Performance library for Deep Learning
1.7.0
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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;
362 const std::unordered_map<int, memory> &args)
const;
376 "could not get a primitive descriptor from a primitive");
387 "could not get a primitive kind from a primitive descriptor");
477 undef = dnnl_alg_kind_undef,
667 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
668 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
669 return static_cast<enum_name>( \
670 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
673 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
674 return static_cast<enum_name>( \
675 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
678 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
679 return static_cast<enum_name>( \
680 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
683 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
684 lhs = static_cast<enum_name>( \
685 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
689 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
690 lhs = static_cast<enum_name>( \
691 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
695 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
696 lhs = static_cast<enum_name>( \
697 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
701 inline enum_name operator~(enum_name rhs) { \
702 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
903 "could not create an engine");
907 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
908 engine(
kind akind, cl_device_id device, cl_context context) {
918 "could not create an engine");
932 "could not get an engine from a primitive_desc");
933 reset(c_engine,
true);
941 "could not get kind of an engine");
945 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
949 cl_context context =
nullptr;
951 "could not get an OpenCL context from an engine");
958 cl_device_id device =
nullptr;
960 "could not get an OpenCL device from an engine");
970 template <
typename primitive_desc>
980 template <
typename primitive_desc>
985 "could not get an engine from a primitive_desc");
986 return engine(c_engine,
true);
1037 "could not create stream attributes");
1041 #if DNNL_CPU_THREADING_RUNTIME == DNNL_RUNTIME_THREADPOOL
1051 "could not set stream threadpool attribute");
1062 "could not set stream threadpool attribute");
1101 "could not create a stream");
1105 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1106 stream(
const engine &aengine, cl_command_queue queue) {
1113 "could not create a stream");
1122 "could not get an engine from a stream object");
1123 return engine(c_engine,
true);
1126 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1130 cl_command_queue queue =
nullptr;
1132 "could not get an OpenCL command queue from a stream");
1233 template <
typename T>
1235 validate_container_size(
1526 Abc16a = dnnl_Abc16a,
1527 ABc16a16b = dnnl_ABc16a16b,
1528 ABc4a4b = dnnl_ABc4a4b,
1531 ABc16b16a = dnnl_ABc16b16a,
1534 ABc4b16a4b = dnnl_ABc4b16a4b,
1535 ABc2b8a4b = dnnl_ABc2b8a4b,
1536 ABc16b16a4b = dnnl_ABc16b16a4b,
1537 ABc16b16a2b = dnnl_ABc16b16a2b,
1538 ABc4b4a = dnnl_ABc4b4a,
1539 ABc8a16b2a = dnnl_ABc8a16b2a,
1540 ABc8a8b = dnnl_ABc8a8b,
1541 ABc8a4b = dnnl_ABc8a4b,
1543 ABc8b16a2b = dnnl_ABc8b16a2b,
1544 ABc8b8a = dnnl_ABc8b8a,
1545 Abcd8a = dnnl_Abcd8a,
1546 Abcd16a = dnnl_Abcd16a,
1547 Abcd32a = dnnl_Abcd32a,
1548 ABcd16a16b = dnnl_ABcd16a16b,
1551 ABcd16b16a = dnnl_ABcd16b16a,
1552 aBCd16b16c = dnnl_aBCd16b16c,
1553 aBCd16c16b = dnnl_aBCd16c16b,
1554 Abcd4a = dnnl_Abcd4a,
1556 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1557 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1558 ABcd4b4a = dnnl_ABcd4b4a,
1559 ABcd4a4b = dnnl_ABcd4a4b,
1560 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1561 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1562 ABcd16b16a4b = dnnl_ABcd16b16a4b,
1563 ABcd16b16a2b = dnnl_ABcd16b16a2b,
1564 aBCd16c16b4c = dnnl_aBCd16c16b4c,
1565 aBCd16c16b2c = dnnl_aBCd16c16b2c,
1566 aBCd4c4b = dnnl_aBCd4c4b,
1567 aBCd4b4c = dnnl_aBCd4b4c,
1568 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1569 ABcd8a8b = dnnl_ABcd8a8b,
1570 ABcd8a4b = dnnl_ABcd8a4b,
1573 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1574 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1577 aBCd8b8c = dnnl_aBCd8b8c,
1578 aBCd8b4c = dnnl_aBCd8b4c,
1579 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1580 aBCd8c8b = dnnl_aBCd8c8b,
1581 Abcde16a = dnnl_Abcde16a,
1582 Abcde32a = dnnl_Abcde32a,
1583 ABcde16a16b = dnnl_ABcde16a16b,
1586 ABcde16b16a = dnnl_ABcde16b16a,
1587 aBCde16b16c = dnnl_aBCde16b16c,
1588 aBCde16c16b = dnnl_aBCde16c16b,
1589 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1590 Abcde4a = dnnl_Abcde4a,
1592 ABcde4b4a = dnnl_ABcde4b4a,
1593 ABcde4a4b = dnnl_ABcde4a4b,
1594 aBCde4b4c = dnnl_aBCde4b4c,
1595 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1596 aBCde16c16b4c = dnnl_aBCde16c16b4c,
1597 aBCde16c16b2c = dnnl_aBCde16c16b2c,
1598 aBCde4c4b = dnnl_aBCde4c4b,
1599 Abcde8a = dnnl_Abcde8a,
1600 ABcde8a8b = dnnl_ABcde8a8b,
1601 ABcde8a4b = dnnl_ABcde8a4b,
1603 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1606 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1607 ABcde8b8a = dnnl_ABcde8b8a,
1608 aBCde8b8c = dnnl_aBCde8b8c,
1609 aBCde8b4c = dnnl_aBCde8b4c,
1610 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1611 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1612 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1613 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1614 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1615 aBCde8c8b = dnnl_aBCde8c8b,
1617 aBCdef16b16c = dnnl_aBCdef16b16c,
1618 aBCdef16c16b = dnnl_aBCdef16c16b,
1621 aBCdef4c4b = dnnl_aBCdef4c4b,
1622 aBCdef4b4c = dnnl_aBCdef4b4c,
1623 aBCdef8b8c = dnnl_aBCdef8b8c,
1624 aBCdef8b4c = dnnl_aBCdef8b4c,
1625 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1626 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1627 aBCdef8c8b = dnnl_aBCdef8c8b,
1628 aBdc16b = dnnl_aBdc16b,
1629 aBdc4b = dnnl_aBdc4b,
1630 aBdc8b = dnnl_aBdc8b,
1631 aBdec16b = dnnl_aBdec16b,
1632 aBdec4b = dnnl_aBdec4b,
1633 aBdec8b = dnnl_aBdec8b,
1634 aBdefc16b = dnnl_aBdefc16b,
1635 aCBdef16c16b = dnnl_aCBdef16c16b,
1636 aCBdef16b16c = dnnl_aCBdef16b16c,
1637 aBdefc4b = dnnl_aBdefc4b,
1638 aBdefc8b = dnnl_aBdefc8b,
1639 Acb16a = dnnl_Acb16a,
1642 aCBd16b16c = dnnl_aCBd16b16c,
1643 aCBd16c16b = dnnl_aCBd16c16b,
1644 aCBde16b16c = dnnl_aCBde16b16c,
1645 aCBde16c16b = dnnl_aCBde16c16b,
1646 Acdb16a = dnnl_Acdb16a,
1647 Acdb4a = dnnl_Acdb4a,
1648 Acdb8a = dnnl_Acdb8a,
1649 Acdeb16a = dnnl_Acdeb16a,
1650 Acdeb4a = dnnl_Acdeb4a,
1651 Acdeb8a = dnnl_Acdeb8a,
1652 BAc16a16b = dnnl_BAc16a16b,
1653 BAc16b16a = dnnl_BAc16b16a,
1654 BAcd16a16b = dnnl_BAcd16a16b,
1655 BAcd16b16a = dnnl_BAcd16b16a,
1656 ABcd32a32b = dnnl_ABcd32a32b,
1657 BAcde16b16a = dnnl_BAcde16b16a,
1658 BAcde16a16b = dnnl_BAcde16a16b,
1659 aBdec32b = dnnl_aBdec32b,
1660 Abcdef16a = dnnl_Abcdef16a,
1661 Abcdef32a = dnnl_Abcdef32a,
1662 Acdb32a = dnnl_Acdb32a,
1666 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1667 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1668 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1669 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1670 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1671 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1672 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1673 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1674 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1687 NCw16n16c = dnnl_NCw16n16c,
1688 NChw16n16c = dnnl_NChw16n16c,
1689 NCdhw16n16c = dnnl_NCdhw16n16c,
1690 NCdhw32n32c = dnnl_NCdhw32n32c,
1691 NChw32n32c = dnnl_NChw32n32c,
1692 IOhw16i16o = dnnl_IOhw16i16o,
1693 Ohwi32o = dnnl_Ohwi32o,
1694 IOdhw16i16o = dnnl_IOdhw16i16o,
1695 gIOhw16i16o = dnnl_gIOhw16i16o,
1696 gOhwi32o = dnnl_gOhwi32o,
1697 Goidhw16g = dnnl_Goidhw16g,
1698 IOw16o16i = dnnl_IOw16o16i,
1699 OIw16i16o = dnnl_OIw16i16o,
1700 IOw16i16o = dnnl_IOw16i16o,
1701 gIOw16i16o = dnnl_gIOw16i16o,
1702 OIw16o16i = dnnl_OIw16o16i,
1703 Oiw16o = dnnl_Oiw16o,
1704 OIw4i16o4i = dnnl_OIw4i16o4i,
1705 OIw2i8o4i = dnnl_OIw2i8o4i,
1706 OIw4i4o = dnnl_OIw4i4o,
1707 OIw4o4i = dnnl_OIw4o4i,
1709 OIw8i16o2i = dnnl_OIw8i16o2i,
1710 OIw8i8o = dnnl_OIw8i8o,
1711 OIw8o16i2o = dnnl_OIw8o16i2o,
1712 OIw8o8i = dnnl_OIw8o8i,
1713 OIw8o4i = dnnl_OIw8o4i,
1714 Owi16o = dnnl_Owi16o,
1715 OwI16o2i = dnnl_OwI16o2i,
1718 IOhw16o16i = dnnl_IOhw16o16i,
1719 Ohwi16o = dnnl_Ohwi16o,
1720 OhwI16o2i = dnnl_OhwI16o2i,
1721 Ohwi4o = dnnl_Ohwi4o,
1722 Ohwi8o = dnnl_Ohwi8o,
1723 OIhw16i16o = dnnl_OIhw16i16o,
1724 OIhw16o16i = dnnl_OIhw16o16i,
1725 Oihw16o = dnnl_Oihw16o,
1726 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1727 OIhw4i4o = dnnl_OIhw4i4o,
1728 OIhw4o4i = dnnl_OIhw4o4i,
1729 Oihw4o = dnnl_Oihw4o,
1730 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1731 OIhw8i8o = dnnl_OIhw8i8o,
1732 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1733 OIhw8o8i = dnnl_OIhw8o8i,
1734 OIhw8o4i = dnnl_OIhw8o4i,
1735 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1736 IOdhw16o16i = dnnl_IOdhw16o16i,
1737 Odhwi16o = dnnl_Odhwi16o,
1738 OdhwI16o2i = dnnl_OdhwI16o2i,
1739 Odhwi4o = dnnl_Odhwi4o,
1740 Odhwi8o = dnnl_Odhwi8o,
1741 OIdhw16i16o = dnnl_OIdhw16i16o,
1742 OIdhw16o16i = dnnl_OIdhw16o16i,
1743 Oidhw16o = dnnl_Oidhw16o,
1744 OIdhw4i4o = dnnl_OIdhw4i4o,
1745 OIdhw4o4i = dnnl_OIdhw4o4i,
1746 Oidhw4o = dnnl_Oidhw4o,
1747 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1748 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1749 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1750 OIdhw8i8o = dnnl_OIdhw8i8o,
1751 OIdhw8o8i = dnnl_OIdhw8o8i,
1752 OIdhw8o4i = dnnl_OIdhw8o4i,
1753 gIOw16o16i = dnnl_gIOw16o16i,
1754 gOIw16i16o = dnnl_gOIw16i16o,
1755 gOIw16o16i = dnnl_gOIw16o16i,
1756 gOiw16o = dnnl_gOiw16o,
1757 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1758 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1759 gOIw4i4o = dnnl_gOIw4i4o,
1760 gOIw4o4i = dnnl_gOIw4o4i,
1761 gOiw4o = dnnl_gOiw4o,
1762 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1763 gOIw8i8o = dnnl_gOIw8i8o,
1764 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1765 gOIw8o8i = dnnl_gOIw8o8i,
1766 gOIw8o4i = dnnl_gOIw8o4i,
1767 gOwi16o = dnnl_gOwi16o,
1768 gOwI16o2i = dnnl_gOwI16o2i,
1769 gOwi4o = dnnl_gOwi4o,
1770 gOwi8o = dnnl_gOwi8o,
1771 Goiw8g = dnnl_Goiw8g,
1772 Goiw16g = dnnl_Goiw16g,
1773 gIOhw16o16i = dnnl_gIOhw16o16i,
1774 gOhwi16o = dnnl_gOhwi16o,
1775 gOhwI16o2i = dnnl_gOhwI16o2i,
1776 gOhwi4o = dnnl_gOhwi4o,
1777 gOhwi8o = dnnl_gOhwi8o,
1778 Goihw16g = dnnl_Goihw16g,
1779 gOIhw16i16o = dnnl_gOIhw16i16o,
1780 gOIhw16o16i = dnnl_gOIhw16o16i,
1781 gOihw16o = dnnl_gOihw16o,
1782 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1783 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1784 gOIhw4i4o = dnnl_gOIhw4i4o,
1785 gOIhw4o4i = dnnl_gOIhw4o4i,
1786 gOihw4o = dnnl_gOihw4o,
1787 Goihw8g = dnnl_Goihw8g,
1788 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1789 gOIhw8i8o = dnnl_gOIhw8i8o,
1790 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1791 OIw4o8i8o4i = dnnl_OIw4o8i8o4i,
1792 OIdhw4o8i8o4i = dnnl_OIdhw4o8i8o4i,
1793 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1794 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1795 gOIw4o8i8o4i = dnnl_gOIw4o8i8o4i,
1796 gOIdhw4o8i8o4i = dnnl_gOIdhw4o8i8o4i,
1797 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1798 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1799 OIhw16i16o4i = dnnl_OIhw16i16o4i,
1800 OIhw16i16o2i = dnnl_OIhw16i16o2i,
1801 gOIhw16i16o4i = dnnl_gOIhw16i16o4i,
1802 gOIhw16i16o2i = dnnl_gOIhw16i16o2i,
1803 gOIhw8o8i = dnnl_gOIhw8o8i,
1804 gOIhw8o4i = dnnl_gOIhw8o4i,
1805 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1806 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1807 gOdhwi16o = dnnl_gOdhwi16o,
1808 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1809 gOdhwi4o = dnnl_gOdhwi4o,
1810 gOdhwi8o = dnnl_gOdhwi8o,
1811 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1812 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1813 gOidhw16o = dnnl_gOidhw16o,
1814 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1815 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1816 gOidhw4o = dnnl_gOidhw4o,
1817 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1818 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1819 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1820 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1821 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1822 gOIdhw8o4i = dnnl_gOIdhw8o4i,
1823 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1824 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1825 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1826 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1827 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1828 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1829 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1830 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1831 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1832 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1833 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1834 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1863 bool allow_empty =
false)
1865 validate_dims(adims);
1867 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1871 "could not construct a memory descriptor using a "
1891 bool allow_empty =
false)
1893 validate_dims(adims);
1894 if (!strides.empty()) validate_dims(strides, (
int)adims.size());
1896 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
1897 strides.empty() ?
nullptr : &strides[0]);
1900 "could not construct a memory descriptor using "
1921 bool allow_empty =
false)
const {
1922 validate_dims(adims, data.
ndims);
1923 validate_dims(offsets, data.
ndims);
1926 &sub_md, &data, adims.data(), offsets.data());
1929 return desc(sub_md);
1977 if (data.
ndims) validate_dims(adims, 1);
1980 &out_md, &data, (
int)adims.size(), adims.data());
1983 status,
"could not reshape a memory descriptor");
1984 return desc(out_md);
2025 bool allow_empty =
false)
const {
2026 validate_dims(permutation, data.
ndims);
2029 &out_md, &data, permutation.data());
2032 "could not permute axes of a memory descriptor");
2033 return desc(out_md);
2078 explicit operator bool()
const {
return data.
ndims != 0; }
2110 "could not create a memory object");
2127 "could not get a memory descriptor from a memory object");
2128 return desc(*cdesc);
2135 "could not get an engine from a memory object");
2136 return engine(c_engine,
true);
2145 "could not get a native handle from a memory object");
2180 "could not set native handle of a memory object");
2196 "could not set native handle of a memory object");
2220 template <
typename T =
void>
2224 "could not map memory object data");
2225 return static_cast<T *
>(mapped_ptr);
2240 "could not unmap memory object data");
2243 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
2244 cl_mem get_ocl_mem_object()
const {
2248 "could not get OpenCL buffer object from a memory object");
2261 "could not set OpenCL buffer object from a memory object");
2344 "post-ops index is out of range");
2381 "could not append a sum post-op");
2384 memory::convert_to_c(data_type)),
2385 "could not append a sum post-op");
2394 "could not get parameters of a sum post-op");
2406 get(), index, &scale, &c_data_type),
2407 "could not get parameters of a sum post-op");
2425 float scale,
algorithm aalgorithm,
float alpha,
float beta) {
2428 "could not append an elementwise post-op");
2439 float &alpha,
float &beta)
const {
2442 get(), index, &scale, &c_alg, &alpha, &beta),
2443 "could not get parameters of an elementwise post-op");
2477 int mask,
const std::vector<float> &scales) {
2480 memory::convert_to_c(weights_data_type),
2481 memory::convert_to_c(bias_data_type),
2482 memory::convert_to_c(dst_data_type),
2483 scales.size(), mask, &scales[0]),
2484 "could not append depthwise post-op");
2503 int &mask, std::vector<float> &scales)
const {
2510 const float *c_scales;
2512 &c_weights_data_type, &c_bias_data_type,
2513 &c_dst_data_type, &count, &c_mask, &c_scales),
2514 "could not get parameters of depthwise post-op");
2519 scales.resize(count);
2523 scales[c] = c_scales[c];
2562 int mask,
const std::vector<float> &scales) {
2565 memory::convert_to_c(weights_data_type),
2566 memory::convert_to_c(bias_data_type),
2567 memory::convert_to_c(dst_data_type),
2568 scales.size(), mask, &scales[0]),
2569 "could not append depthwise post-op");
2588 int &mask, std::vector<float> &scales)
const {
2595 const float *c_scales;
2597 &c_weights_data_type, &c_bias_data_type,
2598 &c_dst_data_type, &count, &c_mask, &c_scales),
2599 "could not get parameters of depthwise post-op");
2604 scales.resize(count);
2608 scales[c] = c_scales[c];
2629 "could not append a binary post-op");
2643 "could not get parameters of a binary post-op");
2645 src1_desc.
data = *data;
2668 "could not create primitive attribute");
2685 "could not get scratchpad mode primitive attribute");
2695 "could not set scratchpad mode primitive attribute");
2710 const float *c_scales;
2712 get(), &count, &c_mask, &c_scales),
2713 "could not get output scales primitive attribute");
2714 scales.resize(count);
2718 scales[c] = c_scales[c];
2767 "could not set output scales primitive attribute");
2781 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2784 const float *c_scales;
2786 get(), arg, &count, &c_mask, &c_scales),
2787 "could not get scales primitive attributes");
2788 scales.resize(count);
2792 scales[c] = c_scales[c];
2811 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
2814 (
dnnl_dim_t)scales.size(), mask, scales.data()),
2815 "could not set scales primitive attribute");
2829 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
2832 const int32_t *c_zero_points;
2834 get(), arg, &count, &c_mask, &c_zero_points),
2835 "could not get zero points primitive attribute");
2836 zero_points.resize(count);
2840 zero_points[c] = c_zero_points[c];
2864 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
2867 zero_points.data()),
2868 "could not set zero points primitive attribute");
2878 "could not get post-ops primitive attribute");
2893 "could not set post-ops primitive attribute");
2932 "could not set RNN data quantization parameters primitive "
2964 (
int)scales.size(), mask, scales.data()),
2965 "could not set RNN weights quantization parameters primitive "
2992 "could not retrieve implementation info string from a "
2993 "primitive descriptor");
3022 std::vector<query> valid_q {query::src_md, query::diff_src_md,
3023 query::weights_md, query::diff_weights_md, query::dst_md,
3024 query::diff_dst_md, query::workspace_md, query::scratchpad_md,
3026 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
3027 [=](
query q) { return what == q; }))
3029 "memory descriptor query is invalid");
3042 return query_md(query::src_md, idx);
3051 return query_md(query::dst_md, idx);
3060 return query_md(query::weights_md, idx);
3069 return query_md(query::diff_src_md, idx);
3078 return query_md(query::diff_dst_md, idx);
3087 return query_md(query::diff_weights_md, idx);
3134 return query_md(query::workspace_md, 0);
3143 return query_md(query::scratchpad_md, 0);
3153 "could not retrieve scratchpad engine from a primitive "
3155 return engine(c_engine,
true);
3163 "could not get attributes from a primitive descriptor");
3166 "could not clone primitive attributes");
3176 "could not get primitive kind from a primitive descriptor");
3187 "could not clone a primitive descriptor");
3240 if (pd ==
nullptr)
return;
3253 rc,
"could not get primitive kind from a primitive descriptor");
3254 if (pd_kind != c_prim_kind)
3256 "primitive descriptor operation kind mismatch");
3266 "could not get propagation kind from the primitive "
3272 && (pd_prop_kind == c_prop_kind1
3273 || pd_prop_kind == c_prop_kind2))) {
3280 "primitive descriptor propagation kind mismatch");
3326 bool allow_empty =
false) {
3330 dst_engine.
get(), attr.get());
3333 "could not create a primitive descriptor for a reorder "
3351 bool allow_empty =
false) {
3360 "could not create a primitive descriptor for a reorder "
3375 return engine::query(*
this, dnnl::query::reorder_src_engine);
3381 return engine::query(*
this, dnnl::query::reorder_dst_engine);
3434 const std::vector<memory::desc> &mems) {
3435 std::vector<dnnl_memory_desc_t> c_mems;
3436 c_mems.reserve(mems.size());
3437 for (
const auto &s : mems)
3438 c_mems.push_back(s.data);
3463 const std::vector<memory::desc> &srcs,
const engine &aengine,
3470 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3471 attr.get(), aengine.
get()),
3472 "could not create a primitive descriptor for a concat "
3490 const std::vector<memory::desc> &srcs,
const engine &aengine,
3497 (
int)c_api_srcs.size(), concat_dimension,
3498 c_api_srcs.data(), attr.get(), aengine.
get()),
3499 "could not create a primitive descriptor for a concat "
3554 const std::vector<float> &scales,
3555 const std::vector<memory::desc> &srcs,
const engine &aengine,
3557 validate_container_size(scales,
3558 "counts of scales and sources are not equal",
3559 (
int)srcs.size(), (
int)srcs.size());
3566 (
int)c_api_srcs.size(), scales.data(),
3567 c_api_srcs.data(), attr.get(), aengine.
get()),
3568 "could not create a primitive descriptor for a sum "
3584 const std::vector<memory::desc> &srcs,
const engine &aengine,
3586 validate_container_size(scales,
3587 "counts of scales and sources are not equal",
3588 (
int)srcs.size(), (
int)srcs.size());
3594 (
int)c_api_srcs.size(), scales.data(),
3595 c_api_srcs.data(), attr.get(), aengine.
get()),
3596 "could not create a primitive descriptor for a sum "
3659 bool allow_empty =
false)
3660 : allow_empty_(allow_empty) {
3663 desc, attr ? attr->
get() :
nullptr, aengine.
get(), hint_fwd_pd);
3666 status,
"could not create a primitive descriptor iterator");
3667 pd_iterator.reset(iterator);
3680 status,
"could not advance a primitive descriptor iterator");
3686 bool allow_empty_ =
false;
3690 pd_iterator.
get(allow_empty_));
3693 "could not fetch a primitive descriptor from a primitive "
3694 "descriptor iterator");
3760 &strides[0], &padding_l[0], &padding_r[0]),
3761 "could not create a descriptor for a convolution forward "
3762 "propagation primitive");
3804 &weights_desc.
data,
nullptr, &dst_desc.
data,
3805 &strides[0], &padding_l[0], &padding_r[0]),
3806 "could not create a descriptor for a convolution forward "
3807 "propagation primitive");
3854 &weights_desc.
data, &bias_desc.
data,
3855 &dst_desc.
data, &strides[0], &dilates[0],
3856 &padding_l[0], &padding_r[0]),
3857 "could not create a descriptor for a dilated convolution "
3858 "forward propagation primitive");
3903 &weights_desc.
data,
nullptr,
3904 &dst_desc.
data, &strides[0], &dilates[0],
3905 &padding_l[0], &padding_r[0]),
3906 "could not create a descriptor for a dilated convolution "
3907 "forward propagation primitive");
3927 bool allow_empty =
false)
3929 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
3943 const engine &aengine,
bool allow_empty =
false)
3945 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4025 &weights_desc.
data, &diff_dst_desc.
data,
4026 &strides[0], &padding_l[0], &padding_r[0]),
4027 "could not create a descriptor for a convolution backward "
4028 "propagation primitive");
4070 &weights_desc.
data, &diff_dst_desc.
data,
4071 &strides[0], &dilates[0], &padding_l[0],
4073 "could not create a descriptor for a dilated convolution "
4074 "backward propagation primitive");
4098 bool allow_empty =
false)
4100 hint_fwd_pd.
get(), allow_empty) {}
4119 bool allow_empty =
false)
4121 hint_fwd_pd.
get(), allow_empty) {}
4196 &diff_weights_desc.
data, &diff_bias_desc.
data,
4197 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4199 "could not create a descriptor for a convolution weights "
4200 "update primitive");
4237 &diff_weights_desc.
data,
nullptr,
4238 &diff_dst_desc.
data, &strides[0],
4239 &padding_l[0], &padding_r[0]),
4240 "could not create a descriptor for a convolution weights "
4241 "update primitive");
4286 &diff_weights_desc.
data, &diff_bias_desc.
data,
4287 &diff_dst_desc.
data, &strides[0], &dilates[0],
4288 &padding_l[0], &padding_r[0]),
4289 "could not create a descriptor for a dilated convolution "
4290 "weights gradient primitive");
4332 &diff_weights_desc.
data,
nullptr,
4333 &diff_dst_desc.
data, &strides[0], &dilates[0],
4334 &padding_l[0], &padding_r[0]),
4335 "could not create a descriptor for a dilated convolution "
4336 "weights gradient primitive");
4359 bool allow_empty =
false)
4361 hint_fwd_pd.
get(), allow_empty) {}
4379 bool allow_empty =
false)
4381 hint_fwd_pd.
get(), allow_empty) {}
4480 &strides[0], &padding_l[0], &padding_r[0]),
4481 "could not create a descriptor for a deconvolution forward "
4482 "propagation primitive");
4523 &weights_desc.
data,
nullptr, &dst_desc.
data,
4524 &strides[0], &padding_l[0], &padding_r[0]),
4525 "could not create a descriptor for a deconvolution forward "
4526 "propagation primitive");
4572 &weights_desc.
data, &bias_desc.
data,
4573 &dst_desc.
data, &strides[0], &dilates[0],
4574 &padding_l[0], &padding_r[0]),
4575 "could not create a descriptor for a dilated deconvolution "
4576 "forward propagation primitive");
4620 &weights_desc.
data,
nullptr,
4621 &dst_desc.
data, &strides[0], &dilates[0],
4622 &padding_l[0], &padding_r[0]),
4623 "could not create a descriptor for a dilated deconvolution "
4624 "forward propagation primitive");
4644 bool allow_empty =
false)
4646 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4660 const engine &aengine,
bool allow_empty =
false)
4662 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4737 &weights_desc.
data, &diff_dst_desc.
data,
4738 &strides[0], &padding_l[0], &padding_r[0]),
4739 "could not create a descriptor for a deconvolution "
4740 "backward propagation primitive");
4781 &weights_desc.
data, &diff_dst_desc.
data,
4782 &strides[0], &dilates[0], &padding_l[0],
4784 "could not create a descriptor for a dilated deconvolution "
4785 "backward propagation primitive");
4809 bool allow_empty =
false)
4811 hint_fwd_pd.
get(), allow_empty) {}
4830 bool allow_empty =
false)
4832 hint_fwd_pd.
get(), allow_empty) {}
4906 &diff_weights_desc.
data, &diff_bias_desc.
data,
4907 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4909 "could not create a descriptor for a deconvolution weights "
4910 "update primitive");
4946 &src_desc.
data, &diff_weights_desc.
data,
4947 nullptr, &diff_dst_desc.
data, &strides[0],
4948 &padding_l[0], &padding_r[0]),
4949 "could not create a descriptor for a deconvolution weights "
4950 "update primitive");
4994 &diff_weights_desc.
data, &diff_bias_desc.
data,
4995 &diff_dst_desc.
data, &strides[0], &dilates[0],
4996 &padding_l[0], &padding_r[0]),
4997 "could not create a descriptor for a dilated deconvolution "
4998 "weights gradient primitive");
5039 &diff_weights_desc.
data,
nullptr,
5040 &diff_dst_desc.
data, &strides[0], &dilates[0],
5041 &padding_l[0], &padding_r[0]),
5042 "could not create a descriptor for a dilated deconvolution "
5043 "weights gradient primitive");
5067 bool allow_empty =
false)
5069 hint_fwd_pd.
get(), allow_empty) {}
5088 bool allow_empty =
false)
5090 hint_fwd_pd.
get(), allow_empty) {}
5160 float alpha,
float beta,
float k = 1.f) {
5164 local_size, alpha, beta, k),
5165 "could not create a descriptor for a lrn forward "
5166 "propagation primitive");
5185 bool allow_empty =
false)
5187 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5200 const engine &aengine,
bool allow_empty =
false)
5202 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5254 float alpha,
float beta,
float k = 1.f) {
5257 &diff_data_desc.
data, &data_desc.
data, local_size,
5259 "could not create a descriptor for a lrn backward "
5260 "propagation primitive");
5283 bool allow_empty =
false)
5285 hint_fwd_pd.
get(), allow_empty) {}
5303 bool allow_empty =
false)
5305 hint_fwd_pd.
get(), allow_empty) {}
5387 &dst_desc.
data, &strides[0], &kernel[0],
5388 &padding_l[0], &padding_r[0]),
5389 "could not create a descriptor for a pooling forward "
5390 "propagation primitive");
5409 bool allow_empty =
false)
5411 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5424 const engine &aengine,
bool allow_empty =
false)
5426 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5496 &diff_dst_desc.
data, &strides[0], &kernel[0],
5497 &padding_l[0], &padding_r[0]),
5498 "could not create a descriptor for a pooling backward "
5499 "propagation primitive");
5522 bool allow_empty =
false)
5524 hint_fwd_pd.
get(), allow_empty) {}
5542 bool allow_empty =
false)
5544 hint_fwd_pd.
get(), allow_empty) {}
5622 &data_desc.
data, alpha, beta),
5623 "could not create a descriptor for an eltwise forward "
5624 "propagation primitive");
5644 bool allow_empty =
false)
5646 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5660 const engine &aengine,
bool allow_empty =
false)
5662 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5714 &diff_data_desc.
data, &data_desc.
data, alpha, beta),
5715 "could not create a descriptor for an eltwise backward "
5716 "propagation primitive");
5740 bool allow_empty =
false)
5742 hint_fwd_pd.
get(), allow_empty) {}
5761 bool allow_empty =
false)
5763 hint_fwd_pd.
get(), allow_empty) {}
5825 &data_desc.
data, softmax_axis),
5826 "could not create a descriptor for a softmax forward "
5827 "propagation primitive");
5847 bool allow_empty =
false)
5849 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5863 const engine &aengine,
bool allow_empty =
false)
5865 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5914 &data_desc.
data, softmax_axis),
5915 "could not create a descriptor for a softmax backward "
5916 "propagation primitive");
5940 bool allow_empty =
false)
5942 hint_fwd_pd.
get(), allow_empty) {}
5961 bool allow_empty =
false)
5963 hint_fwd_pd.
get(), allow_empty) {}
6022 int logsoftmax_axis) {
6025 &data_desc.
data, logsoftmax_axis),
6026 "could not create a descriptor for a logsoftmax forward "
6027 "propagation primitive");
6047 bool allow_empty =
false)
6049 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6063 const engine &aengine,
bool allow_empty =
false)
6065 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6115 int logsoftmax_axis) {
6117 &diff_data_desc.
data, &data_desc.
data,
6119 "could not create a descriptor for a logsoftmax backward "
6120 "propagation primitive");
6144 bool allow_empty =
false)
6146 hint_fwd_pd.
get(), allow_empty) {}
6165 bool allow_empty =
false)
6167 hint_fwd_pd.
get(), allow_empty) {}
6250 "could not create a descriptor for a batch normalization "
6251 "forward propagation primitive");
6272 bool allow_empty =
false)
6274 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6288 const engine &aengine,
bool allow_empty =
false)
6290 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6335 "could not retrieve a descriptor from a primitive "
6336 "descriptor for batch normalization forward propagation "
6376 &diff_data_desc.
data, &data_desc.
data,
6378 "could not create a descriptor for a batch normalization "
6379 "backward propagation primitive");
6404 bool allow_empty =
false)
6406 hint_fwd_pd.
get(), allow_empty) {}
6425 bool allow_empty =
false)
6427 hint_fwd_pd.
get(), allow_empty) {}
6530 "could not create a descriptor for a layer normalization "
6531 "forward propagation primitive");
6550 "could not create a descriptor for a layer normalization "
6551 "forward propagation primitive");
6572 bool allow_empty =
false)
6574 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6588 const engine &aengine,
bool allow_empty =
false)
6590 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6633 "could not retrieve a descriptor from a primitive "
6634 "descriptor for layer normalization forward propagation "
6676 &diff_data_desc.
data, &data_desc.
data,
6678 "could not create a descriptor for a batch normalization "
6679 "backward propagation primitive");
6699 &diff_data_desc.
data, &data_desc.
data,
6701 "could not create a descriptor for a batch normalization "
6702 "backward propagation primitive");
6727 bool allow_empty =
false)
6729 hint_fwd_pd.
get(), allow_empty) {}
6748 bool allow_empty =
false)
6750 hint_fwd_pd.
get(), allow_empty) {}
6840 &src_desc.
data, &weights_desc.
data,
6842 "could not create a descriptor for an inner product "
6843 "forward propagation primitive");
6865 &weights_desc.
data,
nullptr, &dst_desc.
data),
6866 "could not create a descriptor for an inner product "
6867 "forward propagation primitive");
6887 bool allow_empty =
false)
6889 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6903 const engine &aengine,
bool allow_empty =
false)
6905 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6960 &diff_src_desc.
data, &weights_desc.
data,
6961 &diff_dst_desc.
data),
6962 "could not create a descriptor for an inner product "
6963 "backward propagation primitive");
6988 bool allow_empty =
false)
6990 hint_fwd_pd.
get(), allow_empty) {}
7009 bool allow_empty =
false)
7011 hint_fwd_pd.
get(), allow_empty) {}
7065 &src_desc.
data, &diff_weights_desc.
data,
7066 &diff_bias_desc.
data, &diff_dst_desc.
data),
7067 "could not create a descriptor for an inner product "
7068 "weights gradient primitive");
7086 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
7087 &diff_dst_desc.
data),
7088 "could not create a descriptor for an inner product "
7089 "weights gradient primitive");
7113 bool allow_empty =
false)
7115 hint_fwd_pd.
get(), allow_empty) {}
7134 bool allow_empty =
false)
7136 hint_fwd_pd.
get(), allow_empty) {}
7186 using primitive_desc::primitive_desc;
7370 "could not retrieve a descriptor from a primitive descriptor "
7371 "for an RNN primitive");
7384 "mismatch between expected and provided descriptors for an "
7446 float beta = 0.0f) {
7452 &src_iter_desc.
data, &weights_layer_desc.
data,
7453 &weights_iter_desc.
data, &bias_desc.
data,
7454 &dst_layer_desc.
data, &dst_iter_desc.
data,
7456 "could not create a descriptor for a vanilla RNN forward "
7457 "propagation primitive");
7477 bool allow_empty =
false)
7479 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7493 const engine &aengine,
bool allow_empty =
false)
7495 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7626 float beta = 0.0f) {
7632 &src_iter_desc.
data, &weights_layer_desc.
data,
7633 &weights_iter_desc.
data, &bias_desc.
data,
7634 &dst_layer_desc.
data, &dst_iter_desc.
data,
7635 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7636 &diff_weights_layer_desc.
data,
7637 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7638 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7640 "could not create a descriptor for a vanilla RNN backward "
7641 "propagation primitive");
7665 bool allow_empty =
false)
7667 hint_fwd_pd.
get(), allow_empty) {}
7686 bool allow_empty =
false)
7688 hint_fwd_pd.
get(), allow_empty) {}
7850 &src_iter_desc.
data, &src_iter_c_desc.
data,
7851 &weights_layer_desc.
data, &weights_iter_desc.
data,
7852 &weights_peephole_desc.
data,
7853 &weights_projection_desc.
data, &bias_desc.
data,
7854 &dst_layer_desc.
data, &dst_iter_desc.
data,
7856 "could not create a descriptor for an LSTM forward "
7857 "propagation primitive");
7917 &src_iter_desc.
data, &src_iter_c_desc.
data,
7918 &weights_layer_desc.
data, &weights_iter_desc.
data,
7919 &weights_peephole_desc.
data, &bias_desc.
data,
7920 &dst_layer_desc.
data, &dst_iter_desc.
data,
7922 "could not create a descriptor for an LSTM forward "
7923 "propagation primitive");
7977 &src_iter_desc.
data, &src_iter_c_desc.
data,
7978 &weights_layer_desc.
data, &weights_iter_desc.
data,
7979 &bias_desc.
data, &dst_layer_desc.
data,
7980 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
7982 "could not create a descriptor for an LSTM forward "
7983 "propagation primitive");
8002 bool allow_empty =
false)
8004 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8017 const engine &aengine,
bool allow_empty =
false)
8019 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8205 &src_iter_desc.
data, &src_iter_c_desc.
data,
8206 &weights_layer_desc.
data, &weights_iter_desc.
data,
8207 &weights_peephole_desc.
data,
8208 &weights_projection_desc.
data, &bias_desc.
data,
8209 &dst_layer_desc.
data, &dst_iter_desc.
data,
8210 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8211 &diff_src_iter_desc.
data,
8212 &diff_src_iter_c_desc.
data,
8213 &diff_weights_layer_desc.
data,
8214 &diff_weights_iter_desc.
data,
8215 &diff_weights_peephole_desc.
data,
8216 &diff_weights_projection_desc.
data,
8217 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8218 &diff_dst_iter_desc.
data,
8219 &diff_dst_iter_c_desc.
data,
8221 "could not create a descriptor for an LSTM backward "
8222 "propagation primitive");
8315 &src_iter_desc.
data, &src_iter_c_desc.
data,
8316 &weights_layer_desc.
data, &weights_iter_desc.
data,
8317 &weights_peephole_desc.
data, &bias_desc.
data,
8318 &dst_layer_desc.
data, &dst_iter_desc.
data,
8319 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8320 &diff_src_iter_desc.
data,
8321 &diff_src_iter_c_desc.
data,
8322 &diff_weights_layer_desc.
data,
8323 &diff_weights_iter_desc.
data,
8324 &diff_weights_peephole_desc.
data,
8325 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8326 &diff_dst_iter_desc.
data,
8327 &diff_dst_iter_c_desc.
data,
8329 "could not create a descriptor for an LSTM backward "
8330 "propagation primitive");
8412 &src_iter_desc.
data, &src_iter_c_desc.
data,
8413 &weights_layer_desc.
data, &weights_iter_desc.
data,
8414 &bias_desc.
data, &dst_layer_desc.
data,
8415 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8416 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8417 &diff_src_iter_c_desc.
data,
8418 &diff_weights_layer_desc.
data,
8419 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8420 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8421 &diff_dst_iter_c_desc.
data,
8423 "could not create a descriptor for an LSTM backward "
8424 "propagation primitive");
8447 bool allow_empty =
false)
8449 hint_fwd_pd.
get(), allow_empty) {}
8467 bool allow_empty =
false)
8469 hint_fwd_pd.
get(), allow_empty) {}
8651 &src_iter_desc.
data, &weights_layer_desc.
data,
8652 &weights_iter_desc.
data, &bias_desc.
data,
8653 &dst_layer_desc.
data, &dst_iter_desc.
data,
8655 "could not create a descriptor for a GRU forward "
8656 "propagation primitive");
8675 bool allow_empty =
false)
8677 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8690 const engine &aengine,
bool allow_empty =
false)
8692 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8819 &src_iter_desc.
data, &weights_layer_desc.
data,
8820 &weights_iter_desc.
data, &bias_desc.
data,
8821 &dst_layer_desc.
data, &dst_iter_desc.
data,
8822 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8823 &diff_weights_layer_desc.
data,
8824 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8825 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8827 "could not create a descriptor for a GRU backward "
8828 "propagation primitive");
8851 bool allow_empty =
false)
8853 hint_fwd_pd.
get(), allow_empty) {}
8871 bool allow_empty =
false)
8873 hint_fwd_pd.
get(), allow_empty) {}
9016 &src_iter_desc.
data, &weights_layer_desc.
data,
9017 &weights_iter_desc.
data, &bias_desc.
data,
9018 &dst_layer_desc.
data, &dst_iter_desc.
data,
9020 "could not create a descriptor for an LBR GRU forward "
9021 "propagation primitive");
9041 bool allow_empty =
false)
9043 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9057 const engine &aengine,
bool allow_empty =
false)
9059 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9187 &src_iter_desc.
data, &weights_layer_desc.
data,
9188 &weights_iter_desc.
data, &bias_desc.
data,
9189 &dst_layer_desc.
data, &dst_iter_desc.
data,
9190 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9191 &diff_weights_layer_desc.
data,
9192 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9193 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9195 "could not create a descriptor for an LBR GRU backward "
9196 "propagation primitive");
9220 bool allow_empty =
false)
9222 hint_fwd_pd.
get(), allow_empty) {}
9241 bool allow_empty =
false)
9243 hint_fwd_pd.
get(), allow_empty) {}
9363 &data_desc.
data, axis, group_size),
9364 "could not create a descriptor for a shuffle forward "
9365 "propagation primitive");
9387 bool allow_empty =
false)
9389 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9434 &diff_data_desc.
data, axis, group_size),
9435 "could not create a descriptor for a shuffle backward "
9436 "propagation primitive");
9462 bool allow_empty =
false)
9464 hint_fwd_pd.
get(), allow_empty) {}
9524 "could not create a descriptor for a binary operation "
9544 bool allow_empty =
false)
9546 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9559 const engine &aengine,
bool allow_empty =
false)
9561 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9619 &weights_desc.
data,
nullptr, &dst_desc.
data),
9620 "could not create a descriptor for a matmul primitive");
9632 &weights_desc.
data, &bias_desc.
data,
9634 "could not create a descriptor for a matmul primitive");
9652 bool allow_empty =
false)
9654 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9666 const engine &aengine,
bool allow_empty =
false)
9668 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9682 return query_md(query::weights_md, 0);
9687 return query_md(query::weights_md, 1);
9741 "could not create a resampling forward descriptor");
9756 const std::vector<float> &factors,
9762 &src_desc.
data,
nullptr),
9763 "could not create a resampling forward descriptor");
9783 const std::vector<float> &factors,
const memory::desc &src_desc,
9785 if (!factors.empty())
9791 "could not create a resampling forward descriptor");
9811 bool allow_empty =
false)
9813 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9827 const engine &aengine,
bool allow_empty =
false)
9829 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9876 &diff_src_desc.
data, &diff_dst_desc.
data),
9877 "could not create a resampling backward data descriptor");
9892 if (!factors.empty())
9896 &diff_src_desc.
data, &diff_dst_desc.
data),
9897 "could not create a resampling backward data descriptor");
9921 bool allow_empty =
false)
9923 hint_fwd_pd.
get(), allow_empty) {}
9942 bool allow_empty =
false)
9944 hint_fwd_pd.
get(), allow_empty) {}
10030 &dst_desc.
data, &strides[0], &kernel[0],
10031 &dilation[0], &padding_l[0], &padding_r[0]),
10032 "could not create a descriptor for a pooling forward "
10033 "propagation primitive");
10053 bool allow_empty =
false)
10055 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10069 const engine &aengine,
bool allow_empty =
false)
10071 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10146 &diff_dst_desc.
data, &strides[0], &kernel[0],
10147 &dilation[0], &padding_l[0], &padding_r[0]),
10148 "could not create a descriptor for a pooling backward "
10149 "propagation primitive");
10174 bool allow_empty =
false)
10176 hint_fwd_pd.
get(), allow_empty) {}
10195 bool allow_empty =
false)
10197 hint_fwd_pd.
get(), allow_empty) {}
10271 &src_desc.
data, &dst_desc.
data, p, eps),
10272 "could not create a reduction descriptor");
10290 bool allow_empty =
false)
10292 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10304 const engine &aengine,
bool allow_empty =
false)
10306 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10412 return static_cast<status>(
10434 "could not get primitive cache capacity");
10441 "could not set primitive cache capacity");
10458 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10465 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10467 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10474 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10476 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10479 #if DNNL_CPU_RUNTIME == DNNL_RUNTIME_THREADPOOL
10485 return static_cast<status>(dnnl_sgemm_tp(
10486 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc, tp));
10492 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10494 return static_cast<status>(dnnl_gemm_u8s8s32_tp(transa, transb, offsetc, M,
10495 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10502 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10504 return static_cast<status>(dnnl_gemm_s8s8s32_tp(transa, transb, offsetc, M,
10505 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10517 "could not create a primitive");
10523 inline void primitive::execute(
const stream &astream,
10524 const std::unordered_map<int, memory> &args)
const {
10525 std::vector<dnnl_exec_arg_t> c_args;
10526 c_args.reserve(args.size());
10527 for (
const auto &a : args)
10528 c_args.push_back({a.first, a.second.get(
true)});
10531 (
int)c_args.size(), c_args.data()),
10532 "could not execute a primitive");
10537 #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:6986
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2240
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2252
void set_data_handle(void *handle) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2193
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:7735
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:10471
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:9859
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4860
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9571
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1935
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3965
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:2929
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6648
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:7610
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7782
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2325
@ 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:7344
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:7224
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:5991
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5976
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:10108
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8724
@ 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:4670
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:913
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5219
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9530
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:709
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:915
convolution_backward_data()=default
Default constructor. Produces an empty object.
void execute(const stream &astream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
@ all
Any ISA (excepting those listed as initial support)
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8603
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:2054
Reorder primitive.
Definition: dnnl.hpp:3298
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2264
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9419
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6818
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7719
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:9067
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8586
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6788
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7727
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8950
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:8935
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:2586
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:373
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9026
Convolution weights gradient primitive.
Definition: dnnl.hpp:4153
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:973
An execution stream.
Definition: dnnl.hpp:1069
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:1907
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:2501
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:4643
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:4512
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:4357
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:5938
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Constructs a descriptor for an inner product forward propagation primitive with bias.
Definition: dnnl.hpp:6835
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2241
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
prop_kind
Propagation kind.
Definition: dnnl.hpp:440
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5443
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2337
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:9674
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:9543
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:837
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
An opaque structure to describe a memory.
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:211
Softmax backward propagation primitive.
Definition: dnnl.hpp:5895
Primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10277
primitive_desc()=default
Default constructor. Produces an empty object.
An opaque structure to describe a primitive descriptor iterator.
pooling_v2_backward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10227
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:833
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7553
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:7198
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2272
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:10462
Descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7555
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5318
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9117
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:2041
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9678
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7988
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5333
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a dilated convolution forward propagation primitive without bias.
Definition: dnnl.hpp:3891
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2059
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:5738
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:927
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:6859
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:7284
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2251
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3374
memory(const desc &md, const engine &aengine)
Constructs a memory object.
Definition: dnnl.hpp:2120
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8714
#define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:2071
An execution engine.
Definition: dnnl.hpp:866
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:6244
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:3605
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5560
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:5771
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:6937
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:2828
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:827
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution backward propagation primitive from a C API pri...
Definition: dnnl.hpp:4840
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:996
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:5140
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7152
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5694
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:9952
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2269
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:2027
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &dilation, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10016
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1047
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1940
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8551
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:8706
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2329
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:10382
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5504
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8894
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6802
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:1841
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8074
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8752
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:9040
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:3349
An opaque structure to describe an engine.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6774
primitive_desc()=default
Default constructor. Produces an empty object.
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5688
Reduction.
Definition: dnnl.hpp:10242
logsoftmax_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_binary(const_dnnl_post_ops_t post_ops, int index, dnnl_alg_kind_t *alg_kind, const dnnl_memory_desc_t **src1_desc)
Returns the parameters of a binary post-op.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7538
const dnnl_version_t DNNL_API * dnnl_version()
Returns library version information.
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:9717
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5782
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1139
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:874
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1778
@ shuffle
A shuffle primitive.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8719
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:7308
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:882
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5971
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4134
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:2377
@ none
Use no normalization flags.
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:987
pooling_v2_forward()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8581
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9277
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:921
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9810
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3068
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5692
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:8289
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:815
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2261
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:2024
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9605
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9957
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8500
desc()=default
Default constructor. Produces an empty object.
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7236
A descriptor of a convolution operation.
Definition: dnnl_types.h:1277
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4137
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:4096
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3959
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7296
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6442
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:809
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5599
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5563
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:4116
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:5106
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1648
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:927
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
dnnl_status_t DNNL_API dnnl_memory_desc_reshape(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, int ndims, const dnnl_dims_t dims)
Initializes a memory descriptor by reshaping an existing one.
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2302
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2231
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:6073
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:9837
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:2560
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:1920
void set_threadpool(threadpool_iface *threadpool)
Sets the threadpool attribute.
Definition: dnnl.hpp:1049
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:655
A descriptor for an RNN operation.
Definition: dnnl_types.h:1670
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1654
desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8038
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:10387
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:6062
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:819
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:890
void set_data_handle(void *handle, const stream &astream) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2177
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:4389
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9607
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7171
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8735
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:9397
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5171
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:9472
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:802
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3050
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3675
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:9320
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6608
A descriptor of an inner product operation.
Definition: dnnl_types.h:1614
void set_ocl_mem_object(cl_mem mem_object)
Sets the OpenCL memory object mem_object associated with the memory.
Definition: dnnl.hpp:2259
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8069
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7094
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:6598
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1870
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:5446
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6005
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:8799
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:8177
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:8920
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3612
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:9889
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7324
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:9782
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5601
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:2040
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:7696
LSTM backward propagation primitive.
Definition: dnnl.hpp:8097
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6509
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5679
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2283
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:9919
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:8746
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:6758
Descriptor for reduction.
Definition: dnnl.hpp:10244
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2254
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:892
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9086
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8495
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5455
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:825
GRU forward propagation primitive.
Definition: dnnl.hpp:8601
kind
Kinds of engines.
Definition: dnnl.hpp:871
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9310
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6454
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7517
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:8700
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:7833
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8482
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6322
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:9987
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:7039
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:868
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9589
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:884
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2407
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9073
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:981
lstm_backward()=default
Default constructor. Produces an empty object.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:217
reduction(const primitive_desc &pd)
Constructs a reduction primitive.
Definition: dnnl.hpp:10327
stream()=default
Constructs an empty stream.
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:888
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9331
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:1234
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:3793
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:9519
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10411
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1673
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6184
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:6287
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8429
@ pooling
A pooling primitive.
Primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10155
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7030
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:3160
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8904
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:3508
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:5184
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:9218
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:792
dnnl_status_t DNNL_API dnnl_pooling_v2_backward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) backward propagation primitiv...
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4727
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2249
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2284
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2274
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7276
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2692
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:406
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5557
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2268
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7514
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:2139
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1650
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:549
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2259
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8945
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9796
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:8638
@ 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:2422
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6318
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5216
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:3148
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2151
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) backward propagation primitive.
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8566
sum()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7740
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7730
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5231
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const batch_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6422
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7527
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:3539
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:7962
deconvolution_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:899
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:1661
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:3405
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3103
A descriptor of a pooling operation.
Definition: dnnl_types.h:1435
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6507
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4394
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5103
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:2863
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2127
A container for stream attributes.
Definition: dnnl.hpp:1024
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:6694
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:3323
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:938
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7722
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:3942
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:3842
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product descriptor weights update primitive with bias.
Definition: dnnl.hpp:7059
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:937
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:9902
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3127
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:2891
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:979
dnnl_status_t DNNL_API dnnl_primitive_attr_create(dnnl_primitive_attr_t *attr)
Creates an empty (default) primitive attributes with all the parameters set to their default values.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10068
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:8881
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_weights_projection_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or with out recurrent project...
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:955
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &dilation, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10134
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:2475
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5629
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:3172
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_zero_points(const_dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const int32_t **zero_points)
Returns count, correspondence zero point mask, and a pointer to a constant int32_t array of zero_poin...
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:959
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum_v2(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_data_type_t *data_type)
Returns the parameters of an accumulation (sum) post-op with a data type parameter.
@ resampling
A resampling primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_output_scales(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets output scaling factors correspondence mask and values.
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_create(dnnl_primitive_desc_iterator_t *iterator, const_dnnl_op_desc_t op_desc, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine, const_dnnl_primitive_desc_t hint_forward_primitive_desc)
Creates a primitive descriptor iterator.
desc(prop_kind aprop_kind, algorithm aalgorithm, const std::vector< float > &factors, const memory::desc &src_desc)
Constructs a descriptor for a resampling forward propagation primitive using source memory descriptor...
Definition: dnnl.hpp:9755
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:1022
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:905
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9201
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5142
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5832
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2267
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:7437
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5321
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:5210
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:4769
Pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:9985
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:6902
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3388
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:10431
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3385
Post-ops.
Definition: dnnl.hpp:2325
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
cl_device_id get_ocl_device() const
Returns the OpenCL device associated with the engine.
Definition: dnnl.hpp:957
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:965
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7024
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3109
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8940
lstm_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:3133
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6557
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:788
query
Primitive descriptor query specification.
Definition: dnnl.hpp:742
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8732
dnnl_status_t DNNL_API dnnl_primitive_desc_query(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index, void *result)
Queries a primitive descriptor for various pieces of information.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a reduction primitive from a C API primitive descriptor that mu...
Definition: dnnl.hpp:10312
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:880
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1035
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2145
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:2403
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9081
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6199
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:4864
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9099
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6919
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:5910
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:2160
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:8445
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2065
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7212
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3444
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:6101
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:866
Convolution forward propagation primitive.
Definition: dnnl.hpp:3712
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6187
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6356
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:567
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6225
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:1864
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:843
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7750
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6785
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:876
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:99
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8907
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10211
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5440
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:182
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:579
desc(prop_kind aprop_kind, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization forward propagation primitive.
Definition: dnnl.hpp:6544
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:7045
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1205
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:2305
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:5805
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:829
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6354
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2265
dnnl_status_t DNNL_API dnnl_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution backward propagation primitive.
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:798
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6305
dnnl_status_t DNNL_API dnnl_reduction_desc_init(dnnl_reduction_desc_t *desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, float p, float eps)
Initializes a descriptor for a reduction primitive.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7027
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1405
@ undef
Undefined algorithm.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6587
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:9238
@ 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:2417
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:5376
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:7549
@ 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:186
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for pooling backward propagation primitive.
Definition: dnnl.hpp:5485
data_type
Data type specification.
Definition: dnnl.hpp:1240
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:8868
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:4807
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:5313
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:5300
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8967
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:948
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:7476
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:8464
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4341
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6448
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8056
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:9167
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:7302
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:6114
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:2018
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5395
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:971
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:555
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:933
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:5873
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:6745
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:939
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2100
dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(const_dnnl_primitive_desc_t primitive_desc, const_dnnl_primitive_attr_t *attr)
Returns a constant reference to the attributes of a primitive descriptor.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10316
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:983
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1666
@ 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:2121
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:8082
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:909
void set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
Definition: dnnl.hpp:10439
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8077
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4629
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:9665
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:967
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8531
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6777
@ undef
Undefined primitive.
Resampling forward propagation.
Definition: dnnl.hpp:9715
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:9872
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2124
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9406
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7330
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
dnnl_engine_kind_t convert_to_c(engine::kind akind)
Converts engine kind enum value from C++ API to C API type.
Definition: dnnl.hpp:994
Inner product weights gradient primitive.
Definition: dnnl.hpp:7043
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6617
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:9969
@ layer_normalization
A layer normalization primitive.
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:975
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7218
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1315
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2273
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:2238
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:2115
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8711
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:2003
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1907
stream_attr(engine::kind akind)
Constructs stream attributes for a stream that runs on an engine of a particular kind.
Definition: dnnl.hpp:1034
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2271
#define DNNL_MEMORY_ALLOCATE
Special pointer value that indicates that the library needs to allocate an underlying buffer for a me...
Definition: dnnl_types.h:1253
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:951
dnnl_status_t DNNL_API dnnl_lbr_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:796
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9846
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:197
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &data_desc, memory::dim local_size, float alpha, float beta, float k=1.f)
Constructs a descriptor for a LRN forward propagation primitive.
Definition: dnnl.hpp:5158
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:4376
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:612
Inner product backward propagation primitive.
Definition: dnnl.hpp:6941
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1009
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
Constructs a descriptor for a convolution forward propagation primitive with bias.
Definition: dnnl.hpp:3747
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:9699
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:935
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6462
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:6298
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:817
Inner product forward propagation primitive.
Definition: dnnl.hpp:6816
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4848
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2285
@ 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:6099
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:835
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8833
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:10038
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4676
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:9315
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1208
dnnl_status_t DNNL_API dnnl_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution weights gradient primitive.
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc)
Constructs a descriptor for an inner product descriptor weights update primitive without bias.
Definition: dnnl.hpp:7081
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:5520
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7745
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:9251
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:2074
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
An opaque structure to describe a primitive.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution weights gradient primitive from a C API primiti...
Definition: dnnl.hpp:5098
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4851
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:8027
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:6571
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5222
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:1095
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2386
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:8061
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2258
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7701
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:9459
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:2811
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:369
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3912
@ 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:7230
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1079
dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(const_dnnl_memory_t memory, const dnnl_memory_desc_t **memory_desc)
Returns the memory descriptor for a memory object.
primitive_desc(const desc &adesc, const engine &aengine, const layer_normalization_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6725
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:8915
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5676
dnnl_status_t DNNL_API dnnl_resampling_backward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes a descriptor for resampling backward propagation primitive.
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s1p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 1.
desc(prop_kind aprop_kind, const memory::desc &data_desc, int softmax_axis)
Constructs a descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5821
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:7706
desc(const dims &adims, data_type adata_type, const dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:1890
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6654
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8899
@ 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:6162
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2286
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8033
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9691
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5776
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:427
handle()=default
Constructs an empty handle object.
primitive_desc()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:9855
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2260
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2035
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:8016
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:845
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a convolution forward propagation primitive from a C API primit...
Definition: dnnl.hpp:3953
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:9003
@ 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:2157
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:870
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7270
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:813
void append_binary(algorithm aalgorithm, const memory::desc &src1_desc)
Appends a binary post-op.
Definition: dnnl.hpp:2626
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9639
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const pooling_v2_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10192
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6257
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:9686
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:1513
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2311
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:5065
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:2053
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1330
primitive_desc(const desc &adesc, const engine &aengine, const logsoftmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6142
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10214
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8490
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:4273
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6385
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6086
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2276
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3446
gru_backward()=default
Default constructor. Produces an empty object.
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:800
softmax_backward()=default
Default constructor. Produces an empty object.
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2354
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1544
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3121
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3115
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:925
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6652
@ 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:8661
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
Pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10106
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:6175
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7765
softmax_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum_v2(dnnl_post_ops_t post_ops, float scale, dnnl_data_type_t data_type)
Appends an accumulation v2 (sum) to post-ops.
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1352
dnnl_status_t DNNL_API dnnl_eltwise_forward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise forward propagation primitive.
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3077
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:963
layer_normalization_backward()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7264
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:6402
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6611
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:839
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7535
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4397
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:4402
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8505
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:10377
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:6523
desc reshape(const dims &adims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:1976
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2238
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9577
Pooling forward propagation primitive.
Definition: dnnl.hpp:5347
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2389
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
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:10454
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:3000
status
Status values returned by the library functions.
Definition: dnnl.hpp:10344
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9119
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:6768
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:971
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2395
@ 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:2412
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:3489
Convolution backward propagation primitive.
Definition: dnnl.hpp:3984
int ndims
Number of dimensions.
Definition: dnnl_types.h:1190
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7256
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:3097
primitive_desc()=default
Default constructor. Produces an empty object.
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1577
cpu_isa get_effective_cpu_isa()
Gets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10417
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3300
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9477
Elementwise binary operator primitive.
Definition: dnnl.hpp:9503
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5237
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:4937
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4685
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:6943
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:907
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
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:9282
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:923
oneDNN exception class.
Definition: dnnl.hpp:91
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6614
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10086
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:9735
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:929
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6620
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8930
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:2046
@ pooling_v2
A pooling version 2 primitive.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
desc(const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Constructs a descriptor for a matmul primitive.
Definition: dnnl.hpp:9629
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1222
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:4827
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:7503
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:3462
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7157
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8523
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:5048
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:5423
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:823
dnnl_status_t DNNL_API dnnl_inner_product_backward_data_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product backward propagation.
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2707
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10089
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:5199
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:6765
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:8571
Pooling backward propagation primitive.
Definition: dnnl.hpp:5459
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4845
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2309
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6922
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3630
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8597
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization backward propagation primitive.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive fr...
Definition: dnnl.hpp:10080
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:9580
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:5882
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:7111
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9305
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7315
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:821
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7760
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:1073
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7290
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10092
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6470
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:8477
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:5552
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:9432
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:5324
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:5779
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6780
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10217
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:4981
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:7160
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:4560
dnnl_status_t DNNL_API dnnl_stream_get_engine(const_dnnl_stream_t stream, dnnl_engine_t *engine)
Returns the engine of a stream object.
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:831
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7755
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:2280
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:4058
@ 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:2402
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9300
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8925
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6190
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2677
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5572
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9347
void execute(const stream &astream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3417
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9403
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3515
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1918
Primitive attributes.
Definition: dnnl.hpp:2661
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:5891
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9285
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:7131
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6925
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9261
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
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10289
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9489
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6969
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:2234
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:2094
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2263
A descriptor of resampling operation.
Definition: dnnl_types.h:1800
@ 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:9102
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3987
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:919
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9422
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5879
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1868
Memory object.
Definition: dnnl.hpp:1220
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.
pooling_v2_backward()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7338
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:2781
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:4895
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2232
@ undef
Undefined RNN flags.
eltwise_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:903
static void wrap_c_api(dnnl_status_t status, const char *message)
A convenience function for wrapping calls to C API functions.
Definition: dnnl.hpp:110
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:5791
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:9558
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:8689
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3086
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8518
@ 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:6465
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution weights gradient primitive.
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
primitive(const_dnnl_primitive_desc_t c_pd)
Constructs a primitive from a C API primitive descriptor.
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:10362
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2106
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6308
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6872
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:5252
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:9385
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8561
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3041
Abstract threadpool interface.
Definition: dnnl_threadpool_iface.hpp:27
reduction()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
primitive_desc(const memory::desc &dst, const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3553
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8046
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:961
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an inner product weights update primitive from a C API primitiv...
Definition: dnnl.hpp:7144
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6227
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:9567
dnnl_status_t DNNL_API dnnl_memory_create(dnnl_memory_t *memory, const dnnl_memory_desc_t *memory_desc, dnnl_engine_t engine, void *handle)
Creates a memory object.
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:911
dnnl_status_t DNNL_API dnnl_pooling_forward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7709
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:9264
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:5027
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7204
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:4149
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:9939
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6451
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:4659
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8965
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9960
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6479
Memory descriptor.
Definition: dnnl_types.h:1188
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:804
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10303
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7522
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8041
memory(const desc &md, const engine &aengine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:2106
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:847
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7242
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2763
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4419
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:5958
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6095
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:3971
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:6021
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2384
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2012
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:6928
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:2073
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5461
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9370
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:4228
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:4185
batch_normalization_forward()=default
Default constructor. Produces an empty object.
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, float p, float eps)
Constructs a descriptor for a reduction primitive using algorithm specific parameters,...
Definition: dnnl.hpp:10267
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:7006
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4682
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7394
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:9507
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:8674
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:564
@ scratchpad_engine
scratchpad engine
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8536
dnnl_status_t DNNL_API dnnl_pooling_v2_forward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) forward propagation primitive...
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9274
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7149
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:3184
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6708
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:3142
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization forward propagation primitive.
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:561
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9441
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:4790
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2392
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2262
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:4408
engine(kind akind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:899
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9505
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4866
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:957
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive f...
Definition: dnnl.hpp:10206
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3512
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7250
A descriptor of reduction operation.
Definition: dnnl_types.h:1828
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:3059
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9290
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2237
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1225
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5921
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4698
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6314
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8576
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:5862
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:2874
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7509
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6886
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8727
A memory descriptor.
Definition: dnnl.hpp:1838
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3962
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:8001
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:861
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:872
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1265
@ dnnl_cpu_isa_avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2399
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6771
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:1119
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:5408
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:2132
format_kind
Memory format kind.
Definition: dnnl.hpp:1259
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:894
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:3980
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:2065
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9345
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9113
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:9826
dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const int32_t *zero_points)
Sets primitive attributes zero points for primitive operations for a given memory argument.
matmul()=default
Default constructor. Produces an empty object.
lbr_gru_forward()=default
Default constructor. Produces an empty object.
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or without recurrent projecti...
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3714
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:9615
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:2059
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1664
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:8093
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8556
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8066
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:886
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:573
oneDNN namespace
Definition: dnnl.hpp:81
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:943
@ logsoftmax
A logsoftmax primitive.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9091
@ 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:9681
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4155
@ impl_info_str
implementation name
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4700
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9094
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:5659
A descriptor of a binary operation.
Definition: dnnl_types.h:1752
pooling_forward()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9269
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3380
@ 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:7663
dnnl_status_t DNNL_API dnnl_post_ops_append_binary(dnnl_post_ops_t post_ops, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src1_desc)
Appends a binary post-op.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const pooling_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5539
primitive_desc()=default
Default constructor. Produces an empty object.
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2142
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:864
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3926
dnnl_primitive_kind_t DNNL_API dnnl_post_ops_get_kind(const_dnnl_post_ops_t post_ops, int index)
Returns the kind of a post-op entry.
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:969
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3620
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3523
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2281
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
void get_params_eltwise(int index, float &scale, algorithm &aalgorithm, float &alpha, float &beta) const
Returns parameters of an elementwise post-op.
Definition: dnnl.hpp:2438
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7392
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9256
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:9056
cl_command_queue get_ocl_command_queue() const
Returns the underlying OpenCL queue object.
Definition: dnnl.hpp:1129
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7776
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9480
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:5616
void get_params_binary(int index, algorithm &aalgorithm, memory::desc &src1_desc) const
Returns the parameters of a binary post-op.
Definition: dnnl.hpp:2637
A descriptor of a pooling operation.
Definition: dnnl_types.h:1473
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4694
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:10367
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:794
binary()=default
Default constructor. Produces an empty object.
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3396
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:6913
desc(const dims &adims, data_type adata_type, format_tag aformat_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:1862
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:6956
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:2342
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9078
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:475
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4079
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8526
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:785
dnnl_status_t DNNL_API dnnl_resampling_forward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a resampling forward propagation primitive.
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, const memory::desc &stat_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization backward propagation primitive.
Definition: dnnl.hpp:6670
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6445
primitive_desc()=default
Default constructor. Produces an empty object.
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:380
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:5114
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10319
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:5846
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1676
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:7901
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9295
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:2235
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1656
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:5349
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:3369
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5721
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6007
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:878
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9574
@ 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:2221
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4140
threadpool_iface * get_threadpool()
Returns the threadpool attribute.
Definition: dnnl.hpp:1059
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:853
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6350
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8541
primitive_desc()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9415
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:3609
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:7683
dnnl_status_t DNNL_API dnnl_layer_normalization_forward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for layer normalization forward propagation primitive.
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:576
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2681
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN weights tensors.
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(dnnl_primitive_attr_t attr, const_dnnl_post_ops_t post_ops)
Sets primitive attributes post-ops.
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:1845
@ 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:2424
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:7492
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:941
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1866
lrn_backward()=default
Default constructor. Produces an empty object.
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7185
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2665
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:552
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5265
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:849
LSTM forward propagation primitive.
Definition: dnnl.hpp:7780
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:7019
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2392
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:2984
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:977
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:782
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8886
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:2988
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2287
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:4467
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8051
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6311
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:3021
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:5643
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6457
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:6371
dnnl_status_t DNNL_API dnnl_dilated_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution forward propagation primitive.
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:901
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4679
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:2282
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10052
primitive_desc(const desc &adesc, const engine &aengine, const pooling_v2_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10172
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6793
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:3583
@ default_flags
Default stream configuration.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5125
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9651
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:5281
Base class for all primitive descriptors.
Definition: dnnl.hpp:2976
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5897
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:4608
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:6271
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:2266
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:8849
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:917
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9843
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:4129
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8099
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
pooling_v2_forward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10102
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:10372
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8912
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5982
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7530
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4433
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5235
@ 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:8388
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6083
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:1679
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5979
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5807
shuffle_backward()=default
Default constructor. Produces an empty object.
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:811
desc(prop_kind aprop_kind, const memory::desc &data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9359
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:8546
Primitive descriptor for an RNN backward propagation primitive.
Definition: dnnl.hpp:7646
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3537
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6032
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:8510
layer_normalization_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:890
handle(const handle< T, traits > &)=default
Copy constructor.
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8891
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:5708
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7462
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:5434
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:2006
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1658
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:6046
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:8961
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5111
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6605
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6125
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2246
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:4015
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:851
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:2962
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_alg_kind_t *alg_kind, float *alpha, float *beta)
Returns the parameters of an elementwise post-op.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:2029
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:4320
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9861
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:5085
GRU backward propagation primitive.
Definition: dnnl.hpp:8750
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:5758
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2288
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8515
memory()=default
Default constructor.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8487
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4435
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:6435
@ primitive_kind
primitive kind
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:931
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:953
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an eltwise forward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5670
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7714
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.