Deep Neural Network Library (DNNL)
1.91.0
Performance library for Deep Learning
Go to the documentation of this file.
23 #include "dnnl_config.h"
32 #include <unordered_map>
36 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
41 #include <CL/sycl.hpp>
50 #ifndef DNNL_ENABLE_EXCEPTIONS
51 #if __cpp_exceptions || __EXCEPTIONS \
52 || (defined(_MSC_VER) && !defined(__clang__))
53 #define DNNL_ENABLE_EXCEPTIONS 1
55 #define DNNL_ENABLE_EXCEPTIONS 0
59 #if defined(__GNUC__) || defined(__clang__)
60 #define DNNL_TRAP() __builtin_trap()
61 #elif defined(__INTEL_COMPILER) || defined(_MSC_VER)
62 #define DNNL_TRAP() __debugbreak()
64 #error "unknown compiler"
67 #if DNNL_ENABLE_EXCEPTIONS
68 #define DNNL_THROW_ERROR(status, msg) throw error(status, msg)
71 #define DNNL_THROW_ERROR(status, msg) \
92 struct error :
public std::exception {
104 const char *
what() const noexcept
override {
return message; }
117 template <
typename T>
133 template <
typename T,
typename traits = handle_traits<T>>
137 std::shared_ptr<typename std::remove_pointer<T>::type> data_ {0};
140 bool operator==(
const T other)
const {
return other == data_.get(); }
141 bool operator!=(
const T other)
const {
return !(*
this == other); }
174 void reset(T t,
bool weak =
false) {
175 data_.reset(t, weak ? &dummy_destructor : traits::destructor);
183 T
get(
bool allow_empty =
false)
const {
184 T result = data_.get();
185 if (allow_empty ==
false && result ==
nullptr)
195 explicit operator T()
const {
return get(
true); }
200 explicit operator bool()
const {
return get(
true) !=
nullptr; }
209 return other.data_.get() == data_.get();
248 struct primitive_desc;
347 stream &
stream,
const std::unordered_map<int, memory> &args)
const;
349 #ifdef DNNL_SYCL_DPCPP
350 cl::sycl::event DNNL_API execute_sycl(
stream &astream,
365 const std::unordered_map<int, memory> &args,
366 const std::vector<cl::sycl::event> &deps = {})
const;
381 "could not get a primitive descriptor from a primitive");
392 "could not get a primitive kind from a primitive descriptor");
480 undef = dnnl_alg_kind_undef,
638 #define DNNL_DEFINE_BITMASK_OPS(enum_name) \
639 inline enum_name operator|(enum_name lhs, enum_name rhs) { \
640 return static_cast<enum_name>( \
641 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
644 inline enum_name operator&(enum_name lhs, enum_name rhs) { \
645 return static_cast<enum_name>( \
646 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
649 inline enum_name operator^(enum_name lhs, enum_name rhs) { \
650 return static_cast<enum_name>( \
651 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
654 inline enum_name &operator|=(enum_name &lhs, enum_name rhs) { \
655 lhs = static_cast<enum_name>( \
656 static_cast<unsigned>(lhs) | static_cast<unsigned>(rhs)); \
660 inline enum_name &operator&=(enum_name &lhs, enum_name rhs) { \
661 lhs = static_cast<enum_name>( \
662 static_cast<unsigned>(lhs) & static_cast<unsigned>(rhs)); \
666 inline enum_name &operator^=(enum_name &lhs, enum_name rhs) { \
667 lhs = static_cast<enum_name>( \
668 static_cast<unsigned>(lhs) ^ static_cast<unsigned>(rhs)); \
672 inline enum_name operator~(enum_name rhs) { \
673 return static_cast<enum_name>(~static_cast<unsigned>(rhs)); \
853 "post-ops index is out of range");
882 "could not append a sum post-op");
891 "could not get parameters of a sum post-op");
913 "could not append an elementwise post-op");
924 float &alpha,
float &beta)
const {
927 get(), index, &scale, &c_alg, &alpha, &beta),
928 "could not get parameters of an elementwise post-op");
950 "could not create primitive attribute");
967 "could not get primitive scratchpad mode attribute");
977 "could not set primitive scratchpad mode attribute");
992 const float *c_scales;
994 get(), &count, &c_mask, &c_scales),
995 "could not get primitive output scales attribute");
996 scales.resize(count);
1000 scales[c] = c_scales[c];
1047 (
dnnl_dim_t)scales.size(), mask, &scales[0]),
1048 "could not set primitive output scales attribute");
1062 void get_scales(
int arg,
int &mask, std::vector<float> &scales)
const {
1065 const float *c_scales;
1067 get(), arg, &count, &c_mask, &c_scales),
1068 "could not get scales");
1069 scales.resize(count);
1073 scales[c] = c_scales[c];
1092 void set_scales(
int arg,
int mask,
const std::vector<float> &scales) {
1094 (
dnnl_dim_t)scales.size(), mask, &scales[0]),
1095 "could not set scales");
1109 int arg,
int &mask, std::vector<int32_t> &zero_points)
const {
1112 const int32_t *c_zero_points;
1114 get(), arg, &count, &c_mask, &c_zero_points),
1115 "could not get primitive zero points attribute");
1116 zero_points.resize(count);
1120 zero_points[c] = c_zero_points[c];
1145 int arg,
int mask,
const std::vector<int32_t> &zero_points) {
1148 (
dnnl_dim_t)zero_points.size(), mask, &zero_points[0]),
1149 "could not set primitive zero points attribute");
1159 "could not get primitive post-ops attribute");
1174 "could not set primitive post-ops attribute");
1213 "could not get primitive RNN data quantization parameters "
1245 get(), (
int)scales.size(), mask, &scales[0]),
1246 "could not get primitive RNN weights quantization parameters "
1311 "could not create an engine");
1315 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1325 &
engine, convert_to_c(
kind), device, context),
1326 "could not create an engine");
1332 DNNL_API
engine(
kind akind,
const cl::sycl::device &dev,
1338 const cl::sycl::context &ctx);
1350 "could not get an engine from a primitive_desc");
1351 reset(c_engine,
true);
1359 "could not get kind of an engine");
1363 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1367 cl_context context =
nullptr;
1369 "could not get an OpenCL context fron an engine");
1376 cl_device_id device =
nullptr;
1378 "could not get an OpenCL device fron an engine");
1396 template <
class primitive_desc>
1406 template <
class primitive_desc>
1411 "could not get an engine from a primitive_desc");
1412 return engine(c_engine,
true);
1463 "could not create a stream");
1467 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
1475 "could not create a stream");
1482 cl_command_queue queue =
nullptr;
1484 "could not get an OpenCL command queue from a stream");
1490 DNNL_API
stream(
const engine &eng, cl::sycl::queue &aqueue);
1619 template <
typename T>
1860 Abc16a = dnnl_Abc16a,
1861 ABc16a16b = dnnl_ABc16a16b,
1862 ABc4a4b = dnnl_ABc4a4b,
1864 ABc16b16a = dnnl_ABc16b16a,
1867 ABc4b16a4b = dnnl_ABc4b16a4b,
1868 ABc2b8a4b = dnnl_ABc2b8a4b,
1869 ABc4b4a = dnnl_ABc4b4a,
1870 ABc8a16b2a = dnnl_ABc8a16b2a,
1871 ABc8a8b = dnnl_ABc8a8b,
1873 ABc8b16a2b = dnnl_ABc8b16a2b,
1874 ABc8b8a = dnnl_ABc8b8a,
1875 Abcd16a = dnnl_Abcd16a,
1876 ABcd16a16b = dnnl_ABcd16a16b,
1878 ABcd16b16a = dnnl_ABcd16b16a,
1879 aBCd16b16c = dnnl_aBCd16b16c,
1880 aBCd16c16b = dnnl_aBCd16c16b,
1881 Abcd4a = dnnl_Abcd4a,
1883 ABcd4b16a4b = dnnl_ABcd4b16a4b,
1884 ABcd2b8a4b = dnnl_ABcd2b8a4b,
1885 ABcd4b4a = dnnl_ABcd4b4a,
1886 ABcd4a4b = dnnl_ABcd4a4b,
1887 aBCd4c16b4c = dnnl_aBCd4c16b4c,
1888 aBCd2c8b4c = dnnl_aBCd2c8b4c,
1889 aBCd4c4b = dnnl_aBCd4c4b,
1890 aBCd4b4c = dnnl_aBCd4b4c,
1891 ABcd8a16b2a = dnnl_ABcd8a16b2a,
1892 ABcd8a8b = dnnl_ABcd8a8b,
1895 ABcd8b16a2b = dnnl_ABcd8b16a2b,
1896 aBCd8b16c2b = dnnl_aBCd8b16c2b,
1899 aBCd8b8c = dnnl_aBCd8b8c,
1900 aBCd8c16b2c = dnnl_aBCd8c16b2c,
1901 aBCd8c8b = dnnl_aBCd8c8b,
1902 Abcde16a = dnnl_Abcde16a,
1903 ABcde16a16b = dnnl_ABcde16a16b,
1905 ABcde16b16a = dnnl_ABcde16b16a,
1906 aBCde16b16c = dnnl_aBCde16b16c,
1907 aBCde16c16b = dnnl_aBCde16c16b,
1908 aBCde2c8b4c = dnnl_aBCde2c8b4c,
1909 Abcde4a = dnnl_Abcde4a,
1911 ABcde4b4a = dnnl_ABcde4b4a,
1912 ABcde4a4b = dnnl_ABcde4a4b,
1913 aBCde4b4c = dnnl_aBCde4b4c,
1914 aBCde4c16b4c = dnnl_aBCde4c16b4c,
1915 aBCde4c4b = dnnl_aBCde4c4b,
1916 Abcde8a = dnnl_Abcde8a,
1917 ABcde8a8b = dnnl_ABcde8a8b,
1919 ABcde8b16a2b = dnnl_ABcde8b16a2b,
1922 aBCde8b16c2b = dnnl_aBCde8b16c2b,
1923 ABcde8b8a = dnnl_ABcde8b8a,
1924 aBCde8b8c = dnnl_aBCde8b8c,
1925 ABcd4a8b8a4b = dnnl_ABcd4a8b8a4b,
1926 ABcd2a8b8a2b = dnnl_ABcd2a8b8a2b,
1927 aBCde4b8c8b4c = dnnl_aBCde4b8c8b4c,
1928 aBCde2b8c8b2c = dnnl_aBCde2b8c8b2c,
1929 aBCde8c16b2c = dnnl_aBCde8c16b2c,
1930 aBCde8c8b = dnnl_aBCde8c8b,
1932 aBCdef16b16c = dnnl_aBCdef16b16c,
1933 aBCdef16c16b = dnnl_aBCdef16c16b,
1935 aBCdef4c4b = dnnl_aBCdef4c4b,
1936 aBCdef4b4c = dnnl_aBCdef4b4c,
1937 aBCdef8b8c = dnnl_aBCdef8b8c,
1938 aBCdef8c16b2c = dnnl_aBCdef8c16b2c,
1939 aBCdef4c16b4c = dnnl_aBCdef4c16b4c,
1940 aBCdef8c8b = dnnl_aBCdef8c8b,
1941 aBdc16b = dnnl_aBdc16b,
1942 aBdc4b = dnnl_aBdc4b,
1943 aBdc8b = dnnl_aBdc8b,
1944 aBdec16b = dnnl_aBdec16b,
1945 aBdec4b = dnnl_aBdec4b,
1946 aBdec8b = dnnl_aBdec8b,
1947 aBdefc16b = dnnl_aBdefc16b,
1948 aCBdef16c16b = dnnl_aCBdef16c16b,
1949 aBdefc4b = dnnl_aBdefc4b,
1950 aBdefc8b = dnnl_aBdefc8b,
1951 Acb16a = dnnl_Acb16a,
1954 aCBd16b16c = dnnl_aCBd16b16c,
1955 aCBd16c16b = dnnl_aCBd16c16b,
1956 aCBde16b16c = dnnl_aCBde16b16c,
1957 aCBde16c16b = dnnl_aCBde16c16b,
1958 Acdb16a = dnnl_Acdb16a,
1959 Acdb4a = dnnl_Acdb4a,
1960 Acdb8a = dnnl_Acdb8a,
1961 Acdeb16a = dnnl_Acdeb16a,
1962 Acdeb4a = dnnl_Acdeb4a,
1963 Acdeb8a = dnnl_Acdeb8a,
1964 BAc16a16b = dnnl_BAc16a16b,
1965 BAc16b16a = dnnl_BAc16b16a,
1966 BAcd16a16b = dnnl_BAcd16a16b,
1967 BAcd16b16a = dnnl_BAcd16b16a,
1968 ABcd32a32b = dnnl_ABcd32a32b,
1969 BAcde16b16 = dnnl_BAcde16b16a,
1970 aBdec32b = dnnl_aBdec32b,
1971 Abcdef16a = dnnl_Abcdef16a,
1972 Acdb32a = dnnl_Acdb32a,
1984 NCw16n16c = dnnl_NCw16n16c,
1985 NChw16n16c = dnnl_NChw16n16c,
1986 NCdhw16n16c = dnnl_NCdhw16n16c,
1987 NChw32n32c = dnnl_NChw32n32c,
1988 IOhw16i16o = dnnl_IOhw16i16o,
1989 Ohwi32o = dnnl_Ohwi32o,
1990 IOdhw16i16o = dnnl_IOdhw16i16o,
1991 gIOhw16i16o = dnnl_gIOhw16i16o,
1992 gOhwi32o = dnnl_gOhwi32o,
1993 Goidhw16g = dnnl_Goidhw16g,
1994 IOw16o16i = dnnl_IOw16o16i,
1995 OIw16i16o = dnnl_OIw16i16o,
1996 IOw16i16o = dnnl_IOw16i16o,
1997 gIOw16i16o = dnnl_gIOw16i16o,
1998 OIw16o16i = dnnl_OIw16o16i,
1999 Oiw16o = dnnl_Oiw16o,
2000 OIw4i16o4i = dnnl_OIw4i16o4i,
2001 OIw2i8o4i = dnnl_OIw2i8o4i,
2002 OIw4i4o = dnnl_OIw4i4o,
2003 OIw4o4i = dnnl_OIw4o4i,
2005 OIw8i16o2i = dnnl_OIw8i16o2i,
2006 OIw8i8o = dnnl_OIw8i8o,
2007 OIw8o16i2o = dnnl_OIw8o16i2o,
2008 OIw8o8i = dnnl_OIw8o8i,
2009 Owi16o = dnnl_Owi16o,
2010 OwI16o2i = dnnl_OwI16o2i,
2013 IOhw16o16i = dnnl_IOhw16o16i,
2014 Ohwi16o = dnnl_Ohwi16o,
2015 OhwI16o2i = dnnl_OhwI16o2i,
2016 Ohwi4o = dnnl_Ohwi4o,
2017 Ohwi8o = dnnl_Ohwi8o,
2018 OIhw16i16o = dnnl_OIhw16i16o,
2019 OIhw16o16i = dnnl_OIhw16o16i,
2020 Oihw16o = dnnl_Oihw16o,
2021 OIhw4i16o4i = dnnl_OIhw4i16o4i,
2022 OIhw4i4o = dnnl_OIhw4i4o,
2023 OIhw4o4i = dnnl_OIhw4o4i,
2024 Oihw4o = dnnl_Oihw4o,
2025 OIhw8i16o2i = dnnl_OIhw8i16o2i,
2026 OIhw8i8o = dnnl_OIhw8i8o,
2027 OIhw8o16i2o = dnnl_OIhw8o16i2o,
2028 OIhw8o8i = dnnl_OIhw8o8i,
2029 OIhw2i8o4i = dnnl_OIhw2i8o4i,
2030 Odhwi16o = dnnl_Odhwi16o,
2031 OdhwI16o2i = dnnl_OdhwI16o2i,
2032 Odhwi4o = dnnl_Odhwi4o,
2033 Odhwi8o = dnnl_Odhwi8o,
2034 OIdhw16i16o = dnnl_OIdhw16i16o,
2035 OIdhw16o16i = dnnl_OIdhw16o16i,
2036 Oidhw16o = dnnl_Oidhw16o,
2037 OIdhw4i4o = dnnl_OIdhw4i4o,
2038 OIdhw4o4i = dnnl_OIdhw4o4i,
2039 Oidhw4o = dnnl_Oidhw4o,
2040 OIdhw8i16o2i = dnnl_OIdhw8i16o2i,
2041 OIdhw4i16o4i = dnnl_OIdhw4i16o4i,
2042 OIdhw2i8o4i = dnnl_OIdhw2i8o4i,
2043 OIdhw8i8o = dnnl_OIdhw8i8o,
2044 OIdhw8o8i = dnnl_OIdhw8o8i,
2045 gIOw16o16i = dnnl_gIOw16o16i,
2046 gOIw16i16o = dnnl_gOIw16i16o,
2047 gOIw16o16i = dnnl_gOIw16o16i,
2048 gOiw16o = dnnl_gOiw16o,
2049 gOIw4i16o4i = dnnl_gOIw4i16o4i,
2050 gOIw2i8o4i = dnnl_gOIw2i8o4i,
2051 gOIw4i4o = dnnl_gOIw4i4o,
2052 gOIw4o4i = dnnl_gOIw4o4i,
2053 gOiw4o = dnnl_gOiw4o,
2054 gOIw8i16o2i = dnnl_gOIw8i16o2i,
2055 gOIw8i8o = dnnl_gOIw8i8o,
2056 gOIw8o16i2o = dnnl_gOIw8o16i2o,
2057 gOIw8o8i = dnnl_gOIw8o8i,
2058 gOwi16o = dnnl_gOwi16o,
2059 gOwI16o2i = dnnl_gOwI16o2i,
2060 gOwi4o = dnnl_gOwi4o,
2061 gOwi8o = dnnl_gOwi8o,
2062 Goiw8g = dnnl_Goiw8g,
2063 Goiw16g = dnnl_Goiw16g,
2064 gIOhw16o16i = dnnl_gIOhw16o16i,
2065 gOhwi16o = dnnl_gOhwi16o,
2066 gOhwI16o2i = dnnl_gOhwI16o2i,
2067 gOhwi4o = dnnl_gOhwi4o,
2068 gOhwi8o = dnnl_gOhwi8o,
2069 Goihw16g = dnnl_Goihw16g,
2070 gOIhw16i16o = dnnl_gOIhw16i16o,
2071 gOIhw16o16i = dnnl_gOIhw16o16i,
2072 gOihw16o = dnnl_gOihw16o,
2073 gOIhw4i16o4i = dnnl_gOIhw4i16o4i,
2074 gOIhw2i8o4i = dnnl_gOIhw2i8o4i,
2075 gOIhw4i4o = dnnl_gOIhw4i4o,
2076 gOIhw4o4i = dnnl_gOIhw4o4i,
2077 gOihw4o = dnnl_gOihw4o,
2078 Goihw8g = dnnl_Goihw8g,
2079 gOIhw8i16o2i = dnnl_gOIhw8i16o2i,
2080 gOIhw8i8o = dnnl_gOIhw8i8o,
2081 gOIhw8o16i2o = dnnl_gOIhw8o16i2o,
2082 OIhw4o8i8o4i = dnnl_OIhw4o8i8o4i,
2083 OIhw2o8i8o2i = dnnl_OIhw2o8i8o2i,
2084 gOIhw4o8i8o4i = dnnl_gOIhw4o8i8o4i,
2085 gOIhw2o8i8o2i = dnnl_gOIhw2o8i8o2i,
2086 gOIhw8o8i = dnnl_gOIhw8o8i,
2087 gIOdhw16i16o = dnnl_gIOdhw16i16o,
2088 gOdhwi16o = dnnl_gOdhwi16o,
2089 gOdhwI16o2i = dnnl_gOdhwI16o2i,
2090 gOdhwi4o = dnnl_gOdhwi4o,
2091 gOdhwi8o = dnnl_gOdhwi8o,
2092 gOIdhw16i16o = dnnl_gOIdhw16i16o,
2093 gOIdhw16o16i = dnnl_gOIdhw16o16i,
2094 gOidhw16o = dnnl_gOidhw16o,
2095 gOIdhw4i4o = dnnl_gOIdhw4i4o,
2096 gOIdhw4o4i = dnnl_gOIdhw4o4i,
2097 gOidhw4o = dnnl_gOidhw4o,
2098 gOIdhw8i16o2i = dnnl_gOIdhw8i16o2i,
2099 gOIdhw4i16o4i = dnnl_gOIdhw4i16o4i,
2100 gOIdhw2i8o4i = dnnl_gOIdhw2i8o4i,
2101 gOIdhw8i8o = dnnl_gOIdhw8i8o,
2102 gOIdhw8o8i = dnnl_gOIdhw8o8i,
2128 validate_dims(
dims);
2131 dims.size() == 0 ?
nullptr : &
dims[0],
2133 "could not construct a memory descriptor using a format "
2150 validate_dims(
dims);
2153 dims.size() == 0 ?
nullptr : &
dims[0],
2155 strides.size() == 0 ?
nullptr : &strides[0]),
2156 "could not construct a memory descriptor using strides");
2175 &sub_md, &data, &
dims[0], &offsets[0]),
2176 "could not construct a sub-memory");
2177 return desc(sub_md);
2189 "could not reshape a memory descriptor");
2190 return desc(out_md);
2246 #ifdef DNNL_USE_DPCPP_USM
2247 :
memory(with_sycl_tag {}, md, engine, ahandle,
true) {
2250 : memory(with_sycl_tag {}, md,
engine, ahandle,
false) {
2254 memory(
const desc &md,
const engine &engine,
void *handle) {
2264 "could not create a memory object");
2269 #if DNNL_WITH_SYCL && defined(DNNL_USE_SYCL_BUFFERS)
2270 template <
typename T,
int ndims = 1>
2277 cl::sycl::buffer<T, ndims> &buf)
2279 set_sycl_buffer(buf);
2296 "could not get a memory descriptor from a memory object");
2297 return desc(*cdesc);
2304 "could not get an engine from a memory object");
2305 return engine(c_engine,
true);
2314 "could not get a native handle from a memory object");
2324 "could not set native handle of a memory object");
2346 template <
typename T =
void>
2350 "could not map memory object data");
2351 return static_cast<T *
>(mapped_ptr);
2367 "could not unmap memory object data");
2370 #if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
2371 cl_mem get_ocl_mem_object()
const {
2375 "could not get OpenCL buffer object from a memory object");
2386 "could not set OpenCL buffer object from a memory object");
2390 #if DNNL_WITH_SYCL && defined(DNNL_USE_SYCL_BUFFERS)
2391 template <
typename T,
int ndims = 1>
2397 static_assert(ndims == 1,
"only 1D buffers supported");
2401 "could not get SYCL buffer object");
2406 return cl::sycl::buffer<T, ndims>(cl::sycl::range<1>(1));
2408 auto &buf_u8 = *
static_cast<cl::sycl::buffer<uint8_t, 1> *
>(handle_ptr);
2409 if (offset) *offset = 0;
2410 auto range = cl::sycl::range<1>(buf_u8.get_size() /
sizeof(T));
2411 return buf_u8.reinterpret<T, 1>(range);
2419 template <
typename T,
int ndims>
2421 auto range = cl::sycl::range<1>(buf.get_size());
2422 auto buf_u8 = buf.template reinterpret<uint8_t, 1>(range);
2424 get(),
static_cast<void *
>(&buf_u8)),
2425 "could not set SYCL buffer object");
2438 struct with_sycl_tag {};
2440 DNNL_API memory(with_sycl_tag,
const desc &md,
const engine &engine,
2441 void *ahandle,
bool is_usm);
2446 return a == memory::convert_to_c(b);
2459 return a == memory::convert_to_c(b);
2494 "could not retrieve implementation info string from a "
2495 "primitive descriptor");
2526 if (!std::any_of(valid_q.cbegin(), valid_q.cend(),
2527 [=](
query q) { return what == q; }))
2529 "memory descriptor query is invalid");
2653 "could not retrieve scratchpad engine from a primitive "
2655 return engine(c_engine,
true);
2663 "could not get attributes from a primitive descriptor");
2666 "could not clone primitive attributes");
2676 "could not get primitive kind from a primitive descriptor");
2687 "could not clone a primitive descriptor");
2740 if (pd ==
nullptr)
return;
2753 rc,
"could not get primitive kind from a primitive descriptor");
2754 if (pd_kind != c_prim_kind)
2756 "primitive descriptor operation kind mismatch");
2766 "could not get propagation kind from the primitive "
2772 && (pd_prop_kind == c_prop_kind1
2773 || pd_prop_kind == c_prop_kind2))) {
2780 "primitive descriptor propagation kind mismatch");
2830 "could not create a primitive descriptor for a reorder "
2851 "could not create a primitive descriptor for a reorder "
2912 #ifdef DNNL_SYCL_DPCPP
2913 using primitive::execute_sycl;
2916 const std::vector<cl::sycl::event> &deps = {})
const {
2917 return primitive::execute_sycl(astream,
2938 const std::vector<memory::desc> &mems) {
2939 std::vector<dnnl_memory_desc_t> c_mems;
2940 c_mems.reserve(mems.size());
2941 for (
const auto &s : mems)
2942 c_mems.push_back(s.data);
2976 const std::vector<memory::desc> &srcs,
const engine &
engine,
2983 (
int)c_srcs.size(), concat_dimension, &c_srcs[0],
2985 "could not create a primitive descriptor for a concat "
3003 const std::vector<memory::desc> &srcs,
const engine &
engine,
3010 (
int)c_api_srcs.size(), concat_dimension,
3011 &c_api_srcs[0], attr.get(),
engine.
get()),
3012 "could not create a primitive descriptor for a concat "
3076 const std::vector<float> &scales,
3077 const std::vector<memory::desc> &srcs,
const engine &
engine,
3082 "counts of scales and sources are not equal");
3088 (
int)c_api_srcs.size(), &scales[0],
3089 &c_api_srcs[0], attr.get(),
engine.
get()),
3090 "could not create a primitive descriptor for a sum "
3106 const std::vector<memory::desc> &srcs,
const engine &
engine,
3111 "counts of scales and sources are not equal");
3116 (
int)c_api_srcs.size(), &scales[0],
3117 &c_api_srcs[0], attr.get(),
engine.
get()),
3118 "could not create a primitive descriptor for a sum "
3181 bool allow_empty =
false)
3182 : allow_empty_(allow_empty) {
3185 desc, attr ? attr->
get() :
nullptr,
engine.
get(), hint_fwd_pd);
3188 status,
"could not create a primitive descriptor iterator");
3189 pd_iterator.reset(iterator);
3202 status,
"could not advance a primitive descriptor iterator");
3208 bool allow_empty_ =
false;
3212 pd_iterator.
get(allow_empty_));
3215 "could not fetch a primitive descriptor from a primitive "
3216 "descriptor iterator");
3284 &strides[0], &padding_l[0], &padding_r[0]),
3285 "could not create a descriptor for a convolution forward "
3286 "propagation primitive");
3329 &weights_desc.
data,
nullptr, &dst_desc.
data,
3330 &strides[0], &padding_l[0], &padding_r[0]),
3331 "could not create a descriptor for a convolution forward "
3332 "propagation primitive");
3381 &weights_desc.
data, &bias_desc.
data,
3382 &dst_desc.
data, &strides[0], &dilates[0],
3383 &padding_l[0], &padding_r[0]),
3384 "could not create a descriptor for a dilated convolution "
3385 "forward propagation primitive");
3431 &weights_desc.
data,
nullptr,
3432 &dst_desc.
data, &strides[0], &dilates[0],
3433 &padding_l[0], &padding_r[0]),
3434 "could not create a descriptor for a dilated convolution "
3435 "forward propagation primitive");
3455 bool allow_empty =
false)
3457 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
3473 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
3554 &weights_desc.
data, &diff_dst_desc.
data,
3555 &strides[0], &padding_l[0], &padding_r[0]),
3556 "could not create a descriptor for a convolution backward "
3557 "propagation primitive");
3600 &weights_desc.
data, &diff_dst_desc.
data,
3601 &strides[0], &dilates[0], &padding_l[0],
3603 "could not create a descriptor for a dilated convolution "
3604 "backward propagation primitive");
3628 bool allow_empty =
false)
3630 hint_fwd_pd.
get(), allow_empty) {}
3649 bool allow_empty =
false)
3728 &diff_weights_desc.
data, &diff_bias_desc.
data,
3729 &diff_dst_desc.
data, &strides[0], &padding_l[0],
3731 "could not create a descriptor for a convolution weights "
3732 "update primitive");
3770 &diff_weights_desc.
data,
nullptr,
3771 &diff_dst_desc.
data, &strides[0],
3772 &padding_l[0], &padding_r[0]),
3773 "could not create a descriptor for a convolution weights "
3774 "update primitive");
3821 &diff_weights_desc.
data, &diff_bias_desc.
data,
3822 &diff_dst_desc.
data, &strides[0], &dilates[0],
3823 &padding_l[0], &padding_r[0]),
3824 "could not create a descriptor for a dilated convolution "
3825 "weights gradient primitive");
3868 &diff_weights_desc.
data,
nullptr,
3869 &diff_dst_desc.
data, &strides[0], &dilates[0],
3870 &padding_l[0], &padding_r[0]),
3871 "could not create a descriptor for a dilated convolution "
3872 "weights gradient primitive");
3895 bool allow_empty =
false)
3897 hint_fwd_pd.
get(), allow_empty) {}
3915 bool allow_empty =
false)
4017 &strides[0], &padding_l[0], &padding_r[0]),
4018 "could not create a descriptor for a deconvolution forward "
4019 "propagation primitive");
4060 &weights_desc.
data,
nullptr, &dst_desc.
data,
4061 &strides[0], &padding_l[0], &padding_r[0]),
4062 "could not create a descriptor for a deconvolution forward "
4063 "propagation primitive");
4110 &weights_desc.
data, &bias_desc.
data,
4111 &dst_desc.
data, &strides[0], &dilates[0],
4112 &padding_l[0], &padding_r[0]),
4113 "could not create a descriptor for a dilated deconvolution "
4114 "forward propagation primitive");
4158 &weights_desc.
data,
nullptr,
4159 &dst_desc.
data, &strides[0], &dilates[0],
4160 &padding_l[0], &padding_r[0]),
4161 "could not create a descriptor for a dilated deconvolution "
4162 "forward propagation primitive");
4182 bool allow_empty =
false)
4184 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
4200 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
4276 &weights_desc.
data, &diff_dst_desc.
data,
4277 &strides[0], &padding_l[0], &padding_r[0]),
4278 "could not create a descriptor for a deconvolution "
4279 "backward propagation primitive");
4321 &weights_desc.
data, &diff_dst_desc.
data,
4322 &strides[0], &dilates[0], &padding_l[0],
4324 "could not create a descriptor for a dilated deconvolution "
4325 "backward propagation primitive");
4349 bool allow_empty =
false)
4351 hint_fwd_pd.
get(), allow_empty) {}
4370 bool allow_empty =
false)
4448 &diff_weights_desc.
data, &diff_bias_desc.
data,
4449 &diff_dst_desc.
data, &strides[0], &padding_l[0],
4451 "could not create a descriptor for a deconvolution weights "
4452 "update primitive");
4489 &src_desc.
data, &diff_weights_desc.
data,
4490 nullptr, &diff_dst_desc.
data, &strides[0],
4491 &padding_l[0], &padding_r[0]),
4492 "could not create a descriptor for a deconvolution weights "
4493 "update primitive");
4539 &diff_weights_desc.
data, &diff_bias_desc.
data,
4540 &diff_dst_desc.
data, &strides[0], &dilates[0],
4541 &padding_l[0], &padding_r[0]),
4542 "could not create a descriptor for a dilated deconvolution "
4543 "weights gradient primitive");
4585 &diff_weights_desc.
data,
nullptr,
4586 &diff_dst_desc.
data, &strides[0], &dilates[0],
4587 &padding_l[0], &padding_r[0]),
4588 "could not create a descriptor for a dilated deconvolution "
4589 "weights gradient primitive");
4612 bool allow_empty =
false)
4614 hint_fwd_pd.
get(), allow_empty) {}
4632 bool allow_empty =
false)
4715 float alpha,
float beta,
float k = 1.f) {
4719 local_size, alpha, beta, k),
4720 "could not create a descriptor for a lrn forward "
4721 "propagation primitive");
4740 bool allow_empty =
false)
4742 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
4757 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
4819 float alpha,
float beta,
float k = 1.f) {
4822 &diff_data_desc.
data, &data_desc.
data, local_size,
4824 "could not create a descriptor for a lrn backward "
4825 "propagation primitive");
4848 bool allow_empty =
false)
4850 hint_fwd_pd.
get(), allow_empty) {}
4868 bool allow_empty =
false)
4957 &dst_desc.
data, &strides[0], &kernel[0],
4958 &padding_l[0], &padding_r[0]),
4959 "could not create a descriptor for a pooling forward "
4960 "propagation primitive");
4979 bool allow_empty =
false)
4981 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
4996 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5070 &diff_dst_desc.
data, &strides[0], &kernel[0],
5071 &padding_l[0], &padding_r[0]),
5072 "could not create a descriptor for a pooling backward "
5073 "propagation primitive");
5096 bool allow_empty =
false)
5098 hint_fwd_pd.
get(), allow_empty) {}
5116 bool allow_empty =
false)
5203 &data_desc.
data, alpha, beta),
5204 "could not create a descriptor for an eltwise forward "
5205 "propagation primitive");
5225 bool allow_empty =
false)
5227 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5243 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5302 &data_desc.
data, alpha, beta),
5303 "could not create a descriptor for an eltwise backward "
5304 "propagation primitive");
5328 bool allow_empty =
false)
5330 hint_fwd_pd.
get(), allow_empty) {}
5349 bool allow_empty =
false)
5419 &data_desc.
data, softmax_axis),
5420 "could not create a descriptor for a softmax forward "
5421 "propagation primitive");
5441 bool allow_empty =
false)
5443 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5459 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5514 &data_desc.
data, softmax_axis),
5515 "could not create a descriptor for a softmax backward "
5516 "propagation primitive");
5540 bool allow_empty =
false)
5542 hint_fwd_pd.
get(), allow_empty) {}
5561 bool allow_empty =
false)
5628 int logsoftmax_axis) {
5631 &data_desc.
data, logsoftmax_axis),
5632 "could not create a descriptor for a logsoftmax forward "
5633 "propagation primitive");
5653 bool allow_empty =
false)
5655 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5671 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5728 int logsoftmax_axis) {
5730 &diff_data_desc.
data, &data_desc.
data,
5732 "could not create a descriptor for a logsoftmax backward "
5733 "propagation primitive");
5757 bool allow_empty =
false)
5759 hint_fwd_pd.
get(), allow_empty) {}
5778 bool allow_empty =
false)
5885 "could not create a descriptor for a batch normalization "
5886 "forward propagation primitive");
5907 bool allow_empty =
false)
5909 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
5925 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
5970 "could not retrieve a descriptor from a primitive "
5971 "descriptor for batch normalization forward propagation "
6030 "could not create a descriptor for a batch normalization "
6031 "backward propagation primitive");
6056 bool allow_empty =
false)
6058 hint_fwd_pd.
get(), allow_empty) {}
6077 bool allow_empty =
false)
6200 "could not create a descriptor for a layer normalization "
6201 "forward propagation primitive");
6238 "could not create a descriptor for a layer normalization "
6239 "forward propagation primitive");
6260 bool allow_empty =
false)
6262 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
6278 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
6321 "could not retrieve a descriptor from a primitive "
6322 "descriptor for layer normalization forward propagation "
6379 &data_desc.
data, &stat_desc.
data, epsilon,
6381 "could not create a descriptor for a batch normalization "
6382 "backward propagation primitive");
6417 &diff_data_desc.
data, &data_desc.
data,
6419 "could not create a descriptor for a batch normalization "
6420 "backward propagation primitive");
6445 bool allow_empty =
false)
6447 hint_fwd_pd.
get(), allow_empty) {}
6466 bool allow_empty =
false)
6566 &src_desc.
data, &weights_desc.
data,
6568 "could not create a descriptor for an inner product "
6569 "forward propagation primitive");
6598 &weights_desc.
data,
nullptr, &dst_desc.
data),
6599 "could not create a descriptor for an inner product "
6600 "forward propagation primitive");
6620 bool allow_empty =
false)
6622 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
6638 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
6700 &diff_src_desc.
data, &weights_desc.
data,
6701 &diff_dst_desc.
data),
6702 "could not create a descriptor for an inner product "
6703 "backward propagation primitive");
6728 bool allow_empty =
false)
6730 hint_fwd_pd.
get(), allow_empty) {}
6749 bool allow_empty =
false)
6813 &src_desc.
data, &diff_weights_desc.
data,
6814 &diff_bias_desc.
data, &diff_dst_desc.
data),
6815 "could not create a descriptor for an inner product "
6816 "weights gradient primitive");
6841 &src_desc.
data, &diff_weights_desc.
data,
nullptr,
6842 &diff_dst_desc.
data),
6843 "could not create a descriptor for an inner product "
6844 "weights gradient primitive");
6868 bool allow_empty =
false)
6870 hint_fwd_pd.
get(), allow_empty) {}
6889 bool allow_empty =
false)
6941 using primitive_desc::primitive_desc;
7067 "could not retrieve a descriptor from a primitive descriptor "
7068 "for an RNN primitive");
7075 && (
rnn_d->prop_kind == c_prop_kind1
7076 ||
rnn_d->prop_kind == c_prop_kind2)
7077 &&
rnn_d->cell_kind == c_cell_kind;
7081 "mismatch between expected and provided descriptors for an "
7155 float beta = 0.0f) {
7161 &src_iter_desc.
data, &weights_layer_desc.
data,
7162 &weights_iter_desc.
data, &bias_desc.
data,
7163 &dst_layer_desc.
data, &dst_iter_desc.
data,
7165 "could not create a descriptor for a vanilla RNN forward "
7166 "propagation primitive");
7186 bool allow_empty =
false)
7188 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
7204 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
7358 float beta = 0.0f) {
7364 &src_iter_desc.
data, &weights_layer_desc.
data,
7365 &weights_iter_desc.
data, &bias_desc.
data,
7366 &dst_layer_desc.
data, &dst_iter_desc.
data,
7367 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7368 &diff_weights_layer_desc.
data,
7369 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7370 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7372 "could not create a descriptor for a vanilla RNN backward "
7373 "propagation primitive");
7397 bool allow_empty =
false)
7399 hint_fwd_pd.
get(), allow_empty) {}
7418 bool allow_empty =
false)
7420 hint_fwd_pd.
get(), allow_empty) {}
7583 &src_iter_desc.
data, &src_iter_c_desc.
data,
7584 &weights_layer_desc.
data, &weights_iter_desc.
data,
7585 &bias_desc.
data, &dst_layer_desc.
data,
7586 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
7588 "could not create a descriptor for an LSTM forward "
7589 "propagation primitive");
7608 bool allow_empty =
false)
7610 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
7625 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
7804 &src_iter_desc.
data, &src_iter_c_desc.
data,
7805 &weights_layer_desc.
data, &weights_iter_desc.
data,
7806 &bias_desc.
data, &dst_layer_desc.
data,
7807 &dst_iter_desc.
data, &dst_iter_c_desc.
data,
7808 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
7809 &diff_src_iter_c_desc.
data,
7810 &diff_weights_layer_desc.
data,
7811 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
7812 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
7813 &diff_dst_iter_c_desc.
data,
7815 "could not create a descriptor for an LSTM backward "
7816 "propagation primitive");
7839 bool allow_empty =
false)
7841 hint_fwd_pd.
get(), allow_empty) {}
7859 bool allow_empty =
false)
7861 hint_fwd_pd.
get(), allow_empty) {}
8035 &src_iter_desc.
data, &weights_layer_desc.
data,
8036 &weights_iter_desc.
data, &bias_desc.
data,
8037 &dst_layer_desc.
data, &dst_iter_desc.
data,
8039 "could not create a descriptor for a GRU forward "
8040 "propagation primitive");
8059 bool allow_empty =
false)
8061 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
8076 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
8225 &src_iter_desc.
data, &weights_layer_desc.
data,
8226 &weights_iter_desc.
data, &bias_desc.
data,
8227 &dst_layer_desc.
data, &dst_iter_desc.
data,
8228 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8229 &diff_weights_layer_desc.
data,
8230 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8231 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8233 "could not create a descriptor for a GRU backward "
8234 "propagation primitive");
8257 bool allow_empty =
false)
8259 hint_fwd_pd.
get(), allow_empty) {}
8277 bool allow_empty =
false)
8279 hint_fwd_pd.
get(), allow_empty) {}
8433 &src_iter_desc.
data, &weights_layer_desc.
data,
8434 &weights_iter_desc.
data, &bias_desc.
data,
8435 &dst_layer_desc.
data, &dst_iter_desc.
data,
8437 "could not create a descriptor for an LBR GRU forward "
8438 "propagation primitive");
8458 bool allow_empty =
false)
8460 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
8476 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
8626 &src_iter_desc.
data, &weights_layer_desc.
data,
8627 &weights_iter_desc.
data, &bias_desc.
data,
8628 &dst_layer_desc.
data, &dst_iter_desc.
data,
8629 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
8630 &diff_weights_layer_desc.
data,
8631 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
8632 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data,
8634 "could not create a descriptor for an LBR GRU backward "
8635 "propagation primitive");
8659 bool allow_empty =
false)
8661 hint_fwd_pd.
get(), allow_empty) {}
8680 bool allow_empty =
false)
8682 hint_fwd_pd.
get(), allow_empty) {}
8808 &data_desc.
data, axis, group_size),
8809 "could not create a descriptor for a shuffle forward "
8810 "propagation primitive");
8832 bool allow_empty =
false)
8834 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
8885 &diff_data_desc.
data, axis, group_size),
8886 "could not create a descriptor for a shuffle backward "
8887 "propagation primitive");
8913 bool allow_empty =
false)
8979 "could not create a descriptor for a binary operation "
8999 bool allow_empty =
false)
9001 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9016 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9081 &weights_desc.
data,
nullptr, &dst_desc.
data),
9082 "could not create a descriptor for a matmul primitive");
9102 &weights_desc.
data, &bias_desc.
data,
9104 "could not create a descriptor for a matmul primitive");
9122 bool allow_empty =
false)
9124 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9138 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9217 "could not create a resampling forward descriptor");
9235 const std::vector<float> &factors,
9240 &src_desc.
data,
nullptr),
9241 "could not create a resampling forward descriptor");
9267 const std::vector<float> &factors,
const memory::desc &src_desc,
9273 "could not create a resampling forward descriptor");
9293 bool allow_empty =
false)
9295 &
desc.data, nullptr,
engine, nullptr, allow_empty) {}
9310 &
desc.data, &attr,
engine, nullptr, allow_empty) {}
9363 &diff_src_desc.
data, &diff_dst_desc.
data),
9364 "could not create a resampling backward data descriptor");
9387 &diff_src_desc.
data, &diff_dst_desc.
data),
9388 "could not create a resampling backward data descriptor");
9411 bool allow_empty =
false)
9413 hint_fwd_pd.
get(), allow_empty) {}
9431 bool allow_empty =
false)
9541 return static_cast<status>(
9559 transa, transb, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc));
9566 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
9568 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
9575 float beta, int32_t *C,
dnnl_dim_t ldc,
const int32_t *co) {
9577 K, alpha, A, lda, ao, B, ldb, bo, beta, C, ldc, co));
9588 "could not create a primitive");
9594 inline void primitive::execute(
9595 stream &stream,
const std::unordered_map<int, memory> &args)
const {
9596 std::vector<dnnl_exec_arg_t> c_args;
9597 c_args.reserve(args.size());
9598 for (
const auto &a : args)
9599 c_args.push_back({a.first, a.second.get(
true)});
9602 (
int)c_args.size(), c_args.data()),
9603 "could not execute a primitive");
9607 #undef DNNL_DEFINE_BITMASK_OPS
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:1891
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:1903
void set_data_handle(void *handle) const
Sets memory buffer.
Definition: dnnl.hpp:2322
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7467
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:9572
@ eltwise_d
eltwise descriptor
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_next(dnnl_primitive_desc_iterator_t iterator)
Advances the primitive descriptor iterator to point to the next available implementation.
Resampling backward propagation primitive.
Definition: dnnl.hpp:9340
deconvolution_backward_data(const primitive_desc &pd)
Constructs a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4400
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:304
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:9026
@ dnnl_scratchpad_mode_library
The library manages scratchpad (default) The allocation policy is controlled by the DNNL_ENABLE_CONCU...
Definition: dnnl_types.h:1626
@ diff_dst_md
destination grad. memory desc
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3493
void set_rnn_data_qparams(float scale, float shift)
Sets quantization scale and shift parameters for RNN data tensors.
Definition: dnnl.hpp:1210
layer_normalization_forward(const primitive_desc &pd)
Constructs a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6336
logsoftmax_backward()=default
Default constructor. Produces an empty object.
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:2736
Descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7514
@ softmax
A softmax primitive.
engine()=default
Constructs an empty engine.
dnnl_status_t DNNL_API dnnl_set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7043
dnnl_status_t DNNL_API dnnl_inner_product_forward_desc_init(dnnl_inner_product_desc_t *ip_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes descriptor for inner product forward propagation.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:6973
dnnl_status_t DNNL_API dnnl_convolution_forward_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution forward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
softmax_backward(const primitive_desc &pd)
Constructs a softmax backward propagation primitive.
Definition: dnnl.hpp:5591
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5576
vanilla_rnn_backward()=default
Default constructor. Produces an empty object.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8108
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
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:7568
@ success
The operation was successful.
void execute(stream stream, memory &src, memory &dst) const
Executes the reorder primitive.
Definition: dnnl.hpp:2908
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:4208
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4774
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:8985
rnn_direction
A direction of RNN primitive execution.
Definition: dnnl.hpp:680
primitive_desc()=default
Default constructor. Produces an empty object.
convolution_backward_data()=default
Default constructor. Produces an empty object.
desc reshape(const memory::dims &dims) const
Constructs a memory descriptor by reshaping existing one.
Definition: dnnl.hpp:2185
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:4713
@ all
Any ISA (no restrictions)
Descriptor for a GRU forward propagation primitive.
Definition: dnnl.hpp:7975
size_t get_size() const
Returns size of the memory descriptor in bytes.
Definition: dnnl.hpp:2211
Reorder primitive.
Definition: dnnl.hpp:2799
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:1915
@ num_of_inputs_s32
number of inputs expected
Shuffle backward propagation primitive.
Definition: dnnl.hpp:8864
Descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6536
@ resampling_d
resampling descriptor
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7451
@ backward
Backward propagation (with respect to all parameters).
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:8484
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:265
cl::sycl::buffer< T, ndims > get_sycl_buffer(size_t *offset=nullptr) const
Returns the underlying SYCL buffer object.
Definition: dnnl.hpp:2396
memory::desc diff_dst_iter_c_desc() const
Returns diff destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:7958
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6506
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7459
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8356
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:7622
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:4846
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:8657
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:8473
const char * what() const noexcept override
Returns the explanatory string.
Definition: dnnl.hpp:104
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8341
dnnl_status_t DNNL_API dnnl_pooling_backward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling backward propagation primitive.
@ any
An unspecified engine.
@ pooling_d
pooling descriptor
const_dnnl_primitive_desc_t get_primitive_desc() const
Returns the C API primitive descriptor of the underlying C API primitive.
Definition: dnnl.hpp:378
Primitive descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8443
Convolution weights gradient primitive.
Definition: dnnl.hpp:3683
An execution stream.
Definition: dnnl.hpp:1434
@ bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
desc(const dnnl_memory_desc_t &data)
Constructs a memory descriptor from a C API data structure.
Definition: dnnl.hpp:2162
@ diff_src_md
source gradient memory desc
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:1892
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
prop_kind
Propagation kind.
Definition: dnnl.hpp:444
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5013
int len() const
Returns the number of post-ops entries.
Definition: dnnl.hpp:846
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:9144
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution forward propagation primitive.
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:691
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
@ exec_arg_md
memory desc of an execute argument
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:8205
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:201
Softmax backward propagation primitive.
Definition: dnnl.hpp:5489
primitive_desc()=default
Default constructor. Produces an empty object.
An opaque structure to describe a primitive descriptor iterator.
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:5224
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:687
Vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7262
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:1923
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:4817
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:9563
Vanilla RNN descriptor backward propagation primitive.
Definition: dnnl.hpp:7264
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4883
LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8534
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9148
@ eltwise_soft_relu
Elementwise: soft_relu.
Primitive descriptor for an LSTM forward propagation primitive.
Definition: dnnl.hpp:7594
lrn_backward(const primitive_desc &pd)
Constructs an LRN backward propagation primitive.
Definition: dnnl.hpp:4898
dnnl_status_t DNNL_API dnnl_lstm_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *src_iter_c_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *dst_iter_c_desc, unsigned flags)
Initializes a descriptor for LSTM forward propagation primitive.
engine(const handle< dnnl_primitive_desc_t > &pd)
Constructs an engine based on a primitive from the primitive descriptor pd by querying its engine.
Definition: dnnl.hpp:1345
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7007
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:1902
engine get_src_engine() const
Returns the engine on which the source memory is allocated.
Definition: dnnl.hpp:2865
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8098
An execution engine.
Definition: dnnl.hpp:1274
@ avx
Intel(R) Advanced Vector Extensions.
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:3127
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5134
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:7342
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:5359
inner_product_forward(const primitive_desc &pd)
Constructs an inner product forward propagation primitive.
Definition: dnnl.hpp:6670
desc()=default
Default constructor. Produces an empty object.
void get_zero_points(int arg, int &mask, std::vector< int32_t > &zero_points) const
Returns zero points correspondence mask and values.
Definition: dnnl.hpp:1108
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:681
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:4380
Local response normalization (LRN) forward propagation primitive.
Definition: dnnl.hpp:4684
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6907
static void validate_dims(const std::vector< T > &v)
Helper function that validates that an std::vector of dimensions can be safely converted to the C API...
Definition: dnnl.hpp:1620
Descriptor for an elementwise backward propagation primitive.
Definition: dnnl.hpp:5275
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:9441
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:1920
#define DNNL_ARG_TO
A special mnemonic for reorder destination argument.
Definition: dnnl_types.h:1717
@ runtime_error
Primitive or engine failed on execution.
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:839
@ dnnl_scratchpad_mode_user
A user shall query and provide the scratchpad memory to primitives This mode is thread-safe as long a...
Definition: dnnl_types.h:1630
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7933
@ reorder_dst_engine
reorder destination engine
kind
Kinds of primitives.
Definition: dnnl.hpp:267
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8090
engine(kind kind, size_t index)
Constructs an engine.
Definition: dnnl.hpp:1307
post_ops()
Constructs an empty sequence of post-ops.
Definition: dnnl.hpp:838
status set_jit_profiling_jitdumpdir(const std::string &dir)
Sets JIT dump output path.
Definition: dnnl.hpp:9513
Primitive descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5078
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8300
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:202
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:267
layer_normalization_backward(const primitive_desc &pd)
Constructs a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6520
dnnl_memory_desc_t data
The underlying C API data structure.
Definition: dnnl.hpp:2109
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7670
Descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8136
An opaque structure to describe an engine.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6492
desc(const memory::dims &dims, data_type data_type, const memory::dims &strides)
Constructs a memory descriptor by strides.
Definition: dnnl.hpp:2148
eltwise_forward(const primitive_desc &pd)
Constructs an eltwise forward propagation primitive.
Definition: dnnl.hpp:5269
logsoftmax_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7247
const dnnl_version_t DNNL_API * dnnl_version()
Returns library version information.
Descriptor for resampling forward propagation.
Definition: dnnl.hpp:9187
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:5370
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1502
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:720
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:187
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:4197
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1502
@ eltwise_elu
Elementwise: parametric exponential linear unit (elu)
@ shuffle
A shuffle primitive.
@ pooling_avg
Average pooling exclude padding, alias for dnnl::algorithm::pooling_avg_include_padding.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8103
concat()=default
Default constructor. Produces an empty object.
size_t DNNL_API dnnl_memory_desc_get_size(const dnnl_memory_desc_t *memory_desc)
Returns the size of a memory descriptor.
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:728
cl::sycl::device DNNL_API get_sycl_device() const
Returns the underlying SYCL device object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a softmax backward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5571
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:6054
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:3664
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:4610
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:4480
dnnl_normalization_flags_t
Flags for batch normalization primitive.
Definition: dnnl_types.h:789
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7953
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8716
memory::desc diff_src_desc(int idx) const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2568
Elementwise unary operation backward propagation primitive.
Definition: dnnl.hpp:5273
@ unimplemented
The operation failed because requested functionality is not implemented.
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:4573
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:669
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:1912
Matrix multiplication (matmul) primitive.
Definition: dnnl.hpp:9060
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:9446
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:4865
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7892
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:7856
A descriptor of a convolution operation.
Definition: dnnl_types.h:1061
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3667
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3487
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7015
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6094
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:663
Elementwise unary operation forward propagation primitive.
Definition: dnnl.hpp:5174
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5137
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:4650
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1383
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:3002
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:8677
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:753
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:5922
dnnl_status_t DNNL_API dnnl_engine_get_kind(dnnl_engine_t engine, dnnl_engine_kind_t *kind)
Returns the kind of an engine.
dnnl_status_t DNNL_API dnnl_memory_desc_reshape(dnnl_memory_desc_t *out_memory_desc, const dnnl_memory_desc_t *in_memory_desc, int ndims, const dnnl_dims_t dims)
Initializes a memory descriptor by reshaping an existing one.
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:1948
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:1882
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:6193
@ eltwise_bounded_relu
Elementwise: bounded_relu.
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:5679
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:9318
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:8274
dnnl_status_t DNNL_API dnnl_logsoftmax_forward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax forward propagation primitive.
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
rnn_flags
RNN cell flags.
Definition: dnnl.hpp:626
A descriptor for an RNN operation.
Definition: dnnl_types.h:1405
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:197
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1389
desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7644
cpu_isa
CPU instruction set flags.
Definition: dnnl.hpp:9518
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:673
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:3925
@ forward_training
Forward data propagation (training mode).
Descriptor for a matmul primitive.
Definition: dnnl.hpp:9062
inner_product_backward_weights(const primitive_desc &pd)
Constructs an inner product weights gradient primitive.
Definition: dnnl.hpp:6926
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8119
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:8842
Primitive descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:4726
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:8923
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:656
@ layer_normalization_d
layer normalization descriptor
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc(int idx) const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2550
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
bool next_impl()
Advances the primitive iterator to the next implementation.
Definition: dnnl.hpp:3197
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:8759
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6296
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:5558
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:8606
A descriptor of an inner product operation.
Definition: dnnl_types.h:1349
void set_ocl_mem_object(cl_mem mem_object)
Sets the OpenCL memory object mem_object associated with the memory.
Definition: dnnl.hpp:2384
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7665
Primitive descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:6849
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:6286
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1560
primitive()=default
Default constructor. Constructs an empty object.
dnnl_status_t DNNL_API dnnl_memory_unmap_data(const_dnnl_memory_t memory, void *mapped_ptr)
Unmaps a memory objects and writes any changes to the previously mapped buffer back.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5016
Logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5605
dnnl_status_t DNNL_API dnnl_layer_normalization_backward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for a layer normalization backward propagation primitive.
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8326
@ eltwise_abs
Elementwise: abs.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3134
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:5240
@ lrn_across_channels
Local response normalization (LRN) across multiple channels.
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7029
Descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5176
memory::dims dims() const
Returns dimensions of the memory descriptor.
Definition: dnnl.hpp:2197
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:7428
LSTM backward propagation primitive.
Definition: dnnl.hpp:7693
Descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6161
deconvolution_backward_weights()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5260
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:1932
gru_forward(const primitive_desc &pd)
Constructs a GRU forward propagation primitive.
Definition: dnnl.hpp:8130
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:6476
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:1905
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:738
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8503
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:6373
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7887
@ inner_product_d
inner product descriptor
pooling_forward(const primitive_desc &pd)
Constructs a pooling forward propagation primitive.
Definition: dnnl.hpp:5025
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:679
GRU forward propagation primitive.
Definition: dnnl.hpp:7973
@ deconvolution_direct
Direct deconvolution.
kind
Kinds of engines.
Definition: dnnl.hpp:1279
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:210
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8749
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6106
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7226
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:8084
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7874
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:5957
inner_product_backward_data(const primitive_desc &pd)
Constructs an inner product backward propagation primitive.
Definition: dnnl.hpp:6779
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:714
binary(const primitive_desc &pd)
Constructs an elementwise binary operation primitive.
Definition: dnnl.hpp:9044
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:199
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:730
@ dnnl_cpu_isa_avx512_core
Intel(R) Advanced Vector Extensions 512 for Intel(R) Xeon(R) Processor Scalable Family and Intel(R) C...
Definition: dnnl_types.h:2049
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:2975
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8490
lstm_backward()=default
Default constructor. Produces an empty object.
bool operator==(const handle< T, traits > &other) const
Equality operator.
Definition: dnnl.hpp:208
stream()=default
Constructs an empty stream.
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:734
lbr_gru_backward(const primitive_desc &pd)
Constructs an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8770
status set_max_cpu_isa(cpu_isa isa)
Sets the maximal ISA DNNL can dispatch to on the CPU.
Definition: dnnl.hpp:9540
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:3105
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5797
desc()=default
Default constructor. Produces an empty object.
Primitive descriptor for LSTM backward propagation.
Definition: dnnl.hpp:7821
@ pooling
A pooling primitive.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6770
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 LSTM backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory(const desc &md, const engine &engine)
Constructs a memory object.
Definition: dnnl.hpp:2289
primitive_attr get_primitive_attr() const
Returns the primitive attributes.
Definition: dnnl.hpp:2660
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8310
@ reorder_src_engine
reorder source engine
desc()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for concat primitive from a C API primitive descriptor which must h...
Definition: dnnl.hpp:3021
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:646
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:1900
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:1933
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:1925
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7001
void set_scratchpad_mode(scratchpad_mode mode)
Sets scratchpad mode.
Definition: dnnl.hpp:974
scratchpad_mode
Scratchpad mode.
Definition: dnnl.hpp:411
memory::desc diff_src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5131
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:1919
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7223
@ pooling_avg_exclude_padding
Average pooling exclude padding.
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1385
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:461
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:4629
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:374
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:1910
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8351
Primitive descriptor for a resampling forward propagation primitive.
Definition: dnnl.hpp:9278
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:5953
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4771
@ eltwise_sqrt
Elementwise: square root.
primitive_desc()=default
Default constructor. Produces an empty object.
engine scratchpad_engine() const
Returns the engine on which the scratchpad memory is located.
Definition: dnnl.hpp:2648
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:7415
sum()=default
Default constructor. Produces an empty object.
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7472
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7462
@ eltwise_log
Elementwise: natural logarithm.
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:6866
lrn_forward(const primitive_desc &pd)
Constructs an LRN forward propagation primitive.
Definition: dnnl.hpp:4786
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:196
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7236
Primitive descriptor for a sum primitive.
Definition: dnnl.hpp:3052
deconvolution_forward()=default
Default constructor. Produces an empty object.
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1396
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:4309
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:2896
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2603
A descriptor of a pooling operation.
Definition: dnnl_types.h:1210
Layer normalization forward propagation primitive.
Definition: dnnl.hpp:6159
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:3930
@ lbr_gru
GRU cell with linear before reset.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4647
primitive_desc_base()=default
Default constructor. Produces an empty object.
void set_zero_points(int arg, int mask, const std::vector< int32_t > &zero_points)
Sets zero points for primitive operations for a given memory argument.
Definition: dnnl.hpp:1144
@ convolution_winograd
Winograd convolution.
kind get_kind() const
Returns the kind of the engine.
Definition: dnnl.hpp:1356
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7454
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:192
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:6807
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:763
dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory)
Destroys a memory object.
Primitive descriptor for resampling backward propagation primitive.
Definition: dnnl.hpp:9393
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2627
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:1172
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:3075
dnnl_status_t DNNL_API dnnl_primitive_attr_create(dnnl_primitive_attr_t *attr)
Creates an empty (default) primitive attributes with all the parameters set to their default values.
eltwise_backward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a GRU backward propagation primitive from a C API primitive des...
Definition: dnnl.hpp:8287
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:781
Primitive descriptor for an elementwise forward propagation primitive.
Definition: dnnl.hpp:5210
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:6619
dnnl::primitive::kind get_kind() const
Returns the kind of the primitive descriptor.
Definition: dnnl.hpp:2672
@ unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_zero_points(const_dnnl_primitive_attr_t attr, int arg, dnnl_dim_t *count, int *mask, const int32_t **zero_points)
Returns count, correspondence zero point mask, and a pointer to a constant int32_t array of zero_poin...
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
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:6726
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:7837
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:5627
@ resampling
A resampling primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_output_scales(dnnl_primitive_attr_t attr, dnnl_dim_t count, int mask, const float *scales)
Sets output scaling factors correspondence mask and values.
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:3893
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.
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:9292
shuffle_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_softmax_forward_desc_init(dnnl_softmax_desc_t *softmax_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax forward propagation primitive.
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(dnnl_primitive_desc_t *primitive_desc, const_dnnl_primitive_desc_t existing_primitive_desc)
Clones a primitive descriptor.
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:814
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:749
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:5415
Primitive descriptor for an LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8640
Descriptor for an LRN forward propagation primitive.
Definition: dnnl.hpp:4686
Primitive descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5426
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:1918
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4886
dnnl_status_t DNNL_API dnnl_memory_set_data_handle(dnnl_memory_t memory, void *handle)
Sets memory object's data handle.
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:4765
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:2879
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:2876
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:253
Post-ops.
Definition: dnnl.hpp:834
cl_device_id get_ocl_device() const
Returns the OpenCL device associated with the engine.
Definition: dnnl.hpp:1375
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:785
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6764
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:5094
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2609
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:8346
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:9409
lstm_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:2633
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:5879
Primitive descriptor for a layer normalization forward propagation primitive.
Definition: dnnl.hpp:6245
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:642
query
Primitive descriptor query specification.
Definition: dnnl.hpp:713
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8116
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.
void set_sycl_buffer(cl::sycl::buffer< T, ndims > &buf)
Sets the underlying buffer to the given SYCL buffer.
Definition: dnnl.hpp:2420
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:193
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:726
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:827
@ eltwise_clip
Eltwise: clip.
dnnl_status_t DNNL_API dnnl_primitive_execute(const_dnnl_primitive_t primitive, dnnl_stream_t stream, int nargs, const dnnl_exec_arg_t *args)
Executes a primitive.
@ dnnl_cpu_isa_avx512_mic_4ops
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors 7235,...
Definition: dnnl_types.h:2045
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8498
logsoftmax_backward(const primitive_desc &pd)
Constructs a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5812
Deconvolution weights gradient primitive.
Definition: dnnl.hpp:4404
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8516
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6652
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:5510
@ convolution_d
convolution descriptor
dnnl_status_t DNNL_API dnnl_stream_destroy(dnnl_stream_t stream)
Destroys an execution stream.
dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr)
Destroys primitive attributes.
@ fuse_norm_relu
Fuse with ReLU.
primitive_desc(const memory &src, const memory &dst, const primitive_attr &attr=primitive_attr())
Constructs a primitive descriptor for reorder primitive.
Definition: dnnl.hpp:2842
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.
@ num_of_outputs_s32
number of outputs expected
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:8830
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:6965
Tensor concatenation (concat) primitive.
Definition: dnnl.hpp:2948
dnnl_status_t DNNL_API dnnl_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for GRU forward propagation primitive.
dnnl_status_t DNNL_API dnnl_gemm_s8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const int8_t *A, dnnl_dim_t lda, int8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit signed matrix A, 8-bit signed matrix B,...
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
Descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5707
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:712
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:4004
Convolution forward propagation primitive.
Definition: dnnl.hpp:3234
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5800
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:6412
Descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:5991
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:263
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:476
Batch normalization forward propagation primitive.
Definition: dnnl.hpp:5838
dnnl_status_t DNNL_API dnnl_memory_desc_init_submemory(dnnl_memory_desc_t *memory_desc, const dnnl_memory_desc_t *parent_memory_desc, const dnnl_dims_t dims, const dnnl_dims_t offsets)
Initializes a memory descriptor for a region inside an area described by an existing memory descripto...
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1554
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:697
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:200
@ forward_inference
Forward data propagation (inference mode).
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7482
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6503
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:722
error(dnnl_status_t status, const char *message)
Constructs an instance of an exception class.
Definition: dnnl.hpp:100
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8313
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:214
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5010
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:181
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:4946
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:485
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:3454
dnnl_status_t DNNL_API dnnl_post_ops_append_eltwise(dnnl_post_ops_t post_ops, float scale, dnnl_alg_kind_t alg_kind, float alpha, float beta)
Appends an elementwise post-op.
Descriptor for an inner product weights gradient primitive.
Definition: dnnl.hpp:6785
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:994
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:1951
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:5906
@ avx512_core_vnni
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost Support for Intel(R) Xeon(R) Processor...
dnnl_status_t DNNL_API dnnl_primitive_attr_get_scratchpad_mode(const_dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t *mode)
Returns the primitive attributes scratchpad mode.
dnnl_status_t DNNL_API dnnl_concat_primitive_desc_create(dnnl_primitive_desc_t *concat_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, int concat_dimension, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an out-of-place concatenation primitive.
dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops)
Destroys post-ops.
dnnl_status_t DNNL_API dnnl_eltwise_backward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Softmax forward propagation primitive.
Definition: dnnl.hpp:5393
@ resampling_nearest
Nearest Neighbor resampling method.
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:683
Batch normalization backward propagation primitive.
Definition: dnnl.hpp:5989
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:190
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:6635
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:1916
dnnl_status_t DNNL_API dnnl_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a convolution backward propagation primitive.
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:652
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5940
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6767
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1180
@ dnnl_cpu_isa_avx512_core_bf16
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost and Bfloat16 Support for Intel(R) Xeon...
Definition: dnnl_types.h:2059
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:7395
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:5326
dnnl_status_t DNNL_API dnnl_memory_get_data_handle(const_dnnl_memory_t memory, void **handle)
Returns memory object's data handle.
vanilla_rnn_forward(const primitive_desc &pd)
Constructs a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7258
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
@ default_order
Default order execution.
@ scratchpad_md
scratchpad memory desc
data_type
Data type specification.
Definition: dnnl.hpp:1626
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:4878
Descriptor for an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8373
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scales(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const float *scales)
Sets primitive attributes scaling factors for primitive operations for a given memory argument.
cl_context get_ocl_context() const
Returns the OpenCL context associated with the engine.
Definition: dnnl.hpp:1366
dnnl_status_t DNNL_API dnnl_stream_create(dnnl_stream_t *stream, dnnl_engine_t engine, unsigned flags)
Creates an execution stream for engine and with flags.
dnnl_status_t DNNL_API dnnl_sgemm(char transa, char transb, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const float *A, dnnl_dim_t lda, const float *B, dnnl_dim_t ldb, float beta, float *C, dnnl_dim_t ldc)
Performs single-precision matrix-matrix multiply.
Primitive descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:3877
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6100
dnnl_status_t DNNL_API dnnl_stream_wait(dnnl_stream_t stream)
Waits for all primitives in the execution stream to finish computations.
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7021
An opaque structure to describe a primitive descriptor.
desc(const memory::desc &diff_data_desc, const memory::desc &data_desc, int logsoftmax_axis)
Constructs a descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5727
Primitive descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:4965
dnnl_status_t DNNL_API dnnl_sum_primitive_desc_create(dnnl_primitive_desc_t *sum_primitive_desc, const dnnl_memory_desc_t *dst_desc, int n, const float *scales, const dnnl_memory_desc_t *src_descs, const_dnnl_primitive_attr_t attr, dnnl_engine_t engine)
Creates a primitive descriptor for an (out-of-place) sum primitive.
static engine query(const primitive_desc &pd)
Returns the engine of a primitive descriptor.
Definition: dnnl.hpp:1397
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:467
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:759
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:5467
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:4526
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:765
@ weights_md
weights memory descriptor desc
@ avx2
Intel(R) Advanced Vector Extensions 2.
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.
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:3318
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1401
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:6592
@ inner_product
An inner product 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.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7678
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7673
Primitive descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4167
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:7913
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6495
@ undef
Undefined primitive.
Resampling forward propagation.
Definition: dnnl.hpp:9185
desc get_desc() const
Returns the associated memory descriptor.
Definition: dnnl.hpp:2293
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:8851
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7033
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:236
Inner product weights gradient primitive.
Definition: dnnl.hpp:6783
void execute(stream &stream, const std::unordered_map< int, memory > &args) const
Executes computations specified by the primitive in a specified stream.
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:8998
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6305
resampling_backward(const primitive_desc &pd)
Constructs a resampling backward propagation primitive.
Definition: dnnl.hpp:9458
@ layer_normalization
A layer normalization primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc src_iter_c_desc() const
Returns source recurrent cell state memory descriptor.
Definition: dnnl.hpp:6969
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1700
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:1924
void unmap_data(void *mapped_ptr) const
Unmaps the previously mapped data for the memory.
Definition: dnnl.hpp:2365
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:4146
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:9307
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8095
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:1922
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:777
@ not_required
Queried element is not required for given primitive.
dnnl_status_t DNNL_API dnnl_lbr_gru_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
@ backward_weights
Backward weights propagation.
@ dst_md
destination memory desc
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:650
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9327
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ batch_normalization_d
batch normalization descriptor
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:189
normalization_flags
Flags for normalization primitives.
Definition: dnnl.hpp:572
Inner product backward propagation primitive.
Definition: dnnl.hpp:6674
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:801
stream(const engine &engine, flags flags=flags::default_flags)
Constructs a stream for the specified engine and with behavior controlled by the specified flags.
Definition: dnnl.hpp:1459
@ binary_d
binary descriptor
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:4993
matmul(const primitive_desc &pd)
Constructs a matmul primitive.
Definition: dnnl.hpp:9169
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:761
memory::desc mean_desc() const
Returns memory descriptor for mean.
Definition: dnnl.hpp:6114
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:5933
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:671
Inner product forward propagation primitive.
Definition: dnnl.hpp:6534
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4388
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:1934
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
Logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5705
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:297
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:689
@ workspace_md
workspace memory desc
Primitive descriptor for a GRU backward propagation primitive.
Definition: dnnl.hpp:8239
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:4214
dnnl_status_t DNNL_API dnnl_set_max_cpu_isa(dnnl_cpu_isa_t isa)
Sets the maximal ISA DNNL can dispatch to on the CPU.
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:8754
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:997
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.
@ iterator_ends
Primitive iterator passed over last primitive descriptor.
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:6836
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:7477
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:8690
@ src_md
source memory desc
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:4642
@ convolution_direct
Direct convolution.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4391
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:8910
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:7633
convolution_forward()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:4777
@ eltwise_logistic
Elementwise: logistic.
@ dnnl_cpu_isa_all
Any ISA (no restrictions)
Definition: dnnl_types.h:2028
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.
deconvolution_backward_data()=default
Default constructor. Produces an empty object.
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:1909
cl::sycl::queue DNNL_API get_sycl_queue() const
Returns the underlying SYCL queue object.
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:7607
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7433
dnnl_status_t DNNL_API dnnl_softmax_backward_desc_init(dnnl_softmax_desc_t *softmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int softmax_axis)
Initializes a descriptor for softmax backward propagation primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
void set_scales(int arg, int mask, const std::vector< float > &scales)
Sets scaling factors for primitive operations for a given memory argument.
Definition: dnnl.hpp:1092
Primitive descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3440
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:6977
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:871
dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(const_dnnl_memory_t memory, const dnnl_memory_desc_t **memory_desc)
Returns the memory descriptor for a memory object.
dnnl_status_t DNNL_API dnnl_vanilla_rnn_backward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, const dnnl_memory_desc_t *diff_src_layer_desc, const dnnl_memory_desc_t *diff_src_iter_desc, const dnnl_memory_desc_t *diff_weights_layer_desc, const dnnl_memory_desc_t *diff_weights_iter_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_layer_desc, const dnnl_memory_desc_t *diff_dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN backward propagation primitive.
lbr_gru_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8321
vanilla_rnn_forward()=default
Default constructor. Produces an empty object.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5257
@ eltwise_tanh
Elementwise: hyperbolic tangent non-linearity (tanh)
dnnl_status_t DNNL_API dnnl_resampling_backward_desc_init(dnnl_resampling_desc_t *resampling_desc, dnnl_alg_kind_t alg_kind, const float *factors, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes a descriptor for resampling backward propagation primitive.
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
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:9013
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(const_dnnl_primitive_t primitive, const_dnnl_primitive_desc_t *primitive_desc)
Retrieves a constant reference to the primitive descriptor of a given primitive.
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7438
Descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6342
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8305
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:3646
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:1935
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7639
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9161
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5364
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:351
handle()=default
Constructs an empty handle object.
primitive_desc()=default
Default constructor. Produces an empty object.
resampling_forward(const primitive_desc &pd)
Constructs a resampling forward propagation primitive.
Definition: dnnl.hpp:9336
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:6561
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:1911
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:8457
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:699
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:3481
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:716
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:8022
memory::desc dst_iter_c_desc() const
Returns destination recurrent cell state memory descriptor.
Definition: dnnl.hpp:6997
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:4347
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:8420
handle(T t, bool weak=false)
Constructs a handle wrapper object from a C API handle.
Definition: dnnl.hpp:167
int DNNL_API dnnl_memory_desc_equal(const dnnl_memory_desc_t *lhs, const dnnl_memory_desc_t *rhs)
Compares two memory descriptors.
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:667
Primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9109
Primitive descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:5892
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:9156
dnnl_status_t DNNL_API dnnl_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution backward propagation primitive.
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1248
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:5296
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:5197
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:1957
@ avx512_mic
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors x200 Series.
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1114
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:3271
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7882
Primitive descriptor for a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6037
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5692
Primitive descriptor for a concat primitive.
Definition: dnnl.hpp:2950
gru_backward()=default
Default constructor. Produces an empty object.
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:654
@ use_scale_shift
Use scale and shift parameters.
softmax_backward()=default
Default constructor. Produces an empty object.
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:191
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:9135
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:1996
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:7146
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1279
@ memory_consumption_s64
memory consumption (bytes)
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2621
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:2615
Layer normalization backward propagation primitive.
Definition: dnnl.hpp:6340
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:6023
@ library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
resampling_forward()=default
Default constructor. Produces an empty object.
Primitive descriptor GRU forward propagation primitive.
Definition: dnnl.hpp:8045
@ backward_bias
Backward bias propagation.
dnnl_status_t DNNL_API dnnl_set_verbose(int level)
Configures verbose output to stdout.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a logsoftmax backward propagation primitive from a C API primit...
Definition: dnnl.hpp:5788
@ avx512_core
Intel(R) Advanced Vector Extensions 512 for Intel(R) Xeon(R) Processor Scalable Family and Intel(R) C...
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7497
@ eltwise_swish
Elementwise: x*sigmoid(a*x)
softmax_forward()=default
Default constructor. Produces an empty object.
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1136
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:3544
dnnl_status_t DNNL_API dnnl_eltwise_forward_desc_init(dnnl_eltwise_desc_t *eltwise_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, float alpha, float beta)
Initializes a descriptor for eltwise forward propagation primitive.
memory::desc diff_dst_desc(int idx) const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:2577
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:2719
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:230
@ lrn_within_channel
LRN within a single channel.
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:783
layer_normalization_backward()=default
Default constructor. Produces an empty object.
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:6993
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:3179
@ user
A user shall query and provide the scratchpad memory to primitives This mode is thread-safe as long a...
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6299
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:693
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7244
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:3933
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3938
status set_jit_profiling_flags(unsigned flags)
Sets library profiling flags.
Definition: dnnl.hpp:9508
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:1889
memory::desc src1_desc() const
Returns the memory descriptor for source #1.
Definition: dnnl.hpp:9032
Pooling forward propagation primitive.
Definition: dnnl.hpp:4912
@ dnnl_cpu_isa_sse41
Intel(R) SSE4.1.
Definition: dnnl_types.h:2031
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:9555
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:4754
memory::dim query_s64(query what) const
Returns a memory::dim value (same as int64_t).
Definition: dnnl.hpp:2500
status
Status values returned by the library functions.
Definition: dnnl.hpp:9475
Descriptor for a LBR GRU backward propagation primitive.
Definition: dnnl.hpp:8536
dnnl_status_t DNNL_API dnnl_memory_get_engine(const_dnnl_memory_t memory, dnnl_engine_t *engine)
Returns the engine of a memory object.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6486
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:186
@ dnnl_cpu_isa_avx2
Intel(R) Advanced Vector Extensions 2.
Definition: dnnl_types.h:2037
@ dnnl_cpu_isa_avx512_core_vnni
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost Support for Intel(R) Xeon(R) Processor...
Definition: dnnl_types.h:2054
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:4367
Convolution backward propagation primitive.
Definition: dnnl.hpp:3512
int ndims
Number of dimensions.
Definition: dnnl_types.h:979
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:6232
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:221
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:6987
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:3912
T get(bool allow_empty=false) const
Returns the underlying C API handle.
Definition: dnnl.hpp:183
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:2597
primitive_desc()=default
Default constructor. Produces an empty object.
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1312
Primitive descriptor for a reorder primitive.
Definition: dnnl.hpp:2801
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:8928
Elementwise binary operator primitive.
Definition: dnnl.hpp:8954
Descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:4792
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:4223
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:3761
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:8974
Descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6676
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:751
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
size_t DNNL_API dnnl_engine_get_count(dnnl_engine_kind_t kind)
Returns the number of engines of a particular kind.
primitive_desc()=default
Default constructor. Produces an empty object.
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:4978
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8721
dnnl_status_t DNNL_API dnnl_engine_create(dnnl_engine_t *engine, dnnl_engine_kind_t kind, size_t index)
Creates an engine.
DNNL exception class.
Definition: dnnl.hpp:92
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6302
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:3470
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:5538
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:755
@ avx512_core_bf16
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost and Bfloat16 Support for Intel(R) Xeon...
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6308
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8336
memory::data_type data_type() const
Returns the data type of the memory descriptor.
Definition: dnnl.hpp:2203
dnnl_status_t DNNL_API dnnl_set_jit_profiling_jitdumpdir(const char *dir)
Sets JIT dump output path.
void append_eltwise(float scale, algorithm algorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:909
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:9099
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:3369
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1609
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:7212
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:6912
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:7905
dnnl_status_t DNNL_API dnnl_primitive_desc_iterator_destroy(dnnl_primitive_desc_iterator_t iterator)
Destroys a primitive descriptor iterator.
Primitive descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4594
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:677
dnnl_status_t DNNL_API dnnl_inner_product_backward_data_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product backward propagation.
void get_output_scales(int &mask, std::vector< float > &scales) const
Returns output scaling factors correspondence mask and values.
Definition: dnnl.hpp:989
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:274
dnnl_status_t DNNL_API dnnl_memory_map_data(const_dnnl_memory_t memory, void **mapped_ptr)
Maps a memory object and returns a pointer to host-side buffer with a copy of its contents.
@ forward
Forward data propagation, alias for dnnl::prop_kind::forward_training.
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:8804
@ eltwise_relu
Elementwise: ReLU.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6483
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_weights_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution weights gradient primitive.
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7943
Pooling backward propagation primitive.
Definition: dnnl.hpp:5029
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:4385
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:1955
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6655
@ resampling_linear
Linear (Bilinear, Trilinear) resampling method.
A base class for descriptors of all primitives that have an operation descriptor and that support ite...
Definition: dnnl.hpp:3152
lstm_backward(const primitive_desc &pd)
Constructs an LSTM backward propagation primitive.
Definition: dnnl.hpp:7969
@ use_global_stats
Use global statistics.
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization backward propagation primitive.
dnnl_status_t DNNL_API dnnl_lbr_gru_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags)
Initializes a descriptor for LBR GRU forward propagation primitive.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:9035
void reset(T t, bool weak=false)
Resets the handle wrapper objects to wrap a new C API handle.
Definition: dnnl.hpp:174
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5476
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:5652
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:8744
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:675
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7492
flags
Stream flags. Can be combined using the bitwise OR operator.
Definition: dnnl.hpp:1438
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,...
Definition: dnnl.hpp:7780
static size_t get_count(kind kind)
Returns the number of engines of a certain kind.
Definition: dnnl.hpp:1298
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7011
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:5346
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6122
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:5113
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:7869
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:5126
void append_sum(float scale=1.)
Appends an accumulation (sum) post-op.
Definition: dnnl.hpp:880
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Constructs a descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:8883
dnnl_status_t DNNL_API dnnl_inner_product_backward_weights_desc_init(dnnl_inner_product_desc_t *ip_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *diff_weights_desc, const dnnl_memory_desc_t *diff_bias_desc, const dnnl_memory_desc_t *diff_dst_desc)
Initializes descriptor for inner product weights gradient primitive.
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:4889
resampling_backward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5367
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6498
@ bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
An opaque structure for primitive descriptor attributes.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:6915
@ deconvolution_winograd
Winograd deconvolution.
@ unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:685
memory::desc diff_bias_desc() const
Returns diff bias memory descriptor.
Definition: dnnl.hpp:7487
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...
@ eltwise_exp
Elementwise: exponent.
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:1929
dnnl_status_t DNNL_API dnnl_primitive_attr_set_rnn_data_qparams(dnnl_primitive_attr_t attr, const float scale, const float shift)
Set quantization scale and shift parameters for RNN data tensors.
rnn_primitive_desc_base()=default
Default constructor. Produces an empty object.
@ convolution
A convolution primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_get_post_ops(const_dnnl_primitive_attr_t attr, const_dnnl_post_ops_t *post_ops)
Returns primitive attributes post-ops.
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:6443
memory::desc diff_weights_layer_desc() const
Returns diff weights layer memory descriptor.
Definition: dnnl.hpp:8739
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8331
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5803
primitive_attr(dnnl_primitive_attr_t attr)
Creates primitive attributes from a C API dnnl_primitive_attr_t handle.
Definition: dnnl.hpp:959
pooling_backward(const primitive_desc &pd)
Constructs a pooling backward propagation primitive.
Definition: dnnl.hpp:5146
Descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:8786
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:8848
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:4266
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:3028
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1608
Primitive attributes.
Definition: dnnl.hpp:943
softmax_forward(const primitive_desc &pd)
Constructs a softmax forward propagation primitive.
Definition: dnnl.hpp:5485
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8724
primitive_desc()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6658
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8700
desc(algorithm algorithm, 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:9382
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
shuffle_backward(const primitive_desc &pd)
Constructs a shuffle backward propagation primitive.
Definition: dnnl.hpp:8940
Primitive descriptor for an inner product backward propagation primitive.
Definition: dnnl.hpp:6709
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:1885
dnnl_status_t DNNL_API dnnl_dilated_deconvolution_backward_data_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated deconvolution backward propagation primitive.
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:1914
A descriptor of resampling operation.
Definition: dnnl_types.h:1524
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:8519
Descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3515
primitive_desc()=default
Default constructor. Produces an empty object.
Descriptor for a shuffle primitive backward propagation primitive.
Definition: dnnl.hpp:8867
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5473
@ softmax_d
softmax descriptor
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1558
Memory object.
Definition: dnnl.hpp:1607
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:3856
An opaque structure for a chain of post operations.
memory::desc diff_dst_iter_desc() const
Returns diff destination iteration memory descriptor.
Definition: dnnl.hpp:7039
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:1062
@ dnnl_query_undef
no query
Definition: dnnl_types.h:1883
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:8058
@ undef
Undefined RNN flags.
eltwise_forward()=default
Default constructor. Produces an empty object.
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:747
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:111
eltwise_backward(const primitive_desc &pd)
Constructs an eltwise backward propagation primitive.
Definition: dnnl.hpp:5379
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:6746
memory::desc diff_weights_desc(int idx) const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:2586
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7900
@ undef
Undefined propagation kind.
inner_product_forward()=default
Default constructor. Produces an empty object.
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:3626
memory::desc variance_desc() const
Returns memory descriptor for variance.
Definition: dnnl.hpp:6117
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.
@ eltwise_linear
Elementwise: linear.
status set_verbose(int level)
Configures verbose output to stdout.
Definition: dnnl.hpp:9493
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:4181
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5943
Primitive descriptor for an inner product forward propagation primitive.
Definition: dnnl.hpp:6605
DNNL C API handle wrapper class.
Definition: dnnl.hpp:134
pooling_backward()=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 softmax forward propagation primitive.
Definition: dnnl.hpp:5440
memory::desc src_desc(int idx) const
Returns a source memory descriptor.
Definition: dnnl.hpp:2541
@ convolution_auto
Convolution algorithm (either direct or Winograd) is chosen just in time.
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)
Destroys a primitive.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7652
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:6899
Descriptor for a batch normalization forward propagation primitive.
Definition: dnnl.hpp:5840
cl::sycl::context DNNL_API get_sycl_context() const
Returns the underlying SYCL context object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a binary primitive from a C API primitive descriptor that must ...
Definition: dnnl.hpp:9022
dnnl_status_t DNNL_API dnnl_memory_create(dnnl_memory_t *memory, const dnnl_memory_desc_t *memory_desc, dnnl_engine_t engine, void *handle)
Creates a memory object.
dnnl_status_t DNNL_API dnnl_pooling_forward_desc_init(dnnl_pooling_desc_t *pool_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t kernel, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for pooling forward propagation primitive.
dnnl_status_t DNNL_API dnnl_logsoftmax_backward_desc_init(dnnl_logsoftmax_desc_t *logsoftmax_desc, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, int logsoftmax_axis)
Initializes a descriptor for logsoftmax backward propagation primitive.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:7441
inner_product_backward_data()=default
Default constructor. Produces an empty object.
memory::desc weights_layer_desc() const
Returns weights layer memory descriptor.
Definition: dnnl.hpp:8703
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:6959
convolution_backward_data(const primitive_desc &pd)
Constructs a convolution backward propagation primitive.
Definition: dnnl.hpp:3679
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:6886
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:6103
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.
LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8371
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:9449
batch_normalization_backward(const primitive_desc &pd)
Constructs a batch normalization backward propagation primitive.
Definition: dnnl.hpp:6131
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:3717
Memory descriptor.
Definition: dnnl_types.h:977
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:658
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7231
memory::desc src_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7647
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:701
void set_output_scales(int mask, const std::vector< float > &scales)
Sets output scaling factors correspondence mask and values.
Definition: dnnl.hpp:1045
convolution_backward_weights(const primitive_desc &pd)
Constructs a convolution weights gradient primitive.
Definition: dnnl.hpp:3955
logsoftmax_forward(const primitive_desc &pd)
Constructs a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5701
bool operator!=(const handle &other) const
Inequality operator.
Definition: dnnl.hpp:218
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:3499
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2026
memory::desc bias_desc() const
Returns the bias memory descriptor.
Definition: dnnl.hpp:6661
bool operator!=(const desc &other) const
An inequality operator.
Definition: dnnl.hpp:2230
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:6463
Descriptor for a pooling backward propagation primitive.
Definition: dnnl.hpp:5031
Primitive descriptor for a shuffle forward propagation primitive.
Definition: dnnl.hpp:8815
batch_normalization_forward()=default
Default constructor. Produces an empty object.
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:4220
Descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7091
dnnl_status_t DNNL_API dnnl_lrn_forward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN forward propagation primitive.
dnnl_binary_desc_t data
Underlying C operation descriptor.
Definition: dnnl.hpp:8958
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:473
@ scratchpad_engine
scratchpad engine
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:7918
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8713
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6904
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:923
dnnl_status_t DNNL_API dnnl_engine_destroy(dnnl_engine_t engine)
Destroys an engine.
void reset_with_clone(const_dnnl_primitive_desc_t pd)
Resets the value of the handle to a clone of a C API primitive descriptor.
Definition: dnnl.hpp:2684
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:194
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops)
Returns the length of post-ops.
Primitive descriptor for a layer normalization backward propagation primitive.
Definition: dnnl.hpp:6426
memory::desc scratchpad_desc() const
Returns the scratchpad memory descriptor.
Definition: dnnl.hpp:2642
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_desc_init(dnnl_batch_normalization_desc_t *bnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a descriptor for a batch normalization forward propagation primitive.
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:470
Primitive descriptor for a shuffle backward propagation primitive.
Definition: dnnl.hpp:8892
dnnl_status_t DNNL_API dnnl_shuffle_backward_desc_init(dnnl_shuffle_desc_t *shuffle_desc, const dnnl_memory_desc_t *diff_data_desc, int axis, dnnl_dim_t group_size)
Initializes a descriptor for shuffle backward propagation primitive.
Primitive descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4330
void get_params_sum(int index, float &scale) const
Returns the parameters of an accumulation (sum) post-op.
Definition: dnnl.hpp:889
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:1913
handle< T, traits > & operator=(const handle< T, traits > &)=default
Assignment operator.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:3944
@ pooling_max
Max pooling.
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:8956
Descriptor for a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4406
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3025
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:198
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:6983
dnnl_status_t DNNL_API dnnl_lrn_backward_desc_init(dnnl_lrn_desc_t *lrn_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_data_desc, const dnnl_memory_desc_t *data_desc, dnnl_dim_t local_size, float alpha, float beta, float k)
Initializes a descriptor for LRN backward propagation primitive.
A class that provides the destructor for a DNNL C API handle.
Definition: dnnl.hpp:118
memory::desc weights_desc(int idx) const
Returns a weights memory descriptor.
Definition: dnnl.hpp:2559
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:8255
memory::desc diff_src_layer_desc() const
Returns diff source layer memory descriptor.
Definition: dnnl.hpp:8729
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:1888
@ invalid_arguments
The operation failed because of incorrect function arguments.
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1612
Primitive descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5521
Deconvolution backward propagation primitive.
Definition: dnnl.hpp:4236
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:5949
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:188
memory::desc diff_dst_layer_desc() const
Returns diff destination layer memory descriptor.
Definition: dnnl.hpp:7948
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:4049
dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum(const_dnnl_post_ops_t post_ops, int index, float *scale)
Returns the parameters of an accumulation (sum) post-op.
dnnl_status_t DNNL_API dnnl_primitive_attr_set_scratchpad_mode(dnnl_primitive_attr_t attr, dnnl_scratchpad_mode_t mode)
Sets primitive attributes scratchpad mode.
const post_ops get_post_ops() const
Returns post-ops previously set via set_post_ops().
Definition: dnnl.hpp:1155
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:7218
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8111
A memory descriptor.
Definition: dnnl.hpp:2106
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:3490
Base class for all computational primitives.
Definition: dnnl.hpp:260
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:707
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:718
@ dnnl_cpu_isa_avx512_mic
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors x200 Series.
Definition: dnnl_types.h:2041
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:4739
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:5668
memory::desc dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:6489
batch_normalization_backward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_strides(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, const dnnl_dims_t strides)
Initializes a memory descriptor using dimensions and strides.
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
engine get_engine() const
Returns the associated engine.
Definition: dnnl.hpp:2301
format_kind
Memory format kind.
Definition: dnnl.hpp:1644
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:740
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:182
convolution_forward(const primitive_desc &pd)
Constructs a convolution forward propagation primitive.
Definition: dnnl.hpp:3508
bool operator==(const desc &other) const
An equality operator.
Definition: dnnl.hpp:2222
Shuffle forward propagation primitive.
Definition: dnnl.hpp:8784
@ logsoftmax_d
logsoftmax descriptor
memory(const desc &md, const engine &engine, cl::sycl::buffer< T, ndims > &buf)
Constructs a memory from a SYCL buffer.
Definition: dnnl.hpp:2276
lbr_gru_forward(const primitive_desc &pd)
Constructs an LBR GRU forward propagation primitive.
Definition: dnnl.hpp:8530
dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points(dnnl_primitive_attr_t attr, int arg, dnnl_dim_t count, int mask, const int32_t *zero_points)
Sets primitive attributes zero points for primitive operations for a given memory argument.
matmul()=default
Default constructor. Produces an empty object.
lbr_gru_forward()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_create(dnnl_primitive_t *primitive, const_dnnl_primitive_desc_t primitive_desc)
Creates a primitive.
primitive_desc()=default
Default constructor. Produces an empty object.
Descriptor for a convolution forward propagation primitive.
Definition: dnnl.hpp:3236
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:9234
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:9077
bool is_zero() const
Checks whether the memory descriptor is zero (empty).
Definition: dnnl.hpp:2216
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:6953
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1399
lstm_forward(const primitive_desc &pd)
Constructs an LSTM forward propagation primitive.
Definition: dnnl.hpp:7689
memory::desc diff_weights_iter_desc() const
Returns diff weights iteration memory descriptor.
Definition: dnnl.hpp:7938
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7662
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:732
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:479
DNNL namespace.
Definition: dnnl.hpp:82
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:769
@ logsoftmax
A logsoftmax primitive.
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:8508
@ shuffle_d
shuffle descriptor
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:5456
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:9151
Descriptor for a convolution weights gradient primitive.
Definition: dnnl.hpp:3685
@ impl_info_str
implementation name
Descriptor for a deconvolution backward propagation primitive.
Definition: dnnl.hpp:4238
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:8511
A descriptor of a binary operation.
Definition: dnnl_types.h:1477
desc submemory_desc(const memory::dims &dims, const memory::dims &offsets) const
Constructs a memory descriptor for a region inside an area described by this memory descriptor.
Definition: dnnl.hpp:2171
pooling_forward()=default
Default constructor. Produces an empty object.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:8708
engine get_dst_engine() const
Returns the engine on which the destination memory is allocated.
Definition: dnnl.hpp:2871
@ batch_normalization
A batch normalization primitive.
dnnl_status_t DNNL_API dnnl_primitive_attr_clone(dnnl_primitive_attr_t *attr, const_dnnl_primitive_attr_t existing_attr)
Clones primitive attributes.
primitive_desc()=default
Default constructor. Produces an empty object.
void * get_data_handle() const
Returns the underlying memory buffer.
Definition: dnnl.hpp:2311
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:710
dnnl_primitive_kind_t DNNL_API dnnl_post_ops_get_kind(const_dnnl_post_ops_t post_ops, int index)
Returns the kind of a post-op entry.
sum(const primitive_desc &pd)
Constructs a sum primitive.
Definition: dnnl.hpp:3142
concat(const primitive_desc &pd)
Constructs a concatenation primitive.
Definition: dnnl.hpp:3036
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:1930
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:7201
@ eltwise_gelu
Elementwise: gelu.
Vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7089
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8695
@ eltwise_square
Elementwise: square.
cl_command_queue get_ocl_command_queue() const
Returns the underlying OpenCL queue object.
Definition: dnnl.hpp:1481
vanilla_rnn_backward(const primitive_desc &pd)
Constructs a vanilla RNN backward propagation primitive.
Definition: dnnl.hpp:7508
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:8931
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:3419
deconvolution_forward(const primitive_desc &pd)
Constructs a deconvolution forward propagation primitive.
Definition: dnnl.hpp:4232
const version_t * version()
Returns library version information.
Definition: dnnl.hpp:9498
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:648
binary()=default
Default constructor. Produces an empty object.
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:284
reorder(const primitive_desc &pd)
Constructs a reorder primitive.
Definition: dnnl.hpp:2887
primitive_desc(const desc &desc, const engine &engine, bool allow_empty=false)
Constructs a primitive descriptor for a matmul primitive.
Definition: dnnl.hpp:9121
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:6646
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:6696
dnnl_status_t DNNL_API dnnl_deconvolution_forward_desc_init(dnnl_deconvolution_desc_t *deconv_desc, dnnl_prop_kind_t prop_kind, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc, const dnnl_dims_t strides, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a deconvolution forward propagation primitive.
primitive::kind kind(int index) const
Returns the primitive kind of post-op at entry with a certain index.
Definition: dnnl.hpp:851
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8495
algorithm
Kinds of algorithms.
Definition: dnnl.hpp:479
Primitive descriptor for a convolution backward propagation primitive.
Definition: dnnl.hpp:3609
memory::desc dst_iter_c_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7908
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:639
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.
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:6097
primitive_desc()=default
Default constructor. Produces an empty object.
kind get_kind() const
Returns the kind of the primitive.
Definition: dnnl.hpp:385
dnnl_status_t DNNL_API dnnl_matmul_desc_init(dnnl_matmul_desc_t *matmul_desc, const dnnl_memory_desc_t *src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_desc)
Initializes a matrix multiplication descriptor.
memory::desc diff_bias_desc() const
Returns the diff bias memory descriptor.
Definition: dnnl.hpp:4658
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:8734
dnnl_status_t DNNL_API dnnl_memory_desc_init_by_tag(dnnl_memory_desc_t *memory_desc, int ndims, const dnnl_dims_t dims, dnnl_data_type_t data_type, dnnl_format_tag_t tag)
Initializes a memory descriptor using dimensions and memory format tag.
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:1886
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1391
@ time_estimate_f64
runtime estimation (seconds), unimplemented
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:5755
dnnl_primitive_desc_t DNNL_API dnnl_primitive_desc_iterator_fetch(const_dnnl_primitive_desc_iterator_t iterator)
Fetches the current primitive descriptor from a primitive descriptor iterator.
Descriptor for a pooling forward propagation primitive.
Definition: dnnl.hpp:4914
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:2860
Primitive descriptor for eltwise backward propagation.
Definition: dnnl.hpp:5309
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:9211
Descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5607
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:9266
@ dnnl_eltwise_elu
Eltwise: parametric exponential linear unit (elu)
Definition: dnnl_types.h:724
memory::desc src0_desc() const
Returns the memory descriptor for source #0.
Definition: dnnl.hpp:9029
@ in_order
In-order execution.
T * map_data() const
Maps the data of the memory.
Definition: dnnl.hpp:2347
@ avx512_mic_4ops
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors 7235,...
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:3670
@ out_of_memory
The operation failed due to an out-of-memory condition.
primitive_desc()=default
Default constructor. Produces an empty object.
batch_normalization_forward(const primitive_desc &pd)
Constructs a batch normalization forward propagation primitive.
Definition: dnnl.hpp:5985
memory::desc diff_src_iter_desc() const
Returns diff source iteration memory descriptor.
Definition: dnnl.hpp:7923
primitive_desc()=default
Default constructor. Produces an empty object.
shuffle_forward(const primitive_desc &pd)
Constructs a shuffle forward propagation primitive.
Definition: dnnl.hpp:8860
dnnl_status_t DNNL_API dnnl_dilated_convolution_backward_data_desc_init(dnnl_convolution_desc_t *conv_desc, dnnl_alg_kind_t alg_kind, const dnnl_memory_desc_t *diff_src_desc, const dnnl_memory_desc_t *weights_desc, const dnnl_memory_desc_t *diff_dst_desc, const dnnl_dims_t strides, const dnnl_dims_t dilates, const dnnl_dims_t padding_l, const dnnl_dims_t padding_r)
Initializes a descriptor for a dilated convolution backward propagation primitive.
memory::desc src_desc(int idx=0) const
Returns a source memory descriptor.
Definition: dnnl.hpp:3131
dnnl_status_t DNNL_API dnnl_layer_normalization_forward_desc_init(dnnl_layer_normalization_desc_t *lnrm_desc, dnnl_prop_kind_t prop_kind, const dnnl_memory_desc_t *data_desc, const dnnl_memory_desc_t *stat_desc, float epsilon, unsigned flags)
Initializes a descriptor for layer normalization forward propagation primitive.
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:482
scratchpad_mode get_scratchpad_mode() const
Returns the scratchpad mode.
Definition: dnnl.hpp:963
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(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:4437
dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(dnnl_primitive_attr_t attr, const_dnnl_post_ops_t post_ops)
Sets primitive attributes post-ops.
desc()
Constructs a zero (empty) memory descriptor.
Definition: dnnl.hpp:2113
@ out_of_order
Out-of-order execution.
convolution_backward_weights()=default
Default constructor. Produces an empty object.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)
Destroys a primitive descriptor.
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:3588
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:767
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1556
lrn_backward()=default
Default constructor. Produces an empty object.
Base class for primitive descriptors for RNN primitives.
Definition: dnnl.hpp:6940
primitive_attr()
Constructs default (empty) primitive attributes.
Definition: dnnl.hpp:947
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:5059
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:464
Primitive descriptor for an LRN backward propagation primitive.
Definition: dnnl.hpp:4830
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:703
LSTM forward propagation primitive.
Definition: dnnl.hpp:7512
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:6759
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:2704
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:6259
@ matmul_d
matmul descriptor
@ dnnl_cpu_isa_avx
Intel(R) Advanced Vector Extensions.
Definition: dnnl_types.h:2034
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:195
engine get_engine() const
Returns the engine of the primitive descriptor.
Definition: dnnl.hpp:2487
@ diff_weights_md
weights grad. memory desc
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:636
memory::desc src_layer_desc() const
Returns source layer memory descriptor.
Definition: dnnl.hpp:8292
const char * impl_info_str() const
Returns implementation name.
Definition: dnnl.hpp:2490
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:1936
@ forward_scoring
Forward data propagation, alias for dnnl::prop_kind::forward_inference.
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7657
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:5946
memory::desc query_md(query what, int idx=0) const
Returns a memory descriptor.
Definition: dnnl.hpp:2521
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:5775
memory::desc diff_weights_desc() const
Returns a diff weights memory descriptor.
Definition: dnnl.hpp:6109
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.
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:9359
@ dnnl_eltwise_gelu
Eltwise: gelu.
Definition: dnnl_types.h:745
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:3808
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:7185
memory::desc weights_desc() const
Returns a weights memory descriptor.
Definition: dnnl.hpp:4217
dnnl_status_t DNNL_API dnnl_primitive_attr_get_output_scales(const_dnnl_primitive_attr_t attr, dnnl_dim_t *count, int *mask, const float **scales)
Returns primitive attributes output scaling factors correspondence mask and values.
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:1931
memory::desc workspace_desc() const
Returns the workspace memory descriptor.
Definition: dnnl.hpp:6511
@ backward_data
Backward data propagation.
@ default_flags
Default stream configuration.
deconvolution_backward_weights(const primitive_desc &pd)
Constructs a deconvolution weights gradient primitive.
Definition: dnnl.hpp:4669
Base class for all primitive descriptors.
Definition: dnnl.hpp:2480
Descriptor for a softmax backward propagation primitive.
Definition: dnnl.hpp:5491
reorder()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
primitive_desc()=default
Default constructor. Produces an empty object.
const dnnl_memory_desc_t DNNL_API * dnnl_primitive_desc_query_md(const_dnnl_primitive_desc_t primitive_desc, dnnl_query_t what, int index)
Queries primitive descriptor for a memory descriptor.
dnnl_status_t DNNL_API dnnl_gemm_u8s8s32(char transa, char transb, char offsetc, dnnl_dim_t M, dnnl_dim_t N, dnnl_dim_t K, float alpha, const uint8_t *A, dnnl_dim_t lda, uint8_t ao, const int8_t *B, dnnl_dim_t ldb, int8_t bo, float beta, int32_t *C, dnnl_dim_t ldc, const int32_t *co)
Performs integer matrix-matrix multiply on 8-bit unsigned matrix A, 8-bit signed matrix B,...
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:1917
dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t *post_ops)
Creates empty post-ops sequence.
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:9428
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:9324
desc(const memory::dims &dims, data_type data_type, format_tag format_tag)
Constructs a memory descriptor.
Definition: dnnl.hpp:2126
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:3659
Descriptor for an LSTM backward propagation primitive.
Definition: dnnl.hpp:7695
inner_product_backward_weights()=default
Default constructor. Produces an empty object.
status set_jit_dump(int enable)
Configures dumping of JIT-generated code.
Definition: dnnl.hpp:9503
memory::desc dst_iter_desc() const
Returns destination iteration memory descriptor.
Definition: dnnl.hpp:8318
memory::desc diff_dst_desc() const
Returns a destination memory descriptor.
Definition: dnnl.hpp:5582
memory::desc dst_layer_desc() const
Returns destination layer memory descriptor.
Definition: dnnl.hpp:7239
Deconvolution forward propagation primitive.
Definition: dnnl.hpp:3969
Local response normalization (LRN) backward propagation primitive.
Definition: dnnl.hpp:4790
@ eltwise
An element-wise primitive.
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:5689
primitive_desc()=default
Default constructor. Produces an empty object.
gru_forward()=default
Default constructor. Produces an empty object.
memory::desc diff_src_desc() const
Returns a diff source memory descriptor.
Definition: dnnl.hpp:5579
const typedef void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1049
Descriptor for a softmax forward propagation primitive.
Definition: dnnl.hpp:5395
shuffle_backward()=default
Default constructor. Produces an empty object.
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:665
memory::desc diff_src_iter_c_desc() const
Returns diff source recurrent cell state memory descriptor.
Definition: dnnl.hpp:7928
Primitive descriptor for a RNN backward propagation primitive.
Definition: dnnl.hpp:7378
Out-of-place summation (sum) primitive.
Definition: dnnl.hpp:3050
Primitive descriptor for a logsoftmax forward propagation primitive.
Definition: dnnl.hpp:5638
dnnl_status_t DNNL_API dnnl_vanilla_rnn_forward_desc_init(dnnl_rnn_desc_t *rnn_desc, dnnl_prop_kind_t prop_kind, const dnnl_alg_kind_t activation, const dnnl_rnn_direction_t direction, const dnnl_memory_desc_t *src_layer_desc, const dnnl_memory_desc_t *src_iter_desc, const dnnl_memory_desc_t *weights_layer_desc, const dnnl_memory_desc_t *weights_iter_desc, const dnnl_memory_desc_t *bias_desc, const dnnl_memory_desc_t *dst_layer_desc, const dnnl_memory_desc_t *dst_iter_desc, unsigned flags, float alpha, float beta)
Initializes a descriptor for vanilla RNN forward propagation primitive.
@ deconvolution
A deconvolution primitive.
@ unidirectional
Alias for dnnl::rnn_direction::unidirectional_left2right.
layer_normalization_forward()=default
Default constructor. Produces an empty object.
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:6074
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:736
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:2822
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:8297
Primitive descriptor for a vanilla RNN forward propagation primitive.
Definition: dnnl.hpp:7171
lrn_forward()=default
Default constructor. Produces an empty object.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for a pooling forward propagation primitive from a C API primitive ...
Definition: dnnl.hpp:5004
#define DNNL_ARG_FROM
A special mnemonic for reorder source argument.
Definition: dnnl_types.h:1696
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1393
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:248
gru_backward(const primitive_desc &pd)
Constructs a GRU backward propagation primitive.
Definition: dnnl.hpp:8367
@ pooling_avg_include_padding
Average pooling include padding.
memory::desc diff_dst_desc() const
Returns a diff destination memory descriptor.
Definition: dnnl.hpp:4655
memory::desc src_desc() const
Returns a source memory descriptor.
Definition: dnnl.hpp:6293
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:8073
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
Primitive descriptor for a logsoftmax backward propagation primitive.
Definition: dnnl.hpp:5738
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:1897
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Sets quantization scaling factors for RNN weights tensors.
Definition: dnnl.hpp:1243
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
@ deconvolution_d
deconvolution descriptor
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.
Descriptor for a resampling backward propagation primitive.
Definition: dnnl.hpp:9342
GRU backward propagation primitive.
Definition: dnnl.hpp:8134
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:1937
memory::desc bias_desc() const
Returns bias memory descriptor.
Definition: dnnl.hpp:7897
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:4098
memory::desc src_iter_desc() const
Returns source iteration memory descriptor.
Definition: dnnl.hpp:7879
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:6275
Descriptor for a deconvolution forward propagation primitive.
Definition: dnnl.hpp:3971
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:6087
@ primitive_kind
primitive kind
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:757
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:779
dnnl_status_t DNNL_API dnnl_set_jit_dump(int enable)
Configures dumping of JIT-generated code.
primitive_desc(dnnl_primitive_desc_t pd)
Constructs a primitive descriptor for an eltwise forward propagation primitive from a C API primitive...
Definition: dnnl.hpp:5251
memory::desc weights_iter_desc() const
Returns weights iteration memory descriptor.
Definition: dnnl.hpp:7446
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.