oneAPI Deep Neural Network Library (oneDNN)
1.6.4
Performance library for Deep Learning
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23 #include "dnnl_config.h"
32 #include <unordered_map>
36 #if DNNL_CPU_THREADING_RUNTIME == DNNL_RUNTIME_THREADPOOL
37 #include "dnnl_threadpool_iface.hpp"
40 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
49 #ifndef DNNL_ENABLE_EXCEPTIONS
50 #if __cpp_exceptions || __EXCEPTIONS \
51 || (defined(_MSC_VER) && !defined(__clang__))
52 #define DNNL_ENABLE_EXCEPTIONS 1
54 #define DNNL_ENABLE_EXCEPTIONS 0
58 #if defined(__GNUC__) || defined(__clang__)
59 #define DNNL_TRAP() __builtin_trap()
60 #elif defined(__INTEL_COMPILER) || defined(_MSC_VER)
61 #define DNNL_TRAP() __debugbreak()
63 #error "unknown compiler"
66 #if DNNL_ENABLE_EXCEPTIONS
67 #define DNNL_THROW_ERROR(status, msg) throw error(status, msg)
70 #define DNNL_THROW_ERROR(status, msg) \
91 struct error :
public std::exception {
103 const char *
what() const noexcept
override {
return message; }
116 template <
typename T>
117 void validate_container_size(
const T &v,
const char *error_message,
118 int min_size = 1,
int max_size = -1) {
119 const int size = (int)v.size();
120 if (size < min_size || (max_size >= 0 && size > max_size))
126 template <
typename T>
142 template <
typename T,
typename traits = handle_traits<T>>
146 std::shared_ptr<typename std::remove_pointer<T>::type> data_ {0};
149 bool operator==(
const T other)
const {
return other == data_.get(); }
150 bool operator!=(
const T other)
const {
return !(*
this == other); }
183 void reset(T t,
bool weak =
false) {
184 data_.reset(t, weak ? &dummy_destructor : traits::destructor);
192 T
get(
bool allow_empty =
false)
const {
193 T result = data_.get();
194 if (allow_empty ==
false && result ==
nullptr)
204 explicit operator T()
const {
return get(
true); }
209 explicit operator bool()
const {
return get(
true) !=
nullptr; }
218 return other.data_.get() == data_.get();
264 struct primitive_desc;
358 const std::unordered_map<int, memory> &args)
const;
372 "could not get a primitive descriptor from a primitive");
383 "could not get a primitive kind from a primitive descriptor");
473 undef = dnnl_alg_kind_undef,
643 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
644 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
645 return static_cast<enum_name>( \
646 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
649 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
650 return static_cast<enum_name>( \
651 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
654 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
655 return static_cast<enum_name>( \
656 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
659 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
660 lhs = static_cast<enum_name>( \
661 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
665 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
666 lhs = static_cast<enum_name>( \
667 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
671 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
672 lhs = static_cast<enum_name>( \
673 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
677 inline enum_name operator~(enum_name rhs) { \
678 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
877 "could not create an engine");
881 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
882 engine(
kind akind, cl_device_id device, cl_context context) {
892 "could not create an engine");
906 "could not get an engine from a primitive_desc");
907 reset(c_engine,
true);
915 "could not get kind of an engine");
919 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
923 cl_context context =
nullptr;
925 "could not get an OpenCL context from an engine");
932 cl_device_id device =
nullptr;
934 "could not get an OpenCL device from an engine");
944 template <
typename primitive_desc>
954 template <
typename primitive_desc>
959 "could not get an engine from a primitive_desc");
960 return engine(c_engine,
true);
1011 "could not create stream attributes");
1015 #if DNNL_CPU_THREADING_RUNTIME == DNNL_RUNTIME_THREADPOOL
1025 "could not set stream threadpool attribute");
1036 "could not set stream threadpool attribute");
1075 "could not create a stream");
1079 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1080 stream(
const engine &aengine, cl_command_queue queue) {
1087 "could not create a stream");
1094 cl_command_queue queue =
nullptr;
1096 "could not get an OpenCL command queue from a stream");
1197 template <
typename T>
1199 validate_container_size(
1489 Abc16a = dnnl_Abc16a,
1490 ABc16a16b = dnnl_ABc16a16b,
1491 ABc4a4b = dnnl_ABc4a4b,
1494 ABc16b16a = dnnl_ABc16b16a,
1497 ABc4b16a4b = dnnl_ABc4b16a4b,
1498 ABc2b8a4b = dnnl_ABc2b8a4b,
1499 ABc16b16a4b = dnnl_ABc16b16a4b,
1500 ABc16b16a2b = dnnl_ABc16b16a2b,
1501 ABc4b4a = dnnl_ABc4b4a,
1502 ABc8a16b2a = dnnl_ABc8a16b2a,
1503 ABc8a8b = dnnl_ABc8a8b,
1504 ABc8a4b = dnnl_ABc8a4b,
1506 ABc8b16a2b = dnnl_ABc8b16a2b,
1507 ABc8b8a = dnnl_ABc8b8a,
1508 Abcd8a = dnnl_Abcd8a,
1509 Abcd16a = dnnl_Abcd16a,
1510 Abcd32a = dnnl_Abcd32a,
1511 ABcd16a16b = dnnl_ABcd16a16b,
1514 ABcd16b16a = dnnl_ABcd16b16a,
1515 aBCd16b16c = dnnl_aBCd16b16c,
1516 aBCd16c16b = dnnl_aBCd16c16b,
1517 Abcd4a = dnnl_Abcd4a,
1519 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1520 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1521 ABcd4b4a = dnnl_ABcd4b4a,
1522 ABcd4a4b = dnnl_ABcd4a4b,
1523 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1524 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1525 ABcd16b16a4b = dnnl_ABcd16b16a4b,
1526 ABcd16b16a2b = dnnl_ABcd16b16a2b,
1527 aBCd16c16b4c = dnnl_aBCd16c16b4c,
1528 aBCd16c16b2c = dnnl_aBCd16c16b2c,
1529 aBCd4c4b = dnnl_aBCd4c4b,
1530 aBCd4b4c = dnnl_aBCd4b4c,
1531 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1532 ABcd8a8b = dnnl_ABcd8a8b,
1533 ABcd8a4b = dnnl_ABcd8a4b,
1536 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1537 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1540 aBCd8b8c = dnnl_aBCd8b8c,
1541 aBCd8b4c = dnnl_aBCd8b4c,
1542 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1543 aBCd8c8b = dnnl_aBCd8c8b,
1544 Abcde16a = dnnl_Abcde16a,
1545 Abcde32a = dnnl_Abcde32a,
1546 ABcde16a16b = dnnl_ABcde16a16b,
1549 ABcde16b16a = dnnl_ABcde16b16a,
1550 aBCde16b16c = dnnl_aBCde16b16c,
1551 aBCde16c16b = dnnl_aBCde16c16b,
1552 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1553 Abcde4a = dnnl_Abcde4a,
1555 ABcde4b4a = dnnl_ABcde4b4a,
1556 ABcde4a4b = dnnl_ABcde4a4b,
1557 aBCde4b4c = dnnl_aBCde4b4c,
1558 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1559 aBCde16c16b4c = dnnl_aBCde16c16b4c,
1560 aBCde16c16b2c = dnnl_aBCde16c16b2c,
1561 aBCde4c4b = dnnl_aBCde4c4b,
1562 Abcde8a = dnnl_Abcde8a,
1563 ABcde8a8b = dnnl_ABcde8a8b,
1564 ABcde8a4b = dnnl_ABcde8a4b,
1566 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1569 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1570 ABcde8b8a = dnnl_ABcde8b8a,
1571 aBCde8b8c = dnnl_aBCde8b8c,
1572 aBCde8b4c = dnnl_aBCde8b4c,
1573 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1574 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1575 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1576 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1577 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1578 aBCde8c8b = dnnl_aBCde8c8b,
1580 aBCdef16b16c = dnnl_aBCdef16b16c,
1581 aBCdef16c16b = dnnl_aBCdef16c16b,
1584 aBCdef4c4b = dnnl_aBCdef4c4b,
1585 aBCdef4b4c = dnnl_aBCdef4b4c,
1586 aBCdef8b8c = dnnl_aBCdef8b8c,
1587 aBCdef8b4c = dnnl_aBCdef8b4c,
1588 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1589 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1590 aBCdef8c8b = dnnl_aBCdef8c8b,
1591 aBdc16b = dnnl_aBdc16b,
1592 aBdc4b = dnnl_aBdc4b,
1593 aBdc8b = dnnl_aBdc8b,
1594 aBdec16b = dnnl_aBdec16b,
1595 aBdec4b = dnnl_aBdec4b,
1596 aBdec8b = dnnl_aBdec8b,
1597 aBdefc16b = dnnl_aBdefc16b,
1598 aCBdef16c16b = dnnl_aCBdef16c16b,
1599 aCBdef16b16c = dnnl_aCBdef16b16c,
1600 aBdefc4b = dnnl_aBdefc4b,
1601 aBdefc8b = dnnl_aBdefc8b,
1602 Acb16a = dnnl_Acb16a,
1605 aCBd16b16c = dnnl_aCBd16b16c,
1606 aCBd16c16b = dnnl_aCBd16c16b,
1607 aCBde16b16c = dnnl_aCBde16b16c,
1608 aCBde16c16b = dnnl_aCBde16c16b,
1609 Acdb16a = dnnl_Acdb16a,
1610 Acdb4a = dnnl_Acdb4a,
1611 Acdb8a = dnnl_Acdb8a,
1612 Acdeb16a = dnnl_Acdeb16a,
1613 Acdeb4a = dnnl_Acdeb4a,
1614 Acdeb8a = dnnl_Acdeb8a,
1615 BAc16a16b = dnnl_BAc16a16b,
1616 BAc16b16a = dnnl_BAc16b16a,
1617 BAcd16a16b = dnnl_BAcd16a16b,
1618 BAcd16b16a = dnnl_BAcd16b16a,
1619 ABcd32a32b = dnnl_ABcd32a32b,
1620 BAcde16b16a = dnnl_BAcde16b16a,
1621 BAcde16a16b = dnnl_BAcde16a16b,
1622 aBdec32b = dnnl_aBdec32b,
1623 Abcdef16a = dnnl_Abcdef16a,
1624 Abcdef32a = dnnl_Abcdef32a,
1625 Acdb32a = dnnl_Acdb32a,
1629 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1630 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1631 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1632 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1633 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1634 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1635 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1636 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1637 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1650 NCw16n16c = dnnl_NCw16n16c,
1651 NChw16n16c = dnnl_NChw16n16c,
1652 NCdhw16n16c = dnnl_NCdhw16n16c,
1653 NCdhw32n32c = dnnl_NCdhw32n32c,
1654 NChw32n32c = dnnl_NChw32n32c,
1655 IOhw16i16o = dnnl_IOhw16i16o,
1656 Ohwi32o = dnnl_Ohwi32o,
1657 IOdhw16i16o = dnnl_IOdhw16i16o,
1658 gIOhw16i16o = dnnl_gIOhw16i16o,
1659 gOhwi32o = dnnl_gOhwi32o,
1660 Goidhw16g = dnnl_Goidhw16g,
1661 IOw16o16i = dnnl_IOw16o16i,
1662 OIw16i16o = dnnl_OIw16i16o,
1663 IOw16i16o = dnnl_IOw16i16o,
1664 gIOw16i16o = dnnl_gIOw16i16o,
1665 OIw16o16i = dnnl_OIw16o16i,
1666 Oiw16o = dnnl_Oiw16o,
1667 OIw4i16o4i = dnnl_OIw4i16o4i,
1668 OIw2i8o4i = dnnl_OIw2i8o4i,
1669 OIw4i4o = dnnl_OIw4i4o,
1670 OIw4o4i = dnnl_OIw4o4i,
1672 OIw8i16o2i = dnnl_OIw8i16o2i,
1673 OIw8i8o = dnnl_OIw8i8o,
1674 OIw8o16i2o = dnnl_OIw8o16i2o,
1675 OIw8o8i = dnnl_OIw8o8i,
1676 OIw8o4i = dnnl_OIw8o4i,
1677 Owi16o = dnnl_Owi16o,
1678 OwI16o2i = dnnl_OwI16o2i,
1681 IOhw16o16i = dnnl_IOhw16o16i,
1682 Ohwi16o = dnnl_Ohwi16o,
1683 OhwI16o2i = dnnl_OhwI16o2i,
1684 Ohwi4o = dnnl_Ohwi4o,
1685 Ohwi8o = dnnl_Ohwi8o,
1686 OIhw16i16o = dnnl_OIhw16i16o,
1687 OIhw16o16i = dnnl_OIhw16o16i,
1688 Oihw16o = dnnl_Oihw16o,
1689 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1690 OIhw4i4o = dnnl_OIhw4i4o,
1691 OIhw4o4i = dnnl_OIhw4o4i,
1692 Oihw4o = dnnl_Oihw4o,
1693 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1694 OIhw8i8o = dnnl_OIhw8i8o,
1695 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1696 OIhw8o8i = dnnl_OIhw8o8i,
1697 OIhw8o4i = dnnl_OIhw8o4i,
1698 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1699 IOdhw16o16i = dnnl_IOdhw16o16i,
1700 Odhwi16o = dnnl_Odhwi16o,
1701 OdhwI16o2i = dnnl_OdhwI16o2i,
1702 Odhwi4o = dnnl_Odhwi4o,
1703 Odhwi8o = dnnl_Odhwi8o,
1704 OIdhw16i16o = dnnl_OIdhw16i16o,
1705 OIdhw16o16i = dnnl_OIdhw16o16i,
1706 Oidhw16o = dnnl_Oidhw16o,
1707 OIdhw4i4o = dnnl_OIdhw4i4o,
1708 OIdhw4o4i = dnnl_OIdhw4o4i,
1709 Oidhw4o = dnnl_Oidhw4o,
1710 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1711 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1712 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1713 OIdhw8i8o = dnnl_OIdhw8i8o,
1714 OIdhw8o8i = dnnl_OIdhw8o8i,
1715 OIdhw8o4i = dnnl_OIdhw8o4i,
1716 gIOw16o16i = dnnl_gIOw16o16i,
1717 gOIw16i16o = dnnl_gOIw16i16o,
1718 gOIw16o16i = dnnl_gOIw16o16i,
1719 gOiw16o = dnnl_gOiw16o,
1720 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1721 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1722 gOIw4i4o = dnnl_gOIw4i4o,
1723 gOIw4o4i = dnnl_gOIw4o4i,
1724 gOiw4o = dnnl_gOiw4o,
1725 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1726 gOIw8i8o = dnnl_gOIw8i8o,
1727 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1728 gOIw8o8i = dnnl_gOIw8o8i,
1729 gOIw8o4i = dnnl_gOIw8o4i,
1730 gOwi16o = dnnl_gOwi16o,
1731 gOwI16o2i = dnnl_gOwI16o2i,
1732 gOwi4o = dnnl_gOwi4o,
1733 gOwi8o = dnnl_gOwi8o,
1734 Goiw8g = dnnl_Goiw8g,
1735 Goiw16g = dnnl_Goiw16g,
1736 gIOhw16o16i = dnnl_gIOhw16o16i,
1737 gOhwi16o = dnnl_gOhwi16o,
1738 gOhwI16o2i = dnnl_gOhwI16o2i,
1739 gOhwi4o = dnnl_gOhwi4o,
1740 gOhwi8o = dnnl_gOhwi8o,
1741 Goihw16g = dnnl_Goihw16g,
1742 gOIhw16i16o = dnnl_gOIhw16i16o,
1743 gOIhw16o16i = dnnl_gOIhw16o16i,
1744 gOihw16o = dnnl_gOihw16o,
1745 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1746 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1747 gOIhw4i4o = dnnl_gOIhw4i4o,
1748 gOIhw4o4i = dnnl_gOIhw4o4i,
1749 gOihw4o = dnnl_gOihw4o,
1750 Goihw8g = dnnl_Goihw8g,
1751 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1752 gOIhw8i8o = dnnl_gOIhw8i8o,
1753 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1754 OIw4o8i8o4i = dnnl_OIw4o8i8o4i,
1755 OIdhw4o8i8o4i = dnnl_OIdhw4o8i8o4i,
1756 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1757 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1758 gOIw4o8i8o4i = dnnl_gOIw4o8i8o4i,
1759 gOIdhw4o8i8o4i = dnnl_gOIdhw4o8i8o4i,
1760 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1761 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1762 OIhw16i16o4i = dnnl_OIhw16i16o4i,
1763 OIhw16i16o2i = dnnl_OIhw16i16o2i,
1764 gOIhw16i16o4i = dnnl_gOIhw16i16o4i,
1765 gOIhw16i16o2i = dnnl_gOIhw16i16o2i,
1766 gOIhw8o8i = dnnl_gOIhw8o8i,
1767 gOIhw8o4i = dnnl_gOIhw8o4i,
1768 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1769 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1770 gOdhwi16o = dnnl_gOdhwi16o,
1771 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1772 gOdhwi4o = dnnl_gOdhwi4o,
1773 gOdhwi8o = dnnl_gOdhwi8o,
1774 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1775 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1776 gOidhw16o = dnnl_gOidhw16o,
1777 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1778 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1779 gOidhw4o = dnnl_gOidhw4o,
1780 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1781 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1782 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1783 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1784 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1785 gOIdhw8o4i = dnnl_gOIdhw8o4i,
1786 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1787 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1788 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1789 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1790 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1791 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1792 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1793 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1794 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1795 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1796 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1797 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1826 bool allow_empty =
false)
1828 validate_dims(adims);
1830 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1834 "could not construct a memory descriptor using a "
1854 bool allow_empty =
false)
1856 validate_dims(adims);
1857 if (!strides.empty()) validate_dims(strides, (
int)adims.size());
1859 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1860 strides.empty() ?
nullptr : &strides[0]);
1863 "could not construct a memory descriptor using "
1884 bool allow_empty =
false)
const {
1885 validate_dims(adims, data.
ndims);
1886 validate_dims(offsets, data.
ndims);
1889 &sub_md, &data, adims.data(), offsets.data());
1892 return desc(sub_md);
1940 if (data.
ndims) validate_dims(adims, 1);
1943 &out_md, &data, (
int)adims.size(), adims.data());
1946 status,
"could not reshape a memory descriptor");
1947 return desc(out_md);
1987 bool allow_empty =
false)
const {
1988 validate_dims(permutation, data.
ndims);
1991 &out_md, &data, permutation.data());
1994 "could not permute axes of a memory descriptor");
1995 return desc(out_md);
2040 explicit operator bool()
const {
return data.
ndims != 0; }
2073 "could not create a memory object");
2084 :
memory(md, aengine, DNNL_MEMORY_ALLOCATE) {}
2090 "could not get a memory descriptor from a memory object");
2091 return desc(*cdesc);
2098 "could not get an engine from a memory object");
2099 return engine(c_engine,
true);
2108 "could not get a native handle from a memory object");
2141 "could not set native handle of a memory object");
2155 "could not set native handle of a memory object");
2178 template <
typename T =
void>
2182 "could not map memory object data");
2183 return static_cast<T *
>(mapped_ptr);
2197 "could not unmap memory object data");
2200 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
2201 cl_mem get_ocl_mem_object()
const {
2205 "could not get OpenCL buffer object from a memory object");
2218 "could not set OpenCL buffer object from a memory object");
2301 "post-ops index is out of range");
2340 "could not append a sum post-op");
2343 memory::convert_to_c(data_type)),
2344 "could not append a sum post-op");
2353 "could not get parameters of a sum post-op");
2365 get(), index, &scale, &c_data_type),
2366 "could not get parameters of a sum post-op");
2384 float scale,
algorithm aalgorithm,
float alpha,
float beta) {
2387 "could not append an elementwise post-op");
2398 float &alpha,
float &beta)
const {
2401 get(), index, &scale, &c_alg, &alpha, &beta),
2402 "could not get parameters of an elementwise post-op");
2436 int mask,
const std::vector<float> &scales) {
2439 memory::convert_to_c(weights_data_type),
2440 memory::convert_to_c(bias_data_type),
2441 memory::convert_to_c(dst_data_type),
2442 scales.size(), mask, &scales[0]),
2443 "could not append depthwise post-op");
2462 int &mask, std::vector<float> &scales)
const {
2469 const float *c_scales;
2471 &c_weights_data_type, &c_bias_data_type,
2472 &c_dst_data_type, &count, &c_mask, &c_scales),
2473 "could not get parameters of depthwise post-op");
2478 scales.resize(count);
2482 scales[c] = c_scales[c];
2521 int mask,
const std::vector<float> &scales) {
2524 memory::convert_to_c(weights_data_type),
2525 memory::convert_to_c(bias_data_type),
2526 memory::convert_to_c(dst_data_type),
2527 scales.size(), mask, &scales[0]),
2528 "could not append depthwise post-op");
2547 int &mask, std::vector<float> &scales)
const {
2554 const float *c_scales;
2556 &c_weights_data_type, &c_bias_data_type,
2557 &c_dst_data_type, &count, &c_mask, &c_scales),
2558 "could not get parameters of depthwise post-op");
2563 scales.resize(count);
2567 scales[c] = c_scales[c];
2591 "could not create primitive attribute");
2608 "could not get scratchpad mode primitive attribute");
2618 "could not set scratchpad mode primitive attribute");
2633 const float *c_scales;
2635 get(), &count, &c_mask, &c_scales),
2636 "could not get output scales primitive attribute");
2637 scales.resize(count);
2641 scales[c] = c_scales[c];
2690 "could not set output scales primitive attribute");
2704 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2707 const float *c_scales;
2709 get(), arg, &count, &c_mask, &c_scales),
2710 "could not get scales primitive attributes");
2711 scales.resize(count);
2715 scales[c] = c_scales[c];
2734 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
2737 (
dnnl_dim_t)scales.size(), mask, scales.data()),
2738 "could not set scales primitive attribute");
2752 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
2755 const int32_t *c_zero_points;
2757 get(), arg, &count, &c_mask, &c_zero_points),
2758 "could not get zero points primitive attribute");
2759 zero_points.resize(count);
2763 zero_points[c] = c_zero_points[c];
2787 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
2790 zero_points.data()),
2791 "could not set zero points primitive attribute");
2801 "could not get post-ops primitive attribute");
2816 "could not set post-ops primitive attribute");
2855 "could not set RNN data quantization parameters primitive "
2887 (
int)scales.size(), mask, scales.data()),
2888 "could not set RNN weights quantization parameters primitive "
2915 "could not retrieve implementation info string from a "
2916 "primitive descriptor");
2945 std::vector<query> valid_q {query::src_md, query::diff_src_md,
2946 query::weights_md, query::diff_weights_md, query::dst_md,
2947 query::diff_dst_md, query::workspace_md, query::scratchpad_md,
2949 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
2950 [=](
query q) { return what == q; }))
2952 "memory descriptor query is invalid");
2965 return query_md(query::src_md, idx);
2974 return query_md(query::dst_md, idx);
2983 return query_md(query::weights_md, idx);
2992 return query_md(query::diff_src_md, idx);
3001 return query_md(query::diff_dst_md, idx);
3010 return query_md(query::diff_weights_md, idx);
3057 return query_md(query::workspace_md, 0);
3066 return query_md(query::scratchpad_md, 0);
3076 "could not retrieve scratchpad engine from a primitive "
3078 return engine(c_engine,
true);
3086 "could not get attributes from a primitive descriptor");
3089 "could not clone primitive attributes");
3099 "could not get primitive kind from a primitive descriptor");
3110 "could not clone a primitive descriptor");
3163 if (pd ==
nullptr)
return;
3176 rc,
"could not get primitive kind from a primitive descriptor");
3177 if (pd_kind != c_prim_kind)
3179 "primitive descriptor operation kind mismatch");
3189 "could not get propagation kind from the primitive "
3195 && (pd_prop_kind == c_prop_kind1
3196 || pd_prop_kind == c_prop_kind2))) {
3203 "primitive descriptor propagation kind mismatch");
3249 bool allow_empty =
false) {
3253 dst_engine.
get(), attr.get());
3256 "could not create a primitive descriptor for a reorder "
3274 bool allow_empty =
false) {
3283 "could not create a primitive descriptor for a reorder "
3298 return engine::query(*
this, dnnl::query::reorder_src_engine);
3304 return engine::query(*
this, dnnl::query::reorder_dst_engine);
3357 const std::vector<memory::desc> &mems) {
3358 std::vector<dnnl_memory_desc_t> c_mems;
3359 c_mems.reserve(mems.size());
3360 for (
const auto &s : mems)
3361 c_mems.push_back(s.data);
3386 const std::vector<memory::desc> &srcs,
const engine &aengine,
3393 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3394 attr.get(), aengine.
get()),
3395 "could not create a primitive descriptor for a concat "
3413 const std::vector<memory::desc> &srcs,
const engine &aengine,
3420 (
int)c_api_srcs.size(), concat_dimension,
3421 c_api_srcs.data(), attr.get(), aengine.
get()),
3422 "could not create a primitive descriptor for a concat "
3477 const std::vector<float> &scales,
3478 const std::vector<memory::desc> &srcs,
const engine &aengine,
3480 validate_container_size(scales,
3481 "counts of scales and sources are not equal",
3482 (
int)srcs.size(), (
int)srcs.size());
3489 (
int)c_api_srcs.size(), scales.data(),
3490 c_api_srcs.data(), attr.get(), aengine.
get()),
3491 "could not create a primitive descriptor for a sum "
3507 const std::vector<memory::desc> &srcs,
const engine &aengine,
3509 validate_container_size(scales,
3510 "counts of scales and sources are not equal",
3511 (
int)srcs.size(), (
int)srcs.size());
3517 (
int)c_api_srcs.size(), scales.data(),
3518 c_api_srcs.data(), attr.get(), aengine.
get()),
3519 "could not create a primitive descriptor for a sum "
3582 bool allow_empty =
false)
3583 : allow_empty_(allow_empty) {
3586 desc, attr ? attr->
get() :
nullptr, aengine.
get(), hint_fwd_pd);
3589 status,
"could not create a primitive descriptor iterator");
3590 pd_iterator.reset(iterator);
3603 status,
"could not advance a primitive descriptor iterator");
3609 bool allow_empty_ =
false;
3613 pd_iterator.
get(allow_empty_));
3616 "could not fetch a primitive descriptor from a primitive "
3617 "descriptor iterator");
3683 &strides[0], &padding_l[0], &padding_r[0]),
3684 "could not create a descriptor for a convolution forward "
3685 "propagation primitive");
3727 &weights_desc.
data,
nullptr, &dst_desc.
data,
3728 &strides[0], &padding_l[0], &padding_r[0]),
3729 "could not create a descriptor for a convolution forward "
3730 "propagation primitive");
3777 &weights_desc.
data, &bias_desc.
data,
3778 &dst_desc.
data, &strides[0], &dilates[0],
3779 &padding_l[0], &padding_r[0]),
3780 "could not create a descriptor for a dilated convolution "
3781 "forward propagation primitive");
3826 &weights_desc.
data,
nullptr,
3827 &dst_desc.
data, &strides[0], &dilates[0],
3828 &padding_l[0], &padding_r[0]),
3829 "could not create a descriptor for a dilated convolution "
3830 "forward propagation primitive");
3850 bool allow_empty =
false)
3852 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
3866 const engine &aengine,
bool allow_empty =
false)
3868 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
3948 &weights_desc.
data, &diff_dst_desc.
data,
3949 &strides[0], &padding_l[0], &padding_r[0]),
3950 "could not create a descriptor for a convolution backward "
3951 "propagation primitive");
3993 &weights_desc.
data, &diff_dst_desc.
data,
3994 &strides[0], &dilates[0], &padding_l[0],
3996 "could not create a descriptor for a dilated convolution "
3997 "backward propagation primitive");
4021 bool allow_empty =
false)
4023 hint_fwd_pd.
get(), allow_empty) {}
4042 bool allow_empty =
false)
4044 hint_fwd_pd.
get(), allow_empty) {}
4119 &diff_weights_desc.
data, &diff_bias_desc.
data,
4120 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4122 "could not create a descriptor for a convolution weights "
4123 "update primitive");
4160 &diff_weights_desc.
data,
nullptr,
4161 &diff_dst_desc.
data, &strides[0],
4162 &padding_l[0], &padding_r[0]),
4163 "could not create a descriptor for a convolution weights "
4164 "update primitive");
4209 &diff_weights_desc.
data, &diff_bias_desc.
data,
4210 &diff_dst_desc.
data, &strides[0], &dilates[0],
4211 &padding_l[0], &padding_r[0]),
4212 "could not create a descriptor for a dilated convolution "
4213 "weights gradient primitive");
4255 &diff_weights_desc.
data,
nullptr,
4256 &diff_dst_desc.
data, &strides[0], &dilates[0],
4257 &padding_l[0], &padding_r[0]),
4258 "could not create a descriptor for a dilated convolution "
4259 "weights gradient primitive");
4282 bool allow_empty =
false)
4284 hint_fwd_pd.
get(), allow_empty) {}
4302 bool allow_empty =
false)
4304 hint_fwd_pd.
get(), allow_empty) {}
4403 &strides[0], &padding_l[0], &padding_r[0]),
4404 "could not create a descriptor for a deconvolution forward "
4405 "propagation primitive");
4446 &weights_desc.
data,
nullptr, &dst_desc.
data,
4447 &strides[0], &padding_l[0], &padding_r[0]),
4448 "could not create a descriptor for a deconvolution forward "
4449 "propagation primitive");
4495 &weights_desc.
data, &bias_desc.
data,
4496 &dst_desc.
data, &strides[0], &dilates[0],
4497 &padding_l[0], &padding_r[0]),
4498 "could not create a descriptor for a dilated deconvolution "
4499 "forward propagation primitive");
4543 &weights_desc.
data,
nullptr,
4544 &dst_desc.
data, &strides[0], &dilates[0],
4545 &padding_l[0], &padding_r[0]),
4546 "could not create a descriptor for a dilated deconvolution "
4547 "forward propagation primitive");
4567 bool allow_empty =
false)
4569 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4583 const engine &aengine,
bool allow_empty =
false)
4585 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4660 &weights_desc.
data, &diff_dst_desc.
data,
4661 &strides[0], &padding_l[0], &padding_r[0]),
4662 "could not create a descriptor for a deconvolution "
4663 "backward propagation primitive");
4704 &weights_desc.
data, &diff_dst_desc.
data,
4705 &strides[0], &dilates[0], &padding_l[0],
4707 "could not create a descriptor for a dilated deconvolution "
4708 "backward propagation primitive");
4732 bool allow_empty =
false)
4734 hint_fwd_pd.
get(), allow_empty) {}
4753 bool allow_empty =
false)
4755 hint_fwd_pd.
get(), allow_empty) {}
4829 &diff_weights_desc.
data, &diff_bias_desc.
data,
4830 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4832 "could not create a descriptor for a deconvolution weights "
4833 "update primitive");
4869 &src_desc.
data, &diff_weights_desc.
data,
4870 nullptr, &diff_dst_desc.
data, &strides[0],
4871 &padding_l[0], &padding_r[0]),
4872 "could not create a descriptor for a deconvolution weights "
4873 "update primitive");
4917 &diff_weights_desc.
data, &diff_bias_desc.
data,
4918 &diff_dst_desc.
data, &strides[0], &dilates[0],
4919 &padding_l[0], &padding_r[0]),
4920 "could not create a descriptor for a dilated deconvolution "
4921 "weights gradient primitive");
4962 &diff_weights_desc.
data,
nullptr,
4963 &diff_dst_desc.
data, &strides[0], &dilates[0],
4964 &padding_l[0], &padding_r[0]),
4965 "could not create a descriptor for a dilated deconvolution "
4966 "weights gradient primitive");
4990 bool allow_empty =
false)
4992 hint_fwd_pd.
get(), allow_empty) {}
5011 bool allow_empty =
false)
5013 hint_fwd_pd.
get(), allow_empty) {}
5083 float alpha,
float beta,
float k = 1.f) {
5087 local_size, alpha, beta, k),
5088 "could not create a descriptor for a lrn forward "
5089 "propagation primitive");
5108 bool allow_empty =
false)
5110 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5123 const engine &aengine,
bool allow_empty =
false)
5125 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5177 float alpha,
float beta,
float k = 1.f) {
5180 &diff_data_desc.
data, &data_desc.
data, local_size,
5182 "could not create a descriptor for a lrn backward "
5183 "propagation primitive");
5206 bool allow_empty =
false)
5208 hint_fwd_pd.
get(), allow_empty) {}
5226 bool allow_empty =
false)
5228 hint_fwd_pd.
get(), allow_empty) {}
5310 &dst_desc.
data, &strides[0], &kernel[0],
5311 &padding_l[0], &padding_r[0]),
5312 "could not create a descriptor for a pooling forward "
5313 "propagation primitive");
5332 bool allow_empty =
false)
5334 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5347 const engine &aengine,
bool allow_empty =
false)
5349 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5419 &diff_dst_desc.
data, &strides[0], &kernel[0],
5420 &padding_l[0], &padding_r[0]),
5421 "could not create a descriptor for a pooling backward "
5422 "propagation primitive");
5445 bool allow_empty =
false)
5447 hint_fwd_pd.
get(), allow_empty) {}
5465 bool allow_empty =
false)
5467 hint_fwd_pd.
get(), allow_empty) {}
5545 &data_desc.
data, alpha, beta),
5546 "could not create a descriptor for an eltwise forward "
5547 "propagation primitive");
5567 bool allow_empty =
false)
5569 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5583 const engine &aengine,
bool allow_empty =
false)
5585 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5637 &diff_data_desc.
data, &data_desc.
data, alpha, beta),
5638 "could not create a descriptor for an eltwise backward "
5639 "propagation primitive");
5663 bool allow_empty =
false)
5665 hint_fwd_pd.
get(), allow_empty) {}
5684 bool allow_empty =
false)
5686 hint_fwd_pd.
get(), allow_empty) {}
5748 &data_desc.
data, softmax_axis),
5749 "could not create a descriptor for a softmax forward "
5750 "propagation primitive");
5770 bool allow_empty =
false)
5772 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5786 const engine &aengine,
bool allow_empty =
false)
5788 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5837 &data_desc.
data, softmax_axis),
5838 "could not create a descriptor for a softmax backward "
5839 "propagation primitive");
5863 bool allow_empty =
false)
5865 hint_fwd_pd.
get(), allow_empty) {}
5884 bool allow_empty =
false)
5886 hint_fwd_pd.
get(), allow_empty) {}
5945 int logsoftmax_axis) {
5948 &data_desc.
data, logsoftmax_axis),
5949 "could not create a descriptor for a logsoftmax forward "
5950 "propagation primitive");
5970 bool allow_empty =
false)
5972 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5986 const engine &aengine,
bool allow_empty =
false)
5988 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6038 int logsoftmax_axis) {
6040 &diff_data_desc.
data, &data_desc.
data,
6042 "could not create a descriptor for a logsoftmax backward "
6043 "propagation primitive");
6067 bool allow_empty =
false)
6069 hint_fwd_pd.
get(), allow_empty) {}
6088 bool allow_empty =
false)
6090 hint_fwd_pd.
get(), allow_empty) {}
6173 "could not create a descriptor for a batch normalization "
6174 "forward propagation primitive");
6195 bool allow_empty =
false)
6197 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6211 const engine &aengine,
bool allow_empty =
false)
6213 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6258 "could not retrieve a descriptor from a primitive "
6259 "descriptor for batch normalization forward propagation "
6299 &diff_data_desc.
data, &data_desc.
data,
6301 "could not create a descriptor for a batch normalization "
6302 "backward propagation primitive");
6327 bool allow_empty =
false)
6329 hint_fwd_pd.
get(), allow_empty) {}
6348 bool allow_empty =
false)
6350 hint_fwd_pd.
get(), allow_empty) {}
6453 "could not create a descriptor for a layer normalization "
6454 "forward propagation primitive");
6473 "could not create a descriptor for a layer normalization "
6474 "forward propagation primitive");
6495 bool allow_empty =
false)
6497 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6511 const engine &aengine,
bool allow_empty =
false)
6513 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6556 "could not retrieve a descriptor from a primitive "
6557 "descriptor for layer normalization forward propagation "
6599 &diff_data_desc.
data, &data_desc.
data,
6601 "could not create a descriptor for a batch normalization "
6602 "backward propagation primitive");
6622 &diff_data_desc.
data, &data_desc.
data,
6624 "could not create a descriptor for a batch normalization "
6625 "backward propagation primitive");
6650 bool allow_empty =
false)
6652 hint_fwd_pd.
get(), allow_empty) {}
6671 bool allow_empty =
false)
6673 hint_fwd_pd.
get(), allow_empty) {}
6763 &src_desc.
data, &weights_desc.
data,
6765 "could not create a descriptor for an inner product "
6766 "forward propagation primitive");
6788 &weights_desc.
data,
nullptr, &dst_desc.
data),
6789 "could not create a descriptor for an inner product "
6790 "forward propagation primitive");
6810 bool allow_empty =
false)
6812 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6826 const engine &aengine,
bool allow_empty =
false)
6828 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6883 &diff_src_desc.
data, &weights_desc.
data,
6884 &diff_dst_desc.
data),
6885 "could not create a descriptor for an inner product "
6886 "backward propagation primitive");
6911 bool allow_empty =
false)
6913 hint_fwd_pd.
get(), allow_empty) {}
6932 bool allow_empty =
false)
6934 hint_fwd_pd.
get(), allow_empty) {}
6988 &src_desc.
data, &diff_weights_desc.
data,
6989 &diff_bias_desc.
data, &diff_dst_desc.
data),
6990 "could not create a descriptor for an inner product "
6991 "weights gradient primitive");
7009 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
7010 &diff_dst_desc.
data),
7011 "could not create a descriptor for an inner product "
7012 "weights gradient primitive");
7036 bool allow_empty =
false)
7038 hint_fwd_pd.
get(), allow_empty) {}
7057 bool allow_empty =
false)
7059 hint_fwd_pd.
get(), allow_empty) {}
7109 using primitive_desc::primitive_desc;
7293 "could not retrieve a descriptor from a primitive descriptor "
7294 "for an RNN primitive");
7307 "mismatch between expected and provided descriptors for an "
7369 float beta = 0.0f) {
7375 &src_iter_desc.
data, &weights_layer_desc.
data,
7376 &weights_iter_desc.
data, &bias_desc.
data,
7377 &dst_layer_desc.
data, &dst_iter_desc.
data,
7379 "could not create a descriptor for a vanilla RNN forward "
7380 "propagation primitive");
7400 bool allow_empty =
false)
7402 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7416 const engine &aengine,
bool allow_empty =
false)
7418 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7549 float beta = 0.0f) {
7555 &src_iter_desc.
data, &weights_layer_desc.
data,
7556 &weights_iter_desc.
data, &bias_desc.
data,
7557 &dst_layer_desc.
data, &dst_iter_desc.
data,
7558 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7559 &diff_weights_layer_desc.
data,
7560 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7561 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7563 "could not create a descriptor for a vanilla RNN backward "
7564 "propagation primitive");
7588 bool allow_empty =
false)
7590 hint_fwd_pd.
get(), allow_empty) {}
7609 bool allow_empty =
false)
7611 hint_fwd_pd.
get(), allow_empty) {}
7773 &src_iter_desc.
data, &src_iter_c_desc.
data,
7774 &weights_layer_desc.
data, &weights_iter_desc.
data,
7775 &weights_peephole_desc.
data,
7776 &weights_projection_desc.
data, &bias_desc.
data,
7777 &dst_layer_desc.
data, &dst_iter_desc.
data,
7779 "could not create a descriptor for an LSTM forward "
7780 "propagation primitive");
7840 &src_iter_desc.
data, &src_iter_c_desc.
data,
7841 &weights_layer_desc.
data, &weights_iter_desc.
data,
7842 &weights_peephole_desc.
data, &bias_desc.
data,
7843 &dst_layer_desc.
data, &dst_iter_desc.
data,
7845 "could not create a descriptor for an LSTM forward "
7846 "propagation primitive");
7900 &src_iter_desc.
data, &src_iter_c_desc.
data,
7901 &weights_layer_desc.
data, &weights_iter_desc.
data,
7902 &bias_desc.
data, &dst_layer_desc.
data,
7903 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
7905 "could not create a descriptor for an LSTM forward "
7906 "propagation primitive");
7925 bool allow_empty =
false)
7927 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7940 const engine &aengine,
bool allow_empty =
false)
7942 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8128 &src_iter_desc.
data, &src_iter_c_desc.
data,
8129 &weights_layer_desc.
data, &weights_iter_desc.
data,
8130 &weights_peephole_desc.
data,
8131 &weights_projection_desc.
data, &bias_desc.
data,
8132 &dst_layer_desc.
data, &dst_iter_desc.
data,
8133 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8134 &diff_src_iter_desc.
data,
8135 &diff_src_iter_c_desc.
data,
8136 &diff_weights_layer_desc.
data,
8137 &diff_weights_iter_desc.
data,
8138 &diff_weights_peephole_desc.
data,
8139 &diff_weights_projection_desc.
data,
8140 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8141 &diff_dst_iter_desc.
data,
8142 &diff_dst_iter_c_desc.
data,
8144 "could not create a descriptor for an LSTM backward "
8145 "propagation primitive");
8238 &src_iter_desc.
data, &src_iter_c_desc.
data,
8239 &weights_layer_desc.
data, &weights_iter_desc.
data,
8240 &weights_peephole_desc.
data, &bias_desc.
data,
8241 &dst_layer_desc.
data, &dst_iter_desc.
data,
8242 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8243 &diff_src_iter_desc.
data,
8244 &diff_src_iter_c_desc.
data,
8245 &diff_weights_layer_desc.
data,
8246 &diff_weights_iter_desc.
data,
8247 &diff_weights_peephole_desc.
data,
8248 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8249 &diff_dst_iter_desc.
data,
8250 &diff_dst_iter_c_desc.
data,
8252 "could not create a descriptor for an LSTM backward "
8253 "propagation primitive");
8335 &src_iter_desc.
data, &src_iter_c_desc.
data,
8336 &weights_layer_desc.
data, &weights_iter_desc.
data,
8337 &bias_desc.
data, &dst_layer_desc.
data,
8338 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8339 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8340 &diff_src_iter_c_desc.
data,
8341 &diff_weights_layer_desc.
data,
8342 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8343 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8344 &diff_dst_iter_c_desc.
data,
8346 "could not create a descriptor for an LSTM backward "
8347 "propagation primitive");
8370 bool allow_empty =
false)
8372 hint_fwd_pd.
get(), allow_empty) {}
8390 bool allow_empty =
false)
8392 hint_fwd_pd.
get(), allow_empty) {}
8574 &src_iter_desc.
data, &weights_layer_desc.
data,
8575 &weights_iter_desc.
data, &bias_desc.
data,
8576 &dst_layer_desc.
data, &dst_iter_desc.
data,
8578 "could not create a descriptor for a GRU forward "
8579 "propagation primitive");
8598 bool allow_empty =
false)
8600 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8613 const engine &aengine,
bool allow_empty =
false)
8615 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8742 &src_iter_desc.
data, &weights_layer_desc.
data,
8743 &weights_iter_desc.
data, &bias_desc.
data,
8744 &dst_layer_desc.
data, &dst_iter_desc.
data,
8745 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8746 &diff_weights_layer_desc.
data,
8747 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8748 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8750 "could not create a descriptor for a GRU backward "
8751 "propagation primitive");
8774 bool allow_empty =
false)
8776 hint_fwd_pd.
get(), allow_empty) {}
8794 bool allow_empty =
false)
8796 hint_fwd_pd.
get(), allow_empty) {}
8939 &src_iter_desc.
data, &weights_layer_desc.
data,
8940 &weights_iter_desc.
data, &bias_desc.
data,
8941 &dst_layer_desc.
data, &dst_iter_desc.
data,
8943 "could not create a descriptor for an LBR GRU forward "
8944 "propagation primitive");
8964 bool allow_empty =
false)
8966 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8980 const engine &aengine,
bool allow_empty =
false)
8982 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9110 &src_iter_desc.
data, &weights_layer_desc.
data,
9111 &weights_iter_desc.
data, &bias_desc.
data,
9112 &dst_layer_desc.
data, &dst_iter_desc.
data,
9113 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9114 &diff_weights_layer_desc.
data,
9115 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9116 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9118 "could not create a descriptor for an LBR GRU backward "
9119 "propagation primitive");
9143 bool allow_empty =
false)
9145 hint_fwd_pd.
get(), allow_empty) {}
9164 bool allow_empty =
false)
9166 hint_fwd_pd.
get(), allow_empty) {}
9286 &data_desc.
data, axis, group_size),
9287 "could not create a descriptor for a shuffle forward "
9288 "propagation primitive");
9310 bool allow_empty =
false)
9312 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9357 &diff_data_desc.
data, axis, group_size),
9358 "could not create a descriptor for a shuffle backward "
9359 "propagation primitive");
9385 bool allow_empty =
false)
9387 hint_fwd_pd.
get(), allow_empty) {}
9447 "could not create a descriptor for a binary operation "
9467 bool allow_empty =
false)
9469 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9482 const engine &aengine,
bool allow_empty =
false)
9484 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9542 &weights_desc.
data,
nullptr, &dst_desc.
data),
9543 "could not create a descriptor for a matmul primitive");
9555 &weights_desc.
data, &bias_desc.
data,
9557 "could not create a descriptor for a matmul primitive");
9575 bool allow_empty =
false)
9577 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9589 const engine &aengine,
bool allow_empty =
false)
9591 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9605 return query_md(query::weights_md, 0);
9610 return query_md(query::weights_md, 1);
9664 "could not create a resampling forward descriptor");
9679 const std::vector<float> &factors,
9685 &src_desc.
data,
nullptr),
9686 "could not create a resampling forward descriptor");
9706 const std::vector<float> &factors,
const memory::desc &src_desc,
9708 if (!factors.empty())
9714 "could not create a resampling forward descriptor");
9734 bool allow_empty =
false)
9736 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9750 const engine &aengine,
bool allow_empty =
false)
9752 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9799 &diff_src_desc.
data, &diff_dst_desc.
data),
9800 "could not create a resampling backward data descriptor");
9815 if (!factors.empty())
9819 &diff_src_desc.
data, &diff_dst_desc.
data),
9820 "could not create a resampling backward data descriptor");
9844 bool allow_empty =
false)
9846 hint_fwd_pd.
get(), allow_empty) {}
9865 bool allow_empty =
false)
9867 hint_fwd_pd.
get(), allow_empty) {}
9977 return static_cast<status>(
9999 "could not get primitive cache capacity");
10006 "could not set primitive cache capacity");
10023 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10030 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10032 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10039 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10041 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10044 #if DNNL_CPU_RUNTIME == DNNL_RUNTIME_THREADPOOL
10050 return static_cast<status>(dnnl_sgemm_tp(
10051 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc, tp));
10057 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10059 return static_cast<status>(dnnl_gemm_u8s8s32_tp(transa, transb, offsetc, M,
10060 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10067 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10069 return static_cast<status>(dnnl_gemm_s8s8s32_tp(transa, transb, offsetc, M,
10070 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10082 "could not create a primitive");
10088 inline void primitive::execute(
const stream &astream,
10089 const std::unordered_map<int, memory> &args)
const {
10090 std::vector<dnnl_exec_arg_t> c_args;
10091 c_args.reserve(args.size());
10092 for (
const auto &a : args)
10093 c_args.push_back({a.first, a.second.get(
true)});
10096 (
int)c_args.size(), c_args.data()),
10097 "could not execute a primitive");
10102 #undef DNNL_DEFINE_BITMASK_OPS
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:6909
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2116
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2128
void set_data_handle(void *handle) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2152
dnnl_status_t DNNL_API dnnl_memory_set_ocl_mem_object(dnnl_memory_t memory, cl_mem mem_object)
Sets OpenCL memory object associated with a memory object.
handle(handle< T, traits > &&)=default
Move constructor.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7658
primitive(const primitive_desc &pd)
Constructs a primitive from a primitive descriptor.
status gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
Definition: dnnl.hpp:10036
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_next(dnnl_primitive_desc_iterator_t iterator)
Advances the primitive descriptor iterator to point to the next available implementation.
Resampling backward propagation primitive.
Definition: dnnl.hpp:9782
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4783
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:363
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9494
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1822
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3888
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:2852
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6571
logsoftmax_backward()=default
Default constructor. Produces an empty object.
desc(prop_kind aprop_kind, algorithm activation, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, rnn_flags flags=rnn_flags::undef, float alpha=0.0f, float beta=0.0f)
Constructs a descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7533
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7705
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2199
@ softmax
A softmax primitive.
engine()=default
Constructs an empty engine.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7267
dnnl_status_t DNNL_API dnnl_inner_product_forward_desc_init(dnnl_inner_product_desc_t *ip_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes descriptor for inner product forward propagation.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7147
dnnl_status_t DNNL_API dnnl_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:5914
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5899
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8647
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ success
The operation was successful.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution forward propagation primitive from a C API prim...
Definition: dnnl.hpp:4593
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:902
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5142
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9453
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:685
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:904
convolution_backward_data()=default
Default constructor. Produces an empty object.
void execute(const stream &astream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
@ all
Any ISA (excepting those listed as initial support)
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8526
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:2016
Reorder primitive.
Definition: dnnl.hpp:3221
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2140
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9342
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6741
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7642
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:8990
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:303
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8509
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6711
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7650
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8873
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:103
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8858
dnnl_status_t DNNL_API dnnl_pooling_backward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling backward propagation primitive.
@ any
An unspecified engine.
void get_params_dw_k3s2p1(int index, memory::data_type &weights_data_type, memory::data_type &bias_data_type, memory::data_type &dst_data_type, int &mask, std::vector< float > &scales) const
Returns the parameters of an depthwise post-op with stride 2.
Definition: dnnl.hpp:2545
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:369
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8949
Convolution weights gradient primitive.
Definition: dnnl.hpp:4076
An execution stream.
Definition: dnnl.hpp:1043
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:1870
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:2460
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:4566
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:4435
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:4280
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:5861
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:351
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:6758
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2117
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
prop_kind
Propagation kind.
Definition: dnnl.hpp:436
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5366
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2294
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:9597
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution forward propagation primitive.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9466
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:830
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
An opaque structure to describe a memory.
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:210
Softmax backward propagation primitive.
Definition: dnnl.hpp:5818
primitive_desc()=default
Default constructor. Produces an empty object.
An opaque structure to describe a primitive descriptor iterator.
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:826
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7476
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:7121
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2148
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:10027
Descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7478
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5241
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9040
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:1928
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9601
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7911
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5256
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:217
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:3814
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:1946
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:5661
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for LSTM forward propagation primitive.
engine(const handle< dnnl_primitive_desc_t > &pd)
Constructs an engine based on a primitive from the primitive descriptor pd by querying its engine.
Definition: dnnl.hpp:901
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:6782
dnnl_cpu_isa_t DNNL_API dnnl_get_effective_cpu_isa(void)
Gets the maximal ISA the library can dispatch to on the CPU.
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7207
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2127
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3297
memory(const desc &md, const engine &aengine)
Constructs a memory object.
Definition: dnnl.hpp:2083
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8637
#define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:1958
An execution engine.
Definition: dnnl.hpp:840
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:6167
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:3528
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5483
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:5694
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:6860
desc()=default
Default constructor. Produces an empty object.
void get_zero_points(int arg, int &mask, std::vector< int32_t > &zero_points) const
Returns zero points correspondence mask and values.
Definition: dnnl.hpp:2751
dnnl_status_t DNNL_API dnnl_memory_get_ocl_mem_object(const_dnnl_memory_t memory, cl_mem *mem_object)
Returns an OpenCL memory object associated with a memory object.
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:820
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:4763
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:965
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:5063
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7075
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5617
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s2p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 2.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a resampling backward propagation primitive from a C API primit...
Definition: dnnl.hpp:9875
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2145
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:1914
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1016
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1827
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8474
kind
Kinds of primitives supported by the library.
Definition: dnnl.hpp:278
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8629
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2286
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:9947
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5427
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8817
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:211
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:219
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:187
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:305
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6725
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:1804
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7997
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8675
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:8963
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:3272
An opaque structure to describe an engine.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6697
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5611
logsoftmax_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7461
const dnnl_version_t DNNL_API * dnnl_version()
Returns library version information.
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:9640
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5705
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1103
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:863
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:194
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1699
@ shuffle
A shuffle primitive.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8642
concat()=default
Default constructor. Produces an empty object.
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:7231
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:871
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5894
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4057
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:2336
@ none
Use no normalization flags.
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:956
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8504
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9200
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:910
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:9733
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2991
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5615
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:8212
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:808
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2137
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:1986
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9528
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9880
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8423
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7159
A descriptor of a convolution operation.
Definition: dnnl_types.h:1238
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4060
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:4019
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3882
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7219
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6365
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:802
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5522
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5486
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:4039
dnnl_status_t DNNL_API dnnl_memory_desc_permute_axes(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, const int *permutation)
Initializes a memory descriptor by permuting axes in an existing one.
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:5029
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1569
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:916
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
dnnl_status_t DNNL_API dnnl_memory_desc_reshape(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, int ndims, const dnnl_dims_t dims)
Initializes a memory descriptor by reshaping an existing one.
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2176
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2107
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:5996
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:9760
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:2519
dnnl_status_t DNNL_API dnnl_logsoftmax_forward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax forward propagation primitive.
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
desc submemory_desc(const dims &adims, const dims &offsets, bool allow_empty=false) const
Constructs a memory descriptor for a region inside an area described by this memory descriptor.
Definition: dnnl.hpp:1883
void set_threadpool(threadpool_iface *threadpool)
Sets the threadpool attribute.
Definition: dnnl.hpp:1023
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:631
A descriptor for an RNN operation.
Definition: dnnl_types.h:1591
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:205
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1575
desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7961
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:9952
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:5985
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:812
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:864
void set_data_handle(void *handle, const stream &astream) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2138
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:4312
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9530
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7094
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8658
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:9320
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5094
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:9395
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:795
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2973
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3598
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:9243
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6531
A descriptor of an inner product operation.
Definition: dnnl_types.h:1535
void set_ocl_mem_object(cl_mem mem_object)
Sets the OpenCL memory object mem_object associated with the memory.
Definition: dnnl.hpp:2216
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7992
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7017
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s2p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 2.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a layer normalization forward propagation primitive from a C AP...
Definition: dnnl.hpp:6521
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1757
primitive()=default
Default constructor. Constructs an empty object.
dnnl_status_t DNNL_API dnnl_memory_unmap_data(const_dnnl_memory_t memory, void *mapped_ptr)
Unmaps a memory object and writes back any changes made to the previously mapped memory buffer.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5369
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5928
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:8722
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:8100
dnnl_status_t DNNL_API dnnl_layer_normalization_backward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for a layer normalization backward propagation primitive.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8843
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3535
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:9812
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7247
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:9705
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5524
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:2002
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:7619
LSTM backward propagation primitive.
Definition: dnnl.hpp:8020
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6432
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5602
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2157
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:9842
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:8669
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:6681
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2130
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:212
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:881
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9009
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8418
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5378
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:818
GRU forward propagation primitive.
Definition: dnnl.hpp:8524
kind
Kinds of engines.
Definition: dnnl.hpp:845
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:228
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9233
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6377
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7440
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:8623
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:7756
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8405
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6245
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:6962
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:857
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9512
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:207
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:873
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2281
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8996
lstm_backward()=default
Default constructor. Produces an empty object.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:217
stream()=default
Constructs an empty stream.
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:877
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9254
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:1198
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:3716
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:9442
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:9976
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1594
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6107
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:6210
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8352
@ pooling
A pooling primitive.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6953
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:3083
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8827
desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for concat primitive from a C API primitive descriptor which must h...
Definition: dnnl.hpp:3431
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:5107
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:9141
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:785
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:4650
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2125
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2158
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2150
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7199
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2615
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:402
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5480
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2144
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7437
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:2026
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1571
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:546
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2135
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8868
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9719
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:8561
@ 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:2296
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6241
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5139
primitive_desc()=default
Default constructor. Produces an empty object.
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:3071
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2038
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:358
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) backward propagation primitive.
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8489
sum()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7663
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7653
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5154
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:204
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:6345
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7450
dnnl_status_t DNNL_API dnnl_stream_create_v2(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags, const_dnnl_stream_attr_t attr)
Creates an execution stream.
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3462
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:7885
deconvolution_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:888
dnnl_status_t DNNL_API dnnl_engine_create_ocl(dnnl_engine_t *engine, dnnl_engine_kind_t kind, cl_device_id device, cl_context context)
Creates an engine associated with an OpenCL device and an OpenCL context.
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1582
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:3328
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3026
A descriptor of a pooling operation.
Definition: dnnl_types.h:1396
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6430
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4317
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5026
primitive_desc_base()=default
Default constructor. Produces an empty object.
void set_zero_points(int arg, int mask, const std::vector< int32_t > &zero_points)
Sets zero points for primitive operations for a given memory argument.
Definition: dnnl.hpp:2786
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2014
A container for stream attributes.
Definition: dnnl.hpp:998
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:6617
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:3246
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:912
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7645
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:3865
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:3765
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:260
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:199
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:6982
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:926
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:9825
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3050
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:2814
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.
eltwise_backward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a GRU backward propagation primitive from a C API primitive des...
Definition: dnnl.hpp:8804
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_weights_projection_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or with out recurrent project...
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:944
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:2434
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5552
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:3095
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_zero_points(const_dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const int32_t **zero_points)
Returns count, correspondence zero point mask, and a pointer to a constant int32_t array of zero_poin...
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:948
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum_v2(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_data_type_t *data_type)
Returns the parameters of an accumulation (sum) post-op with a data type parameter.
@ resampling
A resampling primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_output_scales(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets output scaling factors correspondence mask and values.
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_create(dnnl_primitive_desc_iterator_t *iterator, const_dnnl_op_desc_t op_desc, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine, const_dnnl_primitive_desc_t hint_forward_primitive_desc)
Creates a primitive descriptor iterator.
desc(prop_kind aprop_kind, algorithm aalgorithm, const std::vector< float > &factors, const memory::desc &src_desc)
Constructs a descriptor for a resampling forward propagation primitive using source memory descriptor...
Definition: dnnl.hpp:9678
shuffle_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_softmax_forward_desc_init(dnnl_softmax_desc_t *softmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax forward propagation primitive.
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(dnnl_primitive_desc_t *primitive_desc, const_dnnl_primitive_desc_t existing_primitive_desc)
Clones a primitive descriptor.
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:991
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:894
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9124
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5065
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5755
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2143
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:7360
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5244
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:5133
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:4692
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:6825
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3311
primitive_desc()=default
Default constructor. Produces an empty object.
int get_primitive_cache_capacity()
Returns the number of primitives that can be held in the primitive cache at the same time.
Definition: dnnl.hpp:9996
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3308
Post-ops.
Definition: dnnl.hpp:2282
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:287
cl_device_id get_ocl_device() const
Returns the OpenCL device associated with the engine.
Definition: dnnl.hpp:931
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:952
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6947
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3032
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8863
lstm_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:3056
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6480
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:781
query
Primitive descriptor query specification.
Definition: dnnl.hpp:718
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8655
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.
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:200
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:869
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1004
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:202
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2032
dnnl_status_t DNNL_API dnnl_primitive_execute(const_dnnl_primitive_t primitive, dnnl_stream_t stream, int nargs, const dnnl_exec_arg_t *args)
Executes a primitive.
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2277
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9004
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6122
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:4787
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9022
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6842
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:5833
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
#define DNNL_ARG_DIFF_BIAS
Gradient (diff) of the bias tensor argument.
Definition: dnnl_types.h:2047
dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr)
Destroys primitive attributes.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum(dnnl_post_ops_t post_ops, float scale)
Appends an accumulation (sum) to post-ops.
primitive_desc(const desc &adesc, const engine &aengine, const lstm_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8368
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:1952
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7135
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3367
dnnl_status_t DNNL_API dnnl_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU forward propagation primitive.
dnnl_status_t DNNL_API dnnl_gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6024
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:855
Convolution forward propagation primitive.
Definition: dnnl.hpp:3635
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6110
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6279
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:301
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:564
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6148
dnnl_status_t DNNL_API dnnl_memory_desc_init_submemory(dnnl_memory_desc_t *memory_desc, const dnnl_memory_desc_t *parent_memory_desc, const dnnl_dims_t dims, const dnnl_dims_t offsets)
Initializes a memory descriptor for a region inside an area described by an existing memory descripto...
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1751
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:836
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:209
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7673
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6708
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:865
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:99
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8830
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:234
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5363
primitive_desc()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_stream_attr_create(dnnl_stream_attr_t *attr, dnnl_engine_kind_t kind)
Creates execution stream attributes for a stream that runs on an engine of a particular kind.
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:181
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:576
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:6467
dnnl_status_t DNNL_API dnnl_post_ops_append_eltwise(dnnl_post_ops_t post_ops, float scale, dnnl_alg_kind_t alg_kind, float alpha, float beta)
Appends an elementwise post-op.
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:6968
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1171
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:2179
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scratchpad_mode(const_dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t *mode)
Returns the primitive attributes scratchpad mode.
dnnl_status_t DNNL_API dnnl_concat_primitive_desc_create(dnnl_primitive_desc_t *concat_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, int concat_dimension, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an out-of-place concatenation primitive.
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
dnnl_status_t DNNL_API dnnl_eltwise_backward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Softmax forward propagation primitive.
Definition: dnnl.hpp:5728
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:822
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6277
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:197
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2141
dnnl_status_t DNNL_API dnnl_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution backward propagation primitive.
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:791
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6228
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6950
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1366
@ undef
Undefined algorithm.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6510
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:9161
@ 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:2291
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:5299
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7472
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
@ default_order
Default order execution.
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:185
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:5408
data_type
Data type specification.
Definition: dnnl.hpp:1204
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:8791
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:4730
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:5236
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:5223
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8890
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.
cl_context get_ocl_context() const
Returns the OpenCL context associated with the engine.
Definition: dnnl.hpp:922
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:7399
dnnl_status_t DNNL_API dnnl_sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const lstm_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8387
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4264
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6371
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7979
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:9090
dnnl_status_t DNNL_API dnnl_stream_wait(dnnl_stream_t stream)
Waits for all primitives in the execution stream to finish computations.
dnnl_status_t DNNL_API dnnl_memory_set_data_handle_v2(dnnl_memory_t memory, void *handle, dnnl_stream_t stream)
Sets the underlying memory buffer.
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7225
An opaque structure to describe a primitive descriptor.
desc(const memory::desc &diff_data_desc, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6037
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:188
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:1905
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5318
dnnl_status_t DNNL_API dnnl_sum_primitive_desc_create(dnnl_primitive_desc_t *sum_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, const float *scales, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an (out-of-place) sum primitive.
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:945
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:552
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:922
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:5796
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:6668
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:928
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1987
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.
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1587
@ inner_product
An inner product primitive.
#define DNNL_ARG_DIFF_DST_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2008
dnnl_status_t DNNL_API dnnl_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU backward propagation primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8005
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:192
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:898
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:10004
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8000
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4552
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:9588
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8454
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6700
@ undef
Undefined primitive.
Resampling forward propagation.
Definition: dnnl.hpp:9638
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:9795
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2087
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9329
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7253
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:262
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:968
Inner product weights gradient primitive.
Definition: dnnl.hpp:6966
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6540
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:9892
@ layer_normalization
A layer normalization primitive.
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7141
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1278
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2149
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:2195
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:2002
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8634
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:1890
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1794
stream_attr(engine::kind akind)
Constructs stream attributes for a stream that runs on an engine of a particular kind.
Definition: dnnl.hpp:1008
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2147
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:940
dnnl_status_t DNNL_API dnnl_lbr_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:789
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9769
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:196
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:5081
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:4299
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:588
Inner product backward propagation primitive.
Definition: dnnl.hpp:6864
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:978
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:3670
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:9622
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:924
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6385
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:6221
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:810
Inner product forward propagation primitive.
Definition: dnnl.hpp:6739
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4771
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2159
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6022
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:353
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:828
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8756
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4599
dnnl_status_t DNNL_API dnnl_set_max_cpu_isa(dnnl_cpu_isa_t isa)
Sets the maximal ISA the library can dispatch to on the CPU.
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9238
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1174
dnnl_status_t DNNL_API dnnl_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution weights gradient primitive.
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product descriptor weights update primitive without bias.
Definition: dnnl.hpp:7004
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:5443
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7668
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:9174
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:1961
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:184
An opaque structure to describe a primitive.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution weights gradient primitive from a C API primiti...
Definition: dnnl.hpp:5021
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4774
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:7950
convolution_forward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6494
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5145
stream(const engine &aengine, flags aflags=flags::default_flags, const stream_attr &attr=stream_attr())
Constructs a stream for the specified engine and with behavior controlled by the specified flags.
Definition: dnnl.hpp:1069
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:186
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2260
dnnl_status_t DNNL_API dnnl_reorder_primitive_desc_create(dnnl_primitive_desc_t *reorder_primitive_desc, const dnnl_memory_desc_t *src_desc, dnnl_engine_t src_engine, const dnnl_memory_desc_t *dst_desc, dnnl_engine_t dst_engine, const_dnnl_primitive_attr_t attr)
Creates a primitive descriptor for a reorder primitive.
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7984
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2134
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7624
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:9382
dnnl_status_t DNNL_API dnnl_softmax_backward_desc_init(dnnl_softmax_desc_t *softmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
void set_scales(int arg, int mask, const std::vector< float > &scales)
Sets scaling factors for primitive operations for a given memory argument.
Definition: dnnl.hpp:2734
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:365
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3835
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7153
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1048
dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(const_dnnl_memory_t memory, const dnnl_memory_desc_t **memory_desc)
Returns the memory descriptor for a memory object.
primitive_desc(const desc &adesc, const engine &aengine, const layer_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6648
dnnl_status_t DNNL_API dnnl_vanilla_rnn_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN backward propagation primitive.
lbr_gru_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8838
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5599
dnnl_status_t DNNL_API dnnl_resampling_backward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes a descriptor for resampling backward propagation primitive.
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:214
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s1p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 1.
desc(prop_kind aprop_kind, const memory::desc &data_desc, int softmax_axis)
Constructs a descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5744
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(const_dnnl_primitive_t primitive, const_dnnl_primitive_desc_t *primitive_desc)
Retrieves a constant reference to the primitive descriptor of a given primitive.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7629
desc(const dims &adims, data_type adata_type, const dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:1853
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6577
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8822
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const logsoftmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6085
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2160
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7956
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9614
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5699
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:424
handle()=default
Constructs an empty handle object.
primitive_desc()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:9778
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2136
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1922
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:7939
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:838
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:3876
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:8926
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
A special mnemonic for diff of RNN weights applied to the projection weights.
Definition: dnnl_types.h:2044
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:859
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7193
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:176
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:806
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9562
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6180
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:9609
dnnl_status_t DNNL_API dnnl_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution backward propagation primitive.
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1434
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2185
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:4988
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:1940
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1291
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:6065
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8413
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:4196
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6308
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6009
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3369
gru_backward()=default
Default constructor. Produces an empty object.
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:793
softmax_backward()=default
Default constructor. Produces an empty object.
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:198
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2228
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1465
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3044
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3038
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:914
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6575
@ library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
resampling_forward()=default
Default constructor. Produces an empty object.
Primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8584
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
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:6098
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7688
softmax_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum_v2(dnnl_post_ops_t post_ops, float scale, dnnl_data_type_t data_type)
Appends an accumulation v2 (sum) to post-ops.
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1313
dnnl_status_t DNNL_API dnnl_eltwise_forward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise forward propagation primitive.
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3000
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:254
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:950
layer_normalization_backward()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7187
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:6325
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6534
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:832
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7458
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4320
handle< T, traits > & operator=(handle< T, traits > &&)=default
Move assignment operator.
@ undef
Undefined data type (used for empty memory descriptors).
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4325
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:232
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8428
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:9942
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:6446
desc reshape(const dims &adims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:1939
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2114
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9500
Pooling forward propagation primitive.
Definition: dnnl.hpp:5270
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2263
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:213
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:299
dnnl_status_t DNNL_API dnnl_engine_get_ocl_device(dnnl_engine_t engine, cl_device_id *device)
Returns the OpenCL device associated with an engine.
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:10019
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:2923
status
Status values returned by the library functions.
Definition: dnnl.hpp:9909
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9042
dnnl_status_t DNNL_API dnnl_memory_get_engine(const_dnnl_memory_t memory, dnnl_engine_t *engine)
Returns the engine of a memory object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6691
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:193
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2269
@ 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:2286
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s1p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 1.
primitive_desc(int concat_dimension, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3412
Convolution backward propagation primitive.
Definition: dnnl.hpp:3907
int ndims
Number of dimensions.
Definition: dnnl_types.h:1156
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:244
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7179
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:192
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3020
primitive_desc()=default
Default constructor. Produces an empty object.
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1498
cpu_isa get_effective_cpu_isa()
Gets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:9982
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3223
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9400
Elementwise binary operator primitive.
Definition: dnnl.hpp:9426
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5160
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:4860
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4608
dnnl_status_t DNNL_API dnnl_stream_create_ocl(dnnl_stream_t *stream, dnnl_engine_t engine, cl_command_queue queue)
Creates an execution stream for a given engine associated with an OpenCL command queue.
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6866
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:896
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
stream_attr()=default
Constructs default (empty) stream attributes.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9205
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:912
oneDNN exception class.
Definition: dnnl.hpp:91
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6537
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:9658
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:183
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:918
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6543
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8853
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:2008
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
desc(const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Constructs a descriptor for a matmul primitive.
Definition: dnnl.hpp:9552
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1186
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:4750
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:7426
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:3385
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7080
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8446
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4971
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:5346
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:816
dnnl_status_t DNNL_API dnnl_inner_product_backward_data_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product backward propagation.
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2630
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:314
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:5122
dnnl_status_t DNNL_API dnnl_memory_map_data(const_dnnl_memory_t memory, void **mapped_ptr)
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6688
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution weights gradient primitive.
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8494
Pooling backward propagation primitive.
Definition: dnnl.hpp:5382
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4768
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2183
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6845
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3553
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8520
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_lbr_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU forward propagation primitive.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9503
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:183
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5805
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:7034
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9228
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7238
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:814
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7683
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:1047
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7213
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6393
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:8400
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:5475
dnnl_status_t DNNL_API dnnl_stream_get_ocl_command_queue(dnnl_stream_t stream, cl_command_queue *queue)
Returns the OpenCL command queue associated with an execution stream.
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9355
dnnl_status_t DNNL_API dnnl_inner_product_backward_weights_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5247
desc()=default
Default constructor. Produces an empty object.
resampling_backward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5702
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6703
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:4904
An opaque structure for primitive descriptor attributes.
dnnl_status_t DNNL_API dnnl_set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:7083
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:4483
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:824
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7678
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes scaling factors correspondence mask and values for a given memory argume...
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2154
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_data_qparams(dnnl_primitive_attr_t attr, const float scale, const float shift)
Set quantization scale and shift parameters for RNN data tensors.
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for dilated convolution backward propagation primitive.
Definition: dnnl.hpp:3981
@ convolution
A convolution primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_post_ops(const_dnnl_primitive_attr_t attr, const_dnnl_post_ops_t *post_ops)
Returns primitive attributes post-ops.
void get_params_sum(int index, float &scale, memory::data_type &data_type) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2361
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9223
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8848
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6113
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2600
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5495
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9270
void execute(const stream &astream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3340
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9326
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3438
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1805
Primitive attributes.
Definition: dnnl.hpp:2584
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:5814
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9208
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product weights update primitive.
Definition: dnnl.hpp:7054
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6848
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9184
dnnl_status_t DNNL_API dnnl_stream_attr_destroy(dnnl_stream_attr_t attr)
Destroys execution stream attributes.
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9412
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6892
dnnl_status_t DNNL_API dnnl_get_primitive_cache_capacity(int *capacity)
Returns the number of primitives that can be held in the primitive cache at the same time.
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2110
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution backward propagation primitive.
#define DNNL_ARG_DIFF_SRC_LAYER
A special mnemonic for gradient (diff) of RNN input vector.
Definition: dnnl_types.h:1981
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2139
A descriptor of resampling operation.
Definition: dnnl_types.h:1721
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9025
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3910
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:908
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9345
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5802
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1755
Memory object.
Definition: dnnl.hpp:1184
dnnl_status_t DNNL_API dnnl_engine_get_ocl_context(dnnl_engine_t engine, cl_context *context)
Returns the OpenCL context associated with an engine.
An opaque structure for a chain of post operations.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7261
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:2704
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:4818
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2108
@ undef
Undefined RNN flags.
eltwise_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:892
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:110
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:5714
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:9481
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:8612
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3009
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8441
@ undef
Undefined propagation kind.
inner_product_forward()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6388
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution weights gradient primitive.
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:215
primitive(const_dnnl_primitive_desc_t c_pd)
Constructs a primitive from a C API primitive descriptor.
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:9927
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:1993
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6231
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6795
oneDNN C API handle wrapper class.
Definition: dnnl.hpp:143
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:5175
pooling_backward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9308
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8484
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:2964
Abstract threadpool interface.
Definition: dnnl_threadpool_iface.hpp:27
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
primitive_desc(const memory::desc &dst, const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3476
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7969
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:7067
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6150
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:9490
dnnl_status_t DNNL_API dnnl_memory_create(dnnl_memory_t *memory, const dnnl_memory_desc_t *memory_desc, dnnl_engine_t engine, void *handle)
Creates a memory object.
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:900
dnnl_status_t DNNL_API dnnl_pooling_forward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7632
inner_product_backward_data()=default
Default constructor. Produces an empty object.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9187
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:4950
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7127
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:4072
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:9862
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6374
dnnl_status_t DNNL_API dnnl_shuffle_forward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle forward propagation primitive.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4582
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8888
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9883
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6402
Memory descriptor.
Definition: dnnl_types.h:1154
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:797
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7445
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7964
memory(const desc &md, const engine &aengine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:2069
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:840
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7165
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2686
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4342
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:5881
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6018
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:227
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:3894
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:5944
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2258
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1899
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:6851
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:2035
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5384
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9293
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:4151
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:4108
batch_normalization_forward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const inner_product_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6929
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4605
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7317
dnnl_status_t DNNL_API dnnl_lrn_forward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN forward propagation primitive.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:9430
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:8597
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:561
@ scratchpad_engine
scratchpad engine
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8459
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9197
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7072
dnnl_status_t DNNL_API dnnl_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
void reset_with_clone(const_dnnl_primitive_desc_t pd)
Resets the value of the handle to a clone of a C API primitive descriptor.
Definition: dnnl.hpp:3107
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:201
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6631
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:3065
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization forward propagation primitive.
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:558
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9364
dnnl_status_t DNNL_API dnnl_shuffle_backward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, const dnnl_memory_desc_t *diff_data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle backward propagation primitive.
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4713
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2351
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2138
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4331
engine(kind akind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:873
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9428
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4789
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:946
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3435
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:206
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7173
dnnl_status_t DNNL_API dnnl_lrn_backward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN backward propagation primitive.
A class that provides the destructor for a oneDNN C API handle.
Definition: dnnl.hpp:127
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2982
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9213
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2113
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1189
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5844
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4621
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6237
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:195
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8499
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum(const_dnnl_post_ops_t post_ops, int index, float *scale)
Returns the parameters of an accumulation (sum) post-op.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5785
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scratchpad_mode(dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t mode)
Sets primitive attributes scratchpad mode.
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:2797
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7432
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:208
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:6809
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8650
A memory descriptor.
Definition: dnnl.hpp:1801
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3885
Base class for all computational primitives.
Definition: dnnl.hpp:276
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:7924
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:850
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:861
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1226
@ 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:2273
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6694
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:5331
batch_normalization_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_strides(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, const dnnl_dims_t strides)
Initializes a memory descriptor using dimensions and strides.
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2095
format_kind
Memory format kind.
Definition: dnnl.hpp:1222
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:883
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:182
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:3903
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:2027
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9268
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9036
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:9749
dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const int32_t *zero_points)
Sets primitive attributes zero points for primitive operations for a given memory argument.
matmul()=default
Default constructor. Produces an empty object.
lbr_gru_forward()=default
Default constructor. Produces an empty object.
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:361
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or without recurrent projecti...
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3637
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:9538
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:2021
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1585
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:8016
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8479
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7989
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:875
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:570
oneDNN namespace
Definition: dnnl.hpp:81
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:932
@ logsoftmax
A logsoftmax primitive.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9014
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
An opaque structure to describe an execution stream.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:9604
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4078
@ impl_info_str
implementation name
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4623
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9017
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:5582
A descriptor of a binary operation.
Definition: dnnl_types.h:1673
pooling_forward()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9192
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3303
@ batch_normalization
A batch normalization primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
primitive_desc(const desc &adesc, const engine &aengine, const vanilla_rnn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7586
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:5462
primitive_desc()=default
Default constructor. Produces an empty object.
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2105
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:853
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:3849
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.
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3543
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3446
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2155
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:216
void get_params_eltwise(int index, float &scale, algorithm &aalgorithm, float &alpha, float &beta) const
Returns parameters of an elementwise post-up.
Definition: dnnl.hpp:2397
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7315
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9179
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:8979
cl_command_queue get_ocl_command_queue() const
Returns the underlying OpenCL queue object.
Definition: dnnl.hpp:1093
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7699
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9403
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:5539
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4617
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:9932
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:787
binary()=default
Default constructor. Produces an empty object.
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:329
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3319
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:6836
desc(const dims &adims, data_type adata_type, format_tag aformat_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:1825
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:6879
dnnl_status_t DNNL_API dnnl_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution forward propagation primitive.
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:2299
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9001
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:471
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4002
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8449
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:778
dnnl_status_t DNNL_API dnnl_resampling_forward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a resampling forward propagation primitive.
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, const memory::desc &stat_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization backward propagation primitive.
Definition: dnnl.hpp:6593
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6368
primitive_desc()=default
Default constructor. Produces an empty object.
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:376
dnnl_status_t DNNL_API dnnl_matmul_desc_init(dnnl_matmul_desc_t *matmul_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a matrix multiplication descriptor.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:5037
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
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:5769
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1597
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:7824
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9218
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_tag(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, dnnl_format_tag_t tag)
Initializes a memory descriptor using dimensions and memory format tag.
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2111
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1577
dnnl_primitive_desc_t DNNL_API dnnl_primitive_desc_iterator_fetch(const_dnnl_primitive_desc_iterator_t iterator)
Fetches the current primitive descriptor from a primitive descriptor iterator.
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5272
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:3292
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5644
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5930
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:867
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9497
@ in_order
In-order execution.
T * map_data() const
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents.
Definition: dnnl.hpp:2179
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4063
threadpool_iface * get_threadpool()
Returns the threadpool attribute.
Definition: dnnl.hpp:1033
primitive_desc()=default
Default constructor. Produces an empty object.
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6273
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8464
primitive_desc()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9338
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution backward propagation primitive.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3532
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:7606
dnnl_status_t DNNL_API dnnl_layer_normalization_forward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for layer normalization forward propagation primitive.
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:573
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2604
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN weights tensors.
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:312
dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(dnnl_primitive_attr_t attr, const_dnnl_post_ops_t post_ops)
Sets primitive attributes post-ops.
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:1808
@ out_of_order
Out-of-order execution.
convolution_backward_weights()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
void append_eltwise(float scale, algorithm aalgorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2383
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:7415
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:930
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1753
lrn_backward()=default
Default constructor. Produces an empty object.
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7108
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2588
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:549
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5188
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:842
LSTM forward propagation primitive.
Definition: dnnl.hpp:7703
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:6942
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2266
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:203
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:2907
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:775
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8809
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:2911
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2161
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:4390
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7974
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6234
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:2944
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:5566
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6380
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:6294
dnnl_status_t DNNL_API dnnl_dilated_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution forward propagation primitive.
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:890
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4602
dnnl_status_t DNNL_API dnnl_primitive_attr_get_output_scales(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes output scaling factors correspondence mask and values.
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2156
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6716
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:3506
@ default_flags
Default stream configuration.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5048
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9574
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:5204
Base class for all primitive descriptors.
Definition: dnnl.hpp:2899
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5820
reorder()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated deconvolution forward propagation primitive without bias.
Definition: dnnl.hpp:4531
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:6194
const dnnl_memory_desc_t DNNL_API * dnnl_primitive_desc_query_md(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index)
Queries primitive descriptor for a memory descriptor.
dnnl_status_t DNNL_API dnnl_gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2142
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:8772
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:906
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9766
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:4052
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8022
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:9937
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8835
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5905
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7453
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4356
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5158
@ eltwise
An element-wise primitive.
desc(prop_kind aprop_kind, rnn_direction direction, const memory::desc &src_layer_desc, const memory::desc &src_iter_desc, const memory::desc &src_iter_c_desc, const memory::desc &weights_layer_desc, const memory::desc &weights_iter_desc, const memory::desc &bias_desc, const memory::desc &dst_layer_desc, const memory::desc &dst_iter_desc, const memory::desc &dst_iter_c_desc, const memory::desc &diff_src_layer_desc, const memory::desc &diff_src_iter_desc, const memory::desc &diff_src_iter_c_desc, const memory::desc &diff_weights_layer_desc, const memory::desc &diff_weights_iter_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_layer_desc, const memory::desc &diff_dst_iter_desc, const memory::desc &diff_dst_iter_c_desc, rnn_flags flags=rnn_flags::undef)
Constructs an LSTM descriptor for backward propagation using prop_kind, direction,...
Definition: dnnl.hpp:8311
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6006
primitive_desc()=default
Default constructor. Produces an empty object.
gru_forward()=default
Default constructor. Produces an empty object.
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1600
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5902
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5730
shuffle_backward()=default
Default constructor. Produces an empty object.
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:804
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:9282
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:8469
Primitive descriptor for an RNN backward propagation primitive.
Definition: dnnl.hpp:7569
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3460
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5955
dnnl_status_t DNNL_API dnnl_vanilla_rnn_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN forward propagation primitive.
@ deconvolution
A deconvolution primitive.
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8433
layer_normalization_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:879
handle(const handle< T, traits > &)=default
Copy constructor.
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:218
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8814
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:5631
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7385
lrn_forward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:5357
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:1893
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1579
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:5969
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:281
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:8884
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5034
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6528
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6048
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2122
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:3938
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:2885
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_alg_kind_t *alg_kind, float *alpha, float *beta)
Returns the parameters of an elementwise post-up.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:1916
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:4243
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9784
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:5008
GRU backward propagation primitive.
Definition: dnnl.hpp:8673
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:5681
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2162
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8438
memory()=default
Default constructor.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8410
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4358
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:6358
@ primitive_kind
primitive kind
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:920
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:942
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an eltwise forward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5593
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7637
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.