23 #include "dnnl_config.h" 32 #include <unordered_map> 36 #if DNNL_CPU_THREADING_RUNTIME == DNNL_RUNTIME_THREADPOOL 37 #include "dnnl_threadpool_iface.hpp" 40 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL 49 #ifndef DNNL_ENABLE_EXCEPTIONS 50 #if __cpp_exceptions || __EXCEPTIONS \ 51 || (defined(_MSC_VER) && !defined(__clang__)) 52 #define DNNL_ENABLE_EXCEPTIONS 1 54 #define DNNL_ENABLE_EXCEPTIONS 0 58 #if defined(__GNUC__) || defined(__clang__) 59 #define DNNL_TRAP() __builtin_trap() 60 #elif defined(__INTEL_COMPILER) || defined(_MSC_VER) 61 #define DNNL_TRAP() __debugbreak() 63 #error "unknown compiler" 66 #if DNNL_ENABLE_EXCEPTIONS 67 #define DNNL_THROW_ERROR(status, msg) throw error(status, msg) 70 #define DNNL_THROW_ERROR(status, msg) \ 91 struct error :
public std::exception {
103 const char *
what() const noexcept
override {
return message; }
116 template <
typename T>
117 void validate_container_size(
const T &v,
const char *error_message,
118 int min_size = 1,
int max_size = -1) {
119 const int size = (int)v.size();
120 if (size < min_size || (max_size >= 0 && size > max_size))
126 template <
typename T>
142 template <
typename T,
typename traits = handle_traits<T>>
146 std::shared_ptr<typename std::remove_pointer<T>::type> data_ {0};
149 bool operator==(
const T other)
const {
return other == data_.get(); }
150 bool operator!=(
const T other)
const {
return !(*
this == other); }
183 void reset(T t,
bool weak =
false) {
184 data_.reset(t, weak ? &dummy_destructor : traits::destructor);
192 T
get(
bool allow_empty =
false)
const {
193 T result = data_.get();
194 if (allow_empty ==
false && result ==
nullptr)
204 explicit operator T()
const {
return get(
true); }
209 explicit operator bool()
const {
return get(
true) !=
nullptr; }
218 return other.data_.get() == data_.get();
265 struct primitive_desc;
362 const std::unordered_map<int, memory> &args)
const;
376 "could not get a primitive descriptor from a primitive");
387 "could not get a primitive kind from a primitive descriptor");
477 undef = dnnl_alg_kind_undef,
645 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \ 646 inline enum_name operator|(enum_name lhs, enum_name rhs) { \ 647 return static_cast<enum_name>( \ 648 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \ 651 inline enum_name operator&(enum_name lhs, enum_name rhs) { \ 652 return static_cast<enum_name>( \ 653 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \ 656 inline enum_name operator^(enum_name lhs, enum_name rhs) { \ 657 return static_cast<enum_name>( \ 658 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \ 661 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \ 662 lhs = static_cast<enum_name>( \ 663 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \ 667 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \ 668 lhs = static_cast<enum_name>( \ 669 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \ 673 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \ 674 lhs = static_cast<enum_name>( \ 675 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \ 679 inline enum_name operator~(enum_name rhs) { \ 680 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \ 881 "could not create an engine");
885 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL 895 &
engine, convert_to_c(
kind), device, context),
896 "could not create an engine");
910 "could not get an engine from a primitive_desc");
911 reset(c_engine,
true);
919 "could not get kind of an engine");
923 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL 927 cl_context context =
nullptr;
929 "could not get an OpenCL context fron an engine");
936 cl_device_id device =
nullptr;
938 "could not get an OpenCL device fron an engine");
948 template <
typename primitive_desc>
958 template <
typename primitive_desc>
963 "could not get an engine from a primitive_desc");
964 return engine(c_engine,
true);
1015 "could not create stream attributes");
1019 #if DNNL_CPU_THREADING_RUNTIME == DNNL_RUNTIME_THREADPOOL 1029 "could not set stream threadpool attribute");
1040 "could not set stream threadpool attribute");
1079 "could not create a stream");
1083 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL 1091 "could not create a stream");
1098 cl_command_queue queue =
nullptr;
1100 "could not get an OpenCL command queue from a stream");
1201 template <
typename T>
1203 validate_container_size(
1454 Abc16a = dnnl_Abc16a,
1455 ABc16a16b = dnnl_ABc16a16b,
1456 ABc4a4b = dnnl_ABc4a4b,
1458 ABc16b16a = dnnl_ABc16b16a,
1461 ABc4b16a4b = dnnl_ABc4b16a4b,
1462 ABc2b8a4b = dnnl_ABc2b8a4b,
1463 ABc4b4a = dnnl_ABc4b4a,
1464 ABc8a16b2a = dnnl_ABc8a16b2a,
1465 ABc8a8b = dnnl_ABc8a8b,
1467 ABc8b16a2b = dnnl_ABc8b16a2b,
1468 ABc8b8a = dnnl_ABc8b8a,
1469 Abcd16a = dnnl_Abcd16a,
1470 ABcd16a16b = dnnl_ABcd16a16b,
1472 ABcd16b16a = dnnl_ABcd16b16a,
1473 aBCd16b16c = dnnl_aBCd16b16c,
1474 aBCd16c16b = dnnl_aBCd16c16b,
1475 Abcd4a = dnnl_Abcd4a,
1477 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1478 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1479 ABcd4b4a = dnnl_ABcd4b4a,
1480 ABcd4a4b = dnnl_ABcd4a4b,
1481 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1482 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1483 aBCd4c4b = dnnl_aBCd4c4b,
1484 aBCd4b4c = dnnl_aBCd4b4c,
1485 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1486 ABcd8a8b = dnnl_ABcd8a8b,
1489 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1490 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1493 aBCd8b8c = dnnl_aBCd8b8c,
1494 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1495 aBCd8c8b = dnnl_aBCd8c8b,
1496 Abcde16a = dnnl_Abcde16a,
1497 ABcde16a16b = dnnl_ABcde16a16b,
1499 ABcde16b16a = dnnl_ABcde16b16a,
1500 aBCde16b16c = dnnl_aBCde16b16c,
1501 aBCde16c16b = dnnl_aBCde16c16b,
1502 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1503 Abcde4a = dnnl_Abcde4a,
1505 ABcde4b4a = dnnl_ABcde4b4a,
1506 ABcde4a4b = dnnl_ABcde4a4b,
1507 aBCde4b4c = dnnl_aBCde4b4c,
1508 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1509 aBCde4c4b = dnnl_aBCde4c4b,
1510 Abcde8a = dnnl_Abcde8a,
1511 ABcde8a8b = dnnl_ABcde8a8b,
1513 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1516 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1517 ABcde8b8a = dnnl_ABcde8b8a,
1518 aBCde8b8c = dnnl_aBCde8b8c,
1519 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1520 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1521 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1522 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1523 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1524 aBCde8c8b = dnnl_aBCde8c8b,
1526 aBCdef16b16c = dnnl_aBCdef16b16c,
1527 aBCdef16c16b = dnnl_aBCdef16c16b,
1529 aBCdef4c4b = dnnl_aBCdef4c4b,
1530 aBCdef4b4c = dnnl_aBCdef4b4c,
1531 aBCdef8b8c = dnnl_aBCdef8b8c,
1532 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1533 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1534 aBCdef8c8b = dnnl_aBCdef8c8b,
1535 aBdc16b = dnnl_aBdc16b,
1536 aBdc4b = dnnl_aBdc4b,
1537 aBdc8b = dnnl_aBdc8b,
1538 aBdec16b = dnnl_aBdec16b,
1539 aBdec4b = dnnl_aBdec4b,
1540 aBdec8b = dnnl_aBdec8b,
1541 aBdefc16b = dnnl_aBdefc16b,
1542 aCBdef16c16b = dnnl_aCBdef16c16b,
1543 aCBdef16b16c = dnnl_aCBdef16b16c,
1544 aBdefc4b = dnnl_aBdefc4b,
1545 aBdefc8b = dnnl_aBdefc8b,
1546 Acb16a = dnnl_Acb16a,
1549 aCBd16b16c = dnnl_aCBd16b16c,
1550 aCBd16c16b = dnnl_aCBd16c16b,
1551 aCBde16b16c = dnnl_aCBde16b16c,
1552 aCBde16c16b = dnnl_aCBde16c16b,
1553 Acdb16a = dnnl_Acdb16a,
1554 Acdb4a = dnnl_Acdb4a,
1555 Acdb8a = dnnl_Acdb8a,
1556 Acdeb16a = dnnl_Acdeb16a,
1557 Acdeb4a = dnnl_Acdeb4a,
1558 Acdeb8a = dnnl_Acdeb8a,
1559 BAc16a16b = dnnl_BAc16a16b,
1560 BAc16b16a = dnnl_BAc16b16a,
1561 BAcd16a16b = dnnl_BAcd16a16b,
1562 BAcd16b16a = dnnl_BAcd16b16a,
1563 ABcd32a32b = dnnl_ABcd32a32b,
1564 BAcde16b16a = dnnl_BAcde16b16a,
1565 BAcde16a16b = dnnl_BAcde16a16b,
1566 aBdec32b = dnnl_aBdec32b,
1567 Abcdef16a = dnnl_Abcdef16a,
1568 Acdb32a = dnnl_Acdb32a,
1572 aBCd2c4b2c = dnnl_aBCd2c4b2c,
1573 aBCde2c4b2c = dnnl_aBCde2c4b2c,
1574 aBCdef2c4b2c = dnnl_aBCdef2c4b2c,
1575 aBCd4b8c2b = dnnl_aBCd4b8c2b,
1576 aBCde4b8c2b = dnnl_aBCde4b8c2b,
1577 aBCdef4b8c2b = dnnl_aBCdef4b8c2b,
1578 aBCd4c8b2c = dnnl_aBCd4c8b2c,
1579 aBCde4c8b2c = dnnl_aBCde4c8b2c,
1580 aBCdef4c8b2c = dnnl_aBCdef4c8b2c,
1593 NCw16n16c = dnnl_NCw16n16c,
1594 NChw16n16c = dnnl_NChw16n16c,
1595 NCdhw16n16c = dnnl_NCdhw16n16c,
1596 NChw32n32c = dnnl_NChw32n32c,
1597 IOhw16i16o = dnnl_IOhw16i16o,
1598 Ohwi32o = dnnl_Ohwi32o,
1599 IOdhw16i16o = dnnl_IOdhw16i16o,
1600 gIOhw16i16o = dnnl_gIOhw16i16o,
1601 gOhwi32o = dnnl_gOhwi32o,
1602 Goidhw16g = dnnl_Goidhw16g,
1603 IOw16o16i = dnnl_IOw16o16i,
1604 OIw16i16o = dnnl_OIw16i16o,
1605 IOw16i16o = dnnl_IOw16i16o,
1606 gIOw16i16o = dnnl_gIOw16i16o,
1607 OIw16o16i = dnnl_OIw16o16i,
1608 Oiw16o = dnnl_Oiw16o,
1609 OIw4i16o4i = dnnl_OIw4i16o4i,
1610 OIw2i8o4i = dnnl_OIw2i8o4i,
1611 OIw4i4o = dnnl_OIw4i4o,
1612 OIw4o4i = dnnl_OIw4o4i,
1614 OIw8i16o2i = dnnl_OIw8i16o2i,
1615 OIw8i8o = dnnl_OIw8i8o,
1616 OIw8o16i2o = dnnl_OIw8o16i2o,
1617 OIw8o8i = dnnl_OIw8o8i,
1618 Owi16o = dnnl_Owi16o,
1619 OwI16o2i = dnnl_OwI16o2i,
1622 IOhw16o16i = dnnl_IOhw16o16i,
1623 Ohwi16o = dnnl_Ohwi16o,
1624 OhwI16o2i = dnnl_OhwI16o2i,
1625 Ohwi4o = dnnl_Ohwi4o,
1626 Ohwi8o = dnnl_Ohwi8o,
1627 OIhw16i16o = dnnl_OIhw16i16o,
1628 OIhw16o16i = dnnl_OIhw16o16i,
1629 Oihw16o = dnnl_Oihw16o,
1630 OIhw4i16o4i = dnnl_OIhw4i16o4i,
1631 OIhw4i4o = dnnl_OIhw4i4o,
1632 OIhw4o4i = dnnl_OIhw4o4i,
1633 Oihw4o = dnnl_Oihw4o,
1634 OIhw8i16o2i = dnnl_OIhw8i16o2i,
1635 OIhw8i8o = dnnl_OIhw8i8o,
1636 OIhw8o16i2o = dnnl_OIhw8o16i2o,
1637 OIhw8o8i = dnnl_OIhw8o8i,
1638 OIhw2i8o4i = dnnl_OIhw2i8o4i,
1639 IOdhw16o16i = dnnl_IOdhw16o16i,
1640 Odhwi16o = dnnl_Odhwi16o,
1641 OdhwI16o2i = dnnl_OdhwI16o2i,
1642 Odhwi4o = dnnl_Odhwi4o,
1643 Odhwi8o = dnnl_Odhwi8o,
1644 OIdhw16i16o = dnnl_OIdhw16i16o,
1645 OIdhw16o16i = dnnl_OIdhw16o16i,
1646 Oidhw16o = dnnl_Oidhw16o,
1647 OIdhw4i4o = dnnl_OIdhw4i4o,
1648 OIdhw4o4i = dnnl_OIdhw4o4i,
1649 Oidhw4o = dnnl_Oidhw4o,
1650 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
1651 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
1652 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
1653 OIdhw8i8o = dnnl_OIdhw8i8o,
1654 OIdhw8o8i = dnnl_OIdhw8o8i,
1655 gIOw16o16i = dnnl_gIOw16o16i,
1656 gOIw16i16o = dnnl_gOIw16i16o,
1657 gOIw16o16i = dnnl_gOIw16o16i,
1658 gOiw16o = dnnl_gOiw16o,
1659 gOIw4i16o4i = dnnl_gOIw4i16o4i,
1660 gOIw2i8o4i = dnnl_gOIw2i8o4i,
1661 gOIw4i4o = dnnl_gOIw4i4o,
1662 gOIw4o4i = dnnl_gOIw4o4i,
1663 gOiw4o = dnnl_gOiw4o,
1664 gOIw8i16o2i = dnnl_gOIw8i16o2i,
1665 gOIw8i8o = dnnl_gOIw8i8o,
1666 gOIw8o16i2o = dnnl_gOIw8o16i2o,
1667 gOIw8o8i = dnnl_gOIw8o8i,
1668 gOwi16o = dnnl_gOwi16o,
1669 gOwI16o2i = dnnl_gOwI16o2i,
1670 gOwi4o = dnnl_gOwi4o,
1671 gOwi8o = dnnl_gOwi8o,
1672 Goiw8g = dnnl_Goiw8g,
1673 Goiw16g = dnnl_Goiw16g,
1674 gIOhw16o16i = dnnl_gIOhw16o16i,
1675 gOhwi16o = dnnl_gOhwi16o,
1676 gOhwI16o2i = dnnl_gOhwI16o2i,
1677 gOhwi4o = dnnl_gOhwi4o,
1678 gOhwi8o = dnnl_gOhwi8o,
1679 Goihw16g = dnnl_Goihw16g,
1680 gOIhw16i16o = dnnl_gOIhw16i16o,
1681 gOIhw16o16i = dnnl_gOIhw16o16i,
1682 gOihw16o = dnnl_gOihw16o,
1683 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
1684 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
1685 gOIhw4i4o = dnnl_gOIhw4i4o,
1686 gOIhw4o4i = dnnl_gOIhw4o4i,
1687 gOihw4o = dnnl_gOihw4o,
1688 Goihw8g = dnnl_Goihw8g,
1689 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
1690 gOIhw8i8o = dnnl_gOIhw8i8o,
1691 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
1692 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
1693 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
1694 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
1695 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
1696 gOIhw8o8i = dnnl_gOIhw8o8i,
1697 gIOdhw16i16o = dnnl_gIOdhw16i16o,
1698 gIOdhw16o16i = dnnl_gIOdhw16o16i,
1699 gOdhwi16o = dnnl_gOdhwi16o,
1700 gOdhwI16o2i = dnnl_gOdhwI16o2i,
1701 gOdhwi4o = dnnl_gOdhwi4o,
1702 gOdhwi8o = dnnl_gOdhwi8o,
1703 gOIdhw16i16o = dnnl_gOIdhw16i16o,
1704 gOIdhw16o16i = dnnl_gOIdhw16o16i,
1705 gOidhw16o = dnnl_gOidhw16o,
1706 gOIdhw4i4o = dnnl_gOIdhw4i4o,
1707 gOIdhw4o4i = dnnl_gOIdhw4o4i,
1708 gOidhw4o = dnnl_gOidhw4o,
1709 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
1710 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
1711 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
1712 gOIdhw8i8o = dnnl_gOIdhw8i8o,
1713 gOIdhw8o8i = dnnl_gOIdhw8o8i,
1714 gOIw2i4o2i = dnnl_gOIw2i4o2i,
1715 gOIhw2i4o2i = dnnl_gOIhw2i4o2i,
1716 gOIdhw2i4o2i = dnnl_gOIdhw2i4o2i,
1717 gOIw2o4i2o = dnnl_gOIw2o4i2o,
1718 gOIhw2o4i2o = dnnl_gOIhw2o4i2o,
1719 gOIdhw2o4i2o = dnnl_gOIdhw2o4i2o,
1720 gOIw4i8o2i = dnnl_gOIw4i8o2i,
1721 gOIhw4i8o2i = dnnl_gOIhw4i8o2i,
1722 gOIdhw4i8o2i = dnnl_gOIdhw4i8o2i,
1723 gOIw4o8i2o = dnnl_gOIw4o8i2o,
1724 gOIhw4o8i2o = dnnl_gOIhw4o8i2o,
1725 gOIdhw4o8i2o = dnnl_gOIdhw4o8i2o,
1756 validate_dims(
dims);
1762 "could not construct a memory descriptor using a " 1784 validate_dims(
dims);
1785 if (!strides.empty()) validate_dims(strides, (
int)
dims.size());
1788 strides.empty() ? nullptr : &strides[0]);
1791 "could not construct a memory descriptor using " 1812 const memory::dims &offsets,
bool allow_empty =
false)
const {
1814 validate_dims(offsets, data.
ndims);
1817 &sub_md, &data,
dims.data(), offsets.data());
1820 return desc(sub_md);
1871 &out_md, &data, (
int)
dims.size(),
dims.data());
1874 status,
"could not reshape a memory descriptor");
1875 return desc(out_md);
1915 bool allow_empty =
false)
const {
1916 validate_dims(permutation, data.
ndims);
1919 &out_md, &data, permutation.data());
1922 "could not permute axes of a memory descriptor");
1923 return desc(out_md);
1996 "could not create a memory object");
2013 "could not get a memory descriptor from a memory object");
2014 return desc(*cdesc);
2021 "could not get an engine from a memory object");
2022 return engine(c_engine,
true);
2031 "could not get a native handle from a memory object");
2064 "could not set native handle of a memory object");
2078 "could not set native handle of a memory object");
2101 template <
typename T =
void>
2105 "could not map memory object data");
2106 return static_cast<T *
>(mapped_ptr);
2120 "could not unmap memory object data");
2123 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL 2124 cl_mem get_ocl_mem_object()
const {
2128 "could not get OpenCL buffer object from a memory object");
2141 "could not set OpenCL buffer object from a memory object");
2224 "post-ops index is out of range");
2253 "could not append a sum post-op");
2262 "could not get parameters of a sum post-op");
2284 "could not append an elementwise post-op");
2295 float &alpha,
float &beta)
const {
2298 get(), index, &scale, &c_alg, &alpha, &beta),
2299 "could not get parameters of an elementwise post-op");
2333 int mask,
const std::vector<float> &scales) {
2336 memory::convert_to_c(weights_data_type),
2337 memory::convert_to_c(bias_data_type),
2338 memory::convert_to_c(dst_data_type),
2339 scales.size(), mask, &scales[0]),
2340 "could not append depthwise post-op");
2359 int &mask, std::vector<float> &scales)
const {
2366 const float *c_scales;
2368 &c_weights_data_type, &c_bias_data_type,
2369 &c_dst_data_type, &count, &c_mask, &c_scales),
2370 "could not get parameters of depthwise post-op");
2375 scales.resize(count);
2379 scales[c] = c_scales[c];
2418 int mask,
const std::vector<float> &scales) {
2421 memory::convert_to_c(weights_data_type),
2422 memory::convert_to_c(bias_data_type),
2423 memory::convert_to_c(dst_data_type),
2424 scales.size(), mask, &scales[0]),
2425 "could not append depthwise post-op");
2444 int &mask, std::vector<float> &scales)
const {
2451 const float *c_scales;
2453 &c_weights_data_type, &c_bias_data_type,
2454 &c_dst_data_type, &count, &c_mask, &c_scales),
2455 "could not get parameters of depthwise post-op");
2460 scales.resize(count);
2464 scales[c] = c_scales[c];
2488 "could not create primitive attribute");
2505 "could not get scratchpad mode primitive attribute");
2515 "could not set scratchpad mode primitive attribute");
2530 const float *c_scales;
2532 get(), &count, &c_mask, &c_scales),
2533 "could not get output scales primitive attribute");
2534 scales.resize(count);
2538 scales[c] = c_scales[c];
2586 get(), (
dnnl_dim_t)scales.size(), mask, scales.data()),
2587 "could not set output scales primitive attribute");
2601 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
2604 const float *c_scales;
2606 get(), arg, &count, &c_mask, &c_scales),
2607 "could not get scales primitive attributes");
2608 scales.resize(count);
2612 scales[c] = c_scales[c];
2631 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
2634 (
dnnl_dim_t)scales.size(), mask, scales.data()),
2635 "could not set scales primitive attribute");
2649 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
2652 const int32_t *c_zero_points;
2654 get(), arg, &count, &c_mask, &c_zero_points),
2655 "could not get zero points primitive attribute");
2656 zero_points.resize(count);
2660 zero_points[c] = c_zero_points[c];
2684 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
2687 zero_points.data()),
2688 "could not set zero points primitive attribute");
2698 "could not get post-ops primitive attribute");
2699 result.
reset(const_cast<dnnl_post_ops_t>(c_result),
true);
2713 "could not set post-ops primitive attribute");
2752 "could not get RNN data quantization parameters primitive " 2784 (
int)scales.size(), mask, scales.data()),
2785 "could not get RNN weights quantization parameters primitive " 2812 "could not retrieve implementation info string from a " 2813 "primitive descriptor");
2846 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
2847 [=](
query q) {
return what == q; }))
2849 "memory descriptor query is invalid");
2973 "could not retrieve scratchpad engine from a primitive " 2975 return engine(c_engine,
true);
2983 "could not get attributes from a primitive descriptor");
2986 "could not clone primitive attributes");
2996 "could not get primitive kind from a primitive descriptor");
3007 "could not clone a primitive descriptor");
3060 if (pd ==
nullptr)
return;
3073 rc,
"could not get primitive kind from a primitive descriptor");
3074 if (pd_kind != c_prim_kind)
3076 "primitive descriptor operation kind mismatch");
3086 "could not get propagation kind from the primitive " 3092 && (pd_prop_kind == c_prop_kind1
3093 || pd_prop_kind == c_prop_kind2))) {
3100 "primitive descriptor propagation kind mismatch");
3149 "could not create a primitive descriptor for a reorder " 3170 "could not create a primitive descriptor for a reorder " 3244 const std::vector<memory::desc> &mems) {
3245 std::vector<dnnl_memory_desc_t> c_mems;
3246 c_mems.reserve(mems.size());
3247 for (
const auto &s : mems)
3248 c_mems.push_back(s.data);
3282 const std::vector<memory::desc> &srcs,
const engine &
engine,
3289 (
int)c_srcs.size(), concat_dimension, c_srcs.data(),
3291 "could not create a primitive descriptor for a concat " 3309 const std::vector<memory::desc> &srcs,
const engine &
engine,
3316 (
int)c_api_srcs.size(), concat_dimension,
3317 c_api_srcs.data(), attr.get(),
engine.
get()),
3318 "could not create a primitive descriptor for a concat " 3382 const std::vector<float> &scales,
3383 const std::vector<memory::desc> &srcs,
const engine &
engine,
3385 validate_container_size(scales,
3386 "counts of scales and sources are not equal",
3387 (
int)srcs.size(), (int)srcs.size());
3394 (
int)c_api_srcs.size(), scales.data(),
3395 c_api_srcs.data(), attr.get(),
engine.
get()),
3396 "could not create a primitive descriptor for a sum " 3412 const std::vector<memory::desc> &srcs,
const engine &
engine,
3414 validate_container_size(scales,
3415 "counts of scales and sources are not equal",
3416 (
int)srcs.size(), (int)srcs.size());
3422 (
int)c_api_srcs.size(), scales.data(),
3423 c_api_srcs.data(), attr.get(),
engine.
get()),
3424 "could not create a primitive descriptor for a sum " 3487 bool allow_empty =
false)
3488 : allow_empty_(allow_empty) {
3491 desc, attr ? attr->
get() :
nullptr,
engine.
get(), hint_fwd_pd);
3494 status,
"could not create a primitive descriptor iterator");
3495 pd_iterator.reset(iterator);
3508 status,
"could not advance a primitive descriptor iterator");
3514 bool allow_empty_ =
false;
3518 pd_iterator.
get(allow_empty_));
3521 "could not fetch a primitive descriptor from a primitive " 3522 "descriptor iterator");
3590 &strides[0], &padding_l[0], &padding_r[0]),
3591 "could not create a descriptor for a convolution forward " 3592 "propagation primitive");
3635 &weights_desc.
data,
nullptr, &dst_desc.
data,
3636 &strides[0], &padding_l[0], &padding_r[0]),
3637 "could not create a descriptor for a convolution forward " 3638 "propagation primitive");
3687 &weights_desc.
data, &bias_desc.
data,
3688 &dst_desc.
data, &strides[0], &dilates[0],
3689 &padding_l[0], &padding_r[0]),
3690 "could not create a descriptor for a dilated convolution " 3691 "forward propagation primitive");
3737 &weights_desc.
data,
nullptr,
3738 &dst_desc.
data, &strides[0], &dilates[0],
3739 &padding_l[0], &padding_r[0]),
3740 "could not create a descriptor for a dilated convolution " 3741 "forward propagation primitive");
3761 bool allow_empty =
false)
3763 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
3779 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
3860 &weights_desc.
data, &diff_dst_desc.
data,
3861 &strides[0], &padding_l[0], &padding_r[0]),
3862 "could not create a descriptor for a convolution backward " 3863 "propagation primitive");
3906 &weights_desc.
data, &diff_dst_desc.
data,
3907 &strides[0], &dilates[0], &padding_l[0],
3909 "could not create a descriptor for a dilated convolution " 3910 "backward propagation primitive");
3934 bool allow_empty =
false)
3936 hint_fwd_pd.
get(), allow_empty) {}
3955 bool allow_empty =
false)
4034 &diff_weights_desc.
data, &diff_bias_desc.
data,
4035 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4037 "could not create a descriptor for a convolution weights " 4038 "update primitive");
4076 &diff_weights_desc.
data,
nullptr,
4077 &diff_dst_desc.
data, &strides[0],
4078 &padding_l[0], &padding_r[0]),
4079 "could not create a descriptor for a convolution weights " 4080 "update primitive");
4127 &diff_weights_desc.
data, &diff_bias_desc.
data,
4128 &diff_dst_desc.
data, &strides[0], &dilates[0],
4129 &padding_l[0], &padding_r[0]),
4130 "could not create a descriptor for a dilated convolution " 4131 "weights gradient primitive");
4174 &diff_weights_desc.
data,
nullptr,
4175 &diff_dst_desc.
data, &strides[0], &dilates[0],
4176 &padding_l[0], &padding_r[0]),
4177 "could not create a descriptor for a dilated convolution " 4178 "weights gradient primitive");
4201 bool allow_empty =
false)
4203 hint_fwd_pd.
get(), allow_empty) {}
4221 bool allow_empty =
false)
4324 &strides[0], &padding_l[0], &padding_r[0]),
4325 "could not create a descriptor for a deconvolution forward " 4326 "propagation primitive");
4368 &weights_desc.
data,
nullptr, &dst_desc.
data,
4369 &strides[0], &padding_l[0], &padding_r[0]),
4370 "could not create a descriptor for a deconvolution forward " 4371 "propagation primitive");
4419 &weights_desc.
data, &bias_desc.
data,
4420 &dst_desc.
data, &strides[0], &dilates[0],
4421 &padding_l[0], &padding_r[0]),
4422 "could not create a descriptor for a dilated deconvolution " 4423 "forward propagation primitive");
4468 &weights_desc.
data,
nullptr,
4469 &dst_desc.
data, &strides[0], &dilates[0],
4470 &padding_l[0], &padding_r[0]),
4471 "could not create a descriptor for a dilated deconvolution " 4472 "forward propagation primitive");
4492 bool allow_empty =
false)
4494 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
4510 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
4586 &weights_desc.
data, &diff_dst_desc.
data,
4587 &strides[0], &padding_l[0], &padding_r[0]),
4588 "could not create a descriptor for a deconvolution " 4589 "backward propagation primitive");
4631 &weights_desc.
data, &diff_dst_desc.
data,
4632 &strides[0], &dilates[0], &padding_l[0],
4634 "could not create a descriptor for a dilated deconvolution " 4635 "backward propagation primitive");
4659 bool allow_empty =
false)
4661 hint_fwd_pd.
get(), allow_empty) {}
4680 bool allow_empty =
false)
4758 &diff_weights_desc.
data, &diff_bias_desc.
data,
4759 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4761 "could not create a descriptor for a deconvolution weights " 4762 "update primitive");
4799 &src_desc.
data, &diff_weights_desc.
data,
4800 nullptr, &diff_dst_desc.
data, &strides[0],
4801 &padding_l[0], &padding_r[0]),
4802 "could not create a descriptor for a deconvolution weights " 4803 "update primitive");
4849 &diff_weights_desc.
data, &diff_bias_desc.
data,
4850 &diff_dst_desc.
data, &strides[0], &dilates[0],
4851 &padding_l[0], &padding_r[0]),
4852 "could not create a descriptor for a dilated deconvolution " 4853 "weights gradient primitive");
4895 &diff_weights_desc.
data,
nullptr,
4896 &diff_dst_desc.
data, &strides[0], &dilates[0],
4897 &padding_l[0], &padding_r[0]),
4898 "could not create a descriptor for a dilated deconvolution " 4899 "weights gradient primitive");
4923 bool allow_empty =
false)
4925 hint_fwd_pd.
get(), allow_empty) {}
4944 bool allow_empty =
false)
5027 float alpha,
float beta,
float k = 1.f) {
5031 local_size, alpha, beta, k),
5032 "could not create a descriptor for a lrn forward " 5033 "propagation primitive");
5052 bool allow_empty =
false)
5054 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5069 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5132 float alpha,
float beta,
float k = 1.f) {
5135 &diff_data_desc.
data, &data_desc.
data, local_size,
5137 "could not create a descriptor for a lrn backward " 5138 "propagation primitive");
5161 bool allow_empty =
false)
5163 hint_fwd_pd.
get(), allow_empty) {}
5181 bool allow_empty =
false)
5270 &dst_desc.
data, &strides[0], &kernel[0],
5271 &padding_l[0], &padding_r[0]),
5272 "could not create a descriptor for a pooling forward " 5273 "propagation primitive");
5292 bool allow_empty =
false)
5294 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5309 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5383 &diff_dst_desc.
data, &strides[0], &kernel[0],
5384 &padding_l[0], &padding_r[0]),
5385 "could not create a descriptor for a pooling backward " 5386 "propagation primitive");
5409 bool allow_empty =
false)
5411 hint_fwd_pd.
get(), allow_empty) {}
5429 bool allow_empty =
false)
5515 &data_desc.
data, alpha, beta),
5516 "could not create a descriptor for an eltwise forward " 5517 "propagation primitive");
5537 bool allow_empty =
false)
5539 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5555 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5614 &data_desc.
data, alpha, beta),
5615 "could not create a descriptor for an eltwise backward " 5616 "propagation primitive");
5640 bool allow_empty =
false)
5642 hint_fwd_pd.
get(), allow_empty) {}
5661 bool allow_empty =
false)
5731 &data_desc.
data, softmax_axis),
5732 "could not create a descriptor for a softmax forward " 5733 "propagation primitive");
5753 bool allow_empty =
false)
5755 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5771 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5827 &data_desc.
data, softmax_axis),
5828 "could not create a descriptor for a softmax backward " 5829 "propagation primitive");
5853 bool allow_empty =
false)
5855 hint_fwd_pd.
get(), allow_empty) {}
5874 bool allow_empty =
false)
5941 int logsoftmax_axis) {
5944 &data_desc.
data, logsoftmax_axis),
5945 "could not create a descriptor for a logsoftmax forward " 5946 "propagation primitive");
5966 bool allow_empty =
false)
5968 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5984 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
6041 int logsoftmax_axis) {
6043 &diff_data_desc.
data, &data_desc.
data,
6045 "could not create a descriptor for a logsoftmax backward " 6046 "propagation primitive");
6070 bool allow_empty =
false)
6072 hint_fwd_pd.
get(), allow_empty) {}
6091 bool allow_empty =
false)
6205 "could not create a descriptor for a batch normalization " 6206 "forward propagation primitive");
6227 bool allow_empty =
false)
6229 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
6245 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
6290 "could not retrieve a descriptor from a primitive " 6291 "descriptor for batch normalization forward propagation " 6352 "could not create a descriptor for a batch normalization " 6353 "backward propagation primitive");
6378 bool allow_empty =
false)
6380 hint_fwd_pd.
get(), allow_empty) {}
6399 bool allow_empty =
false)
6527 "could not create a descriptor for a layer normalization " 6528 "forward propagation primitive");
6570 "could not create a descriptor for a layer normalization " 6571 "forward propagation primitive");
6592 bool allow_empty =
false)
6594 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
6610 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
6653 "could not retrieve a descriptor from a primitive " 6654 "descriptor for layer normalization forward propagation " 6712 &data_desc.
data, &stat_desc.
data, epsilon,
6714 "could not create a descriptor for a batch normalization " 6715 "backward propagation primitive");
6751 &diff_data_desc.
data, &data_desc.
data,
6753 "could not create a descriptor for a batch normalization " 6754 "backward propagation primitive");
6779 bool allow_empty =
false)
6781 hint_fwd_pd.
get(), allow_empty) {}
6800 bool allow_empty =
false)
6900 &src_desc.
data, &weights_desc.
data,
6902 "could not create a descriptor for an inner product " 6903 "forward propagation primitive");
6932 &weights_desc.
data,
nullptr, &dst_desc.
data),
6933 "could not create a descriptor for an inner product " 6934 "forward propagation primitive");
6954 bool allow_empty =
false)
6956 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
6972 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
7034 &diff_src_desc.
data, &weights_desc.
data,
7035 &diff_dst_desc.
data),
7036 "could not create a descriptor for an inner product " 7037 "backward propagation primitive");
7062 bool allow_empty =
false)
7064 hint_fwd_pd.
get(), allow_empty) {}
7083 bool allow_empty =
false)
7147 &src_desc.
data, &diff_weights_desc.
data,
7148 &diff_bias_desc.
data, &diff_dst_desc.
data),
7149 "could not create a descriptor for an inner product " 7150 "weights gradient primitive");
7175 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
7176 &diff_dst_desc.
data),
7177 "could not create a descriptor for an inner product " 7178 "weights gradient primitive");
7202 bool allow_empty =
false)
7204 hint_fwd_pd.
get(), allow_empty) {}
7223 bool allow_empty =
false)
7275 using primitive_desc::primitive_desc;
7459 "could not retrieve a descriptor from a primitive descriptor " 7460 "for an RNN primitive");
7467 && (
rnn_d->prop_kind == c_prop_kind1
7468 ||
rnn_d->prop_kind == c_prop_kind2)
7469 &&
rnn_d->cell_kind == c_cell_kind;
7473 "mismatch between expected and provided descriptors for an " 7548 float beta = 0.0f) {
7554 &src_iter_desc.
data, &weights_layer_desc.
data,
7555 &weights_iter_desc.
data, &bias_desc.
data,
7556 &dst_layer_desc.
data, &dst_iter_desc.
data,
7558 "could not create a descriptor for a vanilla RNN forward " 7559 "propagation primitive");
7579 bool allow_empty =
false)
7581 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
7597 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
7751 float beta = 0.0f) {
7757 &src_iter_desc.
data, &weights_layer_desc.
data,
7758 &weights_iter_desc.
data, &bias_desc.
data,
7759 &dst_layer_desc.
data, &dst_iter_desc.
data,
7760 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7761 &diff_weights_layer_desc.
data,
7762 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7763 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7765 "could not create a descriptor for a vanilla RNN backward " 7766 "propagation primitive");
7790 bool allow_empty =
false)
7792 hint_fwd_pd.
get(), allow_empty) {}
7811 bool allow_empty =
false)
7813 hint_fwd_pd.
get(), allow_empty) {}
8000 &src_iter_desc.
data, &src_iter_c_desc.
data,
8001 &weights_layer_desc.
data, &weights_iter_desc.
data,
8002 &weights_peephole_desc.
data,
8003 &weights_projection_desc.
data, &bias_desc.
data,
8004 &dst_layer_desc.
data, &dst_iter_desc.
data,
8006 "could not create a descriptor for an LSTM forward " 8007 "propagation primitive");
8086 &src_iter_desc.
data, &src_iter_c_desc.
data,
8087 &weights_layer_desc.
data, &weights_iter_desc.
data,
8088 &weights_peephole_desc.
data, &bias_desc.
data,
8089 &dst_layer_desc.
data, &dst_iter_desc.
data,
8091 "could not create a descriptor for an LSTM forward " 8092 "propagation primitive");
8161 &src_iter_desc.
data, &src_iter_c_desc.
data,
8162 &weights_layer_desc.
data, &weights_iter_desc.
data,
8163 &bias_desc.
data, &dst_layer_desc.
data,
8164 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8166 "could not create a descriptor for an LSTM forward " 8167 "propagation primitive");
8186 bool allow_empty =
false)
8188 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
8203 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
8441 &src_iter_desc.
data, &src_iter_c_desc.
data,
8442 &weights_layer_desc.
data, &weights_iter_desc.
data,
8443 &weights_peephole_desc.
data,
8444 &weights_projection_desc.
data, &bias_desc.
data,
8445 &dst_layer_desc.
data, &dst_iter_desc.
data,
8446 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8447 &diff_src_iter_desc.
data,
8448 &diff_src_iter_c_desc.
data,
8449 &diff_weights_layer_desc.
data,
8450 &diff_weights_iter_desc.
data,
8451 &diff_weights_peephole_desc.
data,
8452 &diff_weights_projection_desc.
data,
8453 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8454 &diff_dst_iter_desc.
data,
8455 &diff_dst_iter_c_desc.
data,
8457 "could not create a descriptor for an LSTM backward " 8458 "propagation primitive");
8587 &src_iter_desc.
data, &src_iter_c_desc.
data,
8588 &weights_layer_desc.
data, &weights_iter_desc.
data,
8589 &weights_peephole_desc.
data, &bias_desc.
data,
8590 &dst_layer_desc.
data, &dst_iter_desc.
data,
8591 &dst_iter_c_desc.
data, &diff_src_layer_desc.
data,
8592 &diff_src_iter_desc.
data,
8593 &diff_src_iter_c_desc.
data,
8594 &diff_weights_layer_desc.
data,
8595 &diff_weights_iter_desc.
data,
8596 &diff_weights_peephole_desc.
data,
8597 &diff_bias_desc.
data, &diff_dst_layer_desc.
data,
8598 &diff_dst_iter_desc.
data,
8599 &diff_dst_iter_c_desc.
data,
8601 "could not create a descriptor for an LSTM backward " 8602 "propagation primitive");
8711 &src_iter_desc.
data, &src_iter_c_desc.
data,
8712 &weights_layer_desc.
data, &weights_iter_desc.
data,
8713 &bias_desc.
data, &dst_layer_desc.
data,
8714 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
8715 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8716 &diff_src_iter_c_desc.
data,
8717 &diff_weights_layer_desc.
data,
8718 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8719 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8720 &diff_dst_iter_c_desc.
data,
8722 "could not create a descriptor for an LSTM backward " 8723 "propagation primitive");
8746 bool allow_empty =
false)
8748 hint_fwd_pd.
get(), allow_empty) {}
8766 bool allow_empty =
false)
8768 hint_fwd_pd.
get(), allow_empty) {}
8963 &src_iter_desc.
data, &weights_layer_desc.
data,
8964 &weights_iter_desc.
data, &bias_desc.
data,
8965 &dst_layer_desc.
data, &dst_iter_desc.
data,
8967 "could not create a descriptor for a GRU forward " 8968 "propagation primitive");
8987 bool allow_empty =
false)
8989 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9004 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9153 &src_iter_desc.
data, &weights_layer_desc.
data,
9154 &weights_iter_desc.
data, &bias_desc.
data,
9155 &dst_layer_desc.
data, &dst_iter_desc.
data,
9156 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9157 &diff_weights_layer_desc.
data,
9158 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9159 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9161 "could not create a descriptor for a GRU backward " 9162 "propagation primitive");
9185 bool allow_empty =
false)
9187 hint_fwd_pd.
get(), allow_empty) {}
9205 bool allow_empty =
false)
9207 hint_fwd_pd.
get(), allow_empty) {}
9362 &src_iter_desc.
data, &weights_layer_desc.
data,
9363 &weights_iter_desc.
data, &bias_desc.
data,
9364 &dst_layer_desc.
data, &dst_iter_desc.
data,
9366 "could not create a descriptor for an LBR GRU forward " 9367 "propagation primitive");
9387 bool allow_empty =
false)
9389 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9405 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9555 &src_iter_desc.
data, &weights_layer_desc.
data,
9556 &weights_iter_desc.
data, &bias_desc.
data,
9557 &dst_layer_desc.
data, &dst_iter_desc.
data,
9558 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
9559 &diff_weights_layer_desc.
data,
9560 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
9561 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
9563 "could not create a descriptor for an LBR GRU backward " 9564 "propagation primitive");
9588 bool allow_empty =
false)
9590 hint_fwd_pd.
get(), allow_empty) {}
9609 bool allow_empty =
false)
9611 hint_fwd_pd.
get(), allow_empty) {}
9737 &data_desc.
data, axis, group_size),
9738 "could not create a descriptor for a shuffle forward " 9739 "propagation primitive");
9761 bool allow_empty =
false)
9763 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9814 &diff_data_desc.
data, axis, group_size),
9815 "could not create a descriptor for a shuffle backward " 9816 "propagation primitive");
9842 bool allow_empty =
false)
9911 "could not create a descriptor for a binary operation " 9931 bool allow_empty =
false)
9933 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9948 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
10013 &weights_desc.
data,
nullptr, &dst_desc.
data),
10014 "could not create a descriptor for a matmul primitive");
10034 &weights_desc.
data, &bias_desc.
data,
10036 "could not create a descriptor for a matmul primitive");
10054 bool allow_empty =
false)
10056 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
10070 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
10149 "could not create a resampling forward descriptor");
10167 const std::vector<float> &factors,
10173 &src_desc.
data,
nullptr),
10174 "could not create a resampling forward descriptor");
10200 const std::vector<float> &factors,
const memory::desc &src_desc,
10202 if (!factors.empty())
10208 "could not create a resampling forward descriptor");
10228 bool allow_empty =
false)
10230 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
10246 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
10299 &diff_src_desc.
data, &diff_dst_desc.
data),
10300 "could not create a resampling backward data descriptor");
10321 if (!factors.empty())
10325 &diff_src_desc.
data, &diff_dst_desc.
data),
10326 "could not create a resampling backward data descriptor");
10350 bool allow_empty =
false)
10352 hint_fwd_pd.
get(), allow_empty) {}
10371 bool allow_empty =
false)
10481 return static_cast<status>(
10499 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
10506 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10508 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10515 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
10517 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
10520 #if DNNL_CPU_RUNTIME == DNNL_RUNTIME_THREADPOOL 10526 return static_cast<status>(dnnl_sgemm_tp(
10527 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc, tp));
10533 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10535 return static_cast<status>(dnnl_gemm_u8s8s32_tp(transa, transb, offsetc, M,
10536 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10543 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co,
10545 return static_cast<status>(dnnl_gemm_s8s8s32_tp(transa, transb, offsetc, M,
10546 N, K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co, tp));
10558 "could not create a primitive");
10564 inline void primitive::execute(
const stream &stream,
10565 const std::unordered_map<int, memory> &args)
const {
10566 std::vector<dnnl_exec_arg_t> c_args;
10567 c_args.reserve(args.size());
10568 for (
const auto &a : args)
10569 c_args.push_back({a.first, a.second.get(
true)});
10572 (int)c_args.size(), c_args.data()),
10573 "could not execute a primitive");
10577 #undef DNNL_DEFINE_BITMASK_OPS #define DNNL_ARG_WEIGHTS_PROJECTION
A special mnemonic for RNN weights applied to the projection weights.
Definition: dnnl_types.h:1853
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6481
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...
desc(algorithm algorithm, 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:3850
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.
A layer normalization primitive.
Definition: dnnl_types.h:730
cl_device_id get_ocl_device() const
Returns the OpenCL device associated with the engine.
Definition: dnnl.hpp:935
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_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.
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4542
primitive_desc(const desc &desc, const engine &engine, 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:10348
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8200
destination grad. memory desc
Definition: dnnl_types.h:2054
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2028
An element-wise primitive.
Definition: dnnl_types.h:720
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:1051
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4962
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9744
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.
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:5211
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:3179
prop_kind
Propagation kind.
Definition: dnnl.hpp:440
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:317
primitive_desc(const desc &desc, const engine &engine, 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:9183
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7632
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2897
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10080
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8789
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...
execution engine
Definition: dnnl_types.h:2005
primitive_desc(const desc &desc, const engine &engine, 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:6068
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5291
A batch normalization primitive.
Definition: dnnl_types.h:728
sum()=default
Default constructor. Produces an empty object.
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:7030
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5892
primitive_desc()=default
Default constructor. Produces an empty object.
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.
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:4275
Eltwise: bounded_relu.
Definition: dnnl_types.h:775
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9432
primitive_desc(const desc &desc, const engine &engine, 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:3932
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5083
Undefined memory format tag.
Definition: dnnl_types.h:169
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:5178
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:212
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:9869
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8880
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5278
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:3965
Vanilla RNN descriptor backward propagation primitive.
Definition: dnnl.hpp:7657
CPU engine.
Definition: dnnl_types.h:1650
inner_product_backward_data()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(prop_kind prop_kind, const memory::desc &data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9733
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:800
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9780
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_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...
#define DNNL_ARG_DIFF_WEIGHTS_ITER
A special mnemonic for diff of RNN weights applied to the recurrent input.
Definition: dnnl_types.h:1927
destination memory desc
Definition: dnnl_types.h:2053
Direct deconvolution.
Definition: dnnl_types.h:757
Elementwise: exponential linear unit (ELU)
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const engine &engine, 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:9839
primitive_desc()=default
Default constructor. Produces an empty object.
A descriptor for an RNN operation.
Definition: dnnl_types.h:1486
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1722
The operation failed due to an out-of-memory condition.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8799
layer normalization descriptor
Definition: dnnl_types.h:2038
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:9295
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:7397
Elementwise: erf-based gelu.
primitive_desc(const desc &desc, const engine &engine, 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:6376
memory consumption – extra
Definition: dnnl_types.h:2012
Average pooling exclude padding, alias for dnnl::algorithm::pooling_avg_include_padding.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7313
void execute(const stream &stream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
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:10512
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:704
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:4941
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:2357
Average pooling include padding.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax forward propagation primitive. ...
Definition: dnnl.hpp:5981
eltwise_forward()=default
Default constructor. Produces an empty object.
permuted 3D tensor
Definition: dnnl_types.h:194
Eltwise: linear.
Definition: dnnl_types.h:773
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:6409
desc(prop_kind prop_kind, const memory::desc &data_desc, int softmax_axis)
Constructs a descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5727
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3915
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:5904
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5086
Bidirectional execution of RNN primitive with concatenation of the results.
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5391
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8258
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8809
Elementwise: logistic (dst for backward)
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6832
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7104
memory(const desc &md, const engine &engine)
Constructs a memory object.
Definition: dnnl.hpp:2006
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:2512
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
A resampling primitive.
Definition: dnnl_types.h:744
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:9789
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6226
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6125
An opaque structure to describe a primitive.
GRU cell with linear before reset.
Definition: dnnl_types.h:836
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4981
oneDNN namespace
Definition: dnnl.hpp:81
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3542
Any ISA (no restrictions)
Definition: dnnl_types.h:2152
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6431
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
primitive_desc()=default
Default constructor. Produces an empty object.
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA the library can dispatch to on the CPU.
Definition: dnnl.hpp:10480
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...
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:949
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8786
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.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:1798
desc(prop_kind prop_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, and memory descriptors.
Definition: dnnl.hpp:8687
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7831
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:3805
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7385
primitive_desc(const memory::desc &dst, const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &engine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3381
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9637
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. ...
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5572
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9629
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.
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:4183
primitive_desc(const desc &desc, const engine &engine, 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:7060
desc(algorithm algorithm, 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:4114
binary()=default
Default constructor. Produces an empty object.
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.
#define DNNL_ARG_WEIGHTS_LAYER
A special mnemonic for RNN weights applied to the layer input.
Definition: dnnl_types.h:1835
Use no normalization flags.
Definition: dnnl_types.h:861
scratchpad memory desc
Definition: dnnl_types.h:2056
Elementwise: natural logarithm.
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.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9249
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1122
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2155
Eltwise: clip.
Definition: dnnl_types.h:794
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:7113
Shuffle backward propagation primitive.
Definition: dnnl.hpp:9793
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9402
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3448
An opaque structure for primitive descriptor attributes.
reorder destination engine
cl_context get_ocl_context() const
Returns the OpenCL context associated with the engine.
Definition: dnnl.hpp:926
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9445
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:4714
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:10076
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:7246
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8835
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9777
gru_forward()=default
Default constructor. Produces an empty object.
logsoftmax descriptor
Definition: dnnl_types.h:2043
Backward propagation (with respect to all parameters).
kind
Kinds of primitives supported by the library.
Definition: dnnl.hpp:282
permuted 4D tensor
Definition: dnnl_types.h:191
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2527
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:5871
Use scale and shift parameters.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7373
desc(prop_kind prop_kind, algorithm algorithm, 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:4311
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8222
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4527
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7413
primitive_desc(const desc &desc, const engine &engine, const lrn_forward::primitive_desc &hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5159
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.
#define DNNL_ARG_DST_LAYER
A special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
Definition: dnnl_types.h:1811
desc(prop_kind prop_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:9349
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:4996
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:2861
An opaque structure to describe a memory.
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:7274
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:183
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6242
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7010
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:9852
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6969
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6829
Elementwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
permuted 5D tensor
Definition: dnnl_types.h:192
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:1732
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9463
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6483
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1646
desc(prop_kind prop_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:6706
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:806
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5682
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7619
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3793
primitive_desc()=default
Default constructor. Produces an empty object.
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:5779
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9044
batch_normalization_backward()=default
Default constructor. Produces an empty object.
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...
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
lbr_gru_forward()=default
Default constructor. Produces an empty object.
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:3256
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:1930
#define DNNL_ARG_SRC_LAYER
A special mnemonic for RNN input vector.
Definition: dnnl_types.h:1785
Elementwise: square root (dst for backward)
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a resampling forward propagation primitive. ...
Definition: dnnl.hpp:10243
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:5823
Undefined primitive.
Definition: dnnl_types.h:706
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:2711
number of outputs expected
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5306
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7640
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:2222
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1472
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1717
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7365
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7119
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5326
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:216
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:6040
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:7325
batch normalization descriptor
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9018
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b ...
Definition: dnnl_types.h:512
Nearest Neighbor resampling method.
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8855
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6005
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1067
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:8763
primitive_desc()=default
Default constructor. Produces an empty object.
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b ...
Definition: dnnl_types.h:497
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9437
binary descriptor
Definition: dnnl_types.h:2042
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5536
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6989
Elementwise: square root.
primitive_desc()=default
Default constructor. Produces an empty object.
The operation was successful.
permuted 4D tensor
Definition: dnnl_types.h:186
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2941
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:10260
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6113
Any ISA (no restrictions)
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr)
Destroys primitive attributes.
#define DNNL_ARG_WEIGHTS_ITER
A special mnemonic for RNN weights applied to the recurrent input.
Definition: dnnl_types.h:1841
desc(algorithm algorithm, 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:4790
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6311
memory::desc diff_weights_peephole_desc() const
Returns diff weights peephole memory descriptor.
Definition: dnnl.hpp:8860
primitive_desc(const_dnnl_op_desc_t desc, const primitive_attr *attr, const engine &engine, const_dnnl_primitive_desc_t hint_fwd_pd, bool allow_empty=false)
Constructs a primitive descriptor.
Definition: dnnl.hpp:3485
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7890
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5066
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8850
A descriptor of a pooling operation.
Definition: dnnl_types.h:1291
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:10453
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:1914
plain 2D tensor
Definition: dnnl_types.h:178
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:916
A memory descriptor.
Definition: dnnl.hpp:1729
primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::primitive::kind prim_kind, dnnl::prop_kind prop_kind)
Constructs a primitive descriptor base object from a clone of a C API primitive descriptor after veri...
Definition: dnnl.hpp:3039
permuted 5D tensor
Definition: dnnl_types.h:198
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:687
void set_threadpool(threadpool_iface *threadpool)
Sets the threadpool attribute.
Definition: dnnl.hpp:1027
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3799
destination gradient (diff) memory desc
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9241
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:5658
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:7808
GRU cell with linear before reset.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:9284
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.
desc(prop_kind prop_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:9535
32-bit signed integer.
Definition: dnnl_types.h:72
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1480
primitive_desc(const std::vector< float > &scales, const std::vector< memory::desc > &srcs, const engine &engine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3411
dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(const_dnnl_post_ops_t post_ops, int index, float *scale, dnnl_alg_kind_t *alg_kind, float *alpha, float *beta)
Returns the parameters of an elementwise post-up.
An inner product primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8253
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4959
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6002
Direct convolution.
Definition: dnnl_types.h:751
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:2917
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9668
A container for stream attributes.
Definition: dnnl.hpp:1002
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:370
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5038
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:7141
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7907
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:272
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9246
An opaque structure to describe a primitive descriptor iterator.
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5581
pooling descriptor
Definition: dnnl_types.h:2035
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:755
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9658
Elementwise: bounded_relu.
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6018
An execution engine.
Definition: dnnl.hpp:844
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:10101
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6953
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6110
GRU forward propagation primitive.
Definition: dnnl.hpp:8900
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.
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6577
desc(prop_kind prop_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:7735
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.
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:3985
dnnl_status_t DNNL_API dnnl_memory_unmap_data(const_dnnl_memory_t memory, void *mapped_ptr)
Unmaps a memory object and writes back any changes made to the previously mapped memory buffer...
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3195
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:2808
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9632
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:2118
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9036
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5104
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:7183
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9047
layer_normalization_forward()=default
Default constructor. Produces an empty object.
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...
An element-wise 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.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution weights gradient primitive.
memory desc of an execute argument
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9427
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1474
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.
A deconvolution primitive.
Definition: dnnl_types.h:718
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:4998
A class that provides the destructor for a oneDNN C API handle.
Definition: dnnl.hpp:127
lstm_backward()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:7238
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:3787
LSTM backward propagation primitive.
Definition: dnnl.hpp:8281
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7301
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.
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:293
desc(prop_kind prop_kind, algorithm algorithm, 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:3675
8-bit unsigned integer.
Definition: dnnl_types.h:76
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1594
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4239
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6637
Alias for dnnl::rnn_direction::unidirectional_left2right.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3437
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
permuted 6D tensor
Definition: dnnl_types.h:204
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...
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9645
desc(prop_kind prop_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:7983
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
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.
number of inputs expected
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3970
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7880
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6668
#define DNNL_ARG_DIFF_DST_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1903
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2002
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6820
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2158
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2169
Backward data propagation.
Definition: dnnl_types.h:695
Inner product forward propagation primitive.
Definition: dnnl.hpp:6868
Average pooling exclude padding.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5447
desc(prop_kind prop_kind, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a descriptor for layer normalization forward propagation primitive.
Definition: dnnl.hpp:6564
A descriptor of a binary operation.
Definition: dnnl_types.h:1568
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.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7616
source gradient memory desc
Definition: dnnl_types.h:2050
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:2804
A binary primitive.
Definition: dnnl_types.h:738
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2120
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5585
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:10368
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4710
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:2749
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8781
primitive_desc(int concat_dimension, const std::vector< memory::desc > &srcs, const engine &engine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3308
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...
#define DNNL_ARG_DIFF_SRC_ITER
A special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1882
primitive_desc()=default
Default constructor. Produces an empty object.
LSTM cell.
Definition: dnnl_types.h:826
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:7249
Packed weights format used in RNN.
Definition: dnnl_types.h:93
desc()=default
Default constructor. Produces an empty object.
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
#define DNNL_ARG_DST_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1817
desc(algorithm algorithm, 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:4836
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:3327
desc(prop_kind prop_kind, algorithm algorithm, 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:10199
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5488
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:6101
desc(prop_kind prop_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:6926
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:232
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9653
#define DNNL_ARG_SRC_ITER_C
A special mnemonic for RNN input recurrent cell state vector.
Definition: dnnl_types.h:1800
Inner product weights gradient primitive.
Definition: dnnl.hpp:7117
desc(const memory::dims &dims, data_type data_type, format_tag format_tag, bool allow_empty=false)
Constructs a memory descriptor.
Definition: dnnl.hpp:1753
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4970
A reorder primitive.
Definition: dnnl_types.h:708
memory(const desc &md, const engine &engine, void *handle)
Constructs a memory object.
Definition: dnnl.hpp:1992
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10093
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9642
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.
pooling_forward()=default
Default constructor. Produces an empty object.
A descriptor of a convolution operation.
Definition: dnnl_types.h:1134
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.
desc(prop_kind prop_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:6895
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4491
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7391
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:10278
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:590
matmul()=default
Default constructor. Produces an empty object.
convolution_forward()=default
Default constructor. Produces an empty object.
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:10433
softmax descriptor
Definition: dnnl_types.h:2034
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:5077
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9225
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:9012
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.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:9202
Elementwise: tanh-based gelu.
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:5797
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
Definition: dnnl_types.h:2173
format_kind
Memory format kind.
Definition: dnnl.hpp:1226
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9976
primitive_desc(const desc &desc, const engine &engine, const primitive_attr &attr=primitive_attr(), bool allow_empty=false)
Constructs a primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9759
no query
Definition: dnnl_types.h:2003
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6986
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9930
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1700
Fuse with ReLU.
Definition: dnnl_types.h:900
data_type
Data type specification.
Definition: dnnl.hpp:1208
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2879
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8266
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6051
Forward data propagation (training mode).
batch normalization descriptor
Definition: dnnl_types.h:2037
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8794
The operation failed because requested functionality is not implemented.
primitive_desc()=default
Default constructor. Produces an empty object.
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3356
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:4518
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:8865
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8240
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:10263
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9228
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:9650
runtime estimation (seconds)
Definition: dnnl_types.h:2011
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:693
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:10389
An unspecified engine.
Definition: dnnl_types.h:1648
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:9771
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:3433
Backward weights propagation.
eltwise_backward()=default
Default constructor. Produces an empty object.
threadpool_iface * get_threadpool()
Returns the threadpool attribute.
Definition: dnnl.hpp:1037
static size_t get_count(kind kind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:868
handle()=default
Constructs an empty handle object.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9023
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:9058
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:270
Eltwise: ReLU.
Definition: dnnl_types.h:761
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2906
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9301
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.
GPU engine.
Definition: dnnl_types.h:1652
Local response normalization (LRN) across multiple channels.
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.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:7098
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.
softmax_backward()=default
Default constructor. Produces an empty object.
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:6151
Convolution forward propagation primitive.
Definition: dnnl.hpp:3540
primitive_desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4904
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6436
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5450
primitive_desc(const desc &desc, const engine &engine, 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:8744
primitive_desc(const memory::desc &dst, int concat_dimension, const std::vector< memory::desc > &srcs, const engine &engine, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for an out-of-place concatenation primitive.
Definition: dnnl.hpp:3281
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6428
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5552
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:7004
Use no normalization flags.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7651
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5587
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:5691
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:3004
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2017
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9663
cl_command_queue get_ocl_command_queue() const
Returns the underlying OpenCL queue object.
Definition: dnnl.hpp:1097
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:2962
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5486
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9031
desc(prop_kind prop_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:8070
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:5102
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8817
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9274
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const engine &engine, 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:6777
Eltwise: pow.
Definition: dnnl_types.h:796
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7307
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:281
lstm_forward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8840
permuted 4D tensor
Definition: dnnl_types.h:200
An opaque structure to describe an engine.
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:2648
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5569
desc(prop_kind prop_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:7539
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:2416
desc(prop_kind prop_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:9133
desc(algorithm algorithm, 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:5130
desc()=default
Default constructor. Produces an empty object.
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7481
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4236
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:10398
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:3024
lrn_forward()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(prop_kind prop_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:6746
#define DNNL_ARG_SRC_ITER
A special mnemonic for RNN input recurrent hidden state vector.
Definition: dnnl_types.h:1794
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5089
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:7260
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:10381
Forward data propagation (inference mode).
Definition: dnnl_types.h:687
Undefined RNN flags.
Definition: dnnl_types.h:1466
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:2841
A sum primitive.
Definition: dnnl_types.h:714
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6840
desc(algorithm algorithm, 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:4619
oneDNN exception class.
Definition: dnnl.hpp:91
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:8245
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9857
#define DNNL_ARG_BIAS
Bias tensor argument.
Definition: dnnl_types.h:1856
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7839
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:2442
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2165
stream_attr(engine::kind kind)
Constructs stream attributes for a stream that runs on an engine of a particular kind.
Definition: dnnl.hpp:1012
primitive_desc()=default
Default constructor. Produces an empty object.
void set_data_handle(void *handle) const
Sets data handle.
Definition: dnnl.hpp:2075
Forward data propagation (inference mode).
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1209
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.
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1261
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:3991
An opaque structure for a chain of post operations.
primitive_desc(const memory &src, const memory &dst, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for reorder primitive.
Definition: dnnl.hpp:3161
A descriptor of an inner product operation.
Definition: dnnl_types.h:1430
stream(const engine &engine, flags flags=flags::default_flags, const stream_attr &attr=stream_attr())
Constructs a stream for the specified engine and with behavior controlled by the specified flags...
Definition: dnnl.hpp:1073
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4716
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a resampling forward propagation primitive. ...
Definition: dnnl.hpp:10227
Forward data propagation, alias for dnnl::prop_kind::forward_training.
desc(prop_kind prop_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:6520
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:2217
runtime estimation (seconds), unimplemented
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:10272
desc(prop_kind prop_kind, algorithm algorithm, 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:10166
Pooling forward propagation primitive.
Definition: dnnl.hpp:5225
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6591
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1470
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3796
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7826
desc(algorithm algorithm, 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:5608
inner product descriptor
Definition: dnnl_types.h:2039
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:274
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:319
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:6980
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6305
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:10503
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
Status values returned by the library functions.
Definition: dnnl_types.h:39
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5444
stream()=default
Constructs an empty stream.
Pooling backward propagation primitive.
Definition: dnnl.hpp:5342
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8261
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
Abstract threadpool interface.
Definition: dnnl_threadpool_iface.hpp:27
Binary mul.
Definition: dnnl_types.h:840
LRN within a single channel.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5329
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:4218
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8814
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.
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:9264
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6212
Elementwise: rectified linear unit (ReLU)
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8217
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:6810
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:9233
A softmax primitive.
Definition: dnnl_types.h:722
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5676
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7419
memory::desc weights_peephole_desc() const
Returns weights peephole memory descriptor.
Definition: dnnl.hpp:8804
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:944
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.
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:691
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9440
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:9448
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1107
primitive kind
Definition: dnnl_types.h:2006
dnnl_status_t DNNL_API dnnl_engine_get_ocl_context(dnnl_engine_t engine, cl_context *context)
Returns the OpenCL context associated with an engine.
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2044
shuffle_backward()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9967
Default stream configuration.
Definition: dnnl_types.h:2077
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6422
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:6253
Shuffle forward propagation primitive.
Definition: dnnl.hpp:9713
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5752
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:99
LRN within a single channel.
Definition: dnnl_types.h:822
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_data_type_t
Data type specification.
Definition: dnnl_types.h:62
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:2209
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6625
plain 4D tensor
Definition: dnnl_types.h:180
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:373
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3503
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5459
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:7821
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5895
batch_normalization_forward()=default
Default constructor. Produces an empty object.
plain 6D tensor
Definition: dnnl_types.h:182
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:3254
desc(algorithm algorithm, 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:10295
Primitive attributes.
Definition: dnnl.hpp:2481
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9624
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:810
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3973
Winograd convolution.
Definition: dnnl_types.h:753
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:307
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:2497
#define DNNL_ARG_DIFF_SRC_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:1888
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7655
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:6618
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4967
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5199
desc(prop_kind prop_kind, algorithm algorithm, 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:3577
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7345
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6672
desc(prop_kind prop_kind, algorithm algorithm, 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:10143
desc(prop_kind prop_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:6345
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
void append_eltwise(float scale, algorithm algorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2280
Max pooling.
Definition: dnnl_types.h:812
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.
void get_params_eltwise(int index, float &scale, algorithm &algorithm, float &alpha, float &beta) const
Returns parameters of an elementwise post-up.
Definition: dnnl.hpp:2294
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3760
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7629
Eltwise: natural logarithm.
Definition: dnnl_types.h:792
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7860
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4250
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:8211
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:3056
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:103
primitive_desc()=default
Default constructor. Produces an empty object.
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...
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
A special mnemonic for diff of RNN weights applied to the projection weights.
Definition: dnnl_types.h:1939
Unidirectional execution of RNN primitive from left to right.
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.
primitive_desc()=default
Default constructor. Produces an empty object.
const dnnl_version_t DNNL_API * dnnl_version()
Returns library version information.
kind
Kinds of engines.
Definition: dnnl.hpp:849
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b ...
Definition: dnnl_types.h:500
Base class for all computational primitives.
Definition: dnnl.hpp:277
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:192
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6359
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:10438
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:252
Out-of-order execution.
Definition: dnnl_types.h:2075
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9064
Fuse normalization with ReLU.
Binary min.
Definition: dnnl_types.h:844
pooling_backward()=default
Default constructor. Produces an empty object.
void set_data_handle(void *handle, const stream &stream) const
Sets data handle.
Definition: dnnl.hpp:2061
primitive_desc(const desc &desc, const engine &engine, 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:5851
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:6309
status
Status values returned by the library functions.
Definition: dnnl.hpp:10415
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6631
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4533
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5951
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3976
Default stream configuration.
permuted 3D tensor
Definition: dnnl_types.h:188
primitive_desc()=default
Default constructor. Produces an empty object.
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:268
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b ...
Definition: dnnl_types.h:491
layer_normalization_backward()=default
Default constructor. Produces an empty object.
dnnl_engine_kind_t convert_to_c(engine::kind kind)
Converts engine kind enum value from C++ API to C API type.
Definition: dnnl.hpp:972
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:818
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:6153
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:5143
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9885
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7319
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8185
#define DNNL_ARG_DIFF_BIAS
Gradient (diff) of the bias tensor argument.
Definition: dnnl_types.h:1942
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:9254
void execute(const stream &stream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:3227
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6823
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:223
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:7080
Binary add.
Definition: dnnl_types.h:838
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...
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7359
deconvolution descriptor
Definition: dnnl_types.h:2031
A pooling primitive.
Definition: dnnl_types.h:724
#define DNNL_ARG_WEIGHTS_PEEPHOLE
A special mnemonic for RNN weights applied to the peephole weights.
Definition: dnnl_types.h:1847
desc(prop_kind prop_kind, algorithm algorithm, 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:3725
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:9215
rnn descriptor
Definition: dnnl_types.h:2040
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:2631
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:7101
memory consumption (bytes)
LSTM forward propagation primitive.
Definition: dnnl.hpp:7905
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:1936
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.
Eltwise: logistic.
Definition: dnnl_types.h:779
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:10495
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6826
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3198
desc(prop_kind prop_kind, algorithm algorithm, 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:4456
resampling_backward()=default
Default constructor. Produces an empty object.
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1187
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.
resampling_forward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:10386
memory::desc diff_weights_projection_desc() const
Returns diff weights projection memory descriptor.
Definition: dnnl.hpp:7404
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9386
desc(prop_kind prop_kind, const memory::desc &data_desc, float epsilon, normalization_flags flags)
Constructs a batch normalization descriptor for forward propagation.
Definition: dnnl.hpp:6199
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3440
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:802
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_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_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.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4695
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9459
Winograd deconvolution.
Definition: dnnl_types.h:759
dnnl_status_t DNNL_API dnnl_set_max_cpu_isa(dnnl_cpu_isa_t isa)
Sets the maximal ISA the library can dispatch to on the CPU.
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:10088
permuted 4D tensor
Definition: dnnl_types.h:201
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6634
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.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:9238
primitive_desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9569
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6854
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:7233
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_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1190
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7834
reorder()=default
Default constructor. Produces an empty object.
Convolution backward propagation primitive.
Definition: dnnl.hpp:3818
number of outputs expected
Definition: dnnl_types.h:2009
primitive_desc(const desc &desc, const engine &engine, 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:9586
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4477
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7379
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:3206
desc(prop_kind prop_kind, algorithm algorithm, 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:4407
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:6995
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:7220
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9994
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:912
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:3190
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9699
gru_backward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:10067
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7844
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7564
plain 1D tensor
Definition: dnnl_types.h:177
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7852
Softmax forward propagation primitive.
Definition: dnnl.hpp:5705
primitive_desc()=default
Default constructor. Produces an empty object.
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1477
permuted 2D tensor
Definition: dnnl_types.h:193
permuted 5D tensor
Definition: dnnl_types.h:203
A layer normalization primitive.
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.
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4548
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9683
engine(kind kind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:877
desc(algorithm algorithm, 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:4023
permuted 6D tensor
Definition: dnnl_types.h:190
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7353
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7855
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9964
desc()=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:8845
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:2601
stream_attr()=default
Constructs default (empty) stream attributes.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3331
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:2992
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b ...
Definition: dnnl_types.h:494
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:5884
propagation kind
Definition: dnnl_types.h:2025
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8902
inner_product_forward()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7578
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:10458
desc(prop_kind prop_kind, algorithm algorithm, 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:4357
An inner product primitive.
Definition: dnnl_types.h:732
desc(const memory::dims &dims, data_type data_type, const memory::dims &strides, bool allow_empty=false)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:1781
Use global statistics.
Definition: dnnl_types.h:874
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9917
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.
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:9167
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:9688
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2018
GRU cell.
Definition: dnnl_types.h:828
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6992
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6640
The operation was successful.
Definition: dnnl_types.h:41
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:9026
Undefined propagation kind.
desc(algorithm algorithm, 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:10318
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:4690
deconvolution_forward()=default
Default constructor. Produces an empty object.
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:1202
primitive_desc()=default
Default constructor. Produces an empty object.
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.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7427
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:380
Elementwise: hyperbolic tangent non-linearity (tanh)
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1393
8-bit signed integer.
Definition: dnnl_types.h:74
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5522
convolution descriptor
Definition: dnnl_types.h:2030
concat()=default
Default constructor. Produces an empty object.
RNN cell.
Definition: dnnl_types.h:824
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2929
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1482
A (out-of-place) concat primitive.
Definition: dnnl_types.h:712
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:176
convolution_backward_data()=default
Default constructor. Produces an empty object.
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.
desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9945
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
desc(algorithm algorithm, 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:4067
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2178
Undefined memory format tag.
Definition: dnnl_types.h:166
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:10254
#define DNNL_ARG_DIFF_SRC_LAYER
A special mnemonic for gradient (diff) of RNN input vector.
Definition: dnnl_types.h:1876
The operation failed because of incorrect function arguments.
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_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_post_ops_append_sum(dnnl_post_ops_t post_ops, float scale)
Appends an accumulation (sum) to post-ops.
permuted 5D tensor
Definition: dnnl_types.h:189
Eltwise: square root.
Definition: dnnl_types.h:771
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.
primitive_desc()=default
Default constructor. Produces an empty object.
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:8896
primitive_desc()=default
Default constructor. Produces an empty object.
desc(prop_kind prop_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:8950
desc(algorithm algorithm, 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:3894
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:10331
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4507
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:2583
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.
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2870
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:8172
static void wrap_c_api(dnnl_status_t status, const char *message)
A convenience function for wrapping calls to C API functions.
Definition: dnnl.hpp:110
Intel Advanced Vector Extensions (Intel AVX)
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:5098
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:10009
dnnl_status_t DNNL_API dnnl_stream_create_v2(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags, const_dnnl_stream_attr_t attr)
Creates an execution stream.
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:3814
permuted 3D tensor
Definition: dnnl_types.h:196
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Primitive or engine failed on execution.
GRU backward propagation primitive.
Definition: dnnl.hpp:9062
dnnl_status_t DNNL_API dnnl_memory_set_data_handle_v2(dnnl_memory_t memory, void *handle, dnnl_stream_t stream)
Sets a memory object's data handle.
Inner product backward propagation primitive.
Definition: dnnl.hpp:7008
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.
Backward bias propagation.
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:10053
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9299
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6845
source memory desc
Definition: dnnl_types.h:2049
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3458
#define DNNL_ARG_DIFF_DST_LAYER
A special mnemonic for gradient (diff) of RNN output vector.
Definition: dnnl_types.h:1897
Eltwise: swish.
Definition: dnnl_types.h:790
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4701
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9860
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:3184
desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2923
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9812
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:1809
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5338
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6607
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:10448
dnnl_status_t DNNL_API dnnl_stream_wait(dnnl_stream_t stream)
Waits for all primitives in the execution stream to finish computations.
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:9619
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.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5323
desc(algorithm algorithm, 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:4576
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_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...
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8870
Memory descriptor.
Definition: dnnl_types.h:1050
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2091
dnnl_status_t DNNL_API dnnl_engine_get_ocl_device(dnnl_engine_t engine, cl_device_id *device)
Returns the OpenCL device associated with an engine.
Elementwise binary operator primitive.
Definition: dnnl.hpp:9883
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1070
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:8776
primitive_desc()=default
Default constructor. Produces an empty object.
desc(algorithm algorithm, const memory::desc &src0, const memory::desc &src1, const memory::desc &dst)
Constructs a descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9906
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6837
A matrix multiplication primitive.
Definition: dnnl_types.h:742
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:2260
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5788
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.
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5803
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:2980
Eltwise: erf-based gelu.
Definition: dnnl_types.h:798
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3334
dnnl_status_t DNNL_API dnnl_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4546
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:3120
Backward weights propagation.
Definition: dnnl_types.h:697
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5768
layer normalization descriptor
void append_sum(float scale=1.)
Appends an accumulation (sum) post-op.
Definition: dnnl.hpp:2251
Queried element is not required for given primitive.
desc(prop_kind prop_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:8413
primitive_desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3746
Default order execution.
Definition: dnnl_types.h:2071
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:8885
#define DNNL_ARG_DIFF_DST_ITER_C
A special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
Definition: dnnl_types.h:1909
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7870
workspace memory desc
Definition: dnnl_types.h:2055
primitive_desc(const desc &desc, const engine &engine, 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:7200
weights gradient (diff) memory desc
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_softmax_backward_desc_init(dnnl_softmax_desc_t *softmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax backward propagation primitive.
primitive_desc(const engine &src_engine, const memory::desc &src_md, const engine &dst_engine, const memory::desc &dst_md, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for reorder primitive.
Definition: dnnl.hpp:3141
Memory object.
Definition: dnnl.hpp:1188
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:4261
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.
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7611
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5344
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6266
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9673
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.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8230
Elementwise: exponent (dst for backward)
eltwise descriptor
Definition: dnnl_types.h:2033
number of inputs expected
Definition: dnnl_types.h:2008
shuffle descriptor
Definition: dnnl_types.h:2032
Average pooling include padding.
Definition: dnnl_types.h:814
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8250
Linear (Bilinear, Trilinear) resampling method.
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
logsoftmax_backward()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6439
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5202
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7293
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.
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:10031
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:3952
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:9039
desc(prop_kind prop_kind, algorithm algorithm, const memory::desc &data_desc, float alpha=0, float beta=0)
Constructs a descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5509
dnnl_status_t DNNL_API dnnl_memory_get_ocl_mem_object(const_dnnl_memory_t memory, cl_mem *mem_object)
Returns an OpenCL memory object associated with a memory object.
permuted 5D tensor
Definition: dnnl_types.h:202
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:2968
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2183
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5834
Reorder primitive.
Definition: dnnl.hpp:3118
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b ...
Definition: dnnl_types.h:503
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:1955
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6870
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8225
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:7241
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:9715
lrn descriptor
Definition: dnnl_types.h:2036
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.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6817
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.
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5196
Primitive descriptor for LSTM backward propagation.
Definition: dnnl.hpp:8728
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:258
A shuffle primitive.
Definition: dnnl_types.h:710
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6273
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:905
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a logsoftmax forward propagation primitive. ...
Definition: dnnl.hpp:5965
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6116
for creating scratchpad memory
Definition: dnnl_types.h:2020
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.
primitive_desc(const desc &desc, const engine &engine, 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:7788
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution weights gradient primitive.
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:9269
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6444
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5679
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:9954
dnnl_status_t DNNL_API dnnl_stream_create_ocl(dnnl_stream_t *stream, dnnl_engine_t engine, cl_command_queue queue)
Creates an execution stream for a given engine associated with an OpenCL command queue.
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:227
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2947
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:9413
permuted 4D tensor
Definition: dnnl_types.h:197
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:217
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:7170
Intel Advanced Vector Extensions 2 (Intel AVX2)
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:238
Binary max.
Definition: dnnl_types.h:842
Unspecified format kind.
Definition: dnnl_types.h:85
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:2683
Resampling forward propagation.
Definition: dnnl.hpp:10117
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.
Average pooling exclude padding.
Definition: dnnl_types.h:816
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2888
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4244
desc(algorithm algorithm, 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:4162
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b ...
Definition: dnnl_types.h:506
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:748
primitive_desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for a RNN backward propagation primitive.
Definition: dnnl.hpp:7771
permuted 3D tensor
Definition: dnnl_types.h:199
memory::desc weights_projection_desc() const
Returns weights projection memory descriptor.
Definition: dnnl.hpp:7331
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2010
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1464
dnnl_status_t DNNL_API dnnl_memory_set_ocl_mem_object(dnnl_memory_t memory, cl_mem mem_object)
Sets OpenCL memory object associated with a memory object.
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:1963
Base class for all primitive descriptors.
Definition: dnnl.hpp:2796
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6760
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7483
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4530
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9961
desc reshape(const memory::dims &dims, bool allow_empty=false) const
Constructs a memory descriptor by reshaping an existing one.
Definition: dnnl.hpp:1867
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:9887
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:6396
An LRN primitive.
Definition: dnnl_types.h:726
desc(prop_kind prop_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:8561
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:3215
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1329
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:9821
int ndims
Number of dimensions.
Definition: dnnl_types.h:1052
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2068
Undefined propagation type.
Definition: dnnl_types.h:680
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
oneDNN C API handle wrapper class.
Definition: dnnl.hpp:143
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:2782
op descriptor
Definition: dnnl_types.h:2029
dnnl_status_t DNNL_API dnnl_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
primitive_desc_base()=default
Default constructor. Produces an empty object.
desc submemory_desc(const memory::dims &dims, const memory::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:1811
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3776
lrn_backward()=default
Default constructor. Produces an empty object.
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:7605
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6939
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9958
dnnl_status_t DNNL_API dnnl_stream_attr_destroy(dnnl_stream_attr_t attr)
Destroys execution stream attributes.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7339
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4277
Eltwise: exponent.
Definition: dnnl_types.h:781
desc(algorithm algorithm, 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:4883
weights memory descriptor desc
lbr_gru_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:9424
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:820
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:5426
resampling descriptor
Definition: dnnl_types.h:2045
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.
primitive_desc(const desc &desc, const engine &engine, 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:4657
Forward data propagation, alias for dnnl::prop_kind::forward_inference.
softmax_forward()=default
Default constructor. Produces an empty object.
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:6020
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7885
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9220
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:5439
desc(prop_kind prop_kind, algorithm algorithm, 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:5259
Primitive descriptor GRU forward propagation primitive.
Definition: dnnl.hpp:8973
dnnl_status_t DNNL_API dnnl_inner_product_backward_weights_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product weights gradient primitive.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8235
plain 3D tensor
Definition: dnnl_types.h:179
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2935
Use scale and shift parameters.
Definition: dnnl_types.h:887
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1360
dnnl_status_t DNNL_API dnnl_lbr_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU forward propagation primitive.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7847
primitive_desc()=default
Default constructor. Produces an empty object.
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2161
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b ...
Definition: dnnl_types.h:509
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:804
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5918
Convolution algorithm that is chosen to be either direct or Winograd automatically.
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:765
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_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.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:309
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:689
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5785
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:10041
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b ...
Definition: dnnl_types.h:488
An opaque structure to describe a primitive descriptor.
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:9465
rnn_primitive_desc_base(dnnl_primitive_desc_t pd, dnnl::prop_kind prop_kind, dnnl::algorithm cell_kind)
Constructs an RNN primitive descriptor base from a C API primitive descriptor while checking that it ...
Definition: dnnl.hpp:7287
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6425
Eltwise: abs.
Definition: dnnl_types.h:769
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:1949
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:10119
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:2953
dnnl_primitive_kind_t convert_to_c(primitive::kind kind)
Converts primitive kind enum value from C++ API to C API type.
Definition: dnnl.hpp:369
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6269
Forward data propagation (training mode).
Definition: dnnl_types.h:683
A deconvolution primitive.
permuted 5D tensor
Definition: dnnl_types.h:187
Elementwise: rectified linar unit (ReLU) (dst for backward)
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:8277
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7594
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:5191
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:788
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:5992
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:8283
source gradient (diff) memory desc
A rnn primitive.
Definition: dnnl_types.h:734
An opaque structure to describe an execution stream.
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:7043
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6674
A logsoftmax primitive.
Definition: dnnl_types.h:740
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:9259
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:6088
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:633
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.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6260
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:9796
primitive_desc(const desc &desc, const engine &engine, 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:5407
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7865
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:6014
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
Eltwise: gelu.
Definition: dnnl_types.h:786
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:5563
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4524
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:9279
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:763
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:6797
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4640
desc(prop_kind prop_kind, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5940
Softmax backward propagation primitive.
Definition: dnnl.hpp:5801
Bidirectional execution of RNN primitive with summation of the results.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4698
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:9372
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...
A descriptor of resampling operation.
Definition: dnnl_types.h:1616
void set_ocl_mem_object(cl_mem mem_object)
Sets the OpenCL memory object mem_object associated with the memory.
Definition: dnnl.hpp:2139
desc(algorithm algorithm, 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:4747
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8822
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:5051
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.
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:4231
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:2501
query
Primitive descriptor query specification.
Definition: dnnl.hpp:720
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8875
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3358
T * map_data() const
Maps a memory object and returns a host-side pointer to a memory buffer with a copy of its contents...
Definition: dnnl.hpp:2102
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:677
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
A special mnemonic for diff of RNN weights applied to the layer input.
Definition: dnnl_types.h:1921
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. ...
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:406
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:5227
desc(prop_kind prop_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:8146
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6419
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:9606
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:9001
primitive_desc()=default
Default constructor. Produces an empty object.
Convolution weights gradient primitive.
Definition: dnnl.hpp:3989
Elementwise: gelu alias for dnnl::algorithm::eltwise_gelu_tanh.
primitive_desc(const desc &desc, const engine &engine, 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:4199
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:846
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1193
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3342
permuted 4D tensor
Definition: dnnl_types.h:195
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:2820
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:1736
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
dnnl_status_t DNNL_API dnnl_stream_attr_create(dnnl_stream_attr_t *attr, dnnl_engine_kind_t kind)
Creates execution stream attributes for a stream that runs on an engine of a particular kind...
desc(prop_kind prop_kind, algorithm algorithm, 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:3624
primitive_desc(const desc &desc, const engine &engine, 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:4921
dnnl_status_t DNNL_API dnnl_stream_get_ocl_command_queue(dnnl_stream_t stream, cl_command_queue *queue)
Returns the OpenCL command queue associated with an execution stream.
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:5671
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.
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &engine, 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:4677
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5738
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5621
source engine
Definition: dnnl_types.h:2022
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5707
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.
logsoftmax_forward()=default
Default constructor. Produces an empty object.
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:2694
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:8986
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8825
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_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:852
weights grad. memory desc
Definition: dnnl_types.h:2052
engine()=default
Constructs an empty engine.
shuffle_forward()=default
Default constructor. Produces an empty object.
#define DNNL_ARG_DST_ITER_C
A special mnemonic for LSTM output recurrent cell state vector.
Definition: dnnl_types.h:1823
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:475
Resampling backward propagation primitive.
Definition: dnnl.hpp:10276
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:10443
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6277
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
Primitive iterator passed over last primitive descriptor.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8830
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:10213
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1282
A convolution primitive.
Definition: dnnl_types.h:716
memory desc of an execute argument
Definition: dnnl_types.h:2057
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:1788
Backward bias propagation.
Definition: dnnl_types.h:699
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7637
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:9419
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:4954
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:808
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:7093
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:5317
weights memory descriptor desc
Definition: dnnl_types.h:2051
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7624
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5889
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_engine_create_ocl(dnnl_engine_t *engine, dnnl_engine_kind_t kind, cl_device_id device, cl_context context)
Creates an engine associated with an OpenCL device and an OpenCL context.
primitive_desc()=default
Default constructor. Produces an empty object.
desc(algorithm algorithm, 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:5372
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:2331
Linear Resampling Method.
Definition: dnnl_types.h:848
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5920
Eltwise: soft_relu.
Definition: dnnl_types.h:777
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7901
Unidirectional execution of RNN primitive from right to left.
plain 5D tensor
Definition: dnnl_types.h:181
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6416
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.
primitive_desc(const desc &desc, const engine &engine, 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:5638
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:2485
destination engine
Definition: dnnl_types.h:2023
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:1944
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6453
Eltwise: square.
Definition: dnnl_types.h:767
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:10083
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
A special mnemonic for diff of RNN weights applied to the peephole weights.
Definition: dnnl_types.h:1933
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.
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3821
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7433
A batch normalization primitive.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6263
An execution stream.
Definition: dnnl.hpp:1047
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:9678
Elementwise: exponential linear unit (ELU) (dst for backward)
convolution_backward_weights()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6628
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7875
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.
Post-ops.
Definition: dnnl.hpp:2205
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution forward propagation primitive.
primitive()=default
Default constructor. Constructs an empty object.
desc(prop_kind prop_kind, algorithm algorithm, 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:5025
Backward data propagation.
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9992