20 #ifndef DOXYGEN_SHOULD_SKIP_THIS 55 template <
typename T,
typename traits=handle_traits<T>>
class handle {
57 std::shared_ptr<typename std::remove_pointer<T>::type> _data;
61 bool operator==(
const T other)
const {
return other == _data.get(); }
62 bool operator!=(
const T other)
const {
return !(*
this == other); }
67 handle(T t = 0,
bool weak =
false): _data(0) {
79 void reset(T t,
bool weak =
false) {
80 auto dummy_destructor = [](T) {
return decltype(traits::destructor(0))(0); };
81 _data.reset(t, weak ? dummy_destructor : traits::destructor);
85 T
get()
const {
return _data.get(); }
87 bool operator==(
const handle &other)
const {
return other._data.get() == _data.get(); }
91 #ifndef DOXYGEN_SHOULD_SKIP_THIS 100 template <>
struct handle_traits<mkldnn_primitive_desc_iterator_t> {
109 friend class primitive_at;
110 using handle::handle;
161 struct error:
public std::exception {
174 mkldnn_primitive_t aerror_primitive = 0)
177 , error_primitive(aerror_primitive, true)
189 const std::string &message,
190 mkldnn_primitive_t *error_primitive = 0)
193 if (
nullptr != error_primitive)
194 throw error(status, message, *error_primitive);
196 throw error(status, message,
nullptr);
205 data.output_index, &output),
206 "could not get an output primitive");
207 return primitive(const_cast<mkldnn_primitive_t>(output),
true);
213 "could not get primitive descriptor by primitive");
361 #ifndef DOXYGEN_SHOULD_SKIP_THIS 369 mkldnn_post_ops_t result;
371 "could not create post operation sequence");
380 "post_ops index is out of range");
387 "could not append sum");
392 "could not get sum params");
399 "could not append eltwise");
403 float &alpha,
float &beta)
const {
406 &scale, &c_alg, &alpha, &beta),
407 "could not get eltwise params");
412 #ifndef DOXYGEN_SHOULD_SKIP_THIS 420 mkldnn_primitive_attr_t result;
422 "could not create a primitive attr");
429 get(), &result),
"could not get int output round mode");
436 "could not set int output round mode");
442 const float *c_scales;
444 &count, &c_mask, &c_scales),
445 "could not get int output scales");
446 scales.resize(count);
449 for (
int c = 0; c < count; ++c)
450 scales[c] = c_scales[c];
456 (
int)scales.size(), mask, &scales[0]),
457 "could not set int output scales");
464 "could not get post operation sequence");
465 result.
reset(const_cast<mkldnn_post_ops_t>(c_result),
true);
471 "could not set post operation sequence");
477 scale, shift),
"could not set rnn data int scale/shift");
483 (
int)scales.size(), mask, &scales[0]),
484 "could not set rnn weights int scales");
496 #ifndef DOXYGEN_SHOULD_SKIP_THIS 530 mkldnn_engine_t aengine;
534 "could not create an engine");
538 explicit engine(
const mkldnn_engine_t& aengine)
539 :
handle(aengine, true) {}
542 mkldnn_engine_t engine_q;
546 "could not get engine from primitive_desc");
547 reset(engine_q,
true);
550 template <
class primitive_desc>
552 mkldnn_engine_t engine_q;
556 "could not get engine from primitive_desc");
581 std::shared_ptr<char> _handle;
584 typedef std::vector<std::remove_extent<mkldnn_dims_t>::type>
dims;
589 "invalid dimensions");
736 validate_dims(adims);
739 adims.size() == 0 ? nullptr : &adims[0],
741 "could not initialize a memory descriptor");
759 mkldnn_primitive_desc_t result;
763 "could not initialize a memory primitive descriptor");
780 other.
get())) ? false :
true;
798 mkldnn_primitive_t result;
801 "could not create a memory primitive");
803 auto _malloc = [](
size_t size,
int alignment) {
806 ptr = _aligned_malloc(size, alignment);
807 int rc = ((ptr)? 0 : errno);
809 int rc = ::posix_memalign(&ptr, alignment, size);
811 return (rc == 0) ? (
char*)ptr :
nullptr;
813 auto _free = [](
char* p) {
815 _aligned_free((
void*)p);
820 _handle.reset(_malloc(adesc.
get_size(), 4096), _free);
821 set_data_handle(_handle.get());
825 mkldnn_primitive_t result;
828 "could not create a memory primitive");
830 set_data_handle(ahandle);
839 "could not get primitive descriptor from a memory primitive");
841 adesc.
reset(const_cast<mkldnn_primitive_desc_t>(cdesc),
true);
850 "could not get native handle");
856 "could not set native handle");
880 &aprimitive_desc,
int n_inputs,
int n_outputs,
881 const std::string &prim_name) {
886 if (n_outputs_expected > n_outputs ) {
887 std::string message =
"could not create " + prim_name +
888 " primitive, not enought output parameters";
891 if (n_inputs_expected > n_inputs ) {
892 std::string message =
"could not create " + prim_name +
893 " primitive, not enought input parameters";
905 return ((aprimitive_md !=
nullptr) && (aprimitive_md->
ndims == 0));
946 mkldnn_primitive_desc_t result;
948 &result, input.
get(), output.
get()),
949 "could not create a reorder primitive descriptor");
956 mkldnn_primitive_desc_t result;
958 &result, input.
get(), output.
get(), aattr.
get()),
959 "could not create a reorder primitive descriptor");
968 mkldnn_primitive_t result;
972 aprimitive_desc.
get(), inputs, outputs),
973 "could not create a reorder primitive");
983 mkldnn_primitive_t result;
987 reorder_d.get(), inputs, outputs),
988 "could not create a reorder primitive");
1005 mkldnn_primitive_desc_t result;
1008 &result, input.
get(), &dims[0], &offsets[0]),
1009 "could not create a view primitive descriptor");
1015 mkldnn_primitive_desc_t cdesc;
1021 "could not clone a dst primitive descriptor");
1030 mkldnn_primitive_t result;
1033 view_pd.
get(), inputs,
nullptr),
1034 "could not create a view primitive");
1039 mkldnn_primitive_t result;
1044 view_pd.get(), inputs,
nullptr),
1045 "could not create a view primitive");
1061 std::vector<memory::primitive_desc> inputs) {
1062 std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
1063 c_api_inputs.reserve(inputs.size());
1065 std::transform(inputs.begin(), inputs.end(),
1067 return c_api_inputs;
1071 std::vector<memory::primitive_desc> inputs) {
1072 mkldnn_primitive_desc_t result;
1074 auto c_api_inputs = cpp_to_c(inputs);
1077 &result, &output.
data, (
int)c_api_inputs.size(),
1078 concat_dimension, &c_api_inputs[0]),
1079 "could not create a concat primitive descriptor");
1084 std::vector<memory::primitive_desc> inputs) {
1085 mkldnn_primitive_desc_t result;
1087 auto c_api_inputs = cpp_to_c(inputs);
1090 &result,
nullptr, (
int)c_api_inputs.size(),
1091 concat_dimension, &c_api_inputs[0]),
1092 "could not create a concat primitive descriptor");
1098 mkldnn_primitive_desc_t cdesc;
1103 "could not clone a dst primitive descriptor");
1112 std::vector<primitive::at> &inputs,
const memory &output) {
1113 mkldnn_primitive_t result;
1115 std::vector<mkldnn_primitive_at_t> p_inputs;
1116 for (
size_t i = 0; i < inputs.size(); i++)
1117 p_inputs.push_back(inputs[i].data);
1121 concat_pd.
get(), &p_inputs[0], outputs),
1122 "could not create a concat primitive");
1138 std::vector<memory::primitive_desc> inputs) {
1139 std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
1140 c_api_inputs.reserve(inputs.size());
1142 std::transform(inputs.begin(), inputs.end(),
1144 return c_api_inputs;
1148 const std::vector<float> &scales,
1149 std::vector<memory::primitive_desc> inputs) {
1150 mkldnn_primitive_desc_t result;
1152 auto c_api_inputs = cpp_to_c(inputs);
1157 "number of scales not equal to number of inputs");
1160 &result, &output.
data, (
int)c_api_inputs.size(),
1161 &scales[0], &c_api_inputs[0]),
1162 "could not create a sum primitive descriptor");
1167 std::vector<memory::primitive_desc> inputs) {
1168 mkldnn_primitive_desc_t result;
1170 auto c_api_inputs = cpp_to_c(inputs);
1175 "number of scales not equal to number of inputs");
1178 &result,
nullptr, (
int)c_api_inputs.size(), &scales[0],
1180 "could not create a sum primitive descriptor");
1186 mkldnn_primitive_desc_t cdesc;
1192 "could not clone a dst primitive descriptor");
1201 std::vector<primitive::at> &inputs,
const memory &output) {
1202 mkldnn_primitive_t result;
1204 std::vector<mkldnn_primitive_at_t> p_inputs;
1205 for (
size_t i = 0; i < inputs.size(); i++)
1206 p_inputs.push_back(inputs[i].data);
1210 sum_pd.
get(), &p_inputs[0], outputs),
1211 "could not create a sum primitive");
1230 mkldnn_primitive_desc_iterator_t iterator =
nullptr;
1232 &iterator, desc, attr ? attr->
get() :
nullptr, e.
get(),
1235 "could not create a primitive descriptor iterator");
1236 pd_iterator.reset(iterator);
1245 "could not get attributes");
1246 mkldnn_primitive_attr_t cattr;
1248 "could not clone attributes");
1260 "could not query implementation info string");
1284 if (!std::any_of(valid_w.cbegin(), valid_w.cend(),
1285 [=](
query q) {
return what == q; }))
1293 if (const_cdesc ==
nullptr)
1296 mkldnn_primitive_desc_t cdesc;
1298 "could not clone a memory primitive descriptor");
1306 # define REG_QUERY_MPD(name, what, idx) \ 1307 memory::primitive_desc name ## _primitive_desc() const \ 1308 { return query_mpd(what ## _pd, idx); } 1311 handle<mkldnn_primitive_desc_iterator_t> pd_iterator;
1316 "could not fetch a primitive descriptor from the iterator");
1347 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1349 "could not create a convolution forward descriptor");
1364 &src_desc.
data, &weights_desc.
data,
nullptr,
1365 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1367 "could not create a convolution forward descriptor");
1387 &dst_desc.
data, &strides[0], &dilates[0],
1388 &padding_l[0], &padding_r[0],
1390 "could not create a dilated convolution forward descriptor");
1408 &src_desc.
data, &weights_desc.
data,
nullptr,
1409 &dst_desc.
data, &strides[0], &dilates[0],
1410 &padding_l[0], &padding_r[0],
1412 "could not create a dilated convolution forward descriptor");
1432 mkldnn_primitive_t result;
1437 aprimitive_desc.
get(), inputs, outputs),
1438 "could not create a convolution forward bias primitive");
1445 mkldnn_primitive_t result;
1449 "convolution forward");
1451 aprimitive_desc.
get(), inputs, outputs),
1452 "could not create a convolution forward primitive");
1473 &weights_desc.
data, &diff_dst_desc.
data,
1474 &strides[0], &padding_l[0], &padding_r[0],
1476 "could not create a convolution backward data descriptor");
1494 &weights_desc.
data, &diff_dst_desc.
data,
1495 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1497 "could not create a convolution backward data descriptor");
1517 const memory &diff_src) {
1518 mkldnn_primitive_t result;
1522 "convolution backward data");
1524 aprimitive_desc.
get(), inputs, outputs),
1525 "could not create a convolution backward data primitive");
1547 &diff_weights_desc.
data, &diff_bias_desc.
data,
1548 &diff_dst_desc.
data,
1549 &strides[0], &padding_l[0], &padding_r[0],
1551 "could not create a convolution backward weights descriptor");
1566 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1567 &strides[0], &padding_l[0], &padding_r[0],
1569 "could not create a convolution backward weights descriptor");
1587 &diff_weights_desc.
data, &diff_bias_desc.
data,
1588 &diff_dst_desc.
data,
1589 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1591 "could not create a convolution backward weights descriptor");
1608 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1609 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1611 "could not create a convolution backward weights descriptor");
1634 mkldnn_primitive_t result;
1639 "convolution backward weights");
1641 aprimitive_desc.
get(), inputs, outputs),
1642 "could not create a convolution backward weights primitive");
1647 const memory &diff_weights) {
1648 mkldnn_primitive_t result;
1652 "convolution backward weights");
1654 aprimitive_desc.
get(), inputs, outputs),
1655 "could not create a convolution backward weights primitive");
1686 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1688 "could not create a deconvolution forward descriptor");
1703 &src_desc.
data, &weights_desc.
data,
nullptr,
1704 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1706 "could not create a deconvolution forward descriptor");
1725 &dst_desc.
data, &strides[0], &dilates[0], &padding_l[0],
1727 "could not create a dilated deconvolution forward descriptor");
1744 &src_desc.
data, &weights_desc.
data,
nullptr,
1745 &dst_desc.
data, &strides[0], &dilates[0], &padding_l[0],
1747 "could not create a dilated deconvolution forward descriptor");
1767 mkldnn_primitive_t result;
1772 "deconvolution forward");
1774 aprimitive_desc.
get(), inputs, outputs),
1775 "could not create a deconvolution forward bias primitive");
1782 mkldnn_primitive_t result;
1786 "deconvolution forward");
1788 aprimitive_desc.
get(), inputs, outputs),
1789 "could not create a deconvolution forward primitive");
1810 &weights_desc.
data, &diff_dst_desc.
data,
1811 &strides[0], &padding_l[0], &padding_r[0],
1813 "could not create a deconvolution backward data descriptor");
1830 &weights_desc.
data, &diff_dst_desc.
data,
1831 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1833 "could not create a dilated deconvolution backward data descriptor");
1853 const memory &diff_src) {
1854 mkldnn_primitive_t result;
1858 "deconvolution backward data");
1860 aprimitive_desc.
get(), inputs, outputs),
1861 "could not create a deconvolution backward data primitive");
1883 &diff_weights_desc.
data, &diff_bias_desc.
data,
1884 &diff_dst_desc.
data,
1885 &strides[0], &padding_l[0], &padding_r[0],
1887 "could not create a deconvolution backward weights descriptor");
1902 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1903 &strides[0], &padding_l[0], &padding_r[0],
1905 "could not create a deconvolution backward weights descriptor");
1923 &diff_weights_desc.
data, &diff_bias_desc.
data,
1924 &diff_dst_desc.
data,
1925 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1927 "could not create a dilated deconvolution backward weights descriptor");
1944 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1945 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1947 "could not create a dilated deconvolution backward weights descriptor");
1969 mkldnn_primitive_t result;
1974 "deconvolution backward weights");
1976 aprimitive_desc.
get(), inputs, outputs),
1977 "could not create a deconvolution backward weights primitive");
1982 const memory &diff_weights) {
1983 mkldnn_primitive_t result;
1987 "deconvolution backward weights");
1989 aprimitive_desc.
get(), inputs, outputs),
1990 "could not create a deconvolution backward weights primitive");
2009 int local_size,
float alpha,
float beta,
float k)
2013 &src_desc.
data, local_size, alpha, beta, k),
2014 "could not create a lrn forward descriptor");
2018 int local_size,
float alpha,
float beta)
2022 &src_desc.
data, local_size, alpha, beta,
float(1.0)),
2023 "could not create a lrn forward descriptor");
2042 mkldnn_primitive_t result;
2048 aprimitive_desc.
get(), inputs, outputs),
2049 "could not create a lrn forward primitive");
2055 mkldnn_primitive_t result;
2060 aprimitive_desc.
get(), inputs, outputs),
2061 "could not create a lrn forward primitive");
2072 int local_size,
float alpha,
float beta,
float k)
2076 &data_desc.
data, local_size, alpha, beta, k),
2077 "could not create a lrn backward descriptor");
2082 int local_size,
float alpha,
float beta)
2086 &data_desc.
data, local_size, alpha, beta,
float(1.0)),
2087 "could not create a lrn backward descriptor");
2108 mkldnn_primitive_t result;
2114 aprimitive_desc.
get(), inputs, outputs),
2115 "could not create a lrn backward primitive");
2121 const memory &diff_src) {
2122 mkldnn_primitive_t result;
2127 aprimitive_desc.
get(), inputs, outputs),
2128 "could not create a lrn backward primitive");
2160 &strides[0], &kernel[0],
2161 &padding_l[0], &padding_r[0],
2163 "could not init a forward pooling descriptor");
2181 mkldnn_primitive_t result;
2186 aprimitive_desc.
get(), inputs, outputs),
2187 "could not create a pooling forward primitive");
2193 mkldnn_primitive_t result;
2198 aprimitive_desc.
get(), inputs, outputs),
2199 "could not create a pooling forward primitive");
2221 &diff_src_desc.
data, &diff_dst_desc.
data,
2222 &strides[0], &kernel[0],
2223 &padding_l[0], &padding_r[0],
2225 "could not init a backward pooling descriptor");
2244 const memory &diff_src) {
2245 mkldnn_primitive_t result;
2250 aprimitive_desc.
get(), inputs, outputs),
2251 "could not create a pooling backward primitive");
2257 mkldnn_primitive_t result;
2262 aprimitive_desc.
get(), inputs, outputs),
2263 "could not create a pooling backward primitive");
2280 template <
typename T>
2282 const memory::desc &src_desc, T alpha = 0, T beta = 0) {
2286 static_cast<float>(alpha), static_cast<float>(beta)),
2287 "could not create a eltwise forward descriptor");
2304 mkldnn_primitive_t result;
2309 aprimitive_desc.
get(), inputs, outputs),
2310 "could not create a eltwise forward primitive");
2319 template <
typename T>
2321 const memory::desc &data_desc, T alpha = 0, T beta = 0) {
2324 &data_desc.
data, static_cast<float>(alpha),
2325 static_cast<float>(beta)),
2326 "could not create a eltwise backward descriptor");
2346 const memory &diff_src) {
2347 mkldnn_primitive_t result;
2352 aprimitive_desc.
get(), inputs, outputs),
2353 "could not create a eltwise backward primitive");
2374 "could not create a softmax forward descriptor");
2391 mkldnn_primitive_t result;
2396 aprimitive_desc.
get(), inputs, outputs),
2397 "could not create a softmax forward primitive");
2408 &diff_desc.
data, &data_desc.
data, softmax_axis),
2409 "could not init a backward softmax descriptor");
2430 const memory &diff_src) {
2431 mkldnn_primitive_t result;
2435 aprimitive_desc.
get(), inputs, outputs),
2436 "could not create a softmax backward primitive");
2452 template <
typename T>
2458 static_cast<float>(epsilon), flags),
2459 "could not create a batch normalization forward descriptor");
2476 {
return stat_primitive_desc(mean); }
2478 {
return stat_primitive_desc(var); }
2481 enum { mean = 1, var = 2, };
2486 "could not get a batch-normalization descriptor");
2495 mkldnn_primitive_t result;
2500 "batch normalization forward");
2502 aprimitive_desc.
get(), inputs, outputs),
2503 "could not create a batch normalization forward primitive");
2510 mkldnn_primitive_t result;
2515 "batch normalization forward");
2517 aprimitive_desc.
get(), inputs, outputs),
2518 "could not create a batch normalization forward primitive");
2532 mkldnn_primitive_t result;
2535 mean.
get(), variance.
get() };
2537 "batch normalization forward");
2539 aprimitive_desc.
get(), inputs, outputs),
2540 "could not create a batch normalization forward primitive");
2547 const memory &workspace) {
2548 mkldnn_primitive_t result;
2551 mean.
get(), variance.
get(), workspace.
get() };
2553 "batch normalization forward");
2555 aprimitive_desc.
get(), inputs, outputs),
2556 "could not create a batch normalization forward primitive");
2562 const memory &variance) {
2563 mkldnn_primitive_t result;
2566 mean.
get(), variance.
get() };
2568 "batch normalization forward");
2570 aprimitive_desc.
get(), inputs, outputs),
2571 "could not create a batch normalization forward primitive");
2589 mkldnn_primitive_t result;
2592 mean.
get(), variance.
get(), workspace.
get() };
2599 if (n_inputs_expected == 2 && n_outputs_expected == 3) {
2601 auto _weights = dst;
2602 inputs[1] = {_weights.get(), 0};
2604 auto _dst = mean, _mean = variance, _variance = workspace;
2605 outputs[0] = _dst.get();
2606 outputs[1] = _mean.get();
2607 outputs[2] = _variance.get();
2608 outputs[3] =
nullptr;
2612 aprimitive_desc.
get(), inputs, outputs),
2613 "could not create a batch normalization forward primitive");
2620 mkldnn_primitive_t result;
2624 "batch normalization forward");
2626 aprimitive_desc.
get(), inputs, outputs),
2627 "could not create a batch normalization forward primitive");
2633 mkldnn_primitive_t result;
2637 "batch normalization forward");
2639 aprimitive_desc.
get(), inputs, outputs),
2640 "could not create a batch normalization forward primitive");
2648 template <
typename T>
2650 const memory::desc &data_desc, T epsilon,
unsigned flags) {
2654 &diff_data_desc.
data, &data_desc.
data,
2655 static_cast<float>(epsilon), flags),
2656 "could not create a batch normalization backward descriptor");
2686 const memory &diff_weights) {
2687 mkldnn_primitive_t result;
2691 diff_weights.
get() };
2693 "batch normalization backward");
2695 aprimitive_desc.
get(), inputs, outputs),
2696 "could not create a batch normalization backward primitive");
2706 mkldnn_primitive_t result;
2710 diff_weights.
get() };
2712 "batch normalization backward");
2714 aprimitive_desc.
get(), inputs, outputs),
2715 "could not create a batch normalization backward primitive");
2727 mkldnn_primitive_t result;
2729 diff_dst.
data, weights_or_workspace.
data };
2732 "batch normalization backward");
2734 aprimitive_desc.
get(), inputs, outputs),
2735 "could not create a batch normalization backward primitive");
2743 const memory &diff_src) {
2744 mkldnn_primitive_t result;
2749 "batch normalization backward");
2751 aprimitive_desc.
get(), inputs, outputs),
2752 "could not create a batch normalization backward primitive");
2776 "could not create a inner product forward descriptor");
2785 &weights_desc.
data,
nullptr, &dst_desc.
data),
2786 "could not create a inner product forward descriptor");
2806 mkldnn_primitive_t result;
2811 "inner product forward");
2813 aprimitive_desc.
get(), inputs, outputs),
2814 "could not create a inner product forward primitive");
2821 mkldnn_primitive_t result;
2825 "inner product forward");
2827 aprimitive_desc.
get(), inputs, outputs),
2828 "could not create a inner product forward primitive");
2841 &diff_src_desc.
data, &weights_desc.
data,
2842 &diff_dst_desc.
data),
2843 "could not create a inner product backward data descriptor");
2863 const memory &diff_src) {
2864 mkldnn_primitive_t result;
2868 "inner product backward data");
2870 aprimitive_desc.
get(), inputs, outputs),
2871 "could not create a inner product backward data primitive");
2885 &data, &src_desc.
data, &diff_weights_desc.
data,
2886 &diff_bias_desc.
data, &diff_dst_desc.
data),
2887 "could not create a inner product backward weights descriptor");
2894 &data, &src_desc.
data, &diff_weights_desc.
data,
2895 nullptr, &diff_dst_desc.
data),
2896 "could not create a inner product backward weights descriptor");
2917 const memory &diff_weights) {
2918 mkldnn_primitive_t result;
2922 "inner product backward weights");
2924 aprimitive_desc.
get(), inputs, outputs),
2925 "could not create a inner product backward weights primitive");
2932 mkldnn_primitive_t result;
2935 { diff_weights.
get(), diff_bias.
get()};
2937 "inner product backward weights");
2939 aprimitive_desc.
get(), inputs, outputs),
2940 "could not create a inner product backward weights primitive");
2961 "could not init an rnn cell descriptor");
2975 c_rnn_cell_.
alpha = alpha;
3009 &src_layer_desc.
data, &src_iter_desc.
data,
3010 &weights_layer_desc.
data, &weights_iter_desc.
data,
3012 &dst_layer_desc.
data, &dst_iter_desc.
data),
3013 "could not create an RNN forward descriptor");
3040 const memory &workspace) {
3041 mkldnn_primitive_t result;
3045 inputs[idx++] = src_layer.
data;
3047 inputs[idx++] = src_iter.
data;
3048 inputs[idx++] = weights_layer.
data;
3049 inputs[idx++] = weights_iter.
data;
3053 outputs[idx++] = dst_layer.
get();
3058 aprimitive_desc.
get(), inputs, outputs),
3059 "could not create an RNN forward primitive");
3086 &src_layer_desc.
data, &src_iter_desc.
data,
3087 &weights_layer_desc.
data, &weights_iter_desc.
data,
3089 &dst_layer_desc.
data, &dst_iter_desc.
data,
3090 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
3091 &diff_weights_layer_desc.
data,
3092 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
3093 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data),
3094 "could not create an RNN backward descriptor");
3135 const memory &diff_src_layer,
3136 const memory &diff_src_iter,
3137 const memory &diff_weights_layer,
3138 const memory &diff_weights_iter,
3143 mkldnn_primitive_t result;
3147 inputs[idx++] = src_layer.
data;
3149 inputs[idx++] = src_iter.
data;
3150 inputs[idx++] = weights_layer.
data;
3151 inputs[idx++] = weights_iter.
data;
3153 inputs[idx++] = bias.
data;
3154 inputs[idx++] = dst_layer.
data;
3156 inputs[idx++] = dst_iter.
data;
3157 inputs[idx++] = diff_dst_layer.
data;
3159 inputs[idx++] = diff_dst_iter.
data;
3160 inputs[idx++] = workspace.
data;
3163 outputs[idx++] = diff_src_layer.
get();
3165 outputs[idx++] = diff_src_iter.
get();
3166 outputs[idx++] = diff_weights_layer.
get();
3167 outputs[idx++] = diff_weights_iter.
get();
3170 aprimitive_desc.
get(), inputs, outputs),
3171 "could not create an RNN backward primitive");
3188 int axis,
int group_size) {
3192 "could not create a shuffle forward descriptor");
3206 mkldnn_primitive_t result;
3211 aprimitive_desc.
get(), inputs, outputs),
3212 "could not create a shuffle forward primitive");
3222 &diff_data_desc.
data, axis, group_size),
3223 "could not create a shuffle backward descriptor");
3238 mkldnn_primitive_t result;
3243 aprimitive_desc.
get(), inputs, outputs),
3244 "could not create a shuffle backward primitive");
3259 #ifndef DOXYGEN_SHOULD_SKIP_THIS 3266 using handle::handle;
3277 mkldnn_stream_t astream;
3280 "could not create a stream");
3291 if (primitives.size() == 0)
return *
this;
3292 std::vector<mkldnn_primitive_t> c_api_primitives;
3293 c_api_primitives.reserve(primitives.size());
3295 std::transform(primitives.begin(), primitives.end(),
3298 mkldnn_primitive_t c_api_error_primitive;
3301 c_api_primitives.size(), &c_api_primitives[0],
3302 &c_api_error_primitive),
3303 "could not submit primitives to a stream",
3304 &c_api_error_primitive);
3316 mkldnn_primitive_t c_api_error_primitive;
3318 block, &c_api_error_primitive);
3322 &c_api_error_primitive);
3327 mkldnn_primitive_t c_api_error_primitive;
3330 "could not rerun a stream", &c_api_error_primitive);
3335 #undef REG_QUERY_MPD void append_sum(float scale=1.)
Definition: mkldnn.hpp:385
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2379
Definition: mkldnn.hpp:2330
LRN within a single channel.
Definition: mkldnn_types.h:484
primitive error_primitive
Definition: mkldnn.hpp:164
A descriptor of a Local Response Normalization (LRN) operation.
Definition: mkldnn_types.h:822
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1478
Definition: mkldnn.hpp:342
blocked weights format
Definition: mkldnn_types.h:306
inner_product_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at weights, const memory &dst)
Definition: mkldnn.hpp:2818
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2171
Definition: mkldnn.hpp:269
std::vector< const_mkldnn_primitive_desc_t > cpp_to_c(std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1060
blocked weights format
Definition: mkldnn_types.h:309
op descriptor
Definition: mkldnn_types.h:1164
primitive_desc(const memory::desc &output, int concat_dimension, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1070
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1621
mkldnn_status_t MKLDNN_API mkldnn_convolution_backward_weights_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *diff_weights_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a convolution descriptor conv_desc for backward propagation with respect to weights using...
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:333
Definition: mkldnn.hpp:3064
blocked weights format
Definition: mkldnn_types.h:293
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_destroy(mkldnn_primitive_attr_t attr)
Deletes an attr.
blocked weights format
Definition: mkldnn_types.h:355
mkldnn_status_t MKLDNN_API mkldnn_sum_primitive_desc_create(mkldnn_primitive_desc_t *sum_primitive_desc, const mkldnn_memory_desc_t *output_desc, int n, const float *scales, const_mkldnn_primitive_desc_t *input_pds)
Creates out-of-place sum_primitive_desc for sum of n inputs multiplied by scale with resulting output...
Definition: mkldnn.hpp:257
A Softmax primitive.
Definition: mkldnn_types.h:428
number of outputs expected
Definition: mkldnn_types.h:1153
bool operator!=(const handle &other) const
Definition: mkldnn.hpp:88
mkldnn_status_t MKLDNN_API mkldnn_stream_destroy(mkldnn_stream_t stream)
Destroys an execution stream.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:3022
convolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights, const memory &diff_bias)
Definition: mkldnn.hpp:1631
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:2491
stream & submit(std::vector< primitive > primitives)
Submits a vector of primitives to a stream for computations.
Definition: mkldnn.hpp:3288
bool operator==(const primitive_desc &other) const
Definition: mkldnn.hpp:778
A base class for all primitive descriptors.
Definition: mkldnn.hpp:1227
Definition: mkldnn.hpp:2204
mkldnn_status_t
Status values returned by Intel(R) MKL-DNN functions.
Definition: mkldnn_types.h:39
stream & rerun()
Definition: mkldnn.hpp:3326
Definition: mkldnn.hpp:2167
A descriptor of a convolution operation.
Definition: mkldnn_types.h:675
Definition: mkldnn.hpp:300
desc(prop_kind aprop_kind, const memory::desc &data_desc, int axis, int group_size)
Definition: mkldnn.hpp:3187
Definition: mkldnn.hpp:2142
The operation failed and should be retried.
Definition: mkldnn_types.h:45
memory null_memory(engine eng)
Definition: mkldnn.hpp:874
mkldnn_status_t MKLDNN_API mkldnn_memory_primitive_desc_create(mkldnn_primitive_desc_t *memory_primitive_desc, const mkldnn_memory_desc_t *memory_desc, mkldnn_engine_t engine)
Creates a memory_primitive_desc memory primitive descriptor using memory_desc and engine...
Definition: mkldnn.hpp:1951
blocked weights format
Definition: mkldnn_types.h:265
mkldnn_status_t MKLDNN_API mkldnn_post_ops_create(mkldnn_post_ops_t *post_ops)
Creates an empty sequence of post operations post_ops.
Definition: mkldnn.hpp:329
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_destroy(mkldnn_primitive_desc_t primitive_desc)
Deletes a primitive_desc.
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1571
mkldnn_status_t MKLDNN_API mkldnn_concat_primitive_desc_create(mkldnn_primitive_desc_t *concat_primitive_desc, const mkldnn_memory_desc_t *output_desc, int n, int concat_dimension, const_mkldnn_primitive_desc_t *input_pds)
Creates out-of-place concat_primitive_desc for concatenation of n inputs by concat_dimension with res...
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: mkldnn_types.h:245
4D data tensor with the physical layout chwn, used in Neon.
Definition: mkldnn_types.h:163
Definition: mkldnn.hpp:265
padding_kind
Definition: mkldnn.hpp:232
The operation failed because of incorrect function arguments.
Definition: mkldnn_types.h:47
Forward data propagation (alias for mkldnn_forward_inference)
Definition: mkldnn_types.h:389
Definition: mkldnn.hpp:2005
Definition: mkldnn.hpp:1867
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1533
Definition: mkldnn.hpp:2790
Backward data propagation.
Definition: mkldnn_types.h:395
Definition: mkldnn.hpp:2403
static void validate_dims(std::vector< T > v)
Definition: mkldnn.hpp:586
Definition: mkldnn.hpp:3227
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_get_attr(const_mkldnn_primitive_desc_t primitive_desc, const_mkldnn_primitive_attr_t *attr)
Returns a constant reference to the attribute of a primitive_desc.
Definition: mkldnn.hpp:3217
mkldnn_status_t MKLDNN_API mkldnn_memory_desc_init(mkldnn_memory_desc_t *memory_desc, int ndims, const mkldnn_dims_t dims, mkldnn_data_type_t data_type, mkldnn_memory_format_t format)
Initializes a memory_desc memory descriptor using ndims, dims, data_type, and data format...
desc(prop_kind aprop_kind, const memory::desc &data_desc, int softmax_axis)
Definition: mkldnn.hpp:2369
Definition: mkldnn.hpp:274
blocked weights format
Definition: mkldnn_types.h:289
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:137
const_mkldnn_primitive_desc_t get_primitive_desc() const
Returns the descriptor of the underlying C API primitive.
Definition: mkldnn.hpp:210
concat(const primitive_desc &concat_pd, std::vector< primitive::at > &inputs, const memory &output)
Definition: mkldnn.hpp:1111
memory::desc desc()
Returns the memory primitive descriptor.
Definition: mkldnn.hpp:768
deconvolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights, const memory &diff_bias)
Definition: mkldnn.hpp:1966
mkldnn_status_t MKLDNN_API mkldnn_dilated_convolution_backward_weights_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *diff_weights_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a convolution descriptor conv_desc for backward propagation with respect to weights using...
float alpha
alpha is a negative slope parameter (used only if (flags & mkldnn_rnn_cell_with_relu) != 0) ...
Definition: mkldnn_types.h:926
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_clone(mkldnn_primitive_attr_t *attr, const_mkldnn_primitive_attr_t existing_attr)
Makes a copy of an existing_attr.
#define TENSOR_MAX_DIMS
Maximum number of dimensions a tensor can have.
Definition: mkldnn_types.h:549
format
Memory format specification. See mkldnn_memory_format_t for a detailed description.
Definition: mkldnn.hpp:605
Definition: mkldnn.hpp:290
4D weights tensor with physical layout oihw, used in Caffe.
Definition: mkldnn_types.h:184
A descriptor of a Softmax operation.
Definition: mkldnn_types.h:772
blocked weights format
Definition: mkldnn_types.h:358
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_clone(mkldnn_primitive_desc_t *primitive_desc, const_mkldnn_primitive_desc_t existing_primitive_desc)
Makes a copy of a primitive_desc.
softmax_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2389
blocked weights format
Definition: mkldnn_types.h:359
blocked data format
Definition: mkldnn_types.h:252
mkldnn_status_t MKLDNN_API mkldnn_memory_get_data_handle(const_mkldnn_primitive_t memory, void **handle)
For a memory primitive, returns the data handle.
Definition: mkldnn.hpp:244
mkldnn_status_t MKLDNN_API mkldnn_convolution_backward_data_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a convolution descriptor conv_desc for backward propagation with respect to data using al...
A descriptor of an inner product operation.
Definition: mkldnn_types.h:880
mkldnn_status_t MKLDNN_API mkldnn_post_ops_destroy(mkldnn_post_ops_t post_ops)
Deletes a post_ops sequence.
std::vector< std::remove_extent< mkldnn_dims_t >::type > dims
Definition: mkldnn.hpp:584
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: mkldnn_types.h:221
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:3197
An opaque structure for a chain of post operations.
An opaque structure to describe a primitive descriptor .
batch normalization descriptor
Definition: mkldnn_types.h:1173
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1690
mkldnn_rnn_direction_t
A direction of RNN primitive execution.
Definition: mkldnn_types.h:933
void reset(T t, bool weak=false)
Resets the value of a C handle.
Definition: mkldnn.hpp:79
A convolution primitive.
Definition: mkldnn_types.h:422
primitive_desc(const desc &desc, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1838
mkldnn_lrn_desc_t data
Definition: mkldnn.hpp:2068
mkldnn_status_t MKLDNN_API mkldnn_memory_set_data_handle(mkldnn_primitive_t memory, void *handle)
For a memory primitive, sets the data handle.
engine(const mkldnn_engine_t &aengine)
Definition: mkldnn.hpp:538
engine(const handle< mkldnn_primitive_desc_t > &pd)
Definition: mkldnn.hpp:541
engine get_engine()
Definition: mkldnn.hpp:1240
desc(dims adims, data_type adata_type, format aformat)
Constructs a memory descriptor.
Definition: mkldnn.hpp:734
blocked data format
Definition: mkldnn_types.h:253
mkldnn_status_t MKLDNN_API mkldnn_batch_normalization_forward_desc_init(mkldnn_batch_normalization_desc_t *bnrm_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a batch normalization descriptor bnrm_desc for forward propagation using prop_kind...
Definition: mkldnn.hpp:225
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2767
sum(const primitive_desc &sum_pd, std::vector< primitive::at > &inputs, const memory &output)
Definition: mkldnn.hpp:1200
An execution engine.
Definition: mkldnn.hpp:503
memory(const primitive_desc &adesc, void *ahandle)
Definition: mkldnn.hpp:824
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2835
mkldnn_status_t MKLDNN_API mkldnn_post_ops_append_eltwise(mkldnn_post_ops_t post_ops, float scale, mkldnn_alg_kind_t alg, float alpha, float beta)
Appends eltwise post operation to the post_ops with given parameters kind, alpha and beta (...
static void wrap_c_api(mkldnn_status_t status, const std::string &message, mkldnn_primitive_t *error_primitive=0)
A convenience function for wrapping calls to the C API. Checks the return status and throws an error ...
Definition: mkldnn.hpp:188
mkldnn_pooling_desc_t data
Definition: mkldnn.hpp:2206
Undefined primitive (XXX: why do we have it?).
Definition: mkldnn_types.h:406
mkldnn_status_t MKLDNN_API mkldnn_deconvolution_backward_data_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a deconvolution descriptor conv_desc for backward propagation with respect to data using ...
An inner product primitive.
Definition: mkldnn_types.h:436
Packed weights format used in RNN.
Definition: mkldnn_types.h:363
void check_num_parameters(const const_mkldnn_primitive_desc_t &aprimitive_desc, int n_inputs, int n_outputs, const std::string &prim_name)
Definition: mkldnn.hpp:879
Round down.
Definition: mkldnn_types.h:82
4D grouped weights tensor with the physical layout goiw.
Definition: mkldnn_types.h:202
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const softmax_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2418
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1708
Definition: mkldnn.hpp:264
round_mode get_int_output_round_mode() const
Definition: mkldnn.hpp:426
primitive_attr()
Definition: mkldnn.hpp:419
Definition: mkldnn_types.h:480
Definition: mkldnn.hpp:2315
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_set_rnn_weights_qparams(mkldnn_primitive_attr_t attr, int count, int mask, const float *weights_scales)
Sets quantization scales weights_scales for RNN weights tensors.
mkldnn_primitive_at_t MKLDNN_API mkldnn_primitive_at(const_mkldnn_primitive_t primitive, size_t output_index)
Creates an mkldnn_primitive_at_t structure from a primitive and output_index.
primitive_desc(const desc &desc, const engine &e, const softmax_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2414
mkldnn_softmax_desc_t data
Definition: mkldnn.hpp:2404
Definition: mkldnn.hpp:2378
void get_params_sum(int index, float &scale) const
Definition: mkldnn.hpp:390
Definition: mkldnn.hpp:247
32-bit signed integer.
Definition: mkldnn_types.h:68
primitive_desc(const desc &desc, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2848
Max pooling.
Definition: mkldnn_types.h:475
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1392
memory::desc zero_md()
Definition: mkldnn.hpp:868
Definition: mkldnn.hpp:336
primitive_desc(const memory::primitive_desc &input, memory::dims dims, memory::dims offsets)
Definition: mkldnn.hpp:1003
mkldnn_status_t MKLDNN_API mkldnn_softmax_forward_desc_init(mkldnn_softmax_desc_t *softmax_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *data_desc, int softmax_axis)
Initializes a softmax_desc for forward propagation using prop_kind (possible value are mkldnn_forward...
blocked weights format
Definition: mkldnn_types.h:279
const post_ops get_post_ops() const
Definition: mkldnn.hpp:460
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims kernel, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:2144
execution engine
Definition: mkldnn_types.h:1149
stream(kind akind)
Constructs a stream.
Definition: mkldnn.hpp:3276
Definition: mkldnn.hpp:1002
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_iterator_next(mkldnn_primitive_desc_iterator_t iterator)
Iterates over primitive descriptors.
Definition: mkldnn.hpp:335
desc(const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc)
Definition: mkldnn.hpp:2836
mkldnn_status_t MKLDNN_API mkldnn_pooling_backward_desc_init(mkldnn_pooling_desc_t *pool_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t kernel, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a pooling descriptor pool_desc for backward propagation using alg_kind, memory descriptors, and pooling parameters in spatial domain: strides, kernel sizes, padding_l, padding_r, and padding_kind.
Definition: mkldnn.hpp:2141
blocked weights format
Definition: mkldnn_types.h:286
static mkldnn_memory_format_t convert_to_c(format aformat)
Definition: mkldnn.hpp:863
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const eltwise_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2335
Definition: mkldnn.hpp:2660
Definition: mkldnn.hpp:320
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_create(mkldnn_primitive_attr_t *attr)
Creates an empty (default) attr attribute.
Definition: mkldnn_types.h:911
mkldnn_status_t MKLDNN_API mkldnn_stream_submit(mkldnn_stream_t stream, size_t n, mkldnn_primitive_t primitives[], mkldnn_primitive_t *error_primitive)
Submits primitives to an execution stream.
algorithm
Definition: mkldnn.hpp:255
input memory primitive desc
Definition: mkldnn_types.h:1179
blocked weights format
Definition: mkldnn_types.h:300
mkldnn_shuffle_desc_t data
Definition: mkldnn.hpp:3186
5D grouped weights tensor with the physical layout goihw, used in Caffe.
Definition: mkldnn_types.h:206
const_mkldnn_primitive_t primitive
Primitive to specify the output for.
Definition: mkldnn_types.h:1109
Definition: mkldnn.hpp:289
rnn_forward(const primitive_desc &aprimitive_desc, const primitive::at &src_layer, const primitive::at &src_iter, const primitive::at &weights_layer, const primitive::at &weights_iter, const primitive::at &bias, const memory &dst_layer, const memory &dst_iter, const memory &workspace)
Definition: mkldnn.hpp:3035
mkldnn_status_t MKLDNN_API mkldnn_rnn_cell_desc_init(mkldnn_rnn_cell_desc_t *rnn_cell_desc, mkldnn_alg_kind_t kind, mkldnn_alg_kind_t f, unsigned int flags, float alpha, float clipping)
Initializes a recurrent cell descriptor rnn_cell_desc using rnn_cell_desc, kind (possible values are ...
A descriptor of a element-wise operation.
Definition: mkldnn_types.h:737
rnn descriptor
Definition: mkldnn_types.h:1175
memory::primitive_desc variance_primitive_desc() const
Definition: mkldnn.hpp:2477
An element-wise primitive.
Definition: mkldnn_types.h:426
Definition: mkldnn.hpp:2847
Definition: mkldnn.hpp:2402
destination grad.
Definition: mkldnn_types.h:1186
algorithm get_cell_kind() const
Definition: mkldnn.hpp:2967
engine get_engine()
Definition: mkldnn.hpp:1197
Definition: mkldnn.hpp:2316
mkldnn_status_t MKLDNN_API mkldnn_stream_wait(mkldnn_stream_t stream, int block, mkldnn_primitive_t *error_primitive)
Waits for all primitives in the execution stream to finish.
mkldnn_alg_kind_t activation_kind
Activation function used.
Definition: mkldnn_types.h:921
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1184
blocked weights format
Definition: mkldnn_types.h:303
A descriptor for an rnn operation.
Definition: mkldnn_types.h:948
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1369
Definition: mkldnn.hpp:1058
Definition: mkldnn.hpp:277
Definition: mkldnn.hpp:259
eltwise descriptor
Definition: mkldnn_types.h:1169
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst, const memory &mean, const memory &variance, const memory &workspace)
Definition: mkldnn.hpp:2586
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:1417
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_set_rnn_data_qparams(mkldnn_primitive_attr_t attr, const float scale, const float shift)
Sets quantization scale and shift for RNN data tensors.
Definition: mkldnn.hpp:276
batch_normalization_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const primitive::at &diff_dst, const primitive::at &weights_or_workspace, const memory &diff_src)
Definition: mkldnn.hpp:2723
lrn_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2053
size_t MKLDNN_API mkldnn_engine_get_count(mkldnn_engine_kind_t kind)
Returns the number of engines of a particular kind.
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc)
Definition: mkldnn.hpp:2879
batch_normalization_flag
Definition: mkldnn.hpp:288
A memory primitive.
Definition: mkldnn_types.h:408
float clipping
clipping parameter (used only if (flags & mkldnn_rnn_cell_with_clipping) != 0)
Definition: mkldnn_types.h:929
blocked weights format
Definition: mkldnn_types.h:288
desc(prop_kind aprop_kind, rnn_cell::desc cell, const 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)
Definition: mkldnn.hpp:3067
Eltwise: soft_relu.
Definition: mkldnn_types.h:471
Definition: mkldnn.hpp:1501
void set_post_ops(post_ops ops)
Definition: mkldnn.hpp:469
inner_product_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at weights, const primitive::at &bias, const memory &dst)
Definition: mkldnn.hpp:2803
Definition: mkldnn.hpp:341
Definition: mkldnn.hpp:261
mkldnn_primitive_kind_t MKLDNN_API mkldnn_post_ops_get_kind(const_mkldnn_post_ops_t post_ops, int index)
Returns the type of post operation with index index in given post_ops.
RNN cell.
Definition: mkldnn_types.h:486
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2168
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1729
bool is_null_memory(const const_mkldnn_primitive_t &aprimitive)
Definition: mkldnn.hpp:899
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2852
Definition: mkldnn.hpp:367
Definition: mkldnn.hpp:2834
blocked weights format
Definition: mkldnn_types.h:315
bool operator==(const handle &other) const
Definition: mkldnn.hpp:87
Definition: mkldnn.hpp:1329
Backward weights propagation.
Definition: mkldnn_types.h:397
void set_int_output_round_mode(round_mode mode)
Definition: mkldnn.hpp:433
mkldnn_rnn_desc_t data
Definition: mkldnn.hpp:2995
blocked weights format
Definition: mkldnn_types.h:354
32-bit/single-precision floating point.
Definition: mkldnn_types.h:66
blocked weights format
Definition: mkldnn_types.h:262
blocked data format
Definition: mkldnn_types.h:251
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1553
algorithm get_activation() const
Definition: mkldnn.hpp:2969
pooling_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2179
2D weights tensor with physical layout oi.
Definition: mkldnn_types.h:172
Just a sentinel, not real memory format.
Definition: mkldnn_types.h:367
Memory descriptor.
Definition: mkldnn_types.h:634
Definition: mkldnn.hpp:2766
Definition: mkldnn.hpp:303
mkldnn_status_t MKLDNN_API mkldnn_inner_product_backward_data_desc_init(mkldnn_inner_product_desc_t *ip_desc, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *diff_dst_desc)
Initializes an inner product descriptor ip_desc for backward propagation with respect to data using m...
Base class for all computational primitives.
Definition: mkldnn.hpp:106
shuffle_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:3204
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve.
Definition: mkldnn_types.h:503
void set_clipping(float clipping)
Definition: mkldnn.hpp:2979
convolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights)
Definition: mkldnn.hpp:1645
mkldnn_lrn_desc_t data
Definition: mkldnn.hpp:2006
Definition: mkldnn.hpp:2765
desc(prop_kind aprop_kind, const memory::desc &src_desc, T epsilon, unsigned flags)
Definition: mkldnn.hpp:2453
Definition: mkldnn.hpp:280
pooling descriptor
Definition: mkldnn_types.h:1171
Definition: mkldnn.hpp:2205
const mkldnn_memory_desc_t MKLDNN_API * mkldnn_primitive_desc_query_memory_d(const_mkldnn_primitive_desc_t primitive_desc)
Queries primitive descriptor for memory descriptor.
prop_kind
Definition: mkldnn.hpp:240
mkldnn_pooling_desc_t data
Definition: mkldnn.hpp:2143
Definition: mkldnn.hpp:267
blocked weights format
Definition: mkldnn_types.h:261
3D weights tensor with physical layout wio.
Definition: mkldnn_types.h:181
blocked weights format
Definition: mkldnn_types.h:314
mkldnn_status_t MKLDNN_API mkldnn_dilated_deconvolution_forward_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a dilated deconvolution descriptor deconv_desc for forward propagation using prop_kind (p...
unsigned int flags
RNN cell flags.
Definition: mkldnn_types.h:923
3D data tensor with the physical layout ncw.
Definition: mkldnn_types.h:151
blocked weights format
Definition: mkldnn_types.h:291
convolution_backward_data(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &weights, const memory &diff_src)
Definition: mkldnn.hpp:1515
The operation was successful.
Definition: mkldnn_types.h:41
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:348
mkldnn_status_t MKLDNN_API mkldnn_engine_create(mkldnn_engine_t *engine, mkldnn_engine_kind_t kind, size_t index)
Creates an engine of particular kind and index.
blocked weights format
Definition: mkldnn_types.h:326
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2905
primitive_desc(const desc &desc, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1617
desc(algorithm kind, algorithm activation_f)
Definition: mkldnn.hpp:2957
blocked weights format
Definition: mkldnn_types.h:334
Definition: mkldnn.hpp:326
Definition: mkldnn.hpp:245
primitive_desc(const_mkldnn_op_desc_t desc, const primitive_attr *attr, const engine &e, const_mkldnn_primitive_desc_t hint_fwd_pd)
Definition: mkldnn.hpp:1228
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_get_int_output_round_mode(const_mkldnn_primitive_attr_t attr, mkldnn_round_mode_t *round_mode)
Returns integer output rounding mode round_mode for a given attr, previously set by mkldnn_primitive_...
blocked weights format
Definition: mkldnn_types.h:352
mkldnn_rnn_desc_t data
Definition: mkldnn.hpp:3066
Backward propagation (with respect to all parameters.
Definition: mkldnn_types.h:393
5D data tensor with the physical layout ndhwc, used in TensorFlow.
Definition: mkldnn_types.h:169
inner_product_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at diff_dst, const memory &diff_weights, const memory &diff_bias)
Definition: mkldnn.hpp:2929
softmax descriptor
Definition: mkldnn_types.h:1170
mkldnn_round_mode_t
Rounding mode.
Definition: mkldnn_types.h:78
A deconvolution primitive.
Definition: mkldnn_types.h:424
Definition: mkldnn.hpp:330
Definition: mkldnn.hpp:275
primitive_desc(const desc &adesc, const engine &aengine)
Constructs a memory primitive descriptor.
Definition: mkldnn.hpp:758
Use global statistics.
Definition: mkldnn_types.h:516
Definition: mkldnn.hpp:31
primitive_desc(int concat_dimension, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1083
blocked weights format
Definition: mkldnn_types.h:292
no query
Definition: mkldnn_types.h:1147
Definition: mkldnn.hpp:2877
Definition: mkldnn.hpp:1669
blocked weights format
Definition: mkldnn_types.h:341
blocked weights format
Definition: mkldnn_types.h:304
mkldnn_status_t MKLDNN_API mkldnn_convolution_forward_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a convolution descriptor conv_desc for forward propagation using prop_kind (possible valu...
mkldnn_status_t MKLDNN_API mkldnn_view_primitive_desc_create(mkldnn_primitive_desc_t *view_primitive_desc, const_mkldnn_primitive_desc_t memory_primitive_desc, const mkldnn_dims_t dims, const mkldnn_dims_t offsets)
Creates a view_primitive_desc for a given memory_primitive_desc, with dims sizes and offset offsets...
8-bit unsigned integer.
Definition: mkldnn_types.h:74
Definition: mkldnn.hpp:346
Average pooling include padding.
Definition: mkldnn_types.h:477
Unspecified format.
Definition: mkldnn_types.h:140
inner_product_backward_data(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at weights, const memory &diff_src)
Definition: mkldnn.hpp:2861
Definition: mkldnn.hpp:2027
destination memory primitive desc
Definition: mkldnn_types.h:1185
memory::primitive_desc mean_primitive_desc() const
Definition: mkldnn.hpp:2475
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: mkldnn_types.h:231
GRU cell with linear before reset.
Definition: mkldnn_types.h:499
memory(const primitive_desc &adesc)
Constructs a memory primitive.
Definition: mkldnn.hpp:797
lrn_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const primitive::at &workspace, const memory &diff_src)
Definition: mkldnn.hpp:2105
mkldnn_status_t MKLDNN_API mkldnn_shuffle_forward_desc_init(mkldnn_shuffle_desc_t *shuffle_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *data_desc, int axis, int group_size)
Initializes a shuffle_desc for forward propagation using prop_kind, memory descriptor data_desc...
Local response normalization (LRN) across multiple channels.
Definition: mkldnn_types.h:482
blocked weights format
Definition: mkldnn_types.h:276
GRU cell.
Definition: mkldnn_types.h:490
Eager stream.
Definition: mkldnn_types.h:1200
primitive_desc(const memory::primitive_desc &input, const memory::primitive_desc &output, const primitive_attr &aattr)
Definition: mkldnn.hpp:953
void set_output_scales(int mask, const std::vector< float > &scales)
Definition: mkldnn.hpp:453
at(const primitive &aprimitive, size_t at=0)
Constructs a wrapper specifying aprimitive output with index at.
Definition: mkldnn.hpp:143
implementation name
Definition: mkldnn_types.h:1160
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1907
Definition: mkldnn.hpp:1330
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Definition: mkldnn.hpp:3220
Definition: mkldnn.hpp:3218
Definition: mkldnn.hpp:256
pooling_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2243
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_get_output_scales(const_mkldnn_primitive_attr_t attr, int *count, int *mask, const float **scales)
Returns count, correspondence scale mask, and pointer to a constant floating point array of output sc...
3D weights tensor with physical layout oiw.
Definition: mkldnn_types.h:178
Eltwise: parametric exponential linear unit (elu)
Definition: mkldnn_types.h:459
kind
Kinds of engines.
Definition: mkldnn.hpp:508
Definition: mkldnn.hpp:2067
Definition: mkldnn.hpp:2833
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2382
Intel(R) MKL-DNN exception class.
Definition: mkldnn.hpp:161
round_mode
Definition: mkldnn.hpp:223
bool operator==(mkldnn_data_type_t a, memory::data_type b)
Definition: mkldnn.hpp:908
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1796
Eltwise: ReLU.
Definition: mkldnn_types.h:455
Definition: mkldnn.hpp:2366
mkldnn_convolution_desc_t data
Definition: mkldnn.hpp:1331
Definition: mkldnn.hpp:233
1D data tensor.
Definition: mkldnn_types.h:146
mkldnn_primitive_at_t data
The underlying C API structure.
Definition: mkldnn.hpp:136
memory::primitive_desc query_mpd(query what, int idx=0) const
Queries and returns requested memory primitive descriptor.
Definition: mkldnn.hpp:1281
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const batch_normalization_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2665
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_set_post_ops(mkldnn_primitive_attr_t attr, const_mkldnn_post_ops_t post_ops)
Sets configured post_ops to an attribute attr for future use (when primitive descriptor is being crea...
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const rnn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:3104
primitive_desc(const desc &desc, const engine &e, const shuffle_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:3228
4D weights tensor with physical layout ihwo.
Definition: mkldnn_types.h:190
mkldnn_eltwise_desc_t data
Definition: mkldnn.hpp:2317
mkldnn_memory_format_t
Memory format specification.
Definition: mkldnn_types.h:135
Definition: mkldnn.hpp:1001
Eltwise: square.
Definition: mkldnn_types.h:461
Definition: mkldnn.hpp:1135
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1351
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1013
Definition: mkldnn.hpp:281
mkldnn_status_t MKLDNN_API mkldnn_eltwise_forward_desc_init(mkldnn_eltwise_desc_t *eltwise_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *data_desc, float alpha, float beta)
Initializes a eltwise_desc for forward propagation using prop_kind (possible values are mkldnn_forwar...
int MKLDNN_API mkldnn_memory_primitive_desc_equal(const_mkldnn_primitive_desc_t lhs, const_mkldnn_primitive_desc_t rhs)
Compares two descriptors of memory primitives.
void set_rnn_data_qparams(const float scale, const float shift)
Definition: mkldnn.hpp:474
static mkldnn_data_type_t convert_to_c(data_type adata_type)
Definition: mkldnn.hpp:860
4D data tensor with the physical layout nhwc, used in TensorFlow.
Definition: mkldnn_types.h:160
void set_data_handle(void *handle) const
Definition: mkldnn.hpp:854
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst, const memory &mean, const memory &variance)
Definition: mkldnn.hpp:2560
Definition: mkldnn.hpp:268
desc(algorithm aalgorithm, const memory::desc &data_desc, const memory::desc &diff_data_desc, int local_size, float alpha, float beta, float k)
Definition: mkldnn.hpp:2069
Backward bias propagation.
Definition: mkldnn_types.h:399
Definition: mkldnn.hpp:942
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, int local_size, float alpha, float beta)
Definition: mkldnn.hpp:2016
blocked weights format
Definition: mkldnn_types.h:349
Use scale and shift parameters.
Definition: mkldnn_types.h:529
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1671
mkldnn_status_t MKLDNN_API mkldnn_deconvolution_forward_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a deconvolution descriptor deconv_desc for forward propagation using prop_kind (possible ...
query
Definition: mkldnn.hpp:311
Definition: mkldnn.hpp:279
weights format with additional buffer size equal to the number of output channels multiplied by numbe...
Definition: mkldnn_types.h:325
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_query(const_mkldnn_primitive_desc_t primitive_desc, mkldnn_query_t what, int index, void *result)
Queries primitive descriptor.
float get_alpha() const
Definition: mkldnn.hpp:2972
blocked weights format
Definition: mkldnn_types.h:275
blocked weights format
Definition: mkldnn_types.h:335
A descriptor of a shuffle operation.
Definition: mkldnn_types.h:720
void get_params_eltwise(int index, float &scale, algorithm &alg, float &alpha, float &beta) const
Definition: mkldnn.hpp:402
Definition: mkldnn_types.h:943
mkldnn_status_t MKLDNN_API mkldnn_dilated_deconvolution_backward_weights_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *diff_weights_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a dilated deconvolution descriptor conv_desc for backward propagation with respect to wei...
mkldnn_eltwise_desc_t data
Definition: mkldnn.hpp:2279
primitive_desc(const desc &desc, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1952
Definition: mkldnn.hpp:418
blocked weights format
Definition: mkldnn_types.h:343
blocked weights format
Definition: mkldnn_types.h:311
Definition: mkldnn.hpp:1837
int get_gates_count() const
Definition: mkldnn.hpp:2984
int ndims
Number of dimensions.
Definition: mkldnn_types.h:639
reorder(const primitive_desc &aprimitive_desc, const primitive::at &input, const memory &output)
Definition: mkldnn.hpp:966
Definition: mkldnn.hpp:2004
Definition: mkldnn.hpp:1059
kind
A proxy to C primitive kind enum.
Definition: mkldnn.hpp:113
5D grouped weights tensor with the physical layout giohw.
Definition: mkldnn_types.h:213
void set_alpha(float alpha)
Definition: mkldnn.hpp:2973
mkldnn_status_t MKLDNN_API mkldnn_eltwise_backward_desc_init(mkldnn_eltwise_desc_t *eltwise_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_data_desc, const mkldnn_memory_desc_t *data_desc, float alpha, float beta)
Initializes a eltwise_desc for backward propagation using alg_kind algorithm memory descriptors diff_...
desc(algorithm aalgorithm, const memory::desc &data_desc, const memory::desc &diff_data_desc, int local_size, float alpha, float beta)
Definition: mkldnn.hpp:2079
5D data tensor with the physical layout ncdhw.
Definition: mkldnn_types.h:166
Definition: mkldnn.hpp:3185
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_iterator_destroy(mkldnn_primitive_desc_iterator_t iterator)
Deletes a primitive descriptor iterator.
5D RNN states tensor in the format (num_layers, num_directions, num_states, batch, state channels).
Definition: mkldnn_types.h:224
Definition: mkldnn.hpp:2091
size_t get_size() const
Returns the number of bytes required to allocate the memory described including the padding area...
Definition: mkldnn.hpp:774
mkldnn_status_t MKLDNN_API mkldnn_post_ops_append_sum(mkldnn_post_ops_t post_ops, float scale)
Appends accumulation (sum) post operation to the post_ops.
Definition: mkldnn.hpp:1530
deconvolution_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const primitive::at &bias, const memory &dst)
Definition: mkldnn.hpp:1764
A rnn primitive.
Definition: mkldnn_types.h:438
mkldnn_status_t MKLDNN_API mkldnn_primitive_get_output(const_mkldnn_primitive_t primitive, size_t index, const_mkldnn_primitive_t *output)
For a primitive, returns output at the index position.
blocked weights format
Definition: mkldnn_types.h:299
mkldnn_status_t MKLDNN_API mkldnn_shuffle_backward_desc_init(mkldnn_shuffle_desc_t *shuffle_desc, const mkldnn_memory_desc_t *diff_data_desc, int axis, int group_size)
Initializes a shuffle_desc for backward propagation using memory descriptor diff_data_desc, axis and group number.
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1868
Definition: mkldnn.hpp:2954
eltwise_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2344
mkldnn_prop_kind_t
Kinds of propagation.
Definition: mkldnn_types.h:377
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn.hpp:134
CPU engine.
Definition: mkldnn_types.h:999
Definition: mkldnn.hpp:291
desc(algorithm alg_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, T alpha=0, T beta=0)
Definition: mkldnn.hpp:2320
Eltwise: square root.
Definition: mkldnn_types.h:465
blocked weights format
Definition: mkldnn_types.h:263
mkldnn_stream_kind_t
Kinds of streams.
Definition: mkldnn_types.h:1196
Definition: mkldnn.hpp:271
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_set_int_output_round_mode(mkldnn_primitive_attr_t attr, mkldnn_round_mode_t round_mode)
Sets output rounding mode round_mode for integer operations for a given attr.
4D weights tensor with physical layout hwio, used in TensorFlow.
Definition: mkldnn_types.h:187
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn_types.h:1107
Winograd convolution.
Definition: mkldnn_types.h:447
Definition: mkldnn.hpp:246
Definition: mkldnn.hpp:343
Eltwise: linear.
Definition: mkldnn_types.h:467
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1797
mkldnn_status_t MKLDNN_API mkldnn_softmax_backward_desc_init(mkldnn_softmax_desc_t *softmax_desc, const mkldnn_memory_desc_t *diff_desc, const mkldnn_memory_desc_t *data_desc, int softmax_axis)
Initializes a softmax_desc for backward propagation using memory descriptors diff_desc and data_desc...
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_bias_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1869
reorder(const primitive::at &input, const memory &output)
Definition: mkldnn.hpp:977
Eltwise: logistic.
Definition: mkldnn_types.h:473
Definition: mkldnn.hpp:2645
Direct convolution.
Definition: mkldnn_types.h:445
Primitive iterator passed over last primitive descriptor.
Definition: mkldnn_types.h:54
Definition: mkldnn.hpp:338
Definition: mkldnn.hpp:270
lrn_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &workspace, const memory &dst)
Definition: mkldnn.hpp:2039
source gradient memory primitive desc
Definition: mkldnn_types.h:1182
mkldnn_alg_kind_t cell_kind
RNN cell kind.
Definition: mkldnn_types.h:918
Definition: mkldnn.hpp:1458
mkldnn_batch_normalization_desc_t data
Definition: mkldnn.hpp:2647
Definition: mkldnn_types.h:935
An opaque structure for primitive descriptor attributes.
Definition: mkldnn.hpp:312
blocked data format
Definition: mkldnn_types.h:255
mkldnn_status_t MKLDNN_API mkldnn_pooling_forward_desc_init(mkldnn_pooling_desc_t *pool_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t kernel, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a pooling descriptor pool_desc for forward propagation using prop_kind (possible values a...
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, int local_size, float alpha, float beta, float k)
Definition: mkldnn.hpp:2007
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:2617
mkldnn_rnn_cell_desc_t c_rnn_cell_
Definition: mkldnn.hpp:2955
bool operator!=(const primitive_desc &other) const
Definition: mkldnn.hpp:783
runtime estimation (seconds)
Definition: mkldnn_types.h:1155
blocked weights format
Definition: mkldnn_types.h:342
Definition: mkldnn.hpp:1616
bool operator==(const T other) const
Definition: mkldnn.hpp:61
A (in-place) concat primitive.
Definition: mkldnn_types.h:418
mkldnn_status_t MKLDNN_API mkldnn_stream_create(mkldnn_stream_t *stream, mkldnn_stream_kind_t stream_kind)
Creates an execution stream of stream_kind.
primitive_desc get_primitive_desc() const
Returns the descriptor of the memory primitive.
Definition: mkldnn.hpp:834
blocked weights format
Definition: mkldnn_types.h:277
LSTM cell.
Definition: mkldnn_types.h:488
blocked weights format
Definition: mkldnn_types.h:266
mkldnn_status_t MKLDNN_API mkldnn_batch_normalization_backward_desc_init(mkldnn_batch_normalization_desc_t *bnrm_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *diff_data_desc, const mkldnn_memory_desc_t *data_desc, float epsilon, unsigned flags)
Initializes a batch normalization descriptor bnrm_desc for backward propagation with respect to data ...
Definition: mkldnn_types.h:944
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2464
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2791
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2794
Undefined data type, used for empty memory descriptors.
Definition: mkldnn_types.h:64
Definition: mkldnn.hpp:1794
16-bit signed integer.
Definition: mkldnn_types.h:70
Definition: mkldnn.hpp:2278
A shuffle primitive.
Definition: mkldnn_types.h:414
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:284
mkldnn_shuffle_desc_t data
Definition: mkldnn.hpp:3219
primitive_desc()
Definition: mkldnn.hpp:755
int len() const
Definition: mkldnn.hpp:375
mkldnn_status_t MKLDNN_API mkldnn_primitive_get_primitive_desc(const_mkldnn_primitive_t primitive, const_mkldnn_primitive_desc_t *primitive_desc)
Retrieves a reference to the primitive_desc descriptor of given primitive.
primitive_desc(const memory::desc &output, const std::vector< float > &scales, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1147
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc)
Definition: mkldnn.hpp:2779
mkldnn_status_t MKLDNN_API mkldnn_post_ops_get_params_eltwise(const_mkldnn_post_ops_t post_ops, int index, float *scale, mkldnn_alg_kind_t *alg, float *alpha, float *beta)
Gets the eltwise parameters of the post operation with index index in the sequence of post_ops...
Definition: mkldnn.hpp:1751
Definition: mkldnn.hpp:242
blocked weights format
Definition: mkldnn_types.h:305
Definition: mkldnn.hpp:2900
mkldnn_status_t MKLDNN_API mkldnn_post_ops_get_params_sum(const_mkldnn_post_ops_t post_ops, int index, float *scale)
Gets the parameters of the accumulation (sum) post operation with index index in the sequence of post...
mkldnn_convolution_desc_t data
Definition: mkldnn.hpp:1459
blocked weights format
Definition: mkldnn_types.h:298
A (out-of-place) concat primitive.
Definition: mkldnn_types.h:416
blocked weights format
Definition: mkldnn_types.h:312
Fuse with ReLU.
Definition: mkldnn_types.h:538
Definition: mkldnn.hpp:260
Definition: mkldnn.hpp:278
static size_t get_count(kind akind)
Returns the number of engines of a certain kind.
Definition: mkldnn.hpp:519
mkldnn_query_t
Primitive descriptor query specification.
Definition: mkldnn_types.h:1146
A descriptor of a Batch Normalization operation.
Definition: mkldnn_types.h:849
static engine query(const primitive_desc &pd)
Definition: mkldnn.hpp:551
Definition: mkldnn.hpp:2993
deconvolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights)
Definition: mkldnn.hpp:1980
blocked data format
Definition: mkldnn_types.h:254
A sum primitive.
Definition: mkldnn_types.h:420
batch_normalization_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2740
Definition: mkldnn.hpp:302
blocked weights format
Definition: mkldnn_types.h:339
eltwise_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2302
unsigned flags
Definition: mkldnn_types.h:876
mkldnn_status_t MKLDNN_API mkldnn_reorder_primitive_desc_create_v2(mkldnn_primitive_desc_t *reorder_primitive_desc, const_mkldnn_primitive_desc_t input, const_mkldnn_primitive_desc_t output, const_mkldnn_primitive_attr_t attr)
Initializes a reorder_primitive_desc using an attr attribute and descriptors of input and output memo...
blocked weights format
Definition: mkldnn_types.h:267
blocked weights format
Definition: mkldnn_types.h:316
Definition: mkldnn.hpp:2953
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: mkldnn_types.h:449
softmax_backward(const primitive_desc &aprimitive_desc, const primitive::at &dst, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2428
blocked weights format
Definition: mkldnn_types.h:258
Definition: mkldnn.hpp:2994
Definition: mkldnn.hpp:258
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2292
mkldnn_status_t MKLDNN_API mkldnn_dilated_deconvolution_backward_data_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a dilated deconvolution descriptor conv_desc for backward propagation with respect to dat...
blocked weights format
Definition: mkldnn_types.h:344
mkldnn_status_t MKLDNN_API mkldnn_stream_rerun(mkldnn_stream_t stream, mkldnn_primitive_t *error_primitive)
Reruns all the primitives within the stream.
2D weights tensor with physical layout io.
Definition: mkldnn_types.h:175
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:1156
An batch normalization primitive.
Definition: mkldnn_types.h:434
A class for wrapping an Intel(R) MKL-DNN handle. It is used as the base class for primitive (mkldnn_p...
Definition: mkldnn.hpp:55
Definition: mkldnn_types.h:443
engine(kind akind, size_t index)
Constructs an engine.
Definition: mkldnn.hpp:529
Definition: mkldnn.hpp:2277
A descriptor of a pooling operation.
Definition: mkldnn_types.h:788
Definition: mkldnn.hpp:3265
Definition: mkldnn.hpp:272
Definition: mkldnn.hpp:273
engine get_engine()
Definition: mkldnn.hpp:787
error(mkldnn_status_t astatus, std::string amessage, mkldnn_primitive_t aerror_primitive=0)
Constructs an error instance.
Definition: mkldnn.hpp:173
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1956
const char * impl_info_str() const
Returns implementation name.
Definition: mkldnn.hpp:1256
deconvolution descriptor
Definition: mkldnn_types.h:1167
std::vector< const_mkldnn_primitive_desc_t > cpp_to_c(std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1137
blocked weights format
Definition: mkldnn_types.h:318
shuffle_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:3236
primitive_desc(const memory::primitive_desc &input, const memory::primitive_desc &output)
Definition: mkldnn.hpp:944
primitive_desc(const desc &desc, const engine &e, const pooling_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2230
mkldnn_memory_desc_t data
The underlying C API data structure.
Definition: mkldnn.hpp:727
mkldnn_primitive_desc_t MKLDNN_API mkldnn_primitive_desc_iterator_fetch(const_mkldnn_primitive_desc_iterator_t iterator)
Fetches current primitive descriptor.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:1420
engine get_engine()
Definition: mkldnn.hpp:963
int MKLDNN_API mkldnn_primitive_desc_query_s32(const_mkldnn_primitive_desc_t primitive_desc, mkldnn_query_t what, int index)
Queries primitive descriptor for signed 32bit int.
8-bit signed integer.
Definition: mkldnn_types.h:72
mkldnn_status_t MKLDNN_API mkldnn_reorder_primitive_desc_create(mkldnn_primitive_desc_t *reorder_primitive_desc, const_mkldnn_primitive_desc_t input, const_mkldnn_primitive_desc_t output)
Initializes a reorder_primitive_desc using descriptors of input and output memory primitives...
The data in padding regions is zero.
Definition: mkldnn_types.h:373
int MKLDNN_API mkldnn_rnn_cell_get_states_count(const mkldnn_rnn_cell_desc_t *rnn_cell_desc)
Returns the number of states of a particular rnn_cell_desc.
Definition: mkldnn.hpp:2291
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc)
Definition: mkldnn.hpp:2889
source memory primitive desc
Definition: mkldnn_types.h:1181
mkldnn_primitive_kind_t
Kinds of primitives.
Definition: mkldnn_types.h:404
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1842
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1929
Definition: mkldnn.hpp:3196
Winograd deconvolution.
Definition: mkldnn_types.h:453
Definition: mkldnn.hpp:248
number of inputs expected
Definition: mkldnn_types.h:1152
mkldnn_softmax_desc_t data
Definition: mkldnn.hpp:2368
Definition: mkldnn.hpp:345
Definition: mkldnn.hpp:3018
Definition: mkldnn.hpp:2646
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2467
Definition: mkldnn.hpp:2450
desc(prop_kind aprop_kind, algorithm alg_kind, const memory::desc &src_desc, T alpha=0, T beta=0)
Definition: mkldnn.hpp:2281
An unspecified engine.
Definition: mkldnn_types.h:1198
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:1752
void * get_data_handle() const
Returns a handle of the data contained in the memory primitive. On the CPU engine, this is a pointer to the allocated memory.
Definition: mkldnn.hpp:847
A view primitive.
Definition: mkldnn_types.h:410
size_t MKLDNN_API mkldnn_memory_primitive_desc_get_size(const_mkldnn_primitive_desc_t memory_primitive_desc)
Returns the size (in bytes) that is required for given memory_primitive_desc.
Definition: mkldnn.hpp:3065
Definition: mkldnn.hpp:262
Definition: mkldnn.hpp:328
Definition: mkldnn.hpp:3099
blocked weights format
Definition: mkldnn_types.h:290
mkldnn_primitive_kind_t convert_to_c(primitive::kind akind)
Definition: mkldnn.hpp:154
Definition: mkldnn.hpp:1531
Definition: mkldnn.hpp:340
Definition: mkldnn.hpp:331
Definition: mkldnn.hpp:323
Definition: mkldnn.hpp:333
Average pooling exclude padding.
Definition: mkldnn_types.h:479
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_get_post_ops(const_mkldnn_primitive_attr_t attr, const_mkldnn_post_ops_t *post_ops)
Returns post_ops for given attr.
mkldnn_status_t MKLDNN_API mkldnn_primitive_create(mkldnn_primitive_t *primitive, const_mkldnn_primitive_desc_t primitive_desc, const mkldnn_primitive_at_t *inputs, const_mkldnn_primitive_t *outputs)
Creates a primitive using a primitive_desc descriptor and arrays of inputs and outputs.
primitive::kind kind(int index) const
Definition: mkldnn.hpp:377
Definition: mkldnn_types.h:914
Forward data propagation (inference mode).
Definition: mkldnn_types.h:387
primitive_attr get_primitive_attr() const
Definition: mkldnn.hpp:1242
6D grouped weights tensor with the physical layout goidhw, used in Caffe.
Definition: mkldnn_types.h:217
5D weights tensor with physical layout iodhw, used in Caffe.
Definition: mkldnn_types.h:196
A class that provides the destructor for an Intel(R) MKL-DNN C handle.
Definition: mkldnn.hpp:40
data_type
Data type specification. See mkldnn_data_type_t for a detailed description.
Definition: mkldnn.hpp:594
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const memory &dst)
Definition: mkldnn.hpp:2507
Direct deconvolution.
Definition: mkldnn_types.h:451
Eltwise: abs.
Definition: mkldnn_types.h:463
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst, const memory &mean, const memory &variance)
Definition: mkldnn.hpp:2529
blocked weights format
Definition: mkldnn_types.h:328
pooling_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &workspace, const memory &diff_src)
Definition: mkldnn.hpp:2255
blocked weights format
Definition: mkldnn_types.h:278
A memory descriptor.
Definition: mkldnn.hpp:724
deconvolution_backward_data(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &weights, const memory &diff_src)
Definition: mkldnn.hpp:1851
5D grouped weights tensor with the physical layout hwigo, used in TensorFlow.
Definition: mkldnn_types.h:210
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2295
blocked weights format
Definition: mkldnn_types.h:336
bool operator!=(mkldnn_data_type_t a, memory::data_type b)
Definition: mkldnn.hpp:911
void set_rnn_weights_qparams(int mask, const std::vector< float > &scales)
Definition: mkldnn.hpp:480
handle(T t=0, bool weak=false)
Constructs a C handle wrapper.
Definition: mkldnn.hpp:67
mkldnn_status_t MKLDNN_API mkldnn_dilated_convolution_forward_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a dilated convolution descriptor conv_desc for forward propagation using prop_kind (possi...
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: mkldnn_types.h:457
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2878
mkldnn_status_t status
Definition: mkldnn.hpp:162
deconvolution_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:1779
T get() const
Returns the value of the underlying C handle.
Definition: mkldnn.hpp:85
mkldnn_status_t MKLDNN_API mkldnn_engine_destroy(mkldnn_engine_t engine)
Destroys an engine.
view(const primitive_desc &view_pd, primitive::at input)
Definition: mkldnn.hpp:1029
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1889
blocked weights format
Definition: mkldnn_types.h:317
2D data tensor.
Definition: mkldnn_types.h:148
primitive_desc(const desc &desc, const engine &e, const batch_normalization_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2661
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc)
Definition: mkldnn.hpp:2768
mkldnn_status_t MKLDNN_API mkldnn_dilated_convolution_backward_data_desc_init(mkldnn_convolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t dilates, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a dilated convolution descriptor conv_desc for backward propagation with respect to data ...
bool wait(bool block=true)
Waits for all computations submitted to the stream to complete.
Definition: mkldnn.hpp:3315
mkldnn_status_t MKLDNN_API mkldnn_lrn_backward_desc_init(mkldnn_lrn_desc_t *lrn_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *diff_data_desc, const mkldnn_memory_desc_t *data_desc, int local_size, float alpha, float beta, float k)
Initializes an lrn_desc for backward propagation using alg_kind, memory descriptors data_desc...
Primitive or engine failed on execution.
Definition: mkldnn_types.h:56
memory descriptor for memory and view
Definition: mkldnn_types.h:1165
view(memory input, memory::dims dims, memory::dims offsets)
Definition: mkldnn.hpp:1038
Definition: mkldnn.hpp:1416
Definition: mkldnn.hpp:266
An LRN primitive.
Definition: mkldnn_types.h:432
Definition: mkldnn_types.h:940
mkldnn_padding_kind_t
Kinds of padding.
Definition: mkldnn_types.h:371
rnn_backward(const primitive_desc &aprimitive_desc, const primitive::at &src_layer, const primitive::at &src_iter, const primitive::at &weights_layer, const primitive::at &weights_iter, const primitive::at &bias, const primitive::at &dst_layer, const primitive::at &dst_iter, const memory &diff_src_layer, const memory &diff_src_iter, const memory &diff_weights_layer, const memory &diff_weights_iter, const memory &diff_bias, const primitive::at &diff_dst_layer, const primitive::at &diff_dst_iter, const primitive::at &workspace)
Definition: mkldnn.hpp:3127
Lazy stream.
Definition: mkldnn_types.h:1202
Definition: mkldnn.hpp:332
desc(const memory::desc &diff_desc, const memory::desc &data_desc, int softmax_axis)
Definition: mkldnn.hpp:2405
blocked weights format
Definition: mkldnn_types.h:340
Definition: mkldnn.hpp:304
void get_output_scales(int &mask, std::vector< float > &scales) const
Definition: mkldnn.hpp:439
blocked weights format
Definition: mkldnn_types.h:260
desc(algorithm kind)
Definition: mkldnn.hpp:2963
primitive_desc(const desc &desc, const engine &e, const rnn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:3100
Definition: mkldnn.hpp:1795
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: mkldnn_types.h:238
blocked weights format
Definition: mkldnn_types.h:310
const_mkldnn_primitive_desc_t MKLDNN_API mkldnn_primitive_desc_query_pd(const_mkldnn_primitive_desc_t primitive_desc, mkldnn_query_t what, int index)
Queries primitive descriptor for primitive descriptor.
Definition: mkldnn.hpp:2876
shuffle descriptor
Definition: mkldnn_types.h:1168
Forward data propagation (training mode).
Definition: mkldnn_types.h:383
Definition: mkldnn.hpp:344
primitive_desc(const desc &desc, const engine &e, const lrn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2092
inner_product_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at diff_dst, const memory &diff_weights)
Definition: mkldnn.hpp:2915
mkldnn_convolution_desc_t data
Definition: mkldnn.hpp:1532
memory(const primitive &aprimitive)
Constructs a memory primitive from a generic primitive.
Definition: mkldnn.hpp:793
3D data tensor with the physical layout nwc.
Definition: mkldnn_types.h:154
engine get_engine()
Definition: mkldnn.hpp:1108
post_ops()
Definition: mkldnn.hpp:368
An opaque structure to describe a primitive.
batch_normalization_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const primitive::at &diff_dst, const primitive::at &weights, const primitive::at &workspace, const memory &diff_src, const memory &diff_weights)
Definition: mkldnn.hpp:2701
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: mkldnn_types.h:144
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1332
mkldnn_data_type_t
Data type specification.
Definition: mkldnn_types.h:62
Definition: mkldnn.hpp:1457
Definition: mkldnn.hpp:325
Definition: mkldnn.hpp:318
convolution descriptor
Definition: mkldnn_types.h:1166
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1506
A memory primitive descriptor.
Definition: mkldnn.hpp:751
Definition: mkldnn.hpp:314
Definition: mkldnn.hpp:2413
mkldnn_status_t MKLDNN_API mkldnn_lrn_forward_desc_init(mkldnn_lrn_desc_t *lrn_desc, mkldnn_prop_kind_t prop_kind, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *data_desc, int local_size, float alpha, float beta, float k)
Initializes an lrn_desc for forward propagation using prop_kind (possible values are mkldnn_forward_t...
blocked weights format
Definition: mkldnn_types.h:301
primitive_desc(const desc &desc, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1502
blocked weights format
Definition: mkldnn_types.h:294
handle & operator=(const handle &other)
Definition: mkldnn.hpp:72
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2631
Eltwise: bounded_relu.
Definition: mkldnn_types.h:469
Definition: mkldnn.hpp:2367
#define REG_QUERY_MPD(name, what, idx)
Definition: mkldnn.hpp:1306
Definition: mkldnn_types.h:937
convolution_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:1442
mkldnn_engine_kind_t
Kinds of engines.
Definition: mkldnn_types.h:995
Definition: mkldnn_types.h:910
int MKLDNN_API mkldnn_rnn_cell_get_gates_count(const mkldnn_rnn_cell_desc_t *rnn_cell_desc)
Returns the number of gates of a particular rnn_cell_desc.
Queried element is not required for given primitive.
Definition: mkldnn_types.h:58
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:3019
blocked weights format
Definition: mkldnn_types.h:357
bool operator!=(const T other) const
Definition: mkldnn.hpp:62
Memory primitive that describes the data.
Definition: mkldnn.hpp:579
Weights format used in 8bit Winograd convolution.
Definition: mkldnn_types.h:361
Definition: mkldnn.hpp:327
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2028
Definition: mkldnn.hpp:2066
Definition: mkldnn.hpp:301
Round nearest.
Definition: mkldnn_types.h:80
blocked weights format
Definition: mkldnn_types.h:356
Definition: mkldnn.hpp:243
batch_normalization_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &mean, const primitive::at &variance, const primitive::at &diff_dst, const primitive::at &weights, const memory &diff_src, const memory &diff_weights)
Definition: mkldnn.hpp:2682
Definition: mkldnn.hpp:1668
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: mkldnn_types.h:628
static mkldnn_stream_kind_t convert_to_c(kind akind)
Definition: mkldnn.hpp:3272
blocked weights format
Definition: mkldnn_types.h:259
blocked weights format
Definition: mkldnn_types.h:353
Definition: mkldnn.hpp:1866
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1096
mkldnn_status_t MKLDNN_API mkldnn_primitive_desc_iterator_create_v2(mkldnn_primitive_desc_iterator_t *iterator, const_mkldnn_op_desc_t op_desc, const_mkldnn_primitive_attr_t attr, mkldnn_engine_t engine, const_mkldnn_primitive_desc_t hint_forward_primitive_desc)
Creates a primitive descriptor iterator for given op_desc, attr, engine, and optionally a hint primit...
Definition: mkldnn.hpp:2449
pooling_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst, const memory &workspace)
Definition: mkldnn.hpp:2191
convolution_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const primitive::at &bias, const memory &dst)
Definition: mkldnn.hpp:1429
4D weights tensor with physical layout iohw.
Definition: mkldnn_types.h:193
A reorder primitive.
Definition: mkldnn_types.h:412
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:1755
rnn_direction
Definition: mkldnn.hpp:299
primitive_desc(const std::vector< float > &scales, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1166
blocked weights format
Definition: mkldnn_types.h:337
blocked weights format
Definition: mkldnn_types.h:297
An unspecified engine.
Definition: mkldnn_types.h:997
desc(const mkldnn_memory_desc_t &adata)
Constructs a memory descriptor from a C API data structure.
Definition: mkldnn.hpp:747
blocked weights format
Definition: mkldnn_types.h:313
Definition: mkldnn.hpp:1136
int MKLDNN_API mkldnn_post_ops_len(const_mkldnn_post_ops_t post_ops)
Returns the length of post operations for given post_ops.
engine get_engine()
Definition: mkldnn.hpp:1026
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const pooling_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2234
blocked weights format
Definition: mkldnn_types.h:338
blocked weights format
Definition: mkldnn_types.h:327
mkldnn_alg_kind_t
Kinds of algorithms.
Definition: mkldnn_types.h:442
primitive_desc(const desc &desc, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2901
Definition: mkldnn.hpp:263
inner product descriptor
Definition: mkldnn_types.h:1174
A pooling primitive.
Definition: mkldnn_types.h:430
weights memory primitive descriptor desc
Definition: mkldnn_types.h:1183
output memory primitive desc
Definition: mkldnn_types.h:1180
Definition: mkldnn.hpp:2229
5D weights tensor with physical layout dhwio, used in TensorFlow.
Definition: mkldnn_types.h:199
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2031
mkldnn_batch_normalization_desc_t data
Definition: mkldnn.hpp:2451
Definition: mkldnn.hpp:943
mkldnn_status_t MKLDNN_API mkldnn_primitive_destroy(mkldnn_primitive_t primitive)
Deletes a primitive.
Definition: mkldnn.hpp:334
std::string message
Definition: mkldnn.hpp:163
Definition: mkldnn.hpp:3184
mkldnn_status_t MKLDNN_API mkldnn_deconvolution_backward_weights_desc_init(mkldnn_deconvolution_desc_t *conv_desc, mkldnn_alg_kind_t alg_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *diff_weights_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_desc, const mkldnn_dims_t strides, const mkldnn_dims_t padding_l, const mkldnn_dims_t padding_r, mkldnn_padding_kind_t padding_kind)
Initializes a deconvolution descriptor conv_desc for backward propagation with respect to weights usi...
mkldnn_status_t MKLDNN_API mkldnn_rnn_backward_desc_init(mkldnn_rnn_desc_t *rnn_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_rnn_cell_desc_t *rnn_cell_desc, const mkldnn_rnn_direction_t direction, const mkldnn_memory_desc_t *src_layer_desc, const mkldnn_memory_desc_t *src_iter_desc, const mkldnn_memory_desc_t *weights_layer_desc, const mkldnn_memory_desc_t *weights_iter_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_layer_desc, const mkldnn_memory_desc_t *dst_iter_desc, const mkldnn_memory_desc_t *diff_src_layer_desc, const mkldnn_memory_desc_t *diff_src_iter_desc, const mkldnn_memory_desc_t *diff_weights_layer_desc, const mkldnn_memory_desc_t *diff_weights_iter_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_layer, const mkldnn_memory_desc_t *diff_dst_iter_desc)
Initializes a rnn descriptor rnn_desc for backward propagation using prop_kind, rnn_cell_desc, direction, and memory descriptors.
primitive_desc(const desc &desc, const engine &e, const eltwise_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2331
Definition: mkldnn.hpp:2463
Definition: mkldnn.hpp:315
blocked weights format
Definition: mkldnn_types.h:287
handle(const handle &other)
Definition: mkldnn.hpp:71
Forward data propagation (alias for mkldnn_forward_training)
Definition: mkldnn_types.h:391
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: mkldnn_types.h:219
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_set_output_scales(mkldnn_primitive_attr_t attr, int count, int mask, const float *scales)
Sets output scales for primitive operations.
Definition: mkldnn.hpp:241
lrn descriptor
Definition: mkldnn_types.h:1172
workspace memory primitive desc
Definition: mkldnn_types.h:1187
lrn_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2119
desc(algorithm aalgorithm, const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1593
bool next_impl()
Advances the next implementation for the given op descriptor.
Definition: mkldnn.hpp:1270
mkldnn_status_t MKLDNN_API mkldnn_inner_product_backward_weights_desc_init(mkldnn_inner_product_desc_t *ip_desc, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *diff_weights_desc, const mkldnn_memory_desc_t *diff_bias_desc, const mkldnn_memory_desc_t *diff_dst_desc)
Initializes an inner product descriptor ip_desc for backward propagation with respect to weights usin...
blocked weights format
Definition: mkldnn_types.h:264
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1670
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, T epsilon, unsigned flags)
Definition: mkldnn.hpp:2649
blocked weights format
Definition: mkldnn_types.h:302
Definition: mkldnn.hpp:224
weights format with additional buffer size equal to the number of output channels and containing the ...
Definition: mkldnn_types.h:274
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const lrn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2096
float get_clipping() const
Definition: mkldnn.hpp:2978
weights grad.
Definition: mkldnn_types.h:1184
4D data tensor with the physical layout nchw, used in Caffe.
Definition: mkldnn_types.h:157
Definition: mkldnn.hpp:321
mkldnn_status_t MKLDNN_API mkldnn_rnn_forward_desc_init(mkldnn_rnn_desc_t *rnn_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_rnn_cell_desc_t *rnn_cell_desc, const mkldnn_rnn_direction_t direction, const mkldnn_memory_desc_t *src_layer_desc, const mkldnn_memory_desc_t *src_iter_desc, const mkldnn_memory_desc_t *weights_layer_desc, const mkldnn_memory_desc_t *weights_iter_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_layer_desc, const mkldnn_memory_desc_t *dst_iter_desc)
Initializes a rnn descriptor rnn_desc for forward propagation using prop_kind, rnn_cell_desc, direction, and memory descriptors.
void append_eltwise(float scale, algorithm alg, float alpha, float beta)
Definition: mkldnn.hpp:395
primitive kind
Definition: mkldnn_types.h:1150
blocked data format
Definition: mkldnn_types.h:250
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims dilates, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1815
int get_state_count() const
Definition: mkldnn.hpp:2987
blocked weights format
Definition: mkldnn_types.h:285
Definition: mkldnn.hpp:317
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &diff_dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &padding_l, const memory::dims &padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:2207
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst, const memory &mean, const memory &variance, const memory &workspace)
Definition: mkldnn.hpp:2544
kind
Definition: mkldnn.hpp:3268
desc(algorithm aalgorithm, const memory::desc &diff_src_desc, const memory::desc &weights_desc, const memory::desc &diff_dst_desc, const memory::dims strides, const memory::dims padding_l, const memory::dims padding_r, const padding_kind apadding_kind)
Definition: mkldnn.hpp:1460
Definition: mkldnn.hpp:339
desc(prop_kind aprop_kind, rnn_cell::desc cell, const 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)
Definition: mkldnn.hpp:2996
mkldnn_status_t MKLDNN_API mkldnn_inner_product_forward_desc_init(mkldnn_inner_product_desc_t *ip_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *src_desc, const mkldnn_memory_desc_t *weights_desc, const mkldnn_memory_desc_t *bias_desc, const mkldnn_memory_desc_t *dst_desc)
Initializes an inner product descriptor ip_desc for forward propagation using prop_kind (possible val...