3244 "parameters attributes");
3267 int &mask, std::vector<float> &scales) {
3270 const float *c_scales;
3273 get(), &count, &c_mask, &c_scales),
3274 "could not get primitive RNN weights projection quantization "
3275 "parameters attributes");
3276 scales.resize(count);
3280 scales[c] = c_scales[c];
3306 "could not retrieve implementation info string from a "
3307 "primitive descriptor");
3340 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
3341 [=](
query q) { return what == q; }))
3343 "memory descriptor query is invalid");
3467 "could not retrieve scratchpad engine from a primitive "
3469 return engine(c_engine,
true);
3477 "could not get attributes from a primitive descriptor");
3480 "could not clone primitive attributes");
3490 "could not get primitive kind from a primitive descriptor");
3501 "could not clone a primitive descriptor");
3554 if (pd ==
nullptr)
return;
3567 rc,
"could not get primitive kind from a primitive descriptor");
3568 if (pd_kind != c_prim_kind)
3570 "primitive descriptor operation kind mismatch");
3580 "could not get propagation kind from the primitive "
3586 && (pd_prop_kind == c_prop_kind1
3587 || pd_prop_kind == c_prop_kind2))) {
3594 "primitive descriptor propagation kind mismatch");
3640 bool allow_empty =
false) {
3644 dst_engine.
get(), attr.get());
3647 "could not create a primitive descriptor for a reorder "
3665 bool allow_empty =
false) {
3674 "could not create a primitive descriptor for a reorder "
3748 const std::vector<memory::desc> &mems) {
3749 std::vector<dnnl_memory_desc_t> c_mems;
3750 c_mems.reserve(mems.size());
3751 for (
const auto &s : mems)
3752 c_mems.push_back(s.data);
3777 const std::vector<memory::desc> &srcs,
const engine &aengine,
3784 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3785 attr.get(), aengine.
get()),
3786 "could not create a primitive descriptor for a concat "
3804 const std::vector<memory::desc> &srcs,
const engine &aengine,
3811 (
int)c_api_srcs.size(), concat_dimension,
3812 c_api_srcs.data(), attr.get(), aengine.
get()),
3813 "could not create a primitive descriptor for a concat "
3868 const std::vector<float> &scales,
3869 const std::vector<memory::desc> &srcs,
const engine &aengine,
3871 validate_container_size(scales,
3872 "counts of scales and sources are not equal",
3873 (
int)srcs.size(), (
int)srcs.size());
3880 (
int)c_api_srcs.size(), scales.data(),
3881 c_api_srcs.data(), attr.get(), aengine.
get()),
3882 "could not create a primitive descriptor for a sum "
3898 const std::vector<memory::desc> &srcs,
const engine &aengine,
3900 validate_container_size(scales,
3901 "counts of scales and sources are not equal",
3902 (
int)srcs.size(), (
int)srcs.size());
3908 (
int)c_api_srcs.size(), scales.data(),
3909 c_api_srcs.data(), attr.get(), aengine.
get()),
3910 "could not create a primitive descriptor for a sum "
3973 bool allow_empty =
false)
3974 : allow_empty_(allow_empty) {
3977 desc, attr ? attr->
get() :
nullptr, aengine.
get(), hint_fwd_pd);
3980 status,
"could not create a primitive descriptor iterator");
3981 pd_iterator.reset(iterator);
3994 status,
"could not advance a primitive descriptor iterator");
4000 bool allow_empty_ =
false;
4004 pd_iterator.
get(allow_empty_));
4007 "could not fetch a primitive descriptor from a primitive "
4008 "descriptor iterator");
4074 &strides[0], &padding_l[0], &padding_r[0]),
4075 "could not create a descriptor for a convolution forward "
4076 "propagation primitive");
4118 &weights_desc.
data,
nullptr, &dst_desc.
data,
4119 &strides[0], &padding_l[0], &padding_r[0]),
4120 "could not create a descriptor for a convolution forward "
4121 "propagation primitive");
4168 &weights_desc.
data, &bias_desc.
data,
4169 &dst_desc.
data, &strides[0], &dilates[0],
4170 &padding_l[0], &padding_r[0]),
4171 "could not create a descriptor for a dilated convolution "
4172 "forward propagation primitive");
4217 &weights_desc.
data,
nullptr,
4218 &dst_desc.
data, &strides[0], &dilates[0],
4219 &padding_l[0], &padding_r[0]),
4220 "could not create a descriptor for a dilated convolution "
4221 "forward propagation primitive");
4241 bool allow_empty =
false)
4243 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4257 const engine &aengine,
bool allow_empty =
false)
4259 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4339 &weights_desc.
data, &diff_dst_desc.
data,
4340 &strides[0], &padding_l[0], &padding_r[0]),
4341 "could not create a descriptor for a convolution backward "
4342 "propagation primitive");
4384 &weights_desc.
data, &diff_dst_desc.
data,
4385 &strides[0], &dilates[0], &padding_l[0],
4387 "could not create a descriptor for a dilated convolution "
4388 "backward propagation primitive");
4412 bool allow_empty =
false)
4414 hint_fwd_pd.
get(), allow_empty) {}
4433 bool allow_empty =
false)
4435 hint_fwd_pd.
get(), allow_empty) {}
4510 &diff_weights_desc.
data, &diff_bias_desc.
data,
4511 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4513 "could not create a descriptor for a convolution weights "
4514 "update primitive");
4551 &diff_weights_desc.
data,
nullptr,
4552 &diff_dst_desc.
data, &strides[0],
4553 &padding_l[0], &padding_r[0]),
4554 "could not create a descriptor for a convolution weights "
4555 "update primitive");
4600 &diff_weights_desc.
data, &diff_bias_desc.
data,
4601 &diff_dst_desc.
data, &strides[0], &dilates[0],
4602 &padding_l[0], &padding_r[0]),
4603 "could not create a descriptor for a dilated convolution "
4604 "weights gradient primitive");
4646 &diff_weights_desc.
data,
nullptr,
4647 &diff_dst_desc.
data, &strides[0], &dilates[0],
4648 &padding_l[0], &padding_r[0]),
4649 "could not create a descriptor for a dilated convolution "
4650 "weights gradient primitive");
4673 bool allow_empty =
false)
4675 hint_fwd_pd.
get(), allow_empty) {}
4693 bool allow_empty =
false)
4695 hint_fwd_pd.
get(), allow_empty) {}
4794 &strides[0], &padding_l[0], &padding_r[0]),
4795 "could not create a descriptor for a deconvolution forward "
4796 "propagation primitive");
4837 &weights_desc.
data,
nullptr, &dst_desc.
data,
4838 &strides[0], &padding_l[0], &padding_r[0]),
4839 "could not create a descriptor for a deconvolution forward "
4840 "propagation primitive");
4886 &weights_desc.
data, &bias_desc.
data,
4887 &dst_desc.
data, &strides[0], &dilates[0],
4888 &padding_l[0], &padding_r[0]),
4889 "could not create a descriptor for a dilated deconvolution "
4890 "forward propagation primitive");
4934 &weights_desc.
data,
nullptr,
4935 &dst_desc.
data, &strides[0], &dilates[0],
4936 &padding_l[0], &padding_r[0]),
4937 "could not create a descriptor for a dilated deconvolution "
4938 "forward propagation primitive");
4958 bool allow_empty =
false)
4960 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4974 const engine &aengine,
bool allow_empty =
false)
4976 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5051 &weights_desc.
data, &diff_dst_desc.
data,
5052 &strides[0], &padding_l[0], &padding_r[0]),
5053 "could not create a descriptor for a deconvolution "
5054 "backward propagation primitive");
5095 &weights_desc.
data, &diff_dst_desc.
data,
5096 &strides[0], &dilates[0], &padding_l[0],
5098 "could not create a descriptor for a dilated deconvolution "
5099 "backward propagation primitive");
5123 bool allow_empty =
false)
5125 hint_fwd_pd.
get(), allow_empty) {}
5144 bool allow_empty =
false)
5146 hint_fwd_pd.
get(), allow_empty) {}
5220 &diff_weights_desc.
data, &diff_bias_desc.
data,
5221 &diff_dst_desc.
data, &strides[0], &padding_l[0],
5223 "could not create a descriptor for a deconvolution weights "
5224 "update primitive");
5260 &src_desc.
data, &diff_weights_desc.
data,
5261 nullptr, &diff_dst_desc.
data, &strides[0],
5262 &padding_l[0], &padding_r[0]),
5263 "could not create a descriptor for a deconvolution weights "
5264 "update primitive");
5308 &diff_weights_desc.
data, &diff_bias_desc.
data,
5309 &diff_dst_desc.
data, &strides[0], &dilates[0],
5310 &padding_l[0], &padding_r[0]),
5311 "could not create a descriptor for a dilated deconvolution "
5312 "weights gradient primitive");
5353 &diff_weights_desc.
data,
nullptr,
5354 &diff_dst_desc.
data, &strides[0], &dilates[0],
5355 &padding_l[0], &padding_r[0]),
5356 "could not create a descriptor for a dilated deconvolution "
5357 "weights gradient primitive");
5381 bool allow_empty =
false)
5383 hint_fwd_pd.
get(), allow_empty) {}
5402 bool allow_empty =
false)
5404 hint_fwd_pd.
get(), allow_empty) {}
5474 float alpha,
float beta,
float k = 1.f) {
5478 local_size, alpha, beta, k),
5479 "could not create a descriptor for a lrn forward "
5480 "propagation primitive");
5499 bool allow_empty =
false)
5501 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5514 const engine &aengine,
bool allow_empty =
false)
5516 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5568 float alpha,
float beta,
float k = 1.f) {
5571 &diff_data_desc.
data, &data_desc.
data, local_size,
5573 "could not create a descriptor for a lrn backward "
5574 "propagation primitive");
5597 bool allow_empty =
false)
5599 hint_fwd_pd.
get(), allow_empty) {}
5617 bool allow_empty =
false)
5619 hint_fwd_pd.
get(), allow_empty) {}
5701 &dst_desc.
data, &strides[0], &kernel[0],
5702 &padding_l[0], &padding_r[0]),
5703 "could not create a descriptor for a pooling forward "
5704 "propagation primitive");
5723 bool allow_empty =
false)
5725 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5738 const engine &aengine,
bool allow_empty =
false)
5740 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5810 &diff_dst_desc.
data, &strides[0], &kernel[0],
5811 &padding_l[0], &padding_r[0]),
5812 "could not create a descriptor for a pooling backward "
5813 "propagation primitive");
5836 bool allow_empty =
false)
5838 hint_fwd_pd.
get(), allow_empty) {}
5856 bool allow_empty =
false)
5858 hint_fwd_pd.
get(), allow_empty) {}
5936 &data_desc.
data, alpha, beta),
5937 "could not create a descriptor for an eltwise forward "
5938 "propagation primitive");
5958 bool allow_empty =
false)
5960 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5974 const engine &aengine,
bool allow_empty =
false)
5976 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6028 &diff_data_desc.
data, &data_desc.
data, alpha, beta),
6029 "could not create a descriptor for an eltwise backward "
6030 "propagation primitive");
6054 bool allow_empty =
false)
6056 hint_fwd_pd.
get(), allow_empty) {}
6075 bool allow_empty =
false)
6077 hint_fwd_pd.
get(), allow_empty) {}
6139 &data_desc.
data, softmax_axis),
6140 "could not create a descriptor for a softmax forward "
6141 "propagation primitive");
6161 bool allow_empty =
false)
6163 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6177 const engine &aengine,
bool allow_empty =
false)
6179 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6228 &data_desc.
data, softmax_axis),
6229 "could not create a descriptor for a softmax backward "
6230 "propagation primitive");
6254 bool allow_empty =
false)
6256 hint_fwd_pd.
get(), allow_empty) {}
6275 bool allow_empty =
false)
6277 hint_fwd_pd.
get(), allow_empty) {}
6336 int logsoftmax_axis) {
6339 &data_desc.
data, logsoftmax_axis),
6340 "could not create a descriptor for a logsoftmax forward "
6341 "propagation primitive");
6361 bool allow_empty =
false)
6363 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6377 const engine &aengine,
bool allow_empty =
false)
6379 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6429 int logsoftmax_axis) {
6431 &diff_data_desc.
data, &data_desc.
data,
6433 "could not create a descriptor for a logsoftmax backward "
6434 "propagation primitive");
6458 bool allow_empty =
false)
6460 hint_fwd_pd.
get(), allow_empty) {}
6479 bool allow_empty =
false)
6481 hint_fwd_pd.
get(), allow_empty) {}
6564 "could not create a descriptor for a batch normalization "
6565 "forward propagation primitive");
6586 bool allow_empty =
false)
6588 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6602 const engine &aengine,
bool allow_empty =
false)
6604 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6649 "could not retrieve a descriptor from a primitive "
6650 "descriptor for batch normalization forward propagation "
6690 &diff_data_desc.
data, &data_desc.
data,
6692 "could not create a descriptor for a batch normalization "
6693 "backward propagation primitive");
6718 bool allow_empty =
false)
6720 hint_fwd_pd.
get(), allow_empty) {}
6739 bool allow_empty =
false)
6741 hint_fwd_pd.
get(), allow_empty) {}
6844 "could not create a descriptor for a layer normalization "
6845 "forward propagation primitive");
6864 "could not create a descriptor for a layer normalization "
6865 "forward propagation primitive");
6886 bool allow_empty =
false)
6888 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6902 const engine &aengine,
bool allow_empty =
false)
6904 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6947 "could not retrieve a descriptor from a primitive "
6948 "descriptor for layer normalization forward propagation "
6990 &diff_data_desc.
data, &data_desc.
data,
6992 "could not create a descriptor for a batch normalization "
6993 "backward propagation primitive");
7013 &diff_data_desc.
data, &data_desc.
data,
7015 "could not create a descriptor for a batch normalization "
7016 "backward propagation primitive");
7041 bool allow_empty =
false)
7043 hint_fwd_pd.
get(), allow_empty) {}
7062 bool allow_empty =
false)
7064 hint_fwd_pd.
get(), allow_empty) {}
7154 &src_desc.
data, &weights_desc.
data,
7156 "could not create a descriptor for an inner product "
7157 "forward propagation primitive");
7179 &weights_desc.
data,
nullptr, &dst_desc.
data),
7180 "could not create a descriptor for an inner product "
7181 "forward propagation primitive");
7201 bool allow_empty =
false)
7203 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7217 const engine &aengine,
bool allow_empty =
false)
7219 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7274 &diff_src_desc.
data, &weights_desc.
data,
7275 &diff_dst_desc.
data),
7276 "could not create a descriptor for an inner product "
7277 "backward propagation primitive");
7302 bool allow_empty =
false)
7304 hint_fwd_pd.
get(), allow_empty) {}
7323 bool allow_empty =
false)
7325 hint_fwd_pd.
get(), allow_empty) {}
7379 &src_desc.
data, &diff_weights_desc.
data,
7380 &diff_bias_desc.
data, &diff_dst_desc.
data),
7381 "could not create a descriptor for an inner product "
7382 "weights gradient primitive");
7400 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
7401 &diff_dst_desc.
data),
7402 "could not create a descriptor for an inner product "
7403 "weights gradient primitive");
7427 bool allow_empty =
false)
7429 hint_fwd_pd.
get(), allow_empty) {}
7448 bool allow_empty =
false)
7450 hint_fwd_pd.
get(), allow_empty) {}
7500 using primitive_desc::primitive_desc;
7684 "could not retrieve a descriptor from a primitive descriptor "
7685 "for an RNN primitive");
7692 && (
rnn_d->prop_kind == c_prop_kind1
7693 ||
rnn_d->prop_kind == c_prop_kind2)
7694 &&
rnn_d->cell_kind == c_cell_kind;
7698 "mismatch between expected and provided descriptors for an "
7760 float beta = 0.0f) {
7766 &src_iter_desc.
data, &weights_layer_desc.
data,
7767 &weights_iter_desc.
data, &bias_desc.
data,
7768 &dst_layer_desc.
data, &dst_iter_desc.
data,
7770 "could not create a descriptor for a vanilla RNN forward "
7771 "propagation primitive");
7791 bool allow_empty =
false)
7793 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7807 const engine &aengine,
bool allow_empty =
false)
7809 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7940 float beta = 0.0f) {
7946 &src_iter_desc.
data, &weights_layer_desc.
data,
7947 &weights_iter_desc.
data, &bias_desc.
data,
7948 &dst_layer_desc.
data, &dst_iter_desc.
data,
7949 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7950 &diff_weights_layer_desc.
data,
7951 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7952 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7954 "could not create a descriptor for a vanilla RNN backward "
7955 "propagation primitive");
7979 bool allow_empty =
false)
7981 hint_fwd_pd.
get(), allow_empty) {}
8000 bool allow_empty =
false)
8002 hint_fwd_pd.
get(), allow_empty) {}
8164 &src_iter_desc.
data, &src_iter_c_desc.
data,
8165 &weights_layer_desc.
data, &weights_iter_desc.
data,
8166 &weights_peephole_desc.
data,
8167 &weights_projection_desc.
data, &bias_desc.
data,
8168 &dst_layer_desc.
data, &dst_iter_desc.
data,
8170 "could not create a descriptor for an LSTM forward "
8171 "propagation primitive");
8231 &src_iter_desc.
data, &src_iter_c_desc.
data,
8232 &weights_layer_desc.
data, &weights_iter_desc.
data,
8233 &weights_peephole_desc.
data, &bias_desc.
data,
8234 &dst_layer_desc.
data, &dst_iter_desc.
data,
8236 "could not create a descriptor for an LSTM forward "
8237 "propagation primitive");
8291 &src_iter_desc.
data, &src_iter_c_desc.
data,
8292 &weights_layer_desc.
data, &weights_iter_desc.
data,
8293 &bias_desc.
data, &dst_layer_desc.
data,
8294 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8296 "could not create a descriptor for an LSTM forward "
8297 "propagation primitive");
8316 bool allow_empty =
false)
8318 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8331 const engine &aengine,
bool allow_empty =
false)
8333 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8519 &src_iter_desc.
data, &src_iter_c_desc.
data,
8520 &weights_layer_desc.
data, &weights_iter_desc.
data,
8521 &weights_peephole_desc.
data,
8522 &weights_projection_desc.
data, &bias_desc.
data,
8523 &dst_layer_desc.
data, &dst_iter_desc.
data,
8524 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8525 &diff_src_iter_desc.
data,
8526 &diff_src_iter_c_desc.
data,
8527 &diff_weights_layer_desc.
data,
8528 &diff_weights_iter_desc.
data,
8529 &diff_weights_peephole_desc.
data,
8530 &diff_weights_projection_desc.
data,
8531 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8532 &diff_dst_iter_desc.
data,
8533 &diff_dst_iter_c_desc.
data,
8535 "could not create a descriptor for an LSTM backward "
8536 "propagation primitive");
8629 &src_iter_desc.
data, &src_iter_c_desc.
data,
8630 &weights_layer_desc.
data, &weights_iter_desc.
data,
8631 &weights_peephole_desc.
data, &bias_desc.
data,
8632 &dst_layer_desc.
data, &dst_iter_desc.
data,
8633 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8634 &diff_src_iter_desc.
data,
8635 &diff_src_iter_c_desc.
data,
8636 &diff_weights_layer_desc.
data,
8637 &diff_weights_iter_desc.
data,
8638 &diff_weights_peephole_desc.
data,
8639 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8640 &diff_dst_iter_desc.
data,
8641 &diff_dst_iter_c_desc.
data,
8643 "could not create a descriptor for an LSTM backward "
8644 "propagation primitive");
8726 &src_iter_desc.
data, &src_iter_c_desc.
data,
8727 &weights_layer_desc.
data, &weights_iter_desc.
data,
8728 &bias_desc.
data, &dst_layer_desc.
data,
8729 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8730 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8731 &diff_src_iter_c_desc.
data,
8732 &diff_weights_layer_desc.
data,
8733 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8734 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8735 &diff_dst_iter_c_desc.
data,
8737 "could not create a descriptor for an LSTM backward "
8738 "propagation primitive");
8761 bool allow_empty =
false)
8763 hint_fwd_pd.
get(), allow_empty) {}
8781 bool allow_empty =
false)
8783 hint_fwd_pd.
get(), allow_empty) {}
8965 &src_iter_desc.
data, &weights_layer_desc.
data,
8966 &weights_iter_desc.
data, &bias_desc.
data,
8967 &dst_layer_desc.
data, &dst_iter_desc.
data,
8969 "could not create a descriptor for a GRU forward "
8970 "propagation primitive");
8989 bool allow_empty =
false)
8991 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9004 const engine &aengine,
bool allow_empty =
false)
9006 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9133 &src_iter_desc.
data, &weights_layer_desc.
data,
9134 &weights_iter_desc.
data, &bias_desc.
data,
9135 &dst_layer_desc.
data, &dst_iter_desc.
data,
9136 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9137 &diff_weights_layer_desc.
data,
9138 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9139 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9141 "could not create a descriptor for a GRU backward "
9142 "propagation primitive");
9165 bool allow_empty =
false)
9167 hint_fwd_pd.
get(), allow_empty) {}
9185 bool allow_empty =
false)
9187 hint_fwd_pd.
get(), allow_empty) {}
9330 &src_iter_desc.
data, &weights_layer_desc.
data,
9331 &weights_iter_desc.
data, &bias_desc.
data,
9332 &dst_layer_desc.
data, &dst_iter_desc.
data,
9334 "could not create a descriptor for an LBR GRU forward "
9335 "propagation primitive");
9355 bool allow_empty =
false)
9357 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9371 const engine &aengine,
bool allow_empty =
false)
9373 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9501 &src_iter_desc.
data, &weights_layer_desc.
data,
9502 &weights_iter_desc.
data, &bias_desc.
data,
9503 &dst_layer_desc.
data, &dst_iter_desc.
data,
9504 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9505 &diff_weights_layer_desc.
data,
9506 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9507 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9509 "could not create a descriptor for an LBR GRU backward "
9510 "propagation primitive");
9534 bool allow_empty =
false)
9536 hint_fwd_pd.
get(), allow_empty) {}
9555 bool allow_empty =
false)
9557 hint_fwd_pd.
get(), allow_empty) {}
9677 &data_desc.
data, axis, group_size),
9678 "could not create a descriptor for a shuffle forward "
9679 "propagation primitive");
9701 bool allow_empty =
false)
9703 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9748 &diff_data_desc.
data, axis, group_size),
9749 "could not create a descriptor for a shuffle backward "
9750 "propagation primitive");
9776 bool allow_empty =
false)
9778 hint_fwd_pd.
get(), allow_empty) {}
9838 "could not create a descriptor for a binary operation "
9858 bool allow_empty =
false)
9860 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9873 const engine &aengine,
bool allow_empty =
false)
9875 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9933 &weights_desc.
data,
nullptr, &dst_desc.
data),
9934 "could not create a descriptor for a matmul primitive");
9946 &weights_desc.
data, &bias_desc.
data,
9948 "could not create a descriptor for a matmul primitive");
9966 bool allow_empty =
false)
9968 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9980 const engine &aengine,
bool allow_empty =
false)
9982 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10055 "could not create a resampling forward descriptor");
10070 const std::vector<float> &factors,
10076 &src_desc.
data,
nullptr),
10077 "could not create a resampling forward descriptor");
10097 const std::vector<float> &factors,
const memory::desc &src_desc,
10099 if (!factors.empty())
10105 "could not create a resampling forward descriptor");
10125 bool allow_empty =
false)
10127 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10141 const engine &aengine,
bool allow_empty =
false)
10143 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10190 &diff_src_desc.
data, &diff_dst_desc.
data),
10191 "could not create a resampling backward data descriptor");
10206 if (!factors.empty())
10210 &diff_src_desc.
data, &diff_dst_desc.
data),
10211 "could not create a resampling backward data descriptor");
10235 bool allow_empty =
false)
10237 hint_fwd_pd.
get(), allow_empty) {}
10256 bool allow_empty =
false)
10258 hint_fwd_pd.
get(), allow_empty) {}
10342 &dst_desc.
data, &strides[0], &kernel[0],
10343 &dilation[0], &padding_l[0], &padding_r[0]),
10344 "could not create a descriptor for a pooling forward "
10345 "propagation primitive");
10365 bool allow_empty =
false)
10367 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10381 const engine &aengine,
bool allow_empty =
false)
10383 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10458 &diff_dst_desc.
data, &strides[0], &kernel[0],
10459 &dilation[0], &padding_l[0], &padding_r[0]),
10460 "could not create a descriptor for a pooling backward "
10461 "propagation primitive");
10486 bool allow_empty =
false)
10488 hint_fwd_pd.
get(), allow_empty) {}
10507 bool allow_empty =
false)
10509 hint_fwd_pd.
get(), allow_empty) {}
10557 dnnl_prelu_desc_t data;
10571 &data_desc.
data, &weight_desc.
data),
10572 "could not create a descriptor for a prelu forward "
10573 "propagation primitive");
10593 bool allow_empty =
false)
10595 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10609 const engine &aengine,
bool allow_empty =
false)
10611 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10644 dnnl_prelu_desc_t data;
10659 &weight_desc.
data, &diff_data_desc.
data,
10660 &diff_weights_desc.
data),
10661 "could not create a descriptor for a prelu backward "
10662 "propagation primitive");
10686 bool allow_empty =
false)
10688 hint_fwd_pd.
get(), allow_empty) {}
10707 bool allow_empty =
false)
10709 hint_fwd_pd.
get(), allow_empty) {}
10781 &src_desc.
data, &dst_desc.
data, p, eps),
10782 "could not create a reduction descriptor");
10800 bool allow_empty =
false)
10802 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10814 const engine &aengine,
bool allow_empty =
false)
10816 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10924 return static_cast<status>(
10965 "could not get primitive cache capacity");
10972 "could not set primitive cache capacity");
10989 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10996 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10998 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
11005 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
11007 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
11018 "could not create a primitive");
11024 inline void primitive::execute(
const stream &astream,
11025 const std::unordered_map<int, memory> &args)
const {
11026 std::vector<dnnl_exec_arg_t> c_args;
11027 c_args.reserve(args.size());
11028 for (
const auto &a : args)
11029 c_args.push_back({a.first, a.second.get(
true)});
11032 (
int)c_args.size(), c_args.data()),
11033 "could not execute a primitive");
11038 #undef DNNL_DEFINE_BITMASK_OPS
11048 #ifndef DOXYGEN_SHOULD_SKIP_THIS
11050 namespace dnnl = ::dnnl;
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:470
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.
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.
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.
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.
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.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_weights_qparams(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns the quantization scaling factors for RNN weights tensors.
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.
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
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.
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.
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.
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_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_v2(dnnl_post_ops_t post_ops, float scale, dnnl_data_type_t data_type)
Appends an accumulation v2 (sum) to post-ops.
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
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.
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.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_weights_projection_qparams(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns the quantization scaling factors for RNN projection weights tensors.
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.
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
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.
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_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
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.
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.
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:401
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_projection_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN projection weights tensors.
prop_kind
Propagation kind.
Definition: dnnl.hpp:435
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:2270
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.
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_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.
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.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_data_qparams(const_dnnl_primitive_attr_t attr, float *scale, float *shift)
Returns the quantization scale and shift parameters for RNN data tensors.
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_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_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.
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.
@ eltwise_mish
Elementwise: mish.
@ resampling_linear
Linear (Bilinear, Trilinear) resampling method.
@ resampling_nearest
Nearest Neighbor resampling method.
@ eltwise_elu_use_dst_for_bwd
Elementwise: exponential linear unit (ELU) (dst for backward)
@ eltwise_tanh_use_dst_for_bwd
Elementwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
@ reduction_norm_lp_power_p_sum
Reduction using norm_lp_power_p_sum operation.
@ eltwise_linear
Elementwise: linear.
@ eltwise_clip_v2
Eltwise: clip version 2.
@ eltwise_soft_relu
Elementwise: soft_relu.
@ eltwise_logistic
Elementwise: logistic.
@ eltwise_clip
Elementwise: clip.
@ binary_ge
Binary greater than or equal.
@ eltwise_abs
Elementwise: abs.
@ eltwise_pow
Elementwise: pow.
@ eltwise_tanh
Elementwise: hyperbolic tangent non-linearity (tanh)
@ eltwise_logistic_use_dst_for_bwd
Elementwise: logistic (dst for backward)
@ eltwise_bounded_relu
Elementwise: bounded_relu.
@ reduction_norm_lp_power_p_max
Reduction using norm_lp_power_p_max operation.
@ reduction_max
Reduction using max operation.
@ eltwise_clip_v2_use_dst_for_bwd
Elementwise: clip version 2 (dst for backward)
@ eltwise_square
Elementwise: square.
@ convolution_direct
Direct convolution.
@ eltwise_exp
Elementwise: exponent.
@ binary_gt
Binary greater than.
@ reduction_norm_lp_max
Reduction using norm_lp_max operation.
@ eltwise_elu
Elementwise: exponential linear unit (ELU)
@ convolution_winograd
Winograd convolution.
@ deconvolution_direct
Direct deconvolution.
@ pooling_avg
Average pooling exclude padding, alias for dnnl::algorithm::pooling_avg_include_padding.
@ lbr_gru
GRU cell with linear before reset.
@ pooling_avg_exclude_padding
Average pooling exclude padding.
@ eltwise_gelu
Elementwise: gelu alias for dnnl::algorithm::eltwise_gelu_tanh.
@ eltwise_sqrt
Elementwise: square root.
@ pooling_max
Max pooling.
@ reduction_min
Reduction using min operation.
@ eltwise_gelu_erf
Elementwise: erf-based gelu.
@ eltwise_swish
Elementwise: swish ( )
@ binary_ne
Binary not equal.
@ lrn_within_channel
LRN within a single channel.
@ binary_le
Binary less than or equal.
@ eltwise_hardswish
Elementwise: hardswish.
@ reduction_mul
Reduction using mul operation.
@ lrn_across_channels
Local response normalization (LRN) across multiple channels.
@ eltwise_relu
Elementwise: rectified linear unit (ReLU)
@ eltwise_gelu_tanh
Elementwise: tanh-based gelu.
@ eltwise_relu_use_dst_for_bwd
Elementwise: rectified linar unit (ReLU) (dst for backward)
@ eltwise_logsigmoid
Elementwise: logsigmoid.
@ convolution_auto
Convolution algorithm that is chosen to be either direct or Winograd automatically.
@ eltwise_exp_use_dst_for_bwd
Elementwise: exponent (dst for backward)
@ eltwise_round
Elementwise: round.
@ eltwise_sqrt_use_dst_for_bwd
Elementwise: square root (dst for backward)
@ pooling_avg_include_padding
Average pooling include padding.
@ reduction_norm_lp_sum
Reduction using norm_lp_sum operation.
@ reduction_mean
Reduction using mean operation.
@ deconvolution_winograd
Winograd deconvolution.
@ eltwise_log
Elementwise: natural logarithm.
@ undef
Undefined algorithm.
@ binary_lt
Binary less than.
@ reduction_sum
Reduction using sum operation.
@ library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
@ user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
@ backward
Backward propagation (with respect to all parameters).
@ backward_weights
Backward weights propagation.
@ forward_training
Forward data propagation (training mode).
@ forward_inference
Forward data propagation (inference mode).
@ forward_scoring
Forward data propagation, alias for dnnl::prop_kind::forward_inference.
@ forward
Forward data propagation, alias for dnnl::prop_kind::forward_training.
@ backward_data
Backward data propagation.
@ backward_bias
Backward bias propagation.
@ undef
Undefined propagation kind.
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:2292
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:2287
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.
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_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.
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,...
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:10993
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:11002
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.
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:10985
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_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_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.
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_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_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.
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.
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_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.
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.
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.
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.
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.
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.
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.
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.
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:2216
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_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
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:977
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:2222
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:2220
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:2218
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.
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.
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.
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.
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_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_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.
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.
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_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.
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
size_t DNNL_API dnnl_data_type_size(dnnl_data_type_t data_type)
Returns the size of data type.
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_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
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.
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.
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_status_t DNNL_API dnnl_memory_get_engine(const_dnnl_memory_t memory, dnnl_engine_t *engine)
Returns the engine of a memory object.
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_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.
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
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.
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.
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1399
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1367
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.
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
#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:1576
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_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:186
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:707
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:182
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:211
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:710
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:725
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:722
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:197
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:734
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:719
@ dnnl_abdfce
permuted 6D tensor
Definition: dnnl_types.h:424
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:713
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
@ dnnl_abdefc
permuted 6D tensor
Definition: dnnl_types.h:425
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:737
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:568
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:731
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
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...
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...
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_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.
dnnl_status_t DNNL_API dnnl_prelu_forward_desc_init(dnnl_prelu_desc_t *prelu_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *weights_desc)
Initializes a descriptor for PReLU (leaky ReLU with trainable alpha parameter) forward propagation pr...
dnnl_status_t DNNL_API dnnl_prelu_backward_desc_init(dnnl_prelu_desc_t *prelu_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *diff_weights_desc)
Initializes a descriptor for PReLU (leaky ReLU with trainable alpha parameter) backward propagation p...
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:10970
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.
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.
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:10962
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.
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2387
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:2405
#define DNNL_ARG_DIFF_BIAS
Gradient (diff) of the bias tensor argument.
Definition: dnnl_types.h:2512
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2458
#define DNNL_ARG_DIFF_SRC_LAYER
A special mnemonic for gradient (diff) of RNN input vector.
Definition: dnnl_types.h:2446
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2503
#define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:2423
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:1307
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
A special mnemonic for diff of RNN weights applied to the projection weights.
Definition: dnnl_types.h:2509
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_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.
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2497
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2452
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2479
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.
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2411
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.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1588
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:368
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.
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:2393
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:2370
query
Primitive descriptor query specification.
Definition: dnnl.hpp:761
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:2358
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:1157
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:1103
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2583
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:364
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:2259
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2417
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:375
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:2355
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:2491
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.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:2381
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:2426
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:631
#define DNNL_ARG_DIFF_DST_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2473
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:1076
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.
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2364
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.
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:2379
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:2467
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1355
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:1316
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:1342
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1329
@ batch_normalization_d
batch normalization descriptor
@ weights_md
weights memory descriptor desc
@ memory_consumption_s64
memory required for scratchpad (bytes)
@ shuffle_d
shuffle descriptor
@ deconvolution_d
deconvolution descriptor
@ impl_info_str
implementation name
@ diff_weights_md
weights gradient (diff) memory desc
@ workspace_md
workspace memory desc
@ reduction_d
reduction descriptor
@ eltwise_d
eltwise descriptor
@ matmul_d
matmul descriptor
@ softmax_d
softmax descriptor
@ num_of_outputs_s32
number of outputs expected
@ primitive_kind
primitive kind
@ dst_md
destination memory desc
@ scratchpad_engine
scratchpad engine
@ reorder_src_engine
reorder source engine
@ op_d
operation descriptor
@ layer_normalization_d
layer normalization descriptor
@ logsoftmax_d
logsoftmax descriptor
@ pooling_d
pooling descriptor
@ num_of_inputs_s32
number of inputs expected
@ diff_src_md
source gradient (diff) memory desc
@ src_md
source memory desc
@ scratchpad_md
scratchpad memory desc
@ reorder_dst_engine
reorder destination engine
@ convolution_d
convolution descriptor
@ time_estimate_f64
runtime estimation (seconds), unimplemented
@ binary_d
binary descriptor
@ diff_dst_md
destination gradient (diff) memory desc
@ exec_arg_md
memory desc of an execute argument
@ inner_product_d
inner product descriptor
@ resampling_d
resampling descriptor
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:1237
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:1203
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:1221
@ dnnl_eltwise_logsigmoid
Eltwise: logsigmoid.
Definition: dnnl_types.h:1213
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:1239
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:1195
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:1285
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:1180
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:1265
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:1299
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:1178
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1301
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:1289
@ dnnl_binary_ne
Binary not equal.
Definition: dnnl_types.h:1281
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:1225
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:1190
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:1176
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:1197
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:1162
@ dnnl_eltwise_clip_v2_use_dst_for_bwd
Eltwise: clip version 2 (dst for backward)
Definition: dnnl_types.h:1231
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:1241
@ dnnl_binary_sub
Binary sub.
Definition: dnnl_types.h:1269
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:1166
@ dnnl_binary_eq
Binary equal.
Definition: dnnl_types.h:1279
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:1170
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:1164
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:1199
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:1245
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:1209
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:1247
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:1174
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:1249
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:1257
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:1172
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:1160
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:1186
@ dnnl_binary_ge
Binary greater or equal.
Definition: dnnl_types.h:1271
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:1201
@ dnnl_eltwise_clip_v2
Eltwise: clip version 2.
Definition: dnnl_types.h:1205
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:1243
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:1223
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:1168
@ dnnl_eltwise_hardswish
Eltwise: hardswish.
Definition: dnnl_types.h:1217
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:1293
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:1207
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:1219
@ dnnl_binary_gt
Binary greater than.
Definition: dnnl_types.h:1273
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:1287
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:1188
@ dnnl_binary_lt
Binary less than.
Definition: dnnl_types.h:1277
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:1235
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:1295
@ dnnl_binary_le
Binary less or equal.
Definition: dnnl_types.h:1275
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:1233
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:1227
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:1259
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:1267
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:1297
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1303
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:1211
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:1261
@ dnnl_eltwise_mish
Eltwise: mish.
Definition: dnnl_types.h:1215
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:1291
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:1229
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:1184
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:1182
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:1283
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:1263
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:1137
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:1111
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:1107
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:1115
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:1131
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:1143
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:1127
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:1105
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:1113
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:1145
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:1129
@ dnnl_prelu
A PReLU primitive.
Definition: dnnl_types.h:1149
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:1119
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:1141
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:1109
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:1139
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:1123
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:1117
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:1121
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:1133
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:1147
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:1125
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2626
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2590
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2611
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2635
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2633
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2615
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2623
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2639
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2625
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2589
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2610
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2634
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2640
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2613
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2593
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2620
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2612
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2587
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2618
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2601
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2592
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2614
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2636
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2628
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2604
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2603
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2598
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2584
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2606
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2616
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2641
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2586
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2621
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2619
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2617
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2637
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2638
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2624
@ use_scale_shift
Use scale and shift parameters.
@ none
Use no normalization flags.
@ fuse_norm_relu
Fuse normalization with ReLU.
@ use_global_stats
Use global statistics.
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:1096
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:1086
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:1092
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:1094
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:1079
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:1090
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:1082
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:1098
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:1088
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.
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.
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_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.
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.
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.
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:728
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:2000
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.
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.
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:2006
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.
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_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.
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.
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.
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...
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:674
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.
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.
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
@ unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
@ bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
@ unidirectional
Alias for dnnl::rnn_direction::unidirectional_left2right.
@ bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:2002
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:2018
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:2013
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:2016
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:2008
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:2010
@ undef
Undefined RNN flags.
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10923
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:10882
status set_cpu_isa_hints(cpu_isa_hints isa_hints)
Sets the hints flag for the CPU ISA.
Definition: dnnl.hpp:10942
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2733
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:10872
cpu_isa get_effective_cpu_isa()
Gets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10929
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.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:10892
const dnnl_version_t DNNL_API * dnnl_version(void)
Returns library version information.
status
Status values returned by the library functions.
Definition: dnnl.hpp:10854
cpu_isa_hints get_cpu_isa_hints()
Gets the ISA specific hints that library can follow.
Definition: dnnl.hpp:10948
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:10887
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:10877
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:10897
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 DNNL_API dnnl_set_cpu_isa_hints(dnnl_cpu_isa_hints_t isa_hints)
Sets the hints flag for the CPU ISA.
dnnl_cpu_isa_hints_t DNNL_API dnnl_get_cpu_isa_hints(void)
Gets the ISA specific hints that library can follow.
dnnl_cpu_isa_hints_t
CPU ISA hints flags.
Definition: dnnl_types.h:2779
cpu_isa_hints
CPU ISA hints flags.
Definition: dnnl.hpp:10934
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
@ 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:2748
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2741
@ 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:2771
@ 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:2761
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2744
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2735
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2756
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2738
@ dnnl_cpu_isa_avx2_vnni
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
Definition: dnnl_types.h:2774
@ 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:2766
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2752
@ not_required
Queried element is not required for given primitive.
@ invalid_arguments
The operation failed because of incorrect function arguments.
@ success
The operation was successful.
@ unimplemented
The operation failed because requested functionality is not implemented.
@ runtime_error
Primitive or engine failed on execution.
@ out_of_memory
The operation failed due to an out-of-memory condition.
@ iterator_ends
Primitive iterator passed over last primitive descriptor.
@ avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
@ avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
@ avx2_vnni
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
@ avx
Intel Advanced Vector Extensions (Intel AVX)
@ all
Any ISA (excepting those listed as initial support)
@ avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
@ avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
@ sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
@ avx512_core_vnni
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
@ avx512_core_amx
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
@ avx512_core_bf16
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
@ dnnl_cpu_isa_no_hints
No hints (use default features)
Definition: dnnl_types.h:2781
@ dnnl_cpu_isa_prefer_ymm
Prefer to exclusively use Ymm registers for computations.
Definition: dnnl_types.h:2784
@ no_hints
No hints (use default features)
@ prefer_ymm
Prefer to exclusively use Ymm registers for computations.
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.
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.
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.
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_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2655
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_stream_get_engine(const_dnnl_stream_t stream, dnnl_engine_t *engine)
Returns the engine of a stream object.
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
dnnl_status_t DNNL_API dnnl_stream_create(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags)
Creates an execution stream.
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2659
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2661
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.
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
oneDNN namespace
Definition: dnnl.hpp:74
oneAPI namespace
Definition: dnnl.hpp:11046
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6670
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:6685
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6699
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:6716
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6759
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:6749
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6784
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6765
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6779
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:6736
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6762
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6756
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6768
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6771
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6776
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6668
batch_normalization_backward()=default
Default constructor. Produces an empty object.
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6793
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6541
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:6558
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6571
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6619
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6625
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6632
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:6585
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:6601
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6628
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6636
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:6612
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6622
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6539
batch_normalization_forward()=default
Default constructor. Produces an empty object.
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6664
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9819
desc()=default
Default constructor. Produces an empty object.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:9821
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:9833
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9844
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:9872
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9885
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9888
primitive_desc()=default
Default constructor. Produces an empty object.
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:9881
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9894
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9891
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:9857
Elementwise binary operator primitive.
Definition: dnnl.hpp:9817
binary()=default
Default constructor. Produces an empty object.
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9903
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3760
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3829
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:3822
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:3776
primitive_desc()=default
Default constructor. Produces an empty object.
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:3803
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3826
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3758
concat()=default
Default constructor. Produces an empty object.
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3837
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4301
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:4372
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:4329
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4393
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4451
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4454
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:4443
primitive_desc()=default
Default constructor. Produces an empty object.
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:4410
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4448
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:4430
Convolution backward propagation primitive.
Definition: dnnl.hpp:4298
convolution_backward_data()=default
Default constructor. Produces an empty object.
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:4463
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4469
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:4542
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:4587
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:4634
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:4499
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4655
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4722
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4711
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:4690
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:4703
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4708
primitive_desc()=default
Default constructor. Produces an empty object.
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:4671
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4716
Convolution weights gradient primitive.
Definition: dnnl.hpp:4467
convolution_backward_weights()=default
Default constructor. Produces an empty object.
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4733
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:4028
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:4156
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:4107
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:4205
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:4061
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:4226
primitive_desc()=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 convolution forward propagation primitive.
Definition: dnnl.hpp:4240
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:4256
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4273
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:4267
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4285
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4276
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4279
Convolution forward propagation primitive.
Definition: dnnl.hpp:4026
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:4294
convolution_forward()=default
Default constructor. Produces an empty object.
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:5014
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:5083
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:5041
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:5104
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:5141
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:5162
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5165
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5159
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:5121
primitive_desc()=default
Default constructor. Produces an empty object.
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:5154
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:5012
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:5174
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5180
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:5341
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:5295
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:5251
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:5209
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5362
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5417
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5425
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:5412
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:5399
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:5379
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:5420
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:5428
primitive_desc()=default
Default constructor. Produces an empty object.
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:5178
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5439
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4749
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:4874
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:4826
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:4781
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:4922
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4943
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:4984
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4996
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4990
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:4973
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:4957
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4999
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4993
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4747
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:5008
deconvolution_forward()=default
Default constructor. Produces an empty object.
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:6008
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:6022
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:6035
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6093
primitive_desc()=default
Default constructor. Produces an empty object.
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:6052
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:6072
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6090
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6096
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:6085
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:6006
eltwise_backward()=default
Default constructor. Produces an empty object.
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:6105
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5915
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:5930
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5943
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:5973
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5993
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5990
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:5957
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:5984
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5913
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:6002
eltwise_forward()=default
Default constructor. Produces an empty object.
An execution engine.
Definition: dnnl.hpp:885
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:954
kind
Kinds of engines.
Definition: dnnl.hpp:890
@ any
An unspecified engine.
engine(kind akind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:918
engine()=default
Constructs an empty engine.
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:909
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:930
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:941
oneDNN exception class.
Definition: dnnl.hpp:84
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:92
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
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:96
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9066
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:9113
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9147
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:9163
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9249
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9221
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9208
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9205
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9254
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9213
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9218
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:9264
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9259
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:9195
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9200
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9229
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:9182
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9234
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9239
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9244
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9226
GRU backward propagation primitive.
Definition: dnnl.hpp:9064
gru_backward()=default
Default constructor. Produces an empty object.
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:9275
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8917
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:8952
Primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8975
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:8988
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9033
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9020
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9041
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9028
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9038
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9046
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9049
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9025
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:9014
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:9003
GRU forward propagation primitive.
Definition: dnnl.hpp:8915
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:9060
gru_forward()=default
Default constructor. Produces an empty object.
A class that provides the destructor for a oneDNN C API handle.
Definition: dnnl.hpp:120
oneDNN C API handle wrapper class.
Definition: dnnl.hpp:136
handle(const handle< T, traits > &)=default
Copy constructor.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:210
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:220
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:185
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
handle()=default
Constructs an empty handle object.
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:176
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:169
handle(handle< T, traits > &&)=default
Move constructor.
handle< T, traits > & operator=(handle< T, traits > &&)=default
Move assignment operator.
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7257
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:7270
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7283
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7344
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:7300
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7341
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:7333
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:7320
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7338
primitive_desc()=default
Default constructor. Produces an empty object.
Inner product backward propagation primitive.
Definition: dnnl.hpp:7255
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:7353
inner_product_backward_data()=default
Default constructor. Produces an empty object.
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7359
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:7373
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:7395
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7408
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7463
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7466
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7471
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:7458
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:7445
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:7474
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:7425
Inner product weights gradient primitive.
Definition: dnnl.hpp:7357
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7485
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:7132
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:7173
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:7149
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:7186
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:7227
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:7239
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:7200
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7236
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:7242
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7233
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:7216
Inner product forward propagation primitive.
Definition: dnnl.hpp:7130
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:7251
inner_product_forward()=default
Default constructor. Produces an empty object.
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6968
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:7008
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:6984
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:7022
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7088
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:7099
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7107
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:7072
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7091
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:7085
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:7102
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7082
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:7059
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7094
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:7039
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7079
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6966
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:7116
layer_normalization_backward()=default
Default constructor. Produces an empty object.
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6823
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:6837
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:6858
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6871
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:6885
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6922
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6919
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6928
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:6912
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6934
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:6901
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6925
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6931
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6821
layer_normalization_forward()=default
Default constructor. Produces an empty object.
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6962
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9433
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:9481
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9515
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9578
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9614
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:9532
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:9634
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9624
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:9552
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9596
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9583
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9575
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9609
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:9565
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9599
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9588
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9591
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9570
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9619
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9629
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9604
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9431
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9645
lbr_gru_backward()=default
Default constructor. Produces an empty object.
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9281
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:9317
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9340
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9413
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9392
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:9370
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9408
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9416
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:9381
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:9354
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9405
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9387
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9400
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9395
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9279
lbr_gru_forward()=default
Default constructor. Produces an empty object.
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9427
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6415
desc()=default
Default constructor. Produces an empty object.
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:6428
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6439
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6498
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6504
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6501
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:6489
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:6476
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:6456
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6413
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6513
logsoftmax_backward()=default
Default constructor. Produces an empty object.
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6321
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:6335
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6346
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6400
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6397
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:6376
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:6387
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:6360
primitive_desc()=default
Default constructor. Produces an empty object.
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6319
logsoftmax_forward()=default
Default constructor. Produces an empty object.
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6409
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5551
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:5566
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5579
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:5614
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:5627
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5635
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:5595
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5638
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5632
primitive_desc()=default
Default constructor. Produces an empty object.
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5549
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5647
lrn_backward()=default
Default constructor. Produces an empty object.
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5456
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:5472
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5485
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5530
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5533
primitive_desc()=default
Default constructor. Produces an empty object.
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:5513
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5536
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:5498
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:5524
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:5454
lrn_forward()=default
Default constructor. Produces an empty object.
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5545
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8413
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:8491
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:8702
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:8603
Primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8743
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8814
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8895
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8880
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8819
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:8791
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8875
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8840
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8796
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8837
primitive_desc()=default
Default constructor. Produces an empty object.
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:8759
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8850
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8801
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8870
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8824
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8885
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:8778
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8829
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8804
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8832
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8900
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8855
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8890
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8809
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8865
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8845
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:8860
LSTM backward propagation primitive.
Definition: dnnl.hpp:8411
lstm_backward()=default
Default constructor. Produces an empty object.
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8911
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8096
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:8276
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:8147
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:8215
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8302
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8388
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8370
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8365
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8383
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8396
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:8315
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:8341
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8391
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8360
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8375
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8355
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:8330
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8352
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8380
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8347
LSTM forward propagation primitive.
Definition: dnnl.hpp:8094
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:8407
lstm_forward()=default
Default constructor. Produces an empty object.
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9921
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:9929
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:9943
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9953
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:9979
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:9995
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:9988
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:10000
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9992
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10005
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9965
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9919
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:10013
matmul()=default
Default constructor. Produces an empty object.
A memory descriptor.
Definition: dnnl.hpp:2049
desc(const dims &adims, data_type adata_type, format_tag aformat_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:2073
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:2056
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:2284
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:2235
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:2131
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:2276
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:2270
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:2257
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:2249
desc reshape(const dims &adims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:2187
desc(const dims &adims, data_type adata_type, const dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:2101
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:2265
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:2118
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:2052
Memory object.
Definition: dnnl.hpp:1124
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:2450
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:2433
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:1140
memory()=default
Default constructor.
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1128
memory(const desc &md, const engine &aengine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:2317
void set_data_handle(void *handle, const stream &astream) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2389
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2354
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1227
data_type
Data type specification.
Definition: dnnl.hpp:1146
@ undef
Undefined data type (used for empty memory descriptors).
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2343
format_kind
Memory format kind.
Definition: dnnl.hpp:1171
memory(const desc &md, const engine &aengine)
Constructs a memory object.
Definition: dnnl.hpp:2331
void set_data_handle(void *handle) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2405
static size_t data_type_size(data_type adata_type)
Returns size of data type in bytes.
Definition: dnnl.hpp:1166
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2335
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1131
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5775
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:5799
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5818
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:5834
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5874
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5877
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:5853
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5871
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:5866
Pooling backward propagation primitive.
Definition: dnnl.hpp:5773
pooling_backward()=default
Default constructor. Produces an empty object.
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5886
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5663
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:5690
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5709
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:5737
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5757
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5754
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:5748
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5760
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:5722
Pooling forward propagation primitive.
Definition: dnnl.hpp:5661
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5769
pooling_forward()=default
Default constructor. Produces an empty object.
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:10420
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:10446
Primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10467
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10526
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10523
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive f...
Definition: dnnl.hpp:10518
primitive_desc()=default
Default constructor. Produces an empty object.
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:10484
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:10504
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10529
Pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10418
pooling_v2_backward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10539
pooling_v2_backward()=default
Default constructor. Produces an empty object.
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:10299
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:10328
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:10350
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10404
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10401
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10398
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:10380
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive fr...
Definition: dnnl.hpp:10392
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:10364
Pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10297
pooling_v2_forward()=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:10414
Post-ops.
Definition: dnnl.hpp:2515
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:2691
void get_params_binary(int index, algorithm &aalgorithm, memory::desc &src1_desc) const
Returns the parameters of a binary post-op.
Definition: dnnl.hpp:2827
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:2592
void append_eltwise(float scale, algorithm aalgorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2614
void append_binary(algorithm aalgorithm, const memory::desc &src1_desc)
Appends a binary post-op.
Definition: dnnl.hpp:2816
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:2665
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:2532
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2527
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:2750
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2519
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:2776
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:2628
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2582
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:2567
Descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10643
desc(const memory::desc &data_desc, const memory::desc &weight_desc, const memory::desc &diff_data_desc, const memory::desc &diff_weights_desc)
Constructs a descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10654
Primitive descriptor for prelu backward propagation.
Definition: dnnl.hpp:10667
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10722
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:10725
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const prelu_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10704
primitive_desc(const desc &adesc, const engine &aengine, const prelu_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10684
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10728
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a prelu backward propagation primitive from a C API primitive d...
Definition: dnnl.hpp:10717
primitive_desc()=default
Default constructor. Produces an empty object.
PReLU backward propagation primitive.
Definition: dnnl.hpp:10641
prelu_backward()=default
Default constructor. Produces an empty object.
prelu_backward(const primitive_desc &pd)
Constructs a prelu backward propagation primitive.
Definition: dnnl.hpp:10737
Descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10556
desc(prop_kind aprop_kind, const memory::desc &data_desc, const memory::desc &weight_desc)
Constructs a descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10567
Primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10578
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10628
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10625
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10592
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10608
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a prelu forward propagation primitive from a C API primitive de...
Definition: dnnl.hpp:10619
PReLU forward propagation primitive.
Definition: dnnl.hpp:10554
prelu_forward(const primitive_desc &pd)
Constructs a prelu forward propagation primitive.
Definition: dnnl.hpp:10637
prelu_forward()=default
Default constructor. Produces an empty object.
Primitive attributes.
Definition: dnnl.hpp:2851
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:3018
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:3064
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:3119
void get_rnn_weights_qparams(int &mask, std::vector< float > &scales)
Returns the quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3197
void get_rnn_data_qparams(float &scale, float &shift)
Returns the quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:3135
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2953
void get_rnn_weights_projection_qparams(int &mask, std::vector< float > &scales)
Returns the quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3266
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:3171
void set_rnn_weights_projection_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3238
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2882
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:3001
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:2971
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2897
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2867
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:3081
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2855
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:3053
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2871
Base class for all primitive descriptors.
Definition: dnnl.hpp:3290
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:3474
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3400
primitive_desc_base()=default
Default constructor. Produces an empty object.
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:3298
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:3335
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3364
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3391
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:3456
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:3498
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:3486
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3435
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3382
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3423
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind prop_kind1, dnnl::prop_kind prop_kind2)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3550
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3518
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3429
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3373
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:3314
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:3447
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:3462
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3417
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:3302
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3355
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3411
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind aprop_kind)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3533
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3441
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3944
primitive_desc(const_dnnl_op_desc_t desc, const primitive_attr *attr, const engine &aengine, const_dnnl_primitive_desc_t hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor.
Definition: dnnl.hpp:3971
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3989
Base class for all computational primitives.
Definition: dnnl.hpp:269
void execute(const stream &astream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
primitive()=default
Default constructor. Constructs an empty object.
primitive(const primitive_desc &pd)
Constructs a primitive from a primitive descriptor.
kind
Kinds of primitives supported by the library.
Definition: dnnl.hpp:271
@ deconvolution
A deconvolution primitive.
@ pooling_v2
A pooling version 2 primitive.
@ inner_product
An inner product primitive.
@ logsoftmax
A logsoftmax primitive.
@ layer_normalization
A layer normalization primitive.
@ pooling
A pooling primitive.
@ resampling
A resampling primitive.
@ shuffle
A shuffle primitive.
@ batch_normalization
A batch normalization primitive.
@ prelu
A PReLU primitive.
@ eltwise
An element-wise primitive.
@ convolution
A convolution primitive.
@ softmax
A softmax primitive.
@ undef
Undefined primitive.
primitive(const_dnnl_primitive_desc_t c_pd)
Constructs a primitive from a C API primitive descriptor.
Descriptor for reduction.
Definition: dnnl.hpp:10754
desc()=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:10777
Primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10787
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10826
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10829
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:10822
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:10813
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10799
Reduction.
Definition: dnnl.hpp:10752
reduction(const primitive_desc &pd)
Constructs a reduction primitive.
Definition: dnnl.hpp:10837
reduction()=default
Default constructor. Produces an empty object.
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3614
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3699
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:3637
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:3663
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3688
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:3683
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3694
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3702
Reorder primitive.
Definition: dnnl.hpp:3612
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3710
void execute(const stream &astream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3731
reorder()=default
Default constructor. Produces an empty object.
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:3719
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:10175
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:10186
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:10203
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:10216
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:10266
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:10271
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:10233
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10274
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:10253
Resampling backward propagation primitive.
Definition: dnnl.hpp:10173
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:10283
resampling_backward()=default
Default constructor. Produces an empty object.
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:10031
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:10049
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:10069
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:10096
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:10110
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:10124
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10160
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10157
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:10151
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:10140
primitive_desc()=default
Default constructor. Produces an empty object.
Resampling forward propagation.
Definition: dnnl.hpp:10029
resampling_forward()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:10169
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7499
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7584
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7550
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7610
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7538
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7544
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7598
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7658
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7616
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7652
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7604
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:7512
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7638
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7570
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7629
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7532
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7526
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7564
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7556
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7518
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7644
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7578
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:7622
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7590
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9736
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9746
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9755
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:9786
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9791
primitive_desc()=default
Default constructor. Produces an empty object.
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:9773
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9794
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9733
shuffle_backward()=default
Default constructor. Produces an empty object.
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9803
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9661
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:9673
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9684
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9720
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9717
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:9711
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:9699
primitive_desc()=default
Default constructor. Produces an empty object.
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9659
shuffle_forward()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9729
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:6211
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:6224
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:6235
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:6285
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:6272
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6296
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6293
primitive_desc()=default
Default constructor. Produces an empty object.
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:6252
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6290
Softmax backward propagation primitive.
Definition: dnnl.hpp:6209
softmax_backward()=default
Default constructor. Produces an empty object.
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:6305
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:6121
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:6135
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:6146
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6193
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:6160
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6196
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:6187
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:6176
primitive_desc()=default
Default constructor. Produces an empty object.
Softmax forward propagation primitive.
Definition: dnnl.hpp:6119
softmax_forward()=default
Default constructor. Produces an empty object.
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:6205
An execution stream.
Definition: dnnl.hpp:1001
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:1032
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1041
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:1023
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:1005
@ out_of_order
Out-of-order execution.
@ default_flags
Default stream configuration.
@ in_order
In-order execution.
stream()=default
Constructs an empty stream.
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3853
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3926
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:3923
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:3867
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:3897
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:3919
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3851
sum()=default
Default constructor. Produces an empty object.
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3934
Descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7869
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:7924
Primitive descriptor for an RNN backward propagation primitive.
Definition: dnnl.hpp:7960
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:7997
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8020
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8074
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8036
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8054
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8064
primitive_desc()=default
Default constructor. Produces an empty object.
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:7977
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8069
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8028
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:8010
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8023
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8033
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8041
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8079
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8049
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8015
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8059
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8044
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7867
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:8090
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7708
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:7751
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7776
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:7790
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:7817
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7823
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7828
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7836
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7831
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7852
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7849
primitive_desc()=default
Default constructor. Produces an empty object.
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:7806
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7844
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7841
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7706
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7863
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1896
A descriptor of a binary operation.
Definition: dnnl_types.h:2104
A descriptor of a convolution operation.
Definition: dnnl_types.h:1600
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1675
An opaque structure to describe an engine.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1966
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1929
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1865
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:2130
Memory descriptor.
Definition: dnnl_types.h:1511
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1531
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1528
int ndims
Number of dimensions.
Definition: dnnl_types.h:1513
An opaque structure to describe a memory.
A descriptor of a pooling operation.
Definition: dnnl_types.h:1765
A descriptor of a pooling operation.
Definition: dnnl_types.h:1803
An opaque structure for a chain of post operations.
An opaque structure for primitive descriptor attributes.
An opaque structure to describe a primitive descriptor iterator.
An opaque structure to describe a primitive descriptor.
An opaque structure to describe a primitive.
A descriptor of reduction operation.
Definition: dnnl_types.h:2180
A descriptor of resampling operation.
Definition: dnnl_types.h:2152
A descriptor for an RNN operation.
Definition: dnnl_types.h:2022
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1653
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1735
An opaque structure to describe an execution stream.
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2703