20 #ifndef ONEAPI_DNNL_DNNL_HPP
21 #define ONEAPI_DNNL_DNNL_HPP
23 #include "oneapi/dnnl/dnnl_config.h"
32 #include <unordered_map>
42 #ifndef DNNL_ENABLE_EXCEPTIONS
43 #if __cpp_exceptions || __EXCEPTIONS \
44 || (defined(_MSC_VER) && !defined(__clang__))
45 #define DNNL_ENABLE_EXCEPTIONS 1
47 #define DNNL_ENABLE_EXCEPTIONS 0
51 #if defined(__GNUC__) || defined(__clang__)
52 #define DNNL_TRAP() __builtin_trap()
53 #elif defined(__INTEL_COMPILER) || defined(_MSC_VER)
54 #define DNNL_TRAP() __debugbreak()
56 #error "unknown compiler"
59 #if DNNL_ENABLE_EXCEPTIONS
60 #define DNNL_THROW_ERROR(status, msg) throw error(status, msg)
63 #define DNNL_THROW_ERROR(status, msg) \
84 struct error :
public std::exception {
96 const char *
what() const noexcept
override {
return message; }
109 template <
typename T>
110 void validate_container_size(
const T &v,
const char *error_message,
111 int min_size = 1,
int max_size = -1) {
112 const int size = (int)v.size();
113 if (size < min_size || (max_size >= 0 && size > max_size))
119 template <
typename T>
135 template <
typename T,
typename traits = handle_traits<T>>
139 std::shared_ptr<typename std::remove_pointer<T>::type> data_ {0};
142 bool operator==(
const T other)
const {
return other == data_.get(); }
143 bool operator!=(
const T other)
const {
return !(*
this == other); }
176 void reset(T t,
bool weak =
false) {
177 data_.reset(t, weak ? &dummy_destructor : traits::destructor);
185 T
get(
bool allow_empty =
false)
const {
186 T result = data_.get();
187 if (allow_empty ==
false && result ==
nullptr)
197 explicit operator T()
const {
return get(
true); }
202 explicit operator bool()
const {
return get(
true) !=
nullptr; }
211 return other.data_.get() == data_.get();
257 struct primitive_desc;
357 const std::unordered_map<int, memory> &args)
const;
371 "could not get a primitive descriptor from a primitive");
382 "could not get a primitive kind from a primitive descriptor");
472 undef = dnnl_alg_kind_undef,
670 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
671 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
672 return static_cast<enum_name>( \
673 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
676 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
677 return static_cast<enum_name>( \
678 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
681 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
682 return static_cast<enum_name>( \
683 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
686 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
687 lhs = static_cast<enum_name>( \
688 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
692 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
693 lhs = static_cast<enum_name>( \
694 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
698 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
699 lhs = static_cast<enum_name>( \
700 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
704 inline enum_name operator~(enum_name rhs) { \
705 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
906 "could not create an engine");
919 "could not get an engine from a primitive_desc");
920 reset(c_engine,
true);
928 "could not get kind of an engine");
937 template <
typename primitive_desc>
947 template <
typename primitive_desc>
952 "could not get an engine from a primitive_desc");
953 return engine(c_engine,
true);
1011 "could not create a stream");
1019 "could not get an engine from a stream object");
1020 return engine(c_engine,
true);
1123 template <
typename T>
1125 validate_container_size(
1433 AB16b16a = dnnl_AB16b16a,
1434 AB16b32a = dnnl_AB16b32a,
1435 AB16b64a = dnnl_AB16b64a,
1436 AB8b16a2b = dnnl_AB8b16a2b,
1437 AB8b32a2b = dnnl_AB8b32a2b,
1438 AB8b64a2b = dnnl_AB8b64a2b,
1439 AB4b16a4b = dnnl_AB4b16a4b,
1440 AB4b32a4b = dnnl_AB4b32a4b,
1441 AB4b64a4b = dnnl_AB4b64a4b,
1442 AB16b16a4b = dnnl_AB16b16a4b,
1443 Abc16a = dnnl_Abc16a,
1444 ABc16a16b = dnnl_ABc16a16b,
1445 ABc4a4b = dnnl_ABc4a4b,
1448 ABc16b16a = dnnl_ABc16b16a,
1449 ABc16b32a = dnnl_ABc16b32a,
1450 ABc16b64a = dnnl_ABc16b64a,
1453 ABc4b16a4b = dnnl_ABc4b16a4b,
1454 ABc4b32a4b = dnnl_ABc4b32a4b,
1455 ABc4b64a4b = dnnl_ABc4b64a4b,
1456 ABc2b8a4b = dnnl_ABc2b8a4b,
1457 ABc16a16b2a = dnnl_ABc16a16b2a,
1458 ABc16b16a4b = dnnl_ABc16b16a4b,
1459 ABc16b16a2b = dnnl_ABc16b16a2b,
1460 ABc4b4a = dnnl_ABc4b4a,
1461 ABc8a16b2a = dnnl_ABc8a16b2a,
1462 ABc8a8b = dnnl_ABc8a8b,
1463 ABc8a4b = dnnl_ABc8a4b,
1465 ABc8b16a2b = dnnl_ABc8b16a2b,
1466 ABc8b32a2b = dnnl_ABc8b32a2b,
1467 ABc8b64a2b = dnnl_ABc8b64a2b,
1468 ABc8b8a = dnnl_ABc8b8a,
1469 Abcd8a = dnnl_Abcd8a,
1470 Abcd16a = dnnl_Abcd16a,
1471 Abcd32a = dnnl_Abcd32a,
1472 ABcd16a16b = dnnl_ABcd16a16b,
1475 ABcd16b16a = dnnl_ABcd16b16a,
1476 ABcd16b32a = dnnl_ABcd16b32a,
1477 ABcd16b64a = dnnl_ABcd16b64a,
1478 aBCd16b16c = dnnl_aBCd16b16c,
1479 aBCd16c16b = dnnl_aBCd16c16b,
1480 Abcd4a = dnnl_Abcd4a,
1482 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1483 ABcd4b32a4b = dnnl_ABcd4b32a4b,
1484 ABcd4b64a4b = dnnl_ABcd4b64a4b,
1485 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1486 ABcd4b4a = dnnl_ABcd4b4a,
1487 ABcd4a4b = dnnl_ABcd4a4b,
1488 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1489 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1490 ABcd16a16b2a = dnnl_ABcd16a16b2a,
1491 ABcd16b16a4b = dnnl_ABcd16b16a4b,
1492 ABcd16b16a2b = dnnl_ABcd16b16a2b,
1493 aBCd16b16c2b = dnnl_aBCd16b16c2b,
1494 aBCd16c16b4c = dnnl_aBCd16c16b4c,
1495 aBCd16c16b2c = dnnl_aBCd16c16b2c,
1496 aBCd4c4b = dnnl_aBCd4c4b,
1497 aBCd4b4c = dnnl_aBCd4b4c,
1498 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1499 ABcd8a8b = dnnl_ABcd8a8b,
1500 ABcd8a4b = dnnl_ABcd8a4b,
1503 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1504 ABcd8b32a2b = dnnl_ABcd8b32a2b,
1505 ABcd8b64a2b = dnnl_ABcd8b64a2b,
1506 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1509 aBCd8b8c = dnnl_aBCd8b8c,
1510 aBCd8b4c = dnnl_aBCd8b4c,
1511 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1512 aBCd8c8b = dnnl_aBCd8c8b,
1513 Abcde16a = dnnl_Abcde16a,
1514 Abcde32a = dnnl_Abcde32a,
1515 ABcde16a16b = dnnl_ABcde16a16b,
1518 ABcde16b16a = dnnl_ABcde16b16a,
1519 ABcde16b32a = dnnl_ABcde16b32a,
1520 ABcde16b64a = dnnl_ABcde16b64a,
1521 aBCde16b16c = dnnl_aBCde16b16c,
1522 aBCde16c16b = dnnl_aBCde16c16b,
1523 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1524 Abcde4a = dnnl_Abcde4a,
1526 ABcde4b4a = dnnl_ABcde4b4a,
1527 ABcde4a4b = dnnl_ABcde4a4b,
1528 aBCde4b4c = dnnl_aBCde4b4c,
1529 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1530 aBCde16b16c2b = dnnl_aBCde16b16c2b,
1531 aBCde16c16b4c = dnnl_aBCde16c16b4c,
1532 aBCde16c16b2c = dnnl_aBCde16c16b2c,
1533 aBCdef16c16b2c = dnnl_aBCdef16c16b2c,
1534 aBCde4c4b = dnnl_aBCde4c4b,
1535 Abcde8a = dnnl_Abcde8a,
1536 ABcde8a8b = dnnl_ABcde8a8b,
1537 ABcde8a4b = dnnl_ABcde8a4b,
1539 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1540 ABcde8b32a2b = dnnl_ABcde8b32a2b,
1541 ABcde8b64a2b = dnnl_ABcde8b64a2b,
1543 ABcde4b32a4b = dnnl_ABcde4b32a4b,
1544 ABcde4b64a4b = dnnl_ABcde4b64a4b,
1545 ABcde16b16a4b = dnnl_ABcde16b16a4b,
1546 ABcde16b16a2b = dnnl_ABcde16b16a2b,
1548 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1549 ABcde8b8a = dnnl_ABcde8b8a,
1550 aBCde8b8c = dnnl_aBCde8b8c,
1551 aBCde8b4c = dnnl_aBCde8b4c,
1552 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1553 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1554 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1555 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1556 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1557 aBCde8c8b = dnnl_aBCde8c8b,
1559 aBCdef16b16c = dnnl_aBCdef16b16c,
1560 aBCdef16c16b = dnnl_aBCdef16c16b,
1563 aBCdef4c4b = dnnl_aBCdef4c4b,
1564 aBCdef4b4c = dnnl_aBCdef4b4c,
1565 aBCdef8b8c = dnnl_aBCdef8b8c,
1566 aBCdef8b4c = dnnl_aBCdef8b4c,
1567 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1568 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1569 aBCdef8c8b = dnnl_aBCdef8c8b,
1570 aBdc16b = dnnl_aBdc16b,
1571 aBdc4b = dnnl_aBdc4b,
1572 aBdc8b = dnnl_aBdc8b,
1573 aBdec16b = dnnl_aBdec16b,
1574 aBdec4b = dnnl_aBdec4b,
1575 aBdec8b = dnnl_aBdec8b,
1576 aBdefc16b = dnnl_aBdefc16b,
1577 aCBdef16c16b = dnnl_aCBdef16c16b,
1578 aCBdef16b16c = dnnl_aCBdef16b16c,
1579 aBdefc4b = dnnl_aBdefc4b,
1580 aBdefc8b = dnnl_aBdefc8b,
1581 Acb16a = dnnl_Acb16a,
1584 aCBd16b16c = dnnl_aCBd16b16c,
1585 aCBd16c16b = dnnl_aCBd16c16b,
1586 aCBde16b16c = dnnl_aCBde16b16c,
1587 aCBde16c16b = dnnl_aCBde16c16b,
1588 Acdb16a = dnnl_Acdb16a,
1589 Acdb4a = dnnl_Acdb4a,
1590 Acdb8a = dnnl_Acdb8a,
1591 Acdeb16a = dnnl_Acdeb16a,
1592 Acdeb4a = dnnl_Acdeb4a,
1593 Acdeb8a = dnnl_Acdeb8a,
1594 BAc16a16b = dnnl_BAc16a16b,
1595 BAc16b16a = dnnl_BAc16b16a,
1596 BAcd16a16b = dnnl_BAcd16a16b,
1597 BAcd16b16a = dnnl_BAcd16b16a,
1598 ABcd32a32b = dnnl_ABcd32a32b,
1599 BAcde16b16a = dnnl_BAcde16b16a,
1600 BAcde16a16b = dnnl_BAcde16a16b,
1601 aBdec32b = dnnl_aBdec32b,
1602 Abcdef16a = dnnl_Abcdef16a,
1603 Abcdef32a = dnnl_Abcdef32a,
1604 Acdb32a = dnnl_Acdb32a,
1608 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1609 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1610 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1611 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1612 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1613 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1614 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1615 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1616 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1617 AB32a32b8a4b = dnnl_AB32a32b8a4b,
1618 AB32a32b8a2b = dnnl_AB32a32b8a2b,
1619 AB8a4b = dnnl_AB8a4b,
1620 AB8a2b = dnnl_AB8a2b,
1621 abDc32d = dnnl_abDc32d,
1622 abDC32d4c = dnnl_abDC32d4c,
1623 abdEc32e = dnnl_abdEc32e,
1624 abdEC32e2c = dnnl_abdEC32e2c,
1625 abdEC32e4c = dnnl_abdEC32e4c,
1626 aBCdef16c16b4c = dnnl_aBCdef16c16b4c,
1627 aBdC16b4c = dnnl_aBdC16b4c,
1628 aBdeC16b4c = dnnl_aBdeC16b4c,
1629 AcB16a4b = dnnl_AcB16a4b,
1630 AcdB16a2b = dnnl_AcdB16a2b,
1631 aBdefC16b4c = dnnl_aBdefC16b4c,
1632 AcdeB16a4b = dnnl_AcdeB16a4b,
1634 Acb32a = dnnl_Acb32a,
1635 AcB32a2b = dnnl_AcB32a2b,
1636 AcB32a4b = dnnl_AcB32a4b,
1637 Acb48a = dnnl_Acb48a,
1638 AcB48a2b = dnnl_AcB48a2b,
1639 AcB48a4b = dnnl_AcB48a4b,
1640 Acb64a = dnnl_Acb64a,
1641 AcB64a2b = dnnl_AcB64a2b,
1642 AcB64a4b = dnnl_AcB64a4b,
1645 aBdc32b = dnnl_aBdc32b,
1646 aBdC32b2c = dnnl_aBdC32b2c,
1647 aBdC32b4c = dnnl_aBdC32b4c,
1648 aBdc48b = dnnl_aBdc48b,
1649 aBdC48b2c = dnnl_aBdC48b2c,
1650 aBdC48b4c = dnnl_aBdC48b4c,
1651 aBdc64b = dnnl_aBdc64b,
1652 aBdC64b2c = dnnl_aBdC64b2c,
1653 aBdC64b4c = dnnl_aBdC64b4c,
1655 adCb2c = dnnl_adCb2c,
1656 adCb4c = dnnl_adCb4c,
1657 AcdB32a2b = dnnl_AcdB32a2b,
1658 AcdB32a4b = dnnl_AcdB32a4b,
1659 Acdb48a = dnnl_Acdb48a,
1660 AcdB48a2b = dnnl_AcdB48a2b,
1661 AcdB48a4b = dnnl_AcdB48a4b,
1662 Acdb64a = dnnl_Acdb64a,
1663 AcdB64a2b = dnnl_AcdB64a2b,
1664 AcdB64a4b = dnnl_AcdB64a4b,
1665 cdBa2b = dnnl_cdBa2b,
1666 cdBa4b = dnnl_cdBa4b,
1667 aBdeC32b2c = dnnl_aBdeC32b2c,
1668 aBdeC32b4c = dnnl_aBdeC32b4c,
1669 aBdec48b = dnnl_aBdec48b,
1670 aBdeC48b2c = dnnl_aBdeC48b2c,
1671 aBdeC48b4c = dnnl_aBdeC48b4c,
1672 aBdec64b = dnnl_aBdec64b,
1673 aBdeC64b2c = dnnl_aBdeC64b2c,
1674 aBdeC64b4c = dnnl_aBdeC64b4c,
1676 adeCb2c = dnnl_adeCb2c,
1677 adeCb4c = dnnl_adeCb4c,
1678 Acdeb32a = dnnl_Acdeb32a,
1679 AcdeB32a2b = dnnl_AcdeB32a2b,
1680 AcdeB32a4b = dnnl_AcdeB32a4b,
1681 Acdeb48a = dnnl_Acdeb48a,
1682 AcdeB48a2b = dnnl_AcdeB48a2b,
1683 AcdeB48a4b = dnnl_AcdeB48a4b,
1684 Acdeb64a = dnnl_Acdeb64a,
1685 AcdeB64a2b = dnnl_AcdeB64a2b,
1686 AcdeB64a4b = dnnl_AcdeB64a4b,
1687 cdeBa2b = dnnl_cdeBa2b,
1688 cdeBa4b = dnnl_cdeBa4b,
1689 aBdefc32b = dnnl_aBdefc32b,
1690 aBdefC32b2c = dnnl_aBdefC32b2c,
1691 aBdefC32b4c = dnnl_aBdefC32b4c,
1692 aBdefc48b = dnnl_aBdefc48b,
1693 aBdefC48b2c = dnnl_aBdefC48b2c,
1694 aBdefC48b4c = dnnl_aBdefC48b4c,
1695 aBdefc64b = dnnl_aBdefc64b,
1696 aBdefC64b2c = dnnl_aBdefC64b2c,
1697 aBdefC64b4c = dnnl_aBdefC64b4c,
1698 adefcb = dnnl_adefcb,
1699 adefCb2c = dnnl_adefCb2c,
1700 adefCb4c = dnnl_adefCb4c,
1713 NCw16n16c = dnnl_NCw16n16c,
1714 NChw16n16c = dnnl_NChw16n16c,
1715 NCdhw16n16c = dnnl_NCdhw16n16c,
1716 NCdhw32n32c = dnnl_NCdhw32n32c,
1717 NChw32n32c = dnnl_NChw32n32c,
1718 IOhw16i16o = dnnl_IOhw16i16o,
1719 OI16i16o = dnnl_OI16i16o,
1720 OI16i32o = dnnl_OI16i32o,
1721 OI16i64o = dnnl_OI16i64o,
1722 OI8i16o2i = dnnl_OI8i16o2i,
1723 OI8i32o2i = dnnl_OI8i32o2i,
1724 OI8i64o2i = dnnl_OI8i64o2i,
1725 OI4i16o4i = dnnl_OI4i16o4i,
1726 OI4i32o4i = dnnl_OI4i32o4i,
1727 OI4i64o4i = dnnl_OI4i64o4i,
1728 Ohwi32o = dnnl_Ohwi32o,
1729 IOdhw16i16o = dnnl_IOdhw16i16o,
1730 gIOhw16i16o = dnnl_gIOhw16i16o,
1731 gOhwi32o = dnnl_gOhwi32o,
1732 Goidhw16g = dnnl_Goidhw16g,
1733 IOw16o16i = dnnl_IOw16o16i,
1734 OIw16i16o = dnnl_OIw16i16o,
1735 OIw16i32o = dnnl_OIw16i32o,
1736 OIw16i64o = dnnl_OIw16i64o,
1737 IOw16i16o = dnnl_IOw16i16o,
1738 gIOw16i16o = dnnl_gIOw16i16o,
1739 OIw16o16i = dnnl_OIw16o16i,
1740 Oiw16o = dnnl_Oiw16o,
1741 OIw4i16o4i = dnnl_OIw4i16o4i,
1742 OIw4i32o4i = dnnl_OIw4i32o4i,
1743 OIw4i64o4i = dnnl_OIw4i64o4i,
1744 OIw2i8o4i = dnnl_OIw2i8o4i,
1745 OIw4i4o = dnnl_OIw4i4o,
1746 OIw4o4i = dnnl_OIw4o4i,
1748 OIw8i16o2i = dnnl_OIw8i16o2i,
1749 OIw8i32o2i = dnnl_OIw8i32o2i,
1750 OIw8i64o2i = dnnl_OIw8i64o2i,
1751 OIw8i8o = dnnl_OIw8i8o,
1752 OIw8o16i2o = dnnl_OIw8o16i2o,
1753 OIw8o8i = dnnl_OIw8o8i,
1754 OIw8o4i = dnnl_OIw8o4i,
1755 OIw16i16o4i = dnnl_OIw16i16o4i,
1756 OIw16i16o2i = dnnl_OIw16i16o2i,
1757 OIw16o16i2o = dnnl_OIw16o16i2o,
1758 Owi16o = dnnl_Owi16o,
1759 OwI16o2i = dnnl_OwI16o2i,
1762 IOhw16o16i = dnnl_IOhw16o16i,
1763 Ohwi16o = dnnl_Ohwi16o,
1764 OhwI16o2i = dnnl_OhwI16o2i,
1765 Ohwi4o = dnnl_Ohwi4o,
1766 Ohwi8o = dnnl_Ohwi8o,
1767 OIhw16i16o = dnnl_OIhw16i16o,
1768 OIhw16i32o = dnnl_OIhw16i32o,
1769 OIhw16i64o = dnnl_OIhw16i64o,
1770 OIhw16o16i = dnnl_OIhw16o16i,
1771 Oihw16o = dnnl_Oihw16o,
1772 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1773 OIhw4i32o4i = dnnl_OIhw4i32o4i,
1774 OIhw4i64o4i = dnnl_OIhw4i64o4i,
1775 OIhw4i4o = dnnl_OIhw4i4o,
1776 OIhw4o4i = dnnl_OIhw4o4i,
1777 Oihw4o = dnnl_Oihw4o,
1778 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1779 OIhw8i32o2i = dnnl_OIhw8i32o2i,
1780 OIhw8i64o2i = dnnl_OIhw8i64o2i,
1781 OIhw8i8o = dnnl_OIhw8i8o,
1782 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1783 OIhw8o8i = dnnl_OIhw8o8i,
1784 OIhw8o4i = dnnl_OIhw8o4i,
1785 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1786 IOdhw16o16i = dnnl_IOdhw16o16i,
1787 Odhwi16o = dnnl_Odhwi16o,
1788 OdhwI16o2i = dnnl_OdhwI16o2i,
1789 Odhwi4o = dnnl_Odhwi4o,
1790 Odhwi8o = dnnl_Odhwi8o,
1791 OIdhw16i16o = dnnl_OIdhw16i16o,
1792 OIdhw16i32o = dnnl_OIdhw16i32o,
1793 OIdhw16i64o = dnnl_OIdhw16i64o,
1794 OIdhw16o16i = dnnl_OIdhw16o16i,
1795 Oidhw16o = dnnl_Oidhw16o,
1796 OIdhw4i4o = dnnl_OIdhw4i4o,
1797 OIdhw4o4i = dnnl_OIdhw4o4i,
1798 Oidhw4o = dnnl_Oidhw4o,
1799 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1800 OIdhw8i32o2i = dnnl_OIdhw8i32o2i,
1801 OIdhw8i64o2i = dnnl_OIdhw8i64o2i,
1802 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1803 OIdhw16i16o4i = dnnl_OIdhw16i16o4i,
1804 OIdhw4i32o4i = dnnl_OIdhw4i32o4i,
1805 OIdhw4i64o4i = dnnl_OIdhw4i64o4i,
1806 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1807 OIdhw8i8o = dnnl_OIdhw8i8o,
1808 OIdhw8o8i = dnnl_OIdhw8o8i,
1809 OIdhw8o4i = dnnl_OIdhw8o4i,
1810 gIOw16o16i = dnnl_gIOw16o16i,
1811 gOIw16i16o = dnnl_gOIw16i16o,
1812 gOIw16o16i = dnnl_gOIw16o16i,
1813 gOiw16o = dnnl_gOiw16o,
1814 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1815 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1816 gOIw4i4o = dnnl_gOIw4i4o,
1817 gOIw4o4i = dnnl_gOIw4o4i,
1818 gOiw4o = dnnl_gOiw4o,
1819 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1820 gOIw8i8o = dnnl_gOIw8i8o,
1821 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1822 gOIw8o8i = dnnl_gOIw8o8i,
1823 gOIw8o4i = dnnl_gOIw8o4i,
1824 gOIw16i16o4i = dnnl_gOIw16i16o4i,
1825 gOIw16i16o2i = dnnl_gOIw16i16o2i,
1826 gOIw16o16i2o = dnnl_gOIw16o16i2o,
1827 gOwi16o = dnnl_gOwi16o,
1828 gOwI16o2i = dnnl_gOwI16o2i,
1829 gOwi4o = dnnl_gOwi4o,
1830 gOwi8o = dnnl_gOwi8o,
1831 Goiw8g = dnnl_Goiw8g,
1832 Goiw16g = dnnl_Goiw16g,
1833 gIOhw16o16i = dnnl_gIOhw16o16i,
1834 gOhwi16o = dnnl_gOhwi16o,
1835 gOhwI16o2i = dnnl_gOhwI16o2i,
1836 gOhwi4o = dnnl_gOhwi4o,
1837 gOhwi8o = dnnl_gOhwi8o,
1838 Goihw16g = dnnl_Goihw16g,
1839 gOIhw16i16o = dnnl_gOIhw16i16o,
1840 gOIhw16o16i = dnnl_gOIhw16o16i,
1841 gOihw16o = dnnl_gOihw16o,
1842 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1843 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1844 gOIhw4i4o = dnnl_gOIhw4i4o,
1845 gOIhw4o4i = dnnl_gOIhw4o4i,
1846 gOihw4o = dnnl_gOihw4o,
1847 Goihw8g = dnnl_Goihw8g,
1848 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1849 gOIhw8i8o = dnnl_gOIhw8i8o,
1850 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1851 OIw4o8i8o4i = dnnl_OIw4o8i8o4i,
1852 OIdhw4o8i8o4i = dnnl_OIdhw4o8i8o4i,
1853 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1854 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1855 gOIw4o8i8o4i = dnnl_gOIw4o8i8o4i,
1856 gOIdhw4o8i8o4i = dnnl_gOIdhw4o8i8o4i,
1857 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1858 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1859 OIhw16i16o4i = dnnl_OIhw16i16o4i,
1860 OIhw16i16o2i = dnnl_OIhw16i16o2i,
1861 OIhw16o16i2o = dnnl_OIhw16o16i2o,
1862 OIdhw16i16o2i = dnnl_OIdhw16i16o2i,
1863 gOIhw16i16o4i = dnnl_gOIhw16i16o4i,
1864 gOIhw16i16o2i = dnnl_gOIhw16i16o2i,
1865 gOIhw16o16i2o = dnnl_gOIhw16o16i2o,
1866 gOIhw8o8i = dnnl_gOIhw8o8i,
1867 gOIhw8o4i = dnnl_gOIhw8o4i,
1868 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1869 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1870 gOdhwi16o = dnnl_gOdhwi16o,
1871 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1872 gOdhwi4o = dnnl_gOdhwi4o,
1873 gOdhwi8o = dnnl_gOdhwi8o,
1874 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1875 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1876 gOidhw16o = dnnl_gOidhw16o,
1877 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1878 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1879 gOidhw4o = dnnl_gOidhw4o,
1880 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1881 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1882 gOIdhw16i16o4i = dnnl_gOIdhw16i16o4i,
1883 gOIdhw16i16o2i = dnnl_gOIdhw16i16o2i,
1884 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1885 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1886 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1887 gOIdhw8o4i = dnnl_gOIdhw8o4i,
1888 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1889 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1890 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1891 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1892 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1893 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1894 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1895 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1896 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1897 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1898 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1899 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1901 ldOI32o4i = abDC32d4c,
1902 ldgOi32o = abdEc32e,
1903 ldgOI32o2i = abdEC32e2c,
1904 ldgOI32o4i = abdEC32e4c,
1905 OwI16o4i = dnnl_OwI16o4i,
1906 OhwI16o4i = dnnl_OhwI16o4i,
1907 gOwI16o4i = dnnl_gOwI16o4i,
1908 gOhwI16o4i = dnnl_gOhwI16o4i,
1909 OdhwI16o4i = dnnl_OdhwI16o4i,
1910 gOdhwI16o4i = dnnl_gOdhwI16o4i,
1912 Owi32o = dnnl_Owi32o,
1913 OwI32o2i = dnnl_OwI32o2i,
1914 OwI32o4i = dnnl_OwI32o4i,
1915 Owi48o = dnnl_Owi48o,
1916 OwI48o2i = dnnl_OwI48o2i,
1917 OwI48o4i = dnnl_OwI48o4i,
1918 Owi64o = dnnl_Owi64o,
1919 OwI64o2i = dnnl_OwI64o2i,
1920 OwI64o4i = dnnl_OwI64o4i,
1923 gOwi32o = dnnl_gOwi32o,
1924 gOwI32o2i = dnnl_gOwI32o2i,
1925 gOwI32o4i = dnnl_gOwI32o4i,
1926 gOwi48o = dnnl_gOwi48o,
1927 gOwI48o2i = dnnl_gOwI48o2i,
1928 gOwI48o4i = dnnl_gOwI48o4i,
1929 gOwi64o = dnnl_gOwi64o,
1930 gOwI64o2i = dnnl_gOwI64o2i,
1931 gOwI64o4i = dnnl_gOwI64o4i,
1933 gwIo2i = dnnl_gwIo2i,
1934 gwIo4i = dnnl_gwIo4i,
1935 OhwI32o = dnnl_OhwI32o,
1936 OhwI32o2i = dnnl_OhwI32o2i,
1937 OhwI32o4i = dnnl_OhwI32o4i,
1938 Ohwi48o = dnnl_Ohwi48o,
1939 OhwI48o2i = dnnl_OhwI48o2i,
1940 OhwI48o4i = dnnl_OhwI48o4i,
1941 Ohwi64o = dnnl_Ohwi64o,
1942 OhwI64o2i = dnnl_OhwI64o2i,
1943 OhwI64o4i = dnnl_OhwI64o4i,
1944 hwIo2i = dnnl_hwIo2i,
1945 hwIo4i = dnnl_hwIo4i,
1946 gOhwI32o = dnnl_gOhwI32o,
1947 gOhwI32o2i = dnnl_gOhwI32o2i,
1948 gOhwI32o4i = dnnl_gOhwI32o4i,
1949 gOhwi48o = dnnl_gOhwi48o,
1950 gOhwI48o2i = dnnl_gOhwI48o2i,
1951 gOhwI48o4i = dnnl_gOhwI48o4i,
1952 gOhwi64o = dnnl_gOhwi64o,
1953 gOhwI64o2i = dnnl_gOhwI64o2i,
1954 gOhwI64o4i = dnnl_gOhwI64o4i,
1956 ghwIo2i = dnnl_ghwIo2i,
1957 ghwIo4i = dnnl_ghwIo4i,
1958 Odhwi32o = dnnl_Odhwi32o,
1959 OdhwI32o2i = dnnl_OdhwI32o2i,
1960 OdhwI32o4i = dnnl_OdhwI32o4i,
1961 Odhwi48o = dnnl_Odhwi48o,
1962 OdhwI48o2i = dnnl_OdhwI48o2i,
1963 OdhwI48o4i = dnnl_OdhwI48o4i,
1964 Odhwi64o = dnnl_Odhwi64o,
1965 OdhwI64o2i = dnnl_OdhwI64o2i,
1966 OdhwI64o4i = dnnl_OdhwI64o4i,
1967 dhwIo2i = dnnl_dhwIo2i,
1968 dhwIo4i = dnnl_dhwIo4i,
1969 gOdhwi32o = dnnl_gOdhwi32o,
1970 gOdhwI32o2i = dnnl_gOdhwI32o2i,
1971 gOdhwI32o4i = dnnl_gOdhwI32o4i,
1972 gOdhwi48o = dnnl_gOdhwi48o,
1973 gOdhwI48o2i = dnnl_gOdhwI48o2i,
1974 gOdhwI48o4i = dnnl_gOdhwI48o4i,
1975 gOdhwi64o = dnnl_gOdhwi64o,
1976 gOdhwI64o2i = dnnl_gOdhwI64o2i,
1977 gOdhwI64o4i = dnnl_gOdhwI64o4i,
1978 gdhwio = dnnl_gdhwio,
1979 gdhwIo2i = dnnl_gdhwIo2i,
1980 gdhwIo4i = dnnl_gdhwIo4i,
2009 bool allow_empty =
false)
2011 validate_dims(adims);
2013 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
2017 "could not construct a memory descriptor using a "
2037 bool allow_empty =
false)
2039 validate_dims(adims);
2040 if (!strides.empty()) validate_dims(strides, (
int)adims.size());
2042 (
int)adims.size(), adims.data(),
convert_to_c(adata_type),
2043 strides.empty() ?
nullptr : &strides[0]);
2046 "could not construct a memory descriptor using "
2067 bool allow_empty =
false)
const {
2068 validate_dims(adims, data.
ndims);
2069 validate_dims(offsets, data.
ndims);
2072 &sub_md, &data, adims.data(), offsets.data());
2075 return desc(sub_md);
2123 if (data.
ndims) validate_dims(adims, 1);
2126 &out_md, &data, (
int)adims.size(), adims.data());
2129 status,
"could not reshape a memory descriptor");
2130 return desc(out_md);
2171 bool allow_empty =
false)
const {
2172 validate_dims(permutation, data.
ndims);
2175 &out_md, &data, permutation.data());
2178 "could not permute axes of a memory descriptor");
2179 return desc(out_md);
2224 explicit operator bool()
const {
return data.
ndims != 0; }
2256 "could not create a memory object");
2273 "could not get a memory descriptor from a memory object");
2274 return desc(*cdesc);
2281 "could not get an engine from a memory object");
2282 return engine(c_engine,
true);
2292 "could not get a native handle from a memory object");
2327 "could not set native handle of a memory object");
2343 "could not set native handle of a memory object");
2367 template <
typename T =
void>
2371 "could not map memory object data");
2372 return static_cast<T *
>(mapped_ptr);
2387 "could not unmap memory object data");
2469 "post-ops index is out of range");
2506 "could not append a sum post-op");
2509 memory::convert_to_c(data_type)),
2510 "could not append a sum post-op");
2519 "could not get parameters of a sum post-op");
2531 get(), index, &scale, &c_data_type),
2532 "could not get parameters of a sum post-op");
2550 float scale,
algorithm aalgorithm,
float alpha,
float beta) {
2553 "could not append an elementwise post-op");
2564 float &alpha,
float &beta)
const {
2567 get(), index, &scale, &c_alg, &alpha, &beta),
2568 "could not get parameters of an elementwise post-op");
2602 int mask,
const std::vector<float> &scales) {
2605 memory::convert_to_c(weights_data_type),
2606 memory::convert_to_c(bias_data_type),
2607 memory::convert_to_c(dst_data_type),
2608 scales.size(), mask, &scales[0]),
2609 "could not append depthwise post-op");
2628 int &mask, std::vector<float> &scales)
const {
2635 const float *c_scales;
2637 &c_weights_data_type, &c_bias_data_type,
2638 &c_dst_data_type, &count, &c_mask, &c_scales),
2639 "could not get parameters of depthwise post-op");
2644 scales.resize(count);
2648 scales[c] = c_scales[c];
2687 int mask,
const std::vector<float> &scales) {
2690 memory::convert_to_c(weights_data_type),
2691 memory::convert_to_c(bias_data_type),
2692 memory::convert_to_c(dst_data_type),
2693 scales.size(), mask, &scales[0]),
2694 "could not append depthwise post-op");
2713 int &mask, std::vector<float> &scales)
const {
2720 const float *c_scales;
2722 &c_weights_data_type, &c_bias_data_type,
2723 &c_dst_data_type, &count, &c_mask, &c_scales),
2724 "could not get parameters of depthwise post-op");
2729 scales.resize(count);
2733 scales[c] = c_scales[c];
2754 "could not append a binary post-op");
2768 "could not get parameters of a binary post-op");
2770 src1_desc.
data = *data;
2793 "could not create primitive attribute");
2810 "could not get scratchpad mode primitive attribute");
2820 "could not set scratchpad mode primitive attribute");
2835 const float *c_scales;
2837 get(), &count, &c_mask, &c_scales),
2838 "could not get output scales primitive attribute");
2839 scales.resize(count);
2843 scales[c] = c_scales[c];
2892 "could not set output scales primitive attribute");
2906 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2909 const float *c_scales;
2911 get(), arg, &count, &c_mask, &c_scales),
2912 "could not get scales primitive attributes");
2913 scales.resize(count);
2917 scales[c] = c_scales[c];
2936 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
2939 (
dnnl_dim_t)scales.size(), mask, scales.data()),
2940 "could not set scales primitive attribute");
2954 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
2957 const int32_t *c_zero_points;
2959 get(), arg, &count, &c_mask, &c_zero_points),
2960 "could not get zero points primitive attribute");
2961 zero_points.resize(count);
2965 zero_points[c] = c_zero_points[c];
2989 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
2992 zero_points.data()),
2993 "could not set zero points primitive attribute");
3003 "could not get post-ops primitive attribute");
3018 "could not set post-ops primitive attribute");
3057 "could not set RNN data quantization parameters primitive "
3071 float c_scale, c_shift;
3073 get(), &c_scale, &c_shift),
3074 "could not set RNN data quantization parameters primitive "
3108 (
int)scales.size(), mask, scales.data()),
3109 "could not set RNN weights quantization parameters primitive "
3135 const float *c_scales;
3137 get(), &count, &c_mask, &c_scales),
3138 "could not get primitive RNN weights quantization "
3139 "parameters attributes");
3140 scales.resize(count);
3144 scales[c] = c_scales[c];
3174 int mask,
const std::vector<float> &scales) {
3177 get(), (
int)scales.size(), mask, scales.data()),
3178 "could not set primitive RNN weights projection quantization "
3179 "parameters attributes");
3202 int &mask, std::vector<float> &scales) {
3205 const float *c_scales;
3208 get(), &count, &c_mask, &c_scales),
3209 "could not get primitive RNN weights projection quantization "
3210 "parameters attributes");
3211 scales.resize(count);
3215 scales[c] = c_scales[c];
3241 "could not retrieve implementation info string from a "
3242 "primitive descriptor");
3275 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
3276 [=](
query q) { return what == q; }))
3278 "memory descriptor query is invalid");
3402 "could not retrieve scratchpad engine from a primitive "
3404 return engine(c_engine,
true);
3412 "could not get attributes from a primitive descriptor");
3415 "could not clone primitive attributes");
3425 "could not get primitive kind from a primitive descriptor");
3436 "could not clone a primitive descriptor");
3489 if (pd ==
nullptr)
return;
3502 rc,
"could not get primitive kind from a primitive descriptor");
3503 if (pd_kind != c_prim_kind)
3505 "primitive descriptor operation kind mismatch");
3515 "could not get propagation kind from the primitive "
3521 && (pd_prop_kind == c_prop_kind1
3522 || pd_prop_kind == c_prop_kind2))) {
3529 "primitive descriptor propagation kind mismatch");
3575 bool allow_empty =
false) {
3579 dst_engine.
get(), attr.get());
3582 "could not create a primitive descriptor for a reorder "
3600 bool allow_empty =
false) {
3609 "could not create a primitive descriptor for a reorder "
3683 const std::vector<memory::desc> &mems) {
3684 std::vector<dnnl_memory_desc_t> c_mems;
3685 c_mems.reserve(mems.size());
3686 for (
const auto &s : mems)
3687 c_mems.push_back(s.data);
3712 const std::vector<memory::desc> &srcs,
const engine &aengine,
3719 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3720 attr.get(), aengine.
get()),
3721 "could not create a primitive descriptor for a concat "
3739 const std::vector<memory::desc> &srcs,
const engine &aengine,
3746 (
int)c_api_srcs.size(), concat_dimension,
3747 c_api_srcs.data(), attr.get(), aengine.
get()),
3748 "could not create a primitive descriptor for a concat "
3803 const std::vector<float> &scales,
3804 const std::vector<memory::desc> &srcs,
const engine &aengine,
3806 validate_container_size(scales,
3807 "counts of scales and sources are not equal",
3808 (
int)srcs.size(), (
int)srcs.size());
3815 (
int)c_api_srcs.size(), scales.data(),
3816 c_api_srcs.data(), attr.get(), aengine.
get()),
3817 "could not create a primitive descriptor for a sum "
3833 const std::vector<memory::desc> &srcs,
const engine &aengine,
3835 validate_container_size(scales,
3836 "counts of scales and sources are not equal",
3837 (
int)srcs.size(), (
int)srcs.size());
3843 (
int)c_api_srcs.size(), scales.data(),
3844 c_api_srcs.data(), attr.get(), aengine.
get()),
3845 "could not create a primitive descriptor for a sum "
3908 bool allow_empty =
false)
3909 : allow_empty_(allow_empty) {
3912 desc, attr ? attr->
get() :
nullptr, aengine.
get(), hint_fwd_pd);
3915 status,
"could not create a primitive descriptor iterator");
3916 pd_iterator.reset(iterator);
3929 status,
"could not advance a primitive descriptor iterator");
3935 bool allow_empty_ =
false;
3939 pd_iterator.
get(allow_empty_));
3942 "could not fetch a primitive descriptor from a primitive "
3943 "descriptor iterator");
4009 &strides[0], &padding_l[0], &padding_r[0]),
4010 "could not create a descriptor for a convolution forward "
4011 "propagation primitive");
4053 &weights_desc.
data,
nullptr, &dst_desc.
data,
4054 &strides[0], &padding_l[0], &padding_r[0]),
4055 "could not create a descriptor for a convolution forward "
4056 "propagation primitive");
4103 &weights_desc.
data, &bias_desc.
data,
4104 &dst_desc.
data, &strides[0], &dilates[0],
4105 &padding_l[0], &padding_r[0]),
4106 "could not create a descriptor for a dilated convolution "
4107 "forward propagation primitive");
4152 &weights_desc.
data,
nullptr,
4153 &dst_desc.
data, &strides[0], &dilates[0],
4154 &padding_l[0], &padding_r[0]),
4155 "could not create a descriptor for a dilated convolution "
4156 "forward propagation primitive");
4176 bool allow_empty =
false)
4178 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4192 const engine &aengine,
bool allow_empty =
false)
4194 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4274 &weights_desc.
data, &diff_dst_desc.
data,
4275 &strides[0], &padding_l[0], &padding_r[0]),
4276 "could not create a descriptor for a convolution backward "
4277 "propagation primitive");
4319 &weights_desc.
data, &diff_dst_desc.
data,
4320 &strides[0], &dilates[0], &padding_l[0],
4322 "could not create a descriptor for a dilated convolution "
4323 "backward propagation primitive");
4347 bool allow_empty =
false)
4349 hint_fwd_pd.
get(), allow_empty) {}
4368 bool allow_empty =
false)
4370 hint_fwd_pd.
get(), allow_empty) {}
4445 &diff_weights_desc.
data, &diff_bias_desc.
data,
4446 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4448 "could not create a descriptor for a convolution weights "
4449 "update primitive");
4486 &diff_weights_desc.
data,
nullptr,
4487 &diff_dst_desc.
data, &strides[0],
4488 &padding_l[0], &padding_r[0]),
4489 "could not create a descriptor for a convolution weights "
4490 "update primitive");
4535 &diff_weights_desc.
data, &diff_bias_desc.
data,
4536 &diff_dst_desc.
data, &strides[0], &dilates[0],
4537 &padding_l[0], &padding_r[0]),
4538 "could not create a descriptor for a dilated convolution "
4539 "weights gradient primitive");
4581 &diff_weights_desc.
data,
nullptr,
4582 &diff_dst_desc.
data, &strides[0], &dilates[0],
4583 &padding_l[0], &padding_r[0]),
4584 "could not create a descriptor for a dilated convolution "
4585 "weights gradient primitive");
4608 bool allow_empty =
false)
4610 hint_fwd_pd.
get(), allow_empty) {}
4628 bool allow_empty =
false)
4630 hint_fwd_pd.
get(), allow_empty) {}
4729 &strides[0], &padding_l[0], &padding_r[0]),
4730 "could not create a descriptor for a deconvolution forward "
4731 "propagation primitive");
4772 &weights_desc.
data,
nullptr, &dst_desc.
data,
4773 &strides[0], &padding_l[0], &padding_r[0]),
4774 "could not create a descriptor for a deconvolution forward "
4775 "propagation primitive");
4821 &weights_desc.
data, &bias_desc.
data,
4822 &dst_desc.
data, &strides[0], &dilates[0],
4823 &padding_l[0], &padding_r[0]),
4824 "could not create a descriptor for a dilated deconvolution "
4825 "forward propagation primitive");
4869 &weights_desc.
data,
nullptr,
4870 &dst_desc.
data, &strides[0], &dilates[0],
4871 &padding_l[0], &padding_r[0]),
4872 "could not create a descriptor for a dilated deconvolution "
4873 "forward propagation primitive");
4893 bool allow_empty =
false)
4895 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
4909 const engine &aengine,
bool allow_empty =
false)
4911 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
4986 &weights_desc.
data, &diff_dst_desc.
data,
4987 &strides[0], &padding_l[0], &padding_r[0]),
4988 "could not create a descriptor for a deconvolution "
4989 "backward propagation primitive");
5030 &weights_desc.
data, &diff_dst_desc.
data,
5031 &strides[0], &dilates[0], &padding_l[0],
5033 "could not create a descriptor for a dilated deconvolution "
5034 "backward propagation primitive");
5058 bool allow_empty =
false)
5060 hint_fwd_pd.
get(), allow_empty) {}
5079 bool allow_empty =
false)
5081 hint_fwd_pd.
get(), allow_empty) {}
5155 &diff_weights_desc.
data, &diff_bias_desc.
data,
5156 &diff_dst_desc.
data, &strides[0], &padding_l[0],
5158 "could not create a descriptor for a deconvolution weights "
5159 "update primitive");
5195 &src_desc.
data, &diff_weights_desc.
data,
5196 nullptr, &diff_dst_desc.
data, &strides[0],
5197 &padding_l[0], &padding_r[0]),
5198 "could not create a descriptor for a deconvolution weights "
5199 "update primitive");
5243 &diff_weights_desc.
data, &diff_bias_desc.
data,
5244 &diff_dst_desc.
data, &strides[0], &dilates[0],
5245 &padding_l[0], &padding_r[0]),
5246 "could not create a descriptor for a dilated deconvolution "
5247 "weights gradient primitive");
5288 &diff_weights_desc.
data,
nullptr,
5289 &diff_dst_desc.
data, &strides[0], &dilates[0],
5290 &padding_l[0], &padding_r[0]),
5291 "could not create a descriptor for a dilated deconvolution "
5292 "weights gradient primitive");
5316 bool allow_empty =
false)
5318 hint_fwd_pd.
get(), allow_empty) {}
5337 bool allow_empty =
false)
5339 hint_fwd_pd.
get(), allow_empty) {}
5409 float alpha,
float beta,
float k = 1.f) {
5413 local_size, alpha, beta, k),
5414 "could not create a descriptor for a lrn forward "
5415 "propagation primitive");
5434 bool allow_empty =
false)
5436 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5449 const engine &aengine,
bool allow_empty =
false)
5451 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5503 float alpha,
float beta,
float k = 1.f) {
5506 &diff_data_desc.
data, &data_desc.
data, local_size,
5508 "could not create a descriptor for a lrn backward "
5509 "propagation primitive");
5532 bool allow_empty =
false)
5534 hint_fwd_pd.
get(), allow_empty) {}
5552 bool allow_empty =
false)
5554 hint_fwd_pd.
get(), allow_empty) {}
5636 &dst_desc.
data, &strides[0], &kernel[0],
5637 &padding_l[0], &padding_r[0]),
5638 "could not create a descriptor for a pooling forward "
5639 "propagation primitive");
5658 bool allow_empty =
false)
5660 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5673 const engine &aengine,
bool allow_empty =
false)
5675 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5745 &diff_dst_desc.
data, &strides[0], &kernel[0],
5746 &padding_l[0], &padding_r[0]),
5747 "could not create a descriptor for a pooling backward "
5748 "propagation primitive");
5771 bool allow_empty =
false)
5773 hint_fwd_pd.
get(), allow_empty) {}
5791 bool allow_empty =
false)
5793 hint_fwd_pd.
get(), allow_empty) {}
5871 &data_desc.
data, alpha, beta),
5872 "could not create a descriptor for an eltwise forward "
5873 "propagation primitive");
5893 bool allow_empty =
false)
5895 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
5909 const engine &aengine,
bool allow_empty =
false)
5911 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
5963 &diff_data_desc.
data, &data_desc.
data, alpha, beta),
5964 "could not create a descriptor for an eltwise backward "
5965 "propagation primitive");
5989 bool allow_empty =
false)
5991 hint_fwd_pd.
get(), allow_empty) {}
6010 bool allow_empty =
false)
6012 hint_fwd_pd.
get(), allow_empty) {}
6074 &data_desc.
data, softmax_axis),
6075 "could not create a descriptor for a softmax forward "
6076 "propagation primitive");
6096 bool allow_empty =
false)
6098 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6112 const engine &aengine,
bool allow_empty =
false)
6114 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6163 &data_desc.
data, softmax_axis),
6164 "could not create a descriptor for a softmax backward "
6165 "propagation primitive");
6189 bool allow_empty =
false)
6191 hint_fwd_pd.
get(), allow_empty) {}
6210 bool allow_empty =
false)
6212 hint_fwd_pd.
get(), allow_empty) {}
6271 int logsoftmax_axis) {
6274 &data_desc.
data, logsoftmax_axis),
6275 "could not create a descriptor for a logsoftmax forward "
6276 "propagation primitive");
6296 bool allow_empty =
false)
6298 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6312 const engine &aengine,
bool allow_empty =
false)
6314 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6364 int logsoftmax_axis) {
6366 &diff_data_desc.
data, &data_desc.
data,
6368 "could not create a descriptor for a logsoftmax backward "
6369 "propagation primitive");
6393 bool allow_empty =
false)
6395 hint_fwd_pd.
get(), allow_empty) {}
6414 bool allow_empty =
false)
6416 hint_fwd_pd.
get(), allow_empty) {}
6499 "could not create a descriptor for a batch normalization "
6500 "forward propagation primitive");
6521 bool allow_empty =
false)
6523 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6537 const engine &aengine,
bool allow_empty =
false)
6539 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6584 "could not retrieve a descriptor from a primitive "
6585 "descriptor for batch normalization forward propagation "
6625 &diff_data_desc.
data, &data_desc.
data,
6627 "could not create a descriptor for a batch normalization "
6628 "backward propagation primitive");
6653 bool allow_empty =
false)
6655 hint_fwd_pd.
get(), allow_empty) {}
6674 bool allow_empty =
false)
6676 hint_fwd_pd.
get(), allow_empty) {}
6779 "could not create a descriptor for a layer normalization "
6780 "forward propagation primitive");
6799 "could not create a descriptor for a layer normalization "
6800 "forward propagation primitive");
6821 bool allow_empty =
false)
6823 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
6837 const engine &aengine,
bool allow_empty =
false)
6839 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
6882 "could not retrieve a descriptor from a primitive "
6883 "descriptor for layer normalization forward propagation "
6925 &diff_data_desc.
data, &data_desc.
data,
6927 "could not create a descriptor for a batch normalization "
6928 "backward propagation primitive");
6948 &diff_data_desc.
data, &data_desc.
data,
6950 "could not create a descriptor for a batch normalization "
6951 "backward propagation primitive");
6976 bool allow_empty =
false)
6978 hint_fwd_pd.
get(), allow_empty) {}
6997 bool allow_empty =
false)
6999 hint_fwd_pd.
get(), allow_empty) {}
7089 &src_desc.
data, &weights_desc.
data,
7091 "could not create a descriptor for an inner product "
7092 "forward propagation primitive");
7114 &weights_desc.
data,
nullptr, &dst_desc.
data),
7115 "could not create a descriptor for an inner product "
7116 "forward propagation primitive");
7136 bool allow_empty =
false)
7138 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7152 const engine &aengine,
bool allow_empty =
false)
7154 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7209 &diff_src_desc.
data, &weights_desc.
data,
7210 &diff_dst_desc.
data),
7211 "could not create a descriptor for an inner product "
7212 "backward propagation primitive");
7237 bool allow_empty =
false)
7239 hint_fwd_pd.
get(), allow_empty) {}
7258 bool allow_empty =
false)
7260 hint_fwd_pd.
get(), allow_empty) {}
7314 &src_desc.
data, &diff_weights_desc.
data,
7315 &diff_bias_desc.
data, &diff_dst_desc.
data),
7316 "could not create a descriptor for an inner product "
7317 "weights gradient primitive");
7335 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
7336 &diff_dst_desc.
data),
7337 "could not create a descriptor for an inner product "
7338 "weights gradient primitive");
7362 bool allow_empty =
false)
7364 hint_fwd_pd.
get(), allow_empty) {}
7383 bool allow_empty =
false)
7385 hint_fwd_pd.
get(), allow_empty) {}
7435 using primitive_desc::primitive_desc;
7619 "could not retrieve a descriptor from a primitive descriptor "
7620 "for an RNN primitive");
7627 && (
rnn_d->prop_kind == c_prop_kind1
7628 ||
rnn_d->prop_kind == c_prop_kind2)
7629 &&
rnn_d->cell_kind == c_cell_kind;
7633 "mismatch between expected and provided descriptors for an "
7695 float beta = 0.0f) {
7701 &src_iter_desc.
data, &weights_layer_desc.
data,
7702 &weights_iter_desc.
data, &bias_desc.
data,
7703 &dst_layer_desc.
data, &dst_iter_desc.
data,
7705 "could not create a descriptor for a vanilla RNN forward "
7706 "propagation primitive");
7726 bool allow_empty =
false)
7728 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
7742 const engine &aengine,
bool allow_empty =
false)
7744 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
7875 float beta = 0.0f) {
7881 &src_iter_desc.
data, &weights_layer_desc.
data,
7882 &weights_iter_desc.
data, &bias_desc.
data,
7883 &dst_layer_desc.
data, &dst_iter_desc.
data,
7884 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7885 &diff_weights_layer_desc.
data,
7886 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7887 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7889 "could not create a descriptor for a vanilla RNN backward "
7890 "propagation primitive");
7914 bool allow_empty =
false)
7916 hint_fwd_pd.
get(), allow_empty) {}
7935 bool allow_empty =
false)
7937 hint_fwd_pd.
get(), allow_empty) {}
8099 &src_iter_desc.
data, &src_iter_c_desc.
data,
8100 &weights_layer_desc.
data, &weights_iter_desc.
data,
8101 &weights_peephole_desc.
data,
8102 &weights_projection_desc.
data, &bias_desc.
data,
8103 &dst_layer_desc.
data, &dst_iter_desc.
data,
8105 "could not create a descriptor for an LSTM forward "
8106 "propagation primitive");
8166 &src_iter_desc.
data, &src_iter_c_desc.
data,
8167 &weights_layer_desc.
data, &weights_iter_desc.
data,
8168 &weights_peephole_desc.
data, &bias_desc.
data,
8169 &dst_layer_desc.
data, &dst_iter_desc.
data,
8171 "could not create a descriptor for an LSTM forward "
8172 "propagation primitive");
8226 &src_iter_desc.
data, &src_iter_c_desc.
data,
8227 &weights_layer_desc.
data, &weights_iter_desc.
data,
8228 &bias_desc.
data, &dst_layer_desc.
data,
8229 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8231 "could not create a descriptor for an LSTM forward "
8232 "propagation primitive");
8251 bool allow_empty =
false)
8253 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8266 const engine &aengine,
bool allow_empty =
false)
8268 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
8454 &src_iter_desc.
data, &src_iter_c_desc.
data,
8455 &weights_layer_desc.
data, &weights_iter_desc.
data,
8456 &weights_peephole_desc.
data,
8457 &weights_projection_desc.
data, &bias_desc.
data,
8458 &dst_layer_desc.
data, &dst_iter_desc.
data,
8459 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8460 &diff_src_iter_desc.
data,
8461 &diff_src_iter_c_desc.
data,
8462 &diff_weights_layer_desc.
data,
8463 &diff_weights_iter_desc.
data,
8464 &diff_weights_peephole_desc.
data,
8465 &diff_weights_projection_desc.
data,
8466 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8467 &diff_dst_iter_desc.
data,
8468 &diff_dst_iter_c_desc.
data,
8470 "could not create a descriptor for an LSTM backward "
8471 "propagation primitive");
8564 &src_iter_desc.
data, &src_iter_c_desc.
data,
8565 &weights_layer_desc.
data, &weights_iter_desc.
data,
8566 &weights_peephole_desc.
data, &bias_desc.
data,
8567 &dst_layer_desc.
data, &dst_iter_desc.
data,
8568 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8569 &diff_src_iter_desc.
data,
8570 &diff_src_iter_c_desc.
data,
8571 &diff_weights_layer_desc.
data,
8572 &diff_weights_iter_desc.
data,
8573 &diff_weights_peephole_desc.
data,
8574 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8575 &diff_dst_iter_desc.
data,
8576 &diff_dst_iter_c_desc.
data,
8578 "could not create a descriptor for an LSTM backward "
8579 "propagation primitive");
8661 &src_iter_desc.
data, &src_iter_c_desc.
data,
8662 &weights_layer_desc.
data, &weights_iter_desc.
data,
8663 &bias_desc.
data, &dst_layer_desc.
data,
8664 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8665 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8666 &diff_src_iter_c_desc.
data,
8667 &diff_weights_layer_desc.
data,
8668 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8669 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8670 &diff_dst_iter_c_desc.
data,
8672 "could not create a descriptor for an LSTM backward "
8673 "propagation primitive");
8696 bool allow_empty =
false)
8698 hint_fwd_pd.
get(), allow_empty) {}
8716 bool allow_empty =
false)
8718 hint_fwd_pd.
get(), allow_empty) {}
8900 &src_iter_desc.
data, &weights_layer_desc.
data,
8901 &weights_iter_desc.
data, &bias_desc.
data,
8902 &dst_layer_desc.
data, &dst_iter_desc.
data,
8904 "could not create a descriptor for a GRU forward "
8905 "propagation primitive");
8924 bool allow_empty =
false)
8926 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
8939 const engine &aengine,
bool allow_empty =
false)
8941 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9068 &src_iter_desc.
data, &weights_layer_desc.
data,
9069 &weights_iter_desc.
data, &bias_desc.
data,
9070 &dst_layer_desc.
data, &dst_iter_desc.
data,
9071 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9072 &diff_weights_layer_desc.
data,
9073 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9074 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9076 "could not create a descriptor for a GRU backward "
9077 "propagation primitive");
9100 bool allow_empty =
false)
9102 hint_fwd_pd.
get(), allow_empty) {}
9120 bool allow_empty =
false)
9122 hint_fwd_pd.
get(), allow_empty) {}
9265 &src_iter_desc.
data, &weights_layer_desc.
data,
9266 &weights_iter_desc.
data, &bias_desc.
data,
9267 &dst_layer_desc.
data, &dst_iter_desc.
data,
9269 "could not create a descriptor for an LBR GRU forward "
9270 "propagation primitive");
9290 bool allow_empty =
false)
9292 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9306 const engine &aengine,
bool allow_empty =
false)
9308 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9436 &src_iter_desc.
data, &weights_layer_desc.
data,
9437 &weights_iter_desc.
data, &bias_desc.
data,
9438 &dst_layer_desc.
data, &dst_iter_desc.
data,
9439 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9440 &diff_weights_layer_desc.
data,
9441 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9442 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9444 "could not create a descriptor for an LBR GRU backward "
9445 "propagation primitive");
9469 bool allow_empty =
false)
9471 hint_fwd_pd.
get(), allow_empty) {}
9490 bool allow_empty =
false)
9492 hint_fwd_pd.
get(), allow_empty) {}
9612 &data_desc.
data, axis, group_size),
9613 "could not create a descriptor for a shuffle forward "
9614 "propagation primitive");
9636 bool allow_empty =
false)
9638 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9683 &diff_data_desc.
data, axis, group_size),
9684 "could not create a descriptor for a shuffle backward "
9685 "propagation primitive");
9711 bool allow_empty =
false)
9713 hint_fwd_pd.
get(), allow_empty) {}
9773 "could not create a descriptor for a binary operation "
9793 bool allow_empty =
false)
9795 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9808 const engine &aengine,
bool allow_empty =
false)
9810 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9868 &weights_desc.
data,
nullptr, &dst_desc.
data),
9869 "could not create a descriptor for a matmul primitive");
9881 &weights_desc.
data, &bias_desc.
data,
9883 "could not create a descriptor for a matmul primitive");
9901 bool allow_empty =
false)
9903 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
9915 const engine &aengine,
bool allow_empty =
false)
9917 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
9990 "could not create a resampling forward descriptor");
10005 const std::vector<float> &factors,
10011 &src_desc.
data,
nullptr),
10012 "could not create a resampling forward descriptor");
10032 const std::vector<float> &factors,
const memory::desc &src_desc,
10034 if (!factors.empty())
10040 "could not create a resampling forward descriptor");
10060 bool allow_empty =
false)
10062 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10076 const engine &aengine,
bool allow_empty =
false)
10078 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10125 &diff_src_desc.
data, &diff_dst_desc.
data),
10126 "could not create a resampling backward data descriptor");
10141 if (!factors.empty())
10145 &diff_src_desc.
data, &diff_dst_desc.
data),
10146 "could not create a resampling backward data descriptor");
10170 bool allow_empty =
false)
10172 hint_fwd_pd.
get(), allow_empty) {}
10191 bool allow_empty =
false)
10193 hint_fwd_pd.
get(), allow_empty) {}
10277 &dst_desc.
data, &strides[0], &kernel[0],
10278 &dilation[0], &padding_l[0], &padding_r[0]),
10279 "could not create a descriptor for a pooling forward "
10280 "propagation primitive");
10300 bool allow_empty =
false)
10302 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10316 const engine &aengine,
bool allow_empty =
false)
10318 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10393 &diff_dst_desc.
data, &strides[0], &kernel[0],
10394 &dilation[0], &padding_l[0], &padding_r[0]),
10395 "could not create a descriptor for a pooling backward "
10396 "propagation primitive");
10421 bool allow_empty =
false)
10423 hint_fwd_pd.
get(), allow_empty) {}
10442 bool allow_empty =
false)
10444 hint_fwd_pd.
get(), allow_empty) {}
10492 dnnl_prelu_desc_t data;
10506 &data_desc.
data, &weight_desc.
data),
10507 "could not create a descriptor for a prelu forward "
10508 "propagation primitive");
10528 bool allow_empty =
false)
10530 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10544 const engine &aengine,
bool allow_empty =
false)
10546 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10579 dnnl_prelu_desc_t data;
10594 &weight_desc.
data, &diff_data_desc.
data,
10595 &diff_weights_desc.
data),
10596 "could not create a descriptor for a prelu backward "
10597 "propagation primitive");
10621 bool allow_empty =
false)
10623 hint_fwd_pd.
get(), allow_empty) {}
10642 bool allow_empty =
false)
10644 hint_fwd_pd.
get(), allow_empty) {}
10716 &src_desc.
data, &dst_desc.
data, p, eps),
10717 "could not create a reduction descriptor");
10735 bool allow_empty =
false)
10737 &adesc.data, nullptr, aengine, nullptr, allow_empty) {}
10749 const engine &aengine,
bool allow_empty =
false)
10751 &adesc.data, &attr, aengine, nullptr, allow_empty) {}
10859 return static_cast<status>(
10900 "could not get primitive cache capacity");
10907 "could not set primitive cache capacity");
10924 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10931 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10933 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10940 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10942 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10953 "could not create a primitive");
10959 inline void primitive::execute(
const stream &astream,
10960 const std::unordered_map<int, memory> &args)
const {
10961 std::vector<dnnl_exec_arg_t> c_args;
10962 c_args.reserve(args.size());
10963 for (
const auto &a : args)
10964 c_args.push_back({a.first, a.second.get(
true)});
10967 (
int)c_args.size(), c_args.data()),
10968 "could not execute a primitive");
10973 #undef DNNL_DEFINE_BITMASK_OPS
10983 #ifndef DOXYGEN_SHOULD_SKIP_THIS
10985 namespace dnnl = ::dnnl;
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:470
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_data_qparams(dnnl_primitive_attr_t attr, const float scale, const float shift)
Set quantization scale and shift parameters for RNN data tensors.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum_v2(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_data_type_t *data_type)
Returns the parameters of an accumulation (sum) post-op with a data type parameter.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s2p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 2.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scratchpad_mode(dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t mode)
Sets primitive attributes scratchpad mode.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_post_ops(const_dnnl_primitive_attr_t attr, const_dnnl_post_ops_t *post_ops)
Returns primitive attributes post-ops.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_weights_qparams(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns the quantization scaling factors for RNN weights tensors.
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s1p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 1.
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const int32_t *zero_points)
Sets primitive attributes zero points for primitive operations for a given memory argument.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(dnnl_primitive_attr_t attr, const_dnnl_post_ops_t post_ops)
Sets primitive attributes post-ops.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum(dnnl_post_ops_t post_ops, float scale)
Appends an accumulation (sum) to post-ops.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN weights tensors.
dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr)
Destroys primitive attributes.
dnnl_status_t DNNL_API dnnl_post_ops_append_sum_v2(dnnl_post_ops_t post_ops, float scale, dnnl_data_type_t data_type)
Appends an accumulation v2 (sum) to post-ops.
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
dnnl_status_t DNNL_API dnnl_post_ops_append_binary(dnnl_post_ops_t post_ops, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src1_desc)
Appends a binary post-op.
dnnl_status_t DNNL_API dnnl_post_ops_append_dw_k3s2p1(dnnl_post_ops_t post_ops, dnnl_data_type_t weights_data_type, dnnl_data_type_t bias_data_type, dnnl_data_type_t dst_data_type, dnnl_dim_t count, int mask, const float *scales)
Appends a depthwise post-op convolution with stride 2.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_weights_projection_qparams(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns the quantization scaling factors for RNN projection weights tensors.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_alg_kind_t *alg_kind, float *alpha, float *beta)
Returns the parameters of an elementwise post-op.
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const float *scales)
Sets primitive attributes scaling factors for primitive operations for a given memory argument.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scratchpad_mode(const_dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t *mode)
Returns the primitive attributes scratchpad mode.
dnnl_status_t DNNL_API dnnl_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw_k3s1p1(const_dnnl_post_ops_t post_ops, int index, dnnl_data_type_t *weights_data_type, dnnl_data_type_t *bias_data_type, dnnl_data_type_t *dst_data_type, dnnl_dim_t *count, int *mask, const float **scales)
Returns the parameters of an depthwise post-op with stride 1.
dnnl_primitive_kind_t DNNL_API dnnl_post_ops_get_kind(const_dnnl_post_ops_t post_ops, int index)
Returns the kind of a post-op entry.
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:401
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_weights_projection_qparams(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets quantization scaling factors for RNN projection weights tensors.
prop_kind
Propagation kind.
Definition: dnnl.hpp:435
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:2201
dnnl_status_t DNNL_API dnnl_post_ops_append_eltwise(dnnl_post_ops_t post_ops, float scale, dnnl_alg_kind_t alg_kind, float alpha, float beta)
Appends an elementwise post-op.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_zero_points(const_dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const int32_t **zero_points)
Returns count, correspondence zero point mask, and a pointer to a constant int32_t array of zero_poin...
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum(const_dnnl_post_ops_t post_ops, int index, float *scale)
Returns the parameters of an accumulation (sum) post-op.
dnnl_status_t DNNL_API dnnl_post_ops_get_params_binary(const_dnnl_post_ops_t post_ops, int index, dnnl_alg_kind_t *alg_kind, const dnnl_memory_desc_t **src1_desc)
Returns the parameters of a binary post-op.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_rnn_data_qparams(const_dnnl_primitive_attr_t attr, float *scale, float *shift)
Returns the quantization scale and shift parameters for RNN data tensors.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_output_scales(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets output scaling factors correspondence mask and values.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes scaling factors correspondence mask and values for a given memory argume...
dnnl_status_t DNNL_API dnnl_primitive_attr_create(dnnl_primitive_attr_t *attr)
Creates an empty (default) primitive attributes with all the parameters set to their default values.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_output_scales(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes output scaling factors correspondence mask and values.
@ resampling_linear
Linear (Bilinear, Trilinear) resampling method.
@ resampling_nearest
Nearest Neighbor resampling method.
@ eltwise_elu_use_dst_for_bwd
Elementwise: exponential linear unit (ELU) (dst for backward)
@ eltwise_tanh_use_dst_for_bwd
Elementwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
@ reduction_norm_lp_power_p_sum
Reduction using norm_lp_power_p_sum operation.
@ eltwise_linear
Elementwise: linear.
@ eltwise_clip_v2
Eltwise: clip version 2.
@ eltwise_soft_relu
Elementwise: soft_relu.
@ eltwise_logistic
Elementwise: logistic.
@ eltwise_clip
Elementwise: clip.
@ eltwise_abs
Elementwise: abs.
@ eltwise_pow
Elementwise: pow.
@ eltwise_tanh
Elementwise: hyperbolic tangent non-linearity (tanh)
@ eltwise_logistic_use_dst_for_bwd
Elementwise: logistic (dst for backward)
@ eltwise_bounded_relu
Elementwise: bounded_relu.
@ reduction_norm_lp_power_p_max
Reduction using norm_lp_power_p_max operation.
@ reduction_max
Reduction using max operation.
@ eltwise_clip_v2_use_dst_for_bwd
Elementwise: clip version 2 (dst for backward)
@ eltwise_square
Elementwise: square.
@ convolution_direct
Direct convolution.
@ eltwise_exp
Elementwise: exponent.
@ reduction_norm_lp_max
Reduction using norm_lp_max operation.
@ eltwise_elu
Elementwise: exponential linear unit (ELU)
@ convolution_winograd
Winograd convolution.
@ deconvolution_direct
Direct deconvolution.
@ pooling_avg
Average pooling exclude padding, alias for dnnl::algorithm::pooling_avg_include_padding.
@ lbr_gru
GRU cell with linear before reset.
@ pooling_avg_exclude_padding
Average pooling exclude padding.
@ eltwise_gelu
Elementwise: gelu alias for dnnl::algorithm::eltwise_gelu_tanh.
@ eltwise_sqrt
Elementwise: square root.
@ pooling_max
Max pooling.
@ reduction_min
Reduction using min operation.
@ eltwise_gelu_erf
Elementwise: erf-based gelu.
@ eltwise_swish
Elementwise: swish ( )
@ lrn_within_channel
LRN within a single channel.
@ reduction_mul
Reduction using mul operation.
@ lrn_across_channels
Local response normalization (LRN) across multiple channels.
@ eltwise_relu
Elementwise: rectified linear unit (ReLU)
@ eltwise_gelu_tanh
Elementwise: tanh-based gelu.
@ eltwise_relu_use_dst_for_bwd
Elementwise: rectified linar unit (ReLU) (dst for backward)
@ eltwise_logsigmoid
Elementwise: logsigmoid.
@ convolution_auto
Convolution algorithm that is chosen to be either direct or Winograd automatically.
@ eltwise_exp_use_dst_for_bwd
Elementwise: exponent (dst for backward)
@ eltwise_round
Elementwise: round.
@ eltwise_sqrt_use_dst_for_bwd
Elementwise: square root (dst for backward)
@ pooling_avg_include_padding
Average pooling include padding.
@ reduction_norm_lp_sum
Reduction using norm_lp_sum operation.
@ reduction_mean
Reduction using mean operation.
@ deconvolution_winograd
Winograd deconvolution.
@ eltwise_log
Elementwise: natural logarithm.
@ undef
Undefined algorithm.
@ reduction_sum
Reduction using sum operation.
@ library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
@ user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
@ backward
Backward propagation (with respect to all parameters).
@ backward_weights
Backward weights propagation.
@ forward_training
Forward data propagation (training mode).
@ forward_inference
Forward data propagation (inference mode).
@ forward_scoring
Forward data propagation, alias for dnnl::prop_kind::forward_inference.
@ forward
Forward data propagation, alias for dnnl::prop_kind::forward_training.
@ backward_data
Backward data propagation.
@ backward_bias
Backward bias propagation.
@ undef
Undefined propagation kind.
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:2223
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:2218
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization backward propagation primitive.
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization forward propagation primitive.
dnnl_status_t DNNL_API dnnl_binary_desc_init(dnnl_binary_desc_t *binary_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src0_desc, const dnnl_memory_desc_t *src1_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a binary primitive.
dnnl_status_t DNNL_API dnnl_gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
status gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
Definition: dnnl.hpp:10928
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:10937
dnnl_status_t DNNL_API dnnl_sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
status sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
Definition: dnnl.hpp:10920
dnnl_status_t DNNL_API dnnl_gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
dnnl_status_t DNNL_API dnnl_concat_primitive_desc_create(dnnl_primitive_desc_t *concat_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, int concat_dimension, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an out-of-place concatenation primitive.
dnnl_status_t DNNL_API dnnl_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution forward propagation primitive.
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution weights gradient primitive.
dnnl_status_t DNNL_API dnnl_dilated_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution forward propagation primitive.
dnnl_status_t DNNL_API dnnl_convolution_backward_weights_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution weights gradient primitive.
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution backward propagation primitive.
dnnl_status_t DNNL_API dnnl_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution backward propagation primitive.
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution backward propagation primitive.
dnnl_status_t DNNL_API dnnl_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution forward propagation primitive.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution weights gradient primitive.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution backward propagation primitive.
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution forward propagation primitive.
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution weights gradient primitive.
dnnl_status_t DNNL_API dnnl_eltwise_forward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise forward propagation primitive.
dnnl_status_t DNNL_API dnnl_eltwise_backward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise backward propagation primitive.
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:2147
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
dnnl_status_t DNNL_API dnnl_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
dnnl_engine_kind_t convert_to_c(engine::kind akind)
Converts engine kind enum value from C++ API to C API type.
Definition: dnnl.hpp:961
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:2153
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:2151
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:2149
dnnl_status_t DNNL_API dnnl_inner_product_forward_desc_init(dnnl_inner_product_desc_t *ip_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes descriptor for inner product forward propagation.
dnnl_status_t DNNL_API dnnl_inner_product_backward_weights_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product weights gradient primitive.
dnnl_status_t DNNL_API dnnl_inner_product_backward_data_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product backward propagation.
dnnl_status_t DNNL_API dnnl_layer_normalization_backward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for a layer normalization backward propagation primitive.
dnnl_status_t DNNL_API dnnl_layer_normalization_forward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for layer normalization forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_forward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
dnnl_status_t DNNL_API dnnl_lrn_backward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN backward propagation primitive.
dnnl_status_t DNNL_API dnnl_lrn_forward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN forward propagation primitive.
dnnl_status_t DNNL_API dnnl_matmul_desc_init(dnnl_matmul_desc_t *matmul_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a matrix multiplication descriptor.
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
dnnl_status_t DNNL_API dnnl_memory_desc_init_submemory(dnnl_memory_desc_t *memory_desc, const dnnl_memory_desc_t *parent_memory_desc, const dnnl_dims_t dims, const dnnl_dims_t offsets)
Initializes a memory descriptor for a region inside an area described by an existing memory descripto...
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
dnnl_status_t DNNL_API dnnl_memory_desc_permute_axes(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, const int *permutation)
Initializes a memory descriptor by permuting axes in an existing one.
dnnl_status_t DNNL_API dnnl_memory_unmap_data(const_dnnl_memory_t memory, void *mapped_ptr)
Unmaps a memory object and writes back any changes made to the previously mapped memory buffer.
dnnl_status_t DNNL_API dnnl_memory_create(dnnl_memory_t *memory, const dnnl_memory_desc_t *memory_desc, dnnl_engine_t engine, void *handle)
Creates a memory object.
dnnl_status_t DNNL_API dnnl_memory_get_engine(const_dnnl_memory_t memory, dnnl_engine_t *engine)
Returns the engine of a memory object.
dnnl_status_t DNNL_API dnnl_memory_desc_reshape(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, int ndims, const dnnl_dims_t dims)
Initializes a memory descriptor by reshaping an existing one.
dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(const_dnnl_memory_t memory, const dnnl_memory_desc_t **memory_desc)
Returns the memory descriptor for a memory object.
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
dnnl_status_t DNNL_API dnnl_memory_set_data_handle_v2(dnnl_memory_t memory, void *handle, dnnl_stream_t stream)
Sets the underlying memory buffer.
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_strides(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, const dnnl_dims_t strides)
Initializes a memory descriptor using dimensions and strides.
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1333
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1301
dnnl_status_t DNNL_API dnnl_memory_map_data(const_dnnl_memory_t memory, void **mapped_ptr)
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents.
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
#define DNNL_MEMORY_ALLOCATE
Special pointer value that indicates that the library needs to allocate an underlying buffer for a me...
Definition: dnnl_types.h:1510
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_tag(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, dnnl_format_tag_t tag)
Initializes a memory descriptor using dimensions and memory format tag.
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:186
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:682
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:182
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:211
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:685
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:700
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:697
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:197
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:709
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:694
@ dnnl_abdfce
permuted 6D tensor
Definition: dnnl_types.h:424
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:688
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
@ dnnl_abdefc
permuted 6D tensor
Definition: dnnl_types.h:425
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:712
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:543
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:706
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
dnnl_status_t DNNL_API dnnl_pooling_v2_backward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) backward propagation primitiv...
dnnl_status_t DNNL_API dnnl_pooling_v2_forward_desc_init(dnnl_pooling_v2_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t dilation, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling v2 (pooling with dilation support) forward propagation primitive...
dnnl_status_t DNNL_API dnnl_pooling_forward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_pooling_backward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling backward propagation primitive.
dnnl_status_t DNNL_API dnnl_prelu_forward_desc_init(dnnl_prelu_desc_t *prelu_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *weights_desc)
Initializes a descriptor for PReLU (leaky ReLU with trainable alpha parameter) forward propagation pr...
dnnl_status_t DNNL_API dnnl_prelu_backward_desc_init(dnnl_prelu_desc_t *prelu_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *diff_weights_desc)
Initializes a descriptor for PReLU (leaky ReLU with trainable alpha parameter) backward propagation p...
void set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
Definition: dnnl.hpp:10905
dnnl_status_t DNNL_API dnnl_set_primitive_cache_capacity(int capacity)
Sets a number of primitives that can be held in the primitive cache at a time.
dnnl_status_t DNNL_API dnnl_get_primitive_cache_capacity(int *capacity)
Returns the number of primitives that can be held in the primitive cache at the same time.
int get_primitive_cache_capacity()
Returns the number of primitives that can be held in the primitive cache at the same time.
Definition: dnnl.hpp:10897
dnnl_status_t DNNL_API dnnl_primitive_desc_query(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index, void *result)
Queries a primitive descriptor for various pieces of information.
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2318
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:2336
#define DNNL_ARG_DIFF_BIAS
Gradient (diff) of the bias tensor argument.
Definition: dnnl_types.h:2443
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2389
#define DNNL_ARG_DIFF_SRC_LAYER
A special mnemonic for gradient (diff) of RNN input vector.
Definition: dnnl_types.h:2377
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2434
#define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:2354
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:1241
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
A special mnemonic for diff of RNN weights applied to the projection weights.
Definition: dnnl_types.h:2440
const dnnl_memory_desc_t DNNL_API * dnnl_primitive_desc_query_md(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index)
Queries primitive descriptor for a memory descriptor.
dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(const_dnnl_primitive_desc_t primitive_desc, const_dnnl_primitive_attr_t *attr)
Returns a constant reference to the attributes of a primitive descriptor.
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2428
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2383
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:2410
dnnl_status_t DNNL_API dnnl_primitive_execute(const_dnnl_primitive_t primitive, dnnl_stream_t stream, int nargs, const dnnl_exec_arg_t *args)
Executes a primitive.
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:2342
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_next(dnnl_primitive_desc_iterator_t iterator)
Advances the primitive descriptor iterator to point to the next available implementation.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1522
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:368
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(const_dnnl_primitive_t primitive, const_dnnl_primitive_desc_t *primitive_desc)
Retrieves a constant reference to the primitive descriptor of a given primitive.
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:2324
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:2301
query
Primitive descriptor query specification.
Definition: dnnl.hpp:745
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:2289
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:1107
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:1053
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2514
dnnl_primitive_kind_t convert_to_c(primitive::kind akind)
Converts primitive kind enum value from C++ API to C API type.
Definition: dnnl.hpp:364
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:2190
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:2348
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:375
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:2286
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:2422
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_create(dnnl_primitive_desc_iterator_t *iterator, const_dnnl_op_desc_t op_desc, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine, const_dnnl_primitive_desc_t hint_forward_primitive_desc)
Creates a primitive descriptor iterator.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:2312
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:2357
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:615
#define DNNL_ARG_DIFF_DST_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2404
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:1026
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(dnnl_primitive_desc_t *primitive_desc, const_dnnl_primitive_desc_t existing_primitive_desc)
Clones a primitive descriptor.
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:2295
dnnl_primitive_desc_t DNNL_API dnnl_primitive_desc_iterator_fetch(const_dnnl_primitive_desc_iterator_t iterator)
Fetches the current primitive descriptor from a primitive descriptor iterator.
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:2310
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:2398
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1289
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:1250
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:1276
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1263
@ batch_normalization_d
batch normalization descriptor
@ weights_md
weights memory descriptor desc
@ memory_consumption_s64
memory required for scratchpad (bytes)
@ shuffle_d
shuffle descriptor
@ deconvolution_d
deconvolution descriptor
@ impl_info_str
implementation name
@ diff_weights_md
weights gradient (diff) memory desc
@ workspace_md
workspace memory desc
@ reduction_d
reduction descriptor
@ eltwise_d
eltwise descriptor
@ matmul_d
matmul descriptor
@ softmax_d
softmax descriptor
@ num_of_outputs_s32
number of outputs expected
@ primitive_kind
primitive kind
@ dst_md
destination memory desc
@ scratchpad_engine
scratchpad engine
@ reorder_src_engine
reorder source engine
@ op_d
operation descriptor
@ layer_normalization_d
layer normalization descriptor
@ logsoftmax_d
logsoftmax descriptor
@ pooling_d
pooling descriptor
@ num_of_inputs_s32
number of inputs expected
@ diff_src_md
source gradient (diff) memory desc
@ src_md
source memory desc
@ scratchpad_md
scratchpad memory desc
@ reorder_dst_engine
reorder destination engine
@ convolution_d
convolution descriptor
@ time_estimate_f64
runtime estimation (seconds), unimplemented
@ binary_d
binary descriptor
@ diff_dst_md
destination gradient (diff) memory desc
@ exec_arg_md
memory desc of an execute argument
@ inner_product_d
inner product descriptor
@ resampling_d
resampling descriptor
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:1183
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:1153
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:1167
@ dnnl_eltwise_logsigmoid
Eltwise: logsigmoid.
Definition: dnnl_types.h:1163
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:1185
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:1145
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:1219
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:1130
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:1211
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:1233
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:1128
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1235
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:1223
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:1171
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:1140
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:1126
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:1147
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:1112
@ dnnl_eltwise_clip_v2_use_dst_for_bwd
Eltwise: clip version 2 (dst for backward)
Definition: dnnl_types.h:1177
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:1187
@ dnnl_binary_sub
Binary sub.
Definition: dnnl_types.h:1215
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:1116
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:1120
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:1114
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:1149
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:1191
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:1159
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:1193
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:1124
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:1195
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:1203
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:1122
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:1110
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:1136
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:1151
@ dnnl_eltwise_clip_v2
Eltwise: clip version 2.
Definition: dnnl_types.h:1155
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:1189
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:1169
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:1118
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:1227
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:1157
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:1165
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:1221
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:1138
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:1181
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:1229
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:1179
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:1173
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:1205
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:1213
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:1231
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1237
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:1161
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:1207
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:1225
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:1175
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:1134
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:1132
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:1217
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:1209
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:1087
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:1061
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:1057
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:1065
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:1081
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:1093
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:1077
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:1055
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:1063
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:1095
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:1079
@ dnnl_prelu
A PReLU primitive.
Definition: dnnl_types.h:1099
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:1069
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:1091
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:1059
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:1089
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:1073
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:1067
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:1071
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:1083
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:1097
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:1075
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2557
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2521
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2542
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2566
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2564
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2546
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2554
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2570
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2556
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2520
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2541
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2565
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2571
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2544
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2524
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2551
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2543
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2518
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2549
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2532
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2523
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2545
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2567
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2559
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2535
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2534
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2529
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2515
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2537
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2547
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2572
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2517
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2552
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2550
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2548
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2568
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2569
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2555
@ use_scale_shift
Use scale and shift parameters.
@ none
Use no normalization flags.
@ fuse_norm_relu
Fuse normalization with ReLU.
@ use_global_stats
Use global statistics.
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:1046
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:1036
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:1042
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:1044
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:1029
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:1040
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:1032
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:1048
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:1038
dnnl_status_t DNNL_API dnnl_reduction_desc_init(dnnl_reduction_desc_t *desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, float p, float eps)
Initializes a descriptor for a reduction primitive.
dnnl_status_t DNNL_API dnnl_reorder_primitive_desc_create(dnnl_primitive_desc_t *reorder_primitive_desc, const dnnl_memory_desc_t *src_desc, dnnl_engine_t src_engine, const dnnl_memory_desc_t *dst_desc, dnnl_engine_t dst_engine, const_dnnl_primitive_attr_t attr)
Creates a primitive descriptor for a reorder primitive.
dnnl_status_t DNNL_API dnnl_resampling_backward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes a descriptor for resampling backward propagation primitive.
dnnl_status_t DNNL_API dnnl_resampling_forward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a descriptor for a resampling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_lbr_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU backward propagation primitive.
dnnl_status_t DNNL_API dnnl_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU forward propagation primitive.
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:712
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1931
dnnl_status_t DNNL_API dnnl_vanilla_rnn_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN forward propagation primitive.
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM backward propagation primitive.
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1937
dnnl_status_t DNNL_API dnnl_vanilla_rnn_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN backward propagation primitive.
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_weights_projection_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or with out recurrent project...
dnnl_status_t DNNL_API dnnl_lstm_backward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_src_iter_c_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_weights_peephole_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, const dnnl_memory_desc_t *diff_dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) backward propagation primitive.
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for LSTM forward propagation primitive.
dnnl_status_t DNNL_API dnnl_lbr_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU forward propagation primitive.
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v3(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *weights_projection_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole and with or without recurrent projecti...
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:658
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init_v2(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *weights_peephole_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for an LSTM (with or without peephole) forward propagation primitive.
dnnl_status_t DNNL_API dnnl_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU backward propagation primitive.
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
@ unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
@ bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
@ unidirectional
Alias for dnnl::rnn_direction::unidirectional_left2right.
@ bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1933
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1949
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1944
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1947
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1939
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1941
@ undef
Undefined RNN flags.
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10858
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:10817
status set_cpu_isa_hints(cpu_isa_hints isa_hints)
Sets the hints flag for the CPU ISA.
Definition: dnnl.hpp:10877
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2664
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:10807
cpu_isa get_effective_cpu_isa()
Gets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10864
dnnl_status_t DNNL_API dnnl_set_max_cpu_isa(dnnl_cpu_isa_t isa)
Sets the maximal ISA the library can dispatch to on the CPU.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:10827
const dnnl_version_t DNNL_API * dnnl_version(void)
Returns library version information.
status
Status values returned by the library functions.
Definition: dnnl.hpp:10789
cpu_isa_hints get_cpu_isa_hints()
Gets the ISA specific hints that library can follow.
Definition: dnnl.hpp:10883
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:10822
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:10812
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:10832
dnnl_cpu_isa_t DNNL_API dnnl_get_effective_cpu_isa(void)
Gets the maximal ISA the library can dispatch to on the CPU.
dnnl_status_t DNNL_API dnnl_set_cpu_isa_hints(dnnl_cpu_isa_hints_t isa_hints)
Sets the hints flag for the CPU ISA.
dnnl_cpu_isa_hints_t DNNL_API dnnl_get_cpu_isa_hints(void)
Gets the ISA specific hints that library can follow.
dnnl_cpu_isa_hints_t
CPU ISA hints flags.
Definition: dnnl_types.h:2710
cpu_isa_hints
CPU ISA hints flags.
Definition: dnnl.hpp:10869
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
@ dnnl_cpu_isa_avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2679
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2672
@ 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:2702
@ 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:2692
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2675
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2666
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2687
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2669
@ dnnl_cpu_isa_avx2_vnni
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
Definition: dnnl_types.h:2705
@ 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:2697
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2683
@ not_required
Queried element is not required for given primitive.
@ invalid_arguments
The operation failed because of incorrect function arguments.
@ success
The operation was successful.
@ unimplemented
The operation failed because requested functionality is not implemented.
@ runtime_error
Primitive or engine failed on execution.
@ out_of_memory
The operation failed due to an out-of-memory condition.
@ iterator_ends
Primitive iterator passed over last primitive descriptor.
@ avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
@ avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
@ avx2_vnni
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
@ avx
Intel Advanced Vector Extensions (Intel AVX)
@ all
Any ISA (excepting those listed as initial support)
@ avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
@ avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
@ sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
@ avx512_core_vnni
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
@ avx512_core_amx
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
@ avx512_core_bf16
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
@ dnnl_cpu_isa_no_hints
No hints (use default features)
Definition: dnnl_types.h:2712
@ dnnl_cpu_isa_prefer_ymm
Prefer to exclusively use Ymm registers for computations.
Definition: dnnl_types.h:2715
@ no_hints
No hints (use default features)
@ prefer_ymm
Prefer to exclusively use Ymm registers for computations.
dnnl_status_t DNNL_API dnnl_shuffle_forward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle forward propagation primitive.
dnnl_status_t DNNL_API dnnl_shuffle_backward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, const dnnl_memory_desc_t *diff_data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle backward propagation primitive.
dnnl_status_t DNNL_API dnnl_softmax_backward_desc_init(dnnl_softmax_desc_t *softmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax backward propagation primitive.
dnnl_status_t DNNL_API dnnl_softmax_forward_desc_init(dnnl_softmax_desc_t *softmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax forward propagation primitive.
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2586
dnnl_status_t DNNL_API dnnl_stream_wait(dnnl_stream_t stream)
Waits for all primitives in the execution stream to finish computations.
dnnl_status_t DNNL_API dnnl_stream_get_engine(const_dnnl_stream_t stream, dnnl_engine_t *engine)
Returns the engine of a stream object.
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
dnnl_status_t DNNL_API dnnl_stream_create(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags)
Creates an execution stream.
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2590
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2592
dnnl_status_t DNNL_API dnnl_sum_primitive_desc_create(dnnl_primitive_desc_t *sum_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, const float *scales, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an (out-of-place) sum primitive.
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
oneDNN namespace
Definition: dnnl.hpp:74
oneAPI namespace
Definition: dnnl.hpp:10981
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6605
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:6620
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6634
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:6651
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6694
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:6684
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6719
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6700
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6714
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:6671
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6697
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6691
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6703
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6706
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6711
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6603
batch_normalization_backward()=default
Default constructor. Produces an empty object.
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6728
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6476
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:6493
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6506
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6554
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6560
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6567
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:6520
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:6536
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6563
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6571
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:6547
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6557
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6474
batch_normalization_forward()=default
Default constructor. Produces an empty object.
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6599
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9754
desc()=default
Default constructor. Produces an empty object.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:9756
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:9768
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9779
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:9807
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9820
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9823
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a binary primitive from a C API primitive descriptor that must ...
Definition: dnnl.hpp:9816
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9829
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9826
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:9792
Elementwise binary operator primitive.
Definition: dnnl.hpp:9752
binary()=default
Default constructor. Produces an empty object.
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9838
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3695
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3764
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:3757
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:3711
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(int concat_dimension, const std::vector< memory::desc > &srcs, const engine &aengine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3738
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3761
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3693
concat()=default
Default constructor. Produces an empty object.
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3772
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4236
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:4307
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:4264
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4328
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4386
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4389
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:4378
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:4345
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4383
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:4365
Convolution backward propagation primitive.
Definition: dnnl.hpp:4233
convolution_backward_data()=default
Default constructor. Produces an empty object.
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:4398
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4404
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:4477
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:4522
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:4569
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:4434
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4590
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4657
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4646
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:4625
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:4638
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4643
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const convolution_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4606
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4651
Convolution weights gradient primitive.
Definition: dnnl.hpp:4402
convolution_backward_weights()=default
Default constructor. Produces an empty object.
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4668
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3963
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:4091
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:4042
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:4140
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:3996
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:4161
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:4175
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:4191
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4208
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:4202
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4220
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4211
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4214
Convolution forward propagation primitive.
Definition: dnnl.hpp:3961
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:4229
convolution_forward()=default
Default constructor. Produces an empty object.
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4949
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:5018
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:4976
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:5039
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:5076
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:5097
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5100
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5094
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:5056
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a deconvolution backward propagation primitive from a C API pri...
Definition: dnnl.hpp:5089
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4947
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:5109
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5115
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:5276
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:5230
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:5186
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:5144
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5297
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5352
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5360
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:5347
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:5334
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:5314
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:5355
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:5363
primitive_desc()=default
Default constructor. Produces an empty object.
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:5113
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:5374
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4684
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:4809
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:4761
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:4716
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:4857
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4878
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:4919
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4931
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4925
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:4908
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:4892
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4934
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4928
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4682
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4943
deconvolution_forward()=default
Default constructor. Produces an empty object.
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5943
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:5957
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5970
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6028
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const eltwise_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5987
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:6007
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6025
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6031
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:6020
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5941
eltwise_backward()=default
Default constructor. Produces an empty object.
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:6040
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5850
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:5865
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5878
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:5908
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5928
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5925
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:5892
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:5919
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5848
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5937
eltwise_forward()=default
Default constructor. Produces an empty object.
An execution engine.
Definition: dnnl.hpp:869
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:938
kind
Kinds of engines.
Definition: dnnl.hpp:874
@ any
An unspecified engine.
engine(kind akind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:902
engine()=default
Constructs an empty engine.
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:893
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:914
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:925
oneDNN exception class.
Definition: dnnl.hpp:84
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:92
static void wrap_c_api(dnnl_status_t status, const char *message)
A convenience function for wrapping calls to C API functions.
Definition: dnnl.hpp:103
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:96
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9001
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:9048
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9082
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:9098
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9184
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9156
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9143
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9140
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9189
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9148
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9153
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:9199
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9194
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:9130
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9135
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9164
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:9117
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9169
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9174
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9179
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9161
GRU backward propagation primitive.
Definition: dnnl.hpp:8999
gru_backward()=default
Default constructor. Produces an empty object.
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:9210
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8852
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:8887
Primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8910
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:8923
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8968
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8955
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8976
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8963
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8973
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8981
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8984
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8960
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:8949
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:8938
GRU forward propagation primitive.
Definition: dnnl.hpp:8850
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:8995
gru_forward()=default
Default constructor. Produces an empty object.
A class that provides the destructor for a oneDNN C API handle.
Definition: dnnl.hpp:120
oneDNN C API handle wrapper class.
Definition: dnnl.hpp:136
handle(const handle< T, traits > &)=default
Copy constructor.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:210
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:220
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:185
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
handle()=default
Constructs an empty handle object.
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:176
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:169
handle(handle< T, traits > &&)=default
Move constructor.
handle< T, traits > & operator=(handle< T, traits > &&)=default
Move assignment operator.
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7192
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:7205
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7218
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7279
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:7235
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7276
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:7268
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:7255
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7273
primitive_desc()=default
Default constructor. Produces an empty object.
Inner product backward propagation primitive.
Definition: dnnl.hpp:7190
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:7288
inner_product_backward_data()=default
Default constructor. Produces an empty object.
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7294
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:7308
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:7330
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7343
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7398
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7401
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7406
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:7393
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:7380
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:7409
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:7360
Inner product weights gradient primitive.
Definition: dnnl.hpp:7292
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7420
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:7067
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:7108
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:7084
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:7121
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:7162
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:7174
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:7135
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7171
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:7177
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7168
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:7151
Inner product forward propagation primitive.
Definition: dnnl.hpp:7065
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:7186
inner_product_forward()=default
Default constructor. Produces an empty object.
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6903
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:6943
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:6919
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6957
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7023
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:7034
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7042
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:7007
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7026
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:7020
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:7037
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7017
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:6994
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7029
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:6974
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7014
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6901
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:7051
layer_normalization_backward()=default
Default constructor. Produces an empty object.
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6758
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:6772
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:6793
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6806
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:6820
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6857
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6854
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6863
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:6847
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6869
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:6836
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6860
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6866
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6756
layer_normalization_forward()=default
Default constructor. Produces an empty object.
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6897
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9368
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:9416
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9450
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9513
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9549
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:9467
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:9569
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9559
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:9487
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9531
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9518
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9510
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9544
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:9500
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9534
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9523
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9526
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9505
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9554
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9564
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9539
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9366
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9580
lbr_gru_backward()=default
Default constructor. Produces an empty object.
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9216
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:9252
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9275
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9348
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9327
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:9305
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9343
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9351
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:9316
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:9289
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9340
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9322
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9335
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9330
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9214
lbr_gru_forward()=default
Default constructor. Produces an empty object.
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9362
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6350
desc()=default
Default constructor. Produces an empty object.
desc(const memory::desc &diff_data_desc, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6363
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6374
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6433
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6439
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6436
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:6424
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:6411
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:6391
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6348
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6448
logsoftmax_backward()=default
Default constructor. Produces an empty object.
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6256
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:6270
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6281
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6335
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6332
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:6311
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:6322
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:6295
primitive_desc()=default
Default constructor. Produces an empty object.
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6254
logsoftmax_forward()=default
Default constructor. Produces an empty object.
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6344
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5486
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:5501
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5514
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:5549
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:5562
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5570
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:5530
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5573
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5567
primitive_desc()=default
Default constructor. Produces an empty object.
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5484
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5582
lrn_backward()=default
Default constructor. Produces an empty object.
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5391
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:5407
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5420
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5465
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5468
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5448
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5471
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:5433
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:5459
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:5389
lrn_forward()=default
Default constructor. Produces an empty object.
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5480
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8348
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:8426
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:8637
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:8538
Primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8678
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8749
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8830
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8815
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8754
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:8726
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8810
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8775
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8731
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8772
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const lstm_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8694
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8785
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8736
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8805
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8759
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8820
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:8713
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8764
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8739
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8767
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8835
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8790
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8825
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8744
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8800
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8780
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:8795
LSTM backward propagation primitive.
Definition: dnnl.hpp:8346
lstm_backward()=default
Default constructor. Produces an empty object.
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8846
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8031
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:8211
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:8082
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:8150
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8237
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8323
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8305
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8300
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8318
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8331
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:8250
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:8276
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8326
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8295
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8310
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8290
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:8265
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8287
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8315
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8282
LSTM forward propagation primitive.
Definition: dnnl.hpp:8029
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:8342
lstm_forward()=default
Default constructor. Produces an empty object.
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9856
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:9864
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:9878
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9888
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:9914
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:9930
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:9923
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:9935
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9927
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9940
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9900
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9854
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:9948
matmul()=default
Default constructor. Produces an empty object.
A memory descriptor.
Definition: dnnl.hpp:1984
desc(const dims &adims, data_type adata_type, format_tag aformat_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:2008
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:1991
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:2219
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:2170
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:2066
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:2211
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:2205
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:2186
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:2192
desc reshape(const dims &adims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:2122
desc(const dims &adims, data_type adata_type, const dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:2036
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:2200
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:2053
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:1987
Memory object.
Definition: dnnl.hpp:1108
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:2385
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:2368
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:1124
memory()=default
Default constructor.
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1112
memory(const desc &md, const engine &aengine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:2252
void set_data_handle(void *handle, const stream &astream) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2324
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2289
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1205
data_type
Data type specification.
Definition: dnnl.hpp:1130
@ undef
Undefined data type (used for empty memory descriptors).
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2278
format_kind
Memory format kind.
Definition: dnnl.hpp:1149
memory(const desc &md, const engine &aengine)
Constructs a memory object.
Definition: dnnl.hpp:2266
void set_data_handle(void *handle) const
Sets the underlying memory buffer.
Definition: dnnl.hpp:2340
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2270
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1115
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5710
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:5734
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5753
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:5769
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5809
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5812
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:5788
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5806
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:5801
Pooling backward propagation primitive.
Definition: dnnl.hpp:5708
pooling_backward()=default
Default constructor. Produces an empty object.
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5821
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5598
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:5625
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5644
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:5672
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5692
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5689
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:5683
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5695
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:5657
Pooling forward propagation primitive.
Definition: dnnl.hpp:5596
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5704
pooling_forward()=default
Default constructor. Produces an empty object.
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:10355
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:10381
Primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10402
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10461
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10458
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive f...
Definition: dnnl.hpp:10453
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const pooling_v2_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10419
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:10439
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10464
Pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10353
pooling_v2_backward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) backward propagation primitive.
Definition: dnnl.hpp:10474
pooling_v2_backward()=default
Default constructor. Produces an empty object.
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:10234
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:10263
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:10285
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:10339
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10336
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10333
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:10315
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling v2 (dilated pooling) forward propagation primitive fr...
Definition: dnnl.hpp:10327
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:10299
Pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10232
pooling_v2_forward()=default
Default constructor. Produces an empty object.
pooling_v2_forward(const primitive_desc &pd)
Constructs a pooling v2 (dilated pooling) forward propagation primitive.
Definition: dnnl.hpp:10349
Post-ops.
Definition: dnnl.hpp:2450
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:2626
void get_params_binary(int index, algorithm &aalgorithm, memory::desc &src1_desc) const
Returns the parameters of a binary post-op.
Definition: dnnl.hpp:2762
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:2527
void append_eltwise(float scale, algorithm aalgorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2549
void append_binary(algorithm aalgorithm, const memory::desc &src1_desc)
Appends a binary post-op.
Definition: dnnl.hpp:2751
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:2600
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:2467
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2462
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:2685
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2454
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:2711
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:2563
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2517
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:2502
Descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10578
desc(const memory::desc &data_desc, const memory::desc &weight_desc, const memory::desc &diff_data_desc, const memory::desc &diff_weights_desc)
Constructs a descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10589
Primitive descriptor for prelu backward propagation.
Definition: dnnl.hpp:10602
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10657
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:10660
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, const prelu_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10639
primitive_desc(const desc &adesc, const engine &aengine, const prelu_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU backward propagation primitive.
Definition: dnnl.hpp:10619
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10663
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a prelu backward propagation primitive from a C API primitive d...
Definition: dnnl.hpp:10652
primitive_desc()=default
Default constructor. Produces an empty object.
PReLU backward propagation primitive.
Definition: dnnl.hpp:10576
prelu_backward()=default
Default constructor. Produces an empty object.
prelu_backward(const primitive_desc &pd)
Constructs a prelu backward propagation primitive.
Definition: dnnl.hpp:10672
Descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10491
desc(prop_kind aprop_kind, const memory::desc &data_desc, const memory::desc &weight_desc)
Constructs a descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10502
Primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10513
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10563
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10560
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10527
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a PReLU forward propagation primitive.
Definition: dnnl.hpp:10543
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a prelu forward propagation primitive from a C API primitive de...
Definition: dnnl.hpp:10554
PReLU forward propagation primitive.
Definition: dnnl.hpp:10489
prelu_forward(const primitive_desc &pd)
Constructs a prelu forward propagation primitive.
Definition: dnnl.hpp:10572
prelu_forward()=default
Default constructor. Produces an empty object.
Primitive attributes.
Definition: dnnl.hpp:2786
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:2953
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:2999
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:3054
void get_rnn_weights_qparams(int &mask, std::vector< float > &scales)
Returns the quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3132
void get_rnn_data_qparams(float &scale, float &shift)
Returns the quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:3070
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2888
void get_rnn_weights_projection_qparams(int &mask, std::vector< float > &scales)
Returns the quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3201
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:3106
void set_rnn_weights_projection_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN projection weights tensors.
Definition: dnnl.hpp:3173
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2817
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:2936
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:2906
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2832
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2802
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:3016
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2790
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:2988
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2806
Base class for all primitive descriptors.
Definition: dnnl.hpp:3225
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:3409
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3335
primitive_desc_base()=default
Default constructor. Produces an empty object.
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:3233
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:3270
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3299
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3326
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:3391
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:3433
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:3421
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3370
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3317
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3358
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind prop_kind1, dnnl::prop_kind prop_kind2)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3485
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3453
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3364
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3308
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:3249
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:3382
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:3397
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3352
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:3237
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3290
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3346
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind aprop_kind)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3468
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3376
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3879
primitive_desc(const_dnnl_op_desc_t desc, const primitive_attr *attr, const engine &aengine, const_dnnl_primitive_desc_t hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor.
Definition: dnnl.hpp:3906
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3924
Base class for all computational primitives.
Definition: dnnl.hpp:269
void execute(const stream &astream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
primitive()=default
Default constructor. Constructs an empty object.
primitive(const primitive_desc &pd)
Constructs a primitive from a primitive descriptor.
kind
Kinds of primitives supported by the library.
Definition: dnnl.hpp:271
@ deconvolution
A deconvolution primitive.
@ pooling_v2
A pooling version 2 primitive.
@ inner_product
An inner product primitive.
@ logsoftmax
A logsoftmax primitive.
@ layer_normalization
A layer normalization primitive.
@ pooling
A pooling primitive.
@ resampling
A resampling primitive.
@ shuffle
A shuffle primitive.
@ batch_normalization
A batch normalization primitive.
@ prelu
A PReLU primitive.
@ eltwise
An element-wise primitive.
@ convolution
A convolution primitive.
@ softmax
A softmax primitive.
@ undef
Undefined primitive.
primitive(const_dnnl_primitive_desc_t c_pd)
Constructs a primitive from a C API primitive descriptor.
Descriptor for reduction.
Definition: dnnl.hpp:10689
desc()=default
Default constructor. Produces an empty object.
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, float p, float eps)
Constructs a descriptor for a reduction primitive using algorithm specific parameters,...
Definition: dnnl.hpp:10712
Primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10722
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10761
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10764
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:10757
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:10748
primitive_desc(const desc &adesc, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a reduction primitive.
Definition: dnnl.hpp:10734
Reduction.
Definition: dnnl.hpp:10687
reduction(const primitive_desc &pd)
Constructs a reduction primitive.
Definition: dnnl.hpp:10772
reduction()=default
Default constructor. Produces an empty object.
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3549
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3634
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:3572
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:3598
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3623
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:3618
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3629
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3637
Reorder primitive.
Definition: dnnl.hpp:3547
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3645
void execute(const stream &astream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3666
reorder()=default
Default constructor. Produces an empty object.
reorder(const memory &src, const memory &dst, const primitive_attr &attr=primitive_attr())
Constructs a reorder primitive that would reorder data between memory objects having the same memory ...
Definition: dnnl.hpp:3654
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:10110
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:10121
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:10138
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:10151
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:10201
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:10206
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:10168
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10209
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:10188
Resampling backward propagation primitive.
Definition: dnnl.hpp:10108
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:10218
resampling_backward()=default
Default constructor. Produces an empty object.
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:9966
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:9984
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:10004
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:10031
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:10045
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:10059
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10095
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10092
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:10086
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:10075
primitive_desc()=default
Default constructor. Produces an empty object.
Resampling forward propagation.
Definition: dnnl.hpp:9964
resampling_forward()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:10104
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7434
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7519
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7485
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7545
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7473
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7479
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7533
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7593
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7551
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7587
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7539
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:7447
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7573
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7505
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7564
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7467
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7461
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7499
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7491
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7453
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7579
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7513
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:7557
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7525
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9671
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9681
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9690
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:9721
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9726
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const shuffle_forward::primitive_desc &hint_fwd_pd, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9708
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9729
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9668
shuffle_backward()=default
Default constructor. Produces an empty object.
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9738
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9596
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:9608
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9619
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9655
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9652
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:9646
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:9634
primitive_desc()=default
Default constructor. Produces an empty object.
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9594
shuffle_forward()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9664
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:6146
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:6159
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:6170
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:6220
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:6207
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6231
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6228
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const softmax_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:6187
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6225
Softmax backward propagation primitive.
Definition: dnnl.hpp:6144
softmax_backward()=default
Default constructor. Produces an empty object.
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:6240
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:6056
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:6070
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:6081
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6128
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:6095
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6131
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:6122
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:6111
primitive_desc()=default
Default constructor. Produces an empty object.
Softmax forward propagation primitive.
Definition: dnnl.hpp:6054
softmax_forward()=default
Default constructor. Produces an empty object.
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:6140
An execution stream.
Definition: dnnl.hpp:985
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:1016
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1025
stream(const engine &aengine, flags aflags=flags::default_flags)
Constructs a stream for the specified engine and with behavior controlled by the specified flags.
Definition: dnnl.hpp:1007
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:989
@ out_of_order
Out-of-order execution.
@ default_flags
Default stream configuration.
@ in_order
In-order execution.
stream()=default
Constructs an empty stream.
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3788
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3861
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:3858
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:3802
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:3832
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:3854
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3786
sum()=default
Default constructor. Produces an empty object.
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3869
Descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7804
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:7859
Primitive descriptor for an RNN backward propagation primitive.
Definition: dnnl.hpp:7895
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:7932
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7955
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8009
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7971
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7989
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7999
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const engine &aengine, const vanilla_rnn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7912
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8004
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7963
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:7945
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7958
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7968
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7976
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8014
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7984
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7950
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7994
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7979
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7802
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:8025
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7643
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:7686
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7711
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:7725
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:7752
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7758
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7763
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7771
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7766
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7787
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7784
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &adesc, const primitive_attr &attr, const engine &aengine, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7741
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7779
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7776
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7641
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7798
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1827
A descriptor of a binary operation.
Definition: dnnl_types.h:2035
A descriptor of a convolution operation.
Definition: dnnl_types.h:1534
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1609
An opaque structure to describe an engine.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1897
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1860
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1796
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:2061
Memory descriptor.
Definition: dnnl_types.h:1445
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1465
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1462
int ndims
Number of dimensions.
Definition: dnnl_types.h:1447
An opaque structure to describe a memory.
A descriptor of a pooling operation.
Definition: dnnl_types.h:1696
A descriptor of a pooling operation.
Definition: dnnl_types.h:1734
An opaque structure for a chain of post operations.
An opaque structure for primitive descriptor attributes.
An opaque structure to describe a primitive descriptor iterator.
An opaque structure to describe a primitive descriptor.
An opaque structure to describe a primitive.
A descriptor of reduction operation.
Definition: dnnl_types.h:2111
A descriptor of resampling operation.
Definition: dnnl_types.h:2083
A descriptor for an RNN operation.
Definition: dnnl_types.h:1953
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1587
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1666
An opaque structure to describe an execution stream.
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2634