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
110 using handle::handle;
161 struct error:
public std::exception {
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
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
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
534 "could not create an engine");
539 :
handle(aengine, true) {}
546 "could not get engine from primitive_desc");
547 reset(engine_q,
true);
550 template <
class primitive_desc>
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");
770 adims.size() == 0 ?
nullptr : &adims[0],
772 "could not initialize a memory descriptor");
794 "could not initialize a memory primitive descriptor");
811 other.
get())) ?
false :
true;
832 "could not create a memory primitive");
834 auto _malloc = [](
size_t size,
int alignment) {
837 ptr = _aligned_malloc(size, alignment);
838 int rc = ((ptr)? 0 : errno);
840 int rc = ::posix_memalign(&ptr, alignment, size);
842 return (rc == 0) ? (
char*)ptr :
nullptr;
844 auto _free = [](
char* p) {
846 _aligned_free((
void*)p);
851 _handle.reset(_malloc(adesc.
get_size(), 4096), _free);
859 "could not create a memory primitive");
870 "could not get primitive descriptor from a memory primitive");
872 adesc.
reset(const_cast<mkldnn_primitive_desc_t>(cdesc),
true);
881 "could not get native handle");
887 "could not set native handle");
911 &aprimitive_desc,
int n_inputs,
int n_outputs,
912 const std::string &prim_name) {
917 if (n_outputs_expected > n_outputs ) {
918 std::string message =
"could not create " + prim_name +
919 " primitive, not enought output parameters";
922 if (n_inputs_expected > n_inputs ) {
923 std::string message =
"could not create " + prim_name +
924 " primitive, not enought input parameters";
936 return ((aprimitive_md !=
nullptr) && (aprimitive_md->
ndims == 0));
979 &result, input.
get(), output.
get()),
980 "could not create a reorder primitive descriptor");
989 &result, input.
get(), output.
get(), aattr.
get()),
990 "could not create a reorder primitive descriptor");
1003 aprimitive_desc.
get(), inputs, outputs),
1004 "could not create a reorder primitive");
1018 reorder_d.get(), inputs, outputs),
1019 "could not create a reorder primitive");
1039 &result, input.
get(), &dims[0], &offsets[0]),
1040 "could not create a view primitive descriptor");
1052 "could not clone a dst primitive descriptor");
1064 view_pd.
get(), inputs,
nullptr),
1065 "could not create a view primitive");
1075 view_pd.get(), inputs,
nullptr),
1076 "could not create a view primitive");
1092 std::vector<memory::primitive_desc> inputs) {
1093 std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
1094 c_api_inputs.reserve(inputs.size());
1096 std::transform(inputs.begin(), inputs.end(),
1098 return c_api_inputs;
1102 std::vector<memory::primitive_desc> inputs) {
1105 auto c_api_inputs =
cpp_to_c(inputs);
1108 &result, &output.
data, (
int)c_api_inputs.size(),
1109 concat_dimension, &c_api_inputs[0]),
1110 "could not create a concat primitive descriptor");
1115 std::vector<memory::primitive_desc> inputs) {
1118 auto c_api_inputs =
cpp_to_c(inputs);
1121 &result,
nullptr, (
int)c_api_inputs.size(),
1122 concat_dimension, &c_api_inputs[0]),
1123 "could not create a concat primitive descriptor");
1134 "could not clone a dst primitive descriptor");
1143 std::vector<primitive::at> &inputs,
const memory &output) {
1146 std::vector<mkldnn_primitive_at_t> p_inputs;
1147 for (
size_t i = 0; i < inputs.size(); i++)
1148 p_inputs.push_back(inputs[i].data);
1152 concat_pd.
get(), &p_inputs[0], outputs),
1153 "could not create a concat primitive");
1169 std::vector<memory::primitive_desc> inputs) {
1170 std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
1171 c_api_inputs.reserve(inputs.size());
1173 std::transform(inputs.begin(), inputs.end(),
1175 return c_api_inputs;
1179 const std::vector<float> &scales,
1180 std::vector<memory::primitive_desc> inputs) {
1183 auto c_api_inputs =
cpp_to_c(inputs);
1188 "number of scales not equal to number of inputs");
1191 &result, &output.
data, (
int)c_api_inputs.size(),
1192 &scales[0], &c_api_inputs[0]),
1193 "could not create a sum primitive descriptor");
1198 std::vector<memory::primitive_desc> inputs) {
1201 auto c_api_inputs =
cpp_to_c(inputs);
1206 "number of scales not equal to number of inputs");
1209 &result,
nullptr, (
int)c_api_inputs.size(), &scales[0],
1211 "could not create a sum primitive descriptor");
1223 "could not clone a dst primitive descriptor");
1232 std::vector<primitive::at> &inputs,
const memory &output) {
1235 std::vector<mkldnn_primitive_at_t> p_inputs;
1236 for (
size_t i = 0; i < inputs.size(); i++)
1237 p_inputs.push_back(inputs[i].data);
1241 sum_pd.
get(), &p_inputs[0], outputs),
1242 "could not create a sum primitive");
1263 &iterator, desc, attr ? attr->
get() :
nullptr, e.
get(),
1266 "could not create a primitive descriptor iterator");
1267 pd_iterator.reset(iterator);
1276 "could not get attributes");
1279 "could not clone attributes");
1291 "could not query implementation info string");
1315 if (!std::any_of(valid_w.cbegin(), valid_w.cend(),
1316 [=](
query q) {
return what == q; }))
1324 if (const_cdesc ==
nullptr)
1329 "could not clone a memory primitive descriptor");
1337 # define REG_QUERY_MPD(name, what, idx) \
1338 memory::primitive_desc name ## _primitive_desc() const \
1339 { return query_mpd(what ## _pd, idx); }
1342 handle<mkldnn_primitive_desc_iterator_t> pd_iterator;
1347 "could not fetch a primitive descriptor from the iterator");
1378 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1380 "could not create a convolution forward descriptor");
1395 &src_desc.
data, &weights_desc.
data,
nullptr,
1396 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1398 "could not create a convolution forward descriptor");
1418 &dst_desc.
data, &strides[0], &dilates[0],
1419 &padding_l[0], &padding_r[0],
1421 "could not create a dilated convolution forward descriptor");
1439 &src_desc.
data, &weights_desc.
data,
nullptr,
1440 &dst_desc.
data, &strides[0], &dilates[0],
1441 &padding_l[0], &padding_r[0],
1443 "could not create a dilated convolution forward descriptor");
1468 aprimitive_desc.
get(), inputs, outputs),
1469 "could not create a convolution forward bias primitive");
1480 "convolution forward");
1482 aprimitive_desc.
get(), inputs, outputs),
1483 "could not create a convolution forward primitive");
1504 &weights_desc.
data, &diff_dst_desc.
data,
1505 &strides[0], &padding_l[0], &padding_r[0],
1507 "could not create a convolution backward data descriptor");
1525 &weights_desc.
data, &diff_dst_desc.
data,
1526 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1528 "could not create a convolution backward data descriptor");
1548 const memory &diff_src) {
1553 "convolution backward data");
1555 aprimitive_desc.
get(), inputs, outputs),
1556 "could not create a convolution backward data primitive");
1578 &diff_weights_desc.
data, &diff_bias_desc.
data,
1579 &diff_dst_desc.
data,
1580 &strides[0], &padding_l[0], &padding_r[0],
1582 "could not create a convolution backward weights descriptor");
1597 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1598 &strides[0], &padding_l[0], &padding_r[0],
1600 "could not create a convolution backward weights descriptor");
1618 &diff_weights_desc.
data, &diff_bias_desc.
data,
1619 &diff_dst_desc.
data,
1620 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1622 "could not create a convolution backward weights descriptor");
1639 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1640 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1642 "could not create a convolution backward weights descriptor");
1670 "convolution backward weights");
1672 aprimitive_desc.
get(), inputs, outputs),
1673 "could not create a convolution backward weights primitive");
1678 const memory &diff_weights) {
1683 "convolution backward weights");
1685 aprimitive_desc.
get(), inputs, outputs),
1686 "could not create a convolution backward weights primitive");
1717 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1719 "could not create a deconvolution forward descriptor");
1734 &src_desc.
data, &weights_desc.
data,
nullptr,
1735 &dst_desc.
data, &strides[0], &padding_l[0], &padding_r[0],
1737 "could not create a deconvolution forward descriptor");
1756 &dst_desc.
data, &strides[0], &dilates[0], &padding_l[0],
1758 "could not create a dilated deconvolution forward descriptor");
1775 &src_desc.
data, &weights_desc.
data,
nullptr,
1776 &dst_desc.
data, &strides[0], &dilates[0], &padding_l[0],
1778 "could not create a dilated deconvolution forward descriptor");
1803 "deconvolution forward");
1805 aprimitive_desc.
get(), inputs, outputs),
1806 "could not create a deconvolution forward bias primitive");
1817 "deconvolution forward");
1819 aprimitive_desc.
get(), inputs, outputs),
1820 "could not create a deconvolution forward primitive");
1841 &weights_desc.
data, &diff_dst_desc.
data,
1842 &strides[0], &padding_l[0], &padding_r[0],
1844 "could not create a deconvolution backward data descriptor");
1861 &weights_desc.
data, &diff_dst_desc.
data,
1862 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1864 "could not create a dilated deconvolution backward data descriptor");
1884 const memory &diff_src) {
1889 "deconvolution backward data");
1891 aprimitive_desc.
get(), inputs, outputs),
1892 "could not create a deconvolution backward data primitive");
1914 &diff_weights_desc.
data, &diff_bias_desc.
data,
1915 &diff_dst_desc.
data,
1916 &strides[0], &padding_l[0], &padding_r[0],
1918 "could not create a deconvolution backward weights descriptor");
1933 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1934 &strides[0], &padding_l[0], &padding_r[0],
1936 "could not create a deconvolution backward weights descriptor");
1954 &diff_weights_desc.
data, &diff_bias_desc.
data,
1955 &diff_dst_desc.
data,
1956 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1958 "could not create a dilated deconvolution backward weights descriptor");
1975 &diff_weights_desc.
data,
nullptr, &diff_dst_desc.
data,
1976 &strides[0], &dilates[0], &padding_l[0], &padding_r[0],
1978 "could not create a dilated deconvolution backward weights descriptor");
2005 "deconvolution backward weights");
2007 aprimitive_desc.
get(), inputs, outputs),
2008 "could not create a deconvolution backward weights primitive");
2013 const memory &diff_weights) {
2018 "deconvolution backward weights");
2020 aprimitive_desc.
get(), inputs, outputs),
2021 "could not create a deconvolution backward weights primitive");
2040 int local_size,
float alpha,
float beta,
float k)
2044 &src_desc.
data, local_size, alpha, beta, k),
2045 "could not create a lrn forward descriptor");
2049 int local_size,
float alpha,
float beta)
2053 &src_desc.
data, local_size, alpha, beta,
float(1.0)),
2054 "could not create a lrn forward descriptor");
2079 aprimitive_desc.
get(), inputs, outputs),
2080 "could not create a lrn forward primitive");
2091 aprimitive_desc.
get(), inputs, outputs),
2092 "could not create a lrn forward primitive");
2103 int local_size,
float alpha,
float beta,
float k)
2107 &data_desc.
data, local_size, alpha, beta, k),
2108 "could not create a lrn backward descriptor");
2113 int local_size,
float alpha,
float beta)
2117 &data_desc.
data, local_size, alpha, beta,
float(1.0)),
2118 "could not create a lrn backward descriptor");
2145 aprimitive_desc.
get(), inputs, outputs),
2146 "could not create a lrn backward primitive");
2152 const memory &diff_src) {
2158 aprimitive_desc.
get(), inputs, outputs),
2159 "could not create a lrn backward primitive");
2191 &strides[0], &kernel[0],
2192 &padding_l[0], &padding_r[0],
2194 "could not init a forward pooling descriptor");
2217 aprimitive_desc.
get(), inputs, outputs),
2218 "could not create a pooling forward primitive");
2229 aprimitive_desc.
get(), inputs, outputs),
2230 "could not create a pooling forward primitive");
2252 &diff_src_desc.
data, &diff_dst_desc.
data,
2253 &strides[0], &kernel[0],
2254 &padding_l[0], &padding_r[0],
2256 "could not init a backward pooling descriptor");
2275 const memory &diff_src) {
2281 aprimitive_desc.
get(), inputs, outputs),
2282 "could not create a pooling backward primitive");
2293 aprimitive_desc.
get(), inputs, outputs),
2294 "could not create a pooling backward primitive");
2311 template <
typename T>
2313 const memory::desc &src_desc, T alpha = 0, T beta = 0) {
2317 static_cast<float>(alpha), static_cast<float>(beta)),
2318 "could not create a eltwise forward descriptor");
2340 aprimitive_desc.
get(), inputs, outputs),
2341 "could not create a eltwise forward primitive");
2350 template <
typename T>
2352 const memory::desc &data_desc, T alpha = 0, T beta = 0) {
2355 &data_desc.
data, static_cast<float>(alpha),
2356 static_cast<float>(beta)),
2357 "could not create a eltwise backward descriptor");
2377 const memory &diff_src) {
2383 aprimitive_desc.
get(), inputs, outputs),
2384 "could not create a eltwise backward primitive");
2405 "could not create a softmax forward descriptor");
2427 aprimitive_desc.
get(), inputs, outputs),
2428 "could not create a softmax forward primitive");
2439 &diff_desc.
data, &data_desc.
data, softmax_axis),
2440 "could not init a backward softmax descriptor");
2461 const memory &diff_src) {
2466 aprimitive_desc.
get(), inputs, outputs),
2467 "could not create a softmax backward primitive");
2483 template <
typename T>
2489 static_cast<float>(epsilon), flags),
2490 "could not create a batch normalization forward descriptor");
2507 {
return stat_primitive_desc(mean); }
2509 {
return stat_primitive_desc(var); }
2512 enum { mean = 1, var = 2, };
2517 "could not get a batch-normalization descriptor");
2531 "batch normalization forward");
2533 aprimitive_desc.
get(), inputs, outputs),
2534 "could not create a batch normalization forward primitive");
2546 "batch normalization forward");
2548 aprimitive_desc.
get(), inputs, outputs),
2549 "could not create a batch normalization forward primitive");
2566 mean.
get(), variance.
get() };
2568 "batch normalization forward");
2570 aprimitive_desc.
get(), inputs, outputs),
2571 "could not create a batch normalization forward primitive");
2578 const memory &workspace) {
2582 mean.
get(), variance.
get(), workspace.
get() };
2584 "batch normalization forward");
2586 aprimitive_desc.
get(), inputs, outputs),
2587 "could not create a batch normalization forward primitive");
2593 const memory &variance) {
2597 mean.
get(), variance.
get() };
2599 "batch normalization forward");
2601 aprimitive_desc.
get(), inputs, outputs),
2602 "could not create a batch normalization forward primitive");
2622 mean.
get(), variance.
get(), workspace.
get() };
2629 if (n_inputs_expected == 2 && n_outputs_expected == 3) {
2631 auto _weights = dst;
2632 inputs[1] = {_weights.get(), 0};
2634 auto _dst = mean, _mean = variance, _variance = workspace;
2635 outputs[0] = _dst.get();
2636 outputs[1] = _mean.get();
2637 outputs[2] = _variance.get();
2638 outputs[3] =
nullptr;
2642 aprimitive_desc.
get(), inputs, outputs),
2643 "could not create a batch normalization forward primitive");
2654 "batch normalization forward");
2656 aprimitive_desc.
get(), inputs, outputs),
2657 "could not create a batch normalization forward primitive");
2667 "batch normalization forward");
2669 aprimitive_desc.
get(), inputs, outputs),
2670 "could not create a batch normalization forward primitive");
2678 template <
typename T>
2680 const memory::desc &data_desc, T epsilon,
unsigned flags) {
2684 &diff_data_desc.
data, &data_desc.
data,
2685 static_cast<float>(epsilon), flags),
2686 "could not create a batch normalization backward descriptor");
2716 const memory &diff_weights) {
2721 diff_weights.
get() };
2723 "batch normalization backward");
2725 aprimitive_desc.
get(), inputs, outputs),
2726 "could not create a batch normalization backward primitive");
2740 diff_weights.
get() };
2742 "batch normalization backward");
2744 aprimitive_desc.
get(), inputs, outputs),
2745 "could not create a batch normalization backward primitive");
2759 diff_dst.
data, weights_or_workspace.
data };
2762 "batch normalization backward");
2764 aprimitive_desc.
get(), inputs, outputs),
2765 "could not create a batch normalization backward primitive");
2773 const memory &diff_src) {
2779 "batch normalization backward");
2781 aprimitive_desc.
get(), inputs, outputs),
2782 "could not create a batch normalization backward primitive");
2806 "could not create a inner product forward descriptor");
2815 &weights_desc.
data,
nullptr, &dst_desc.
data),
2816 "could not create a inner product forward descriptor");
2841 "inner product forward");
2843 aprimitive_desc.
get(), inputs, outputs),
2844 "could not create a inner product forward primitive");
2855 "inner product forward");
2857 aprimitive_desc.
get(), inputs, outputs),
2858 "could not create a inner product forward primitive");
2871 &diff_src_desc.
data, &weights_desc.
data,
2872 &diff_dst_desc.
data),
2873 "could not create a inner product backward data descriptor");
2893 const memory &diff_src) {
2898 "inner product backward data");
2900 aprimitive_desc.
get(), inputs, outputs),
2901 "could not create a inner product backward data primitive");
2916 &diff_bias_desc.
data, &diff_dst_desc.
data),
2917 "could not create a inner product backward weights descriptor");
2925 nullptr, &diff_dst_desc.
data),
2926 "could not create a inner product backward weights descriptor");
2947 const memory &diff_weights) {
2952 "inner product backward weights");
2954 aprimitive_desc.
get(), inputs, outputs),
2955 "could not create a inner product backward weights primitive");
2965 { diff_weights.
get(), diff_bias.
get()};
2967 "inner product backward weights");
2969 aprimitive_desc.
get(), inputs, outputs),
2970 "could not create a inner product backward weights primitive");
2991 "could not init an rnn cell descriptor");
3039 &src_layer_desc.
data, &src_iter_desc.
data,
3040 &weights_layer_desc.
data, &weights_iter_desc.
data,
3042 &dst_layer_desc.
data, &dst_iter_desc.
data),
3043 "could not create an RNN forward descriptor");
3070 const memory &workspace) {
3075 inputs[idx++] = src_layer.
data;
3077 inputs[idx++] = src_iter.
data;
3078 inputs[idx++] = weights_layer.
data;
3079 inputs[idx++] = weights_iter.
data;
3083 outputs[idx++] = dst_layer.
get();
3088 aprimitive_desc.
get(), inputs, outputs),
3089 "could not create an RNN forward primitive");
3116 &src_layer_desc.
data, &src_iter_desc.
data,
3117 &weights_layer_desc.
data, &weights_iter_desc.
data,
3119 &dst_layer_desc.
data, &dst_iter_desc.
data,
3120 &diff_src_layer_desc.
data, &diff_src_iter_desc.
data,
3121 &diff_weights_layer_desc.
data,
3122 &diff_weights_iter_desc.
data, &diff_bias_desc.
data,
3123 &diff_dst_layer_desc.
data, &diff_dst_iter_desc.
data),
3124 "could not create an RNN backward descriptor");
3165 const memory &diff_src_layer,
3166 const memory &diff_src_iter,
3167 const memory &diff_weights_layer,
3168 const memory &diff_weights_iter,
3177 inputs[idx++] = src_layer.
data;
3179 inputs[idx++] = src_iter.
data;
3180 inputs[idx++] = weights_layer.
data;
3181 inputs[idx++] = weights_iter.
data;
3183 inputs[idx++] = bias.
data;
3184 inputs[idx++] = dst_layer.
data;
3186 inputs[idx++] = dst_iter.
data;
3187 inputs[idx++] = diff_dst_layer.
data;
3189 inputs[idx++] = diff_dst_iter.
data;
3190 inputs[idx++] = workspace.
data;
3193 outputs[idx++] = diff_src_layer.
get();
3195 outputs[idx++] = diff_src_iter.
get();
3196 outputs[idx++] = diff_weights_layer.
get();
3197 outputs[idx++] = diff_weights_iter.
get();
3200 aprimitive_desc.
get(), inputs, outputs),
3201 "could not create an RNN backward primitive");
3218 int axis,
int group_size) {
3222 "could not create a shuffle forward descriptor");
3241 aprimitive_desc.
get(), inputs, outputs),
3242 "could not create a shuffle forward primitive");
3252 &diff_data_desc.
data, axis, group_size),
3253 "could not create a shuffle backward descriptor");
3273 aprimitive_desc.
get(), inputs, outputs),
3274 "could not create a shuffle backward primitive");
3289 #ifndef DOXYGEN_SHOULD_SKIP_THIS
3296 using handle::handle;
3310 "could not create a stream");
3321 if (primitives.size() == 0)
return *
this;
3322 std::vector<mkldnn_primitive_t> c_api_primitives;
3323 c_api_primitives.reserve(primitives.size());
3325 std::transform(primitives.begin(), primitives.end(),
3331 c_api_primitives.size(), &c_api_primitives[0],
3332 &c_api_error_primitive),
3333 "could not submit primitives to a stream",
3334 &c_api_error_primitive);
3348 block, &c_api_error_primitive);
3352 &c_api_error_primitive);
3360 "could not rerun a stream", &c_api_error_primitive);
3365 #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:2410
Definition: mkldnn.hpp:2361
bool operator!=(const handle &other) const
Definition: mkldnn.hpp:88
LRN within a single channel.
Definition: mkldnn_types.h:542
primitive error_primitive
Definition: mkldnn.hpp:164
A descriptor of a Local Response Normalization (LRN) operation.
Definition: mkldnn_types.h:880
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:1509
Definition: mkldnn.hpp:730
Definition: mkldnn.hpp:342
blocked weights format
Definition: mkldnn_types.h:332
inner_product_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at weights, const memory &dst)
Definition: mkldnn.hpp:2848
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2202
Definition: mkldnn.hpp:269
std::vector< const_mkldnn_primitive_desc_t > cpp_to_c(std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1091
blocked weights format
Definition: mkldnn_types.h:337
op descriptor
Definition: mkldnn_types.h:1222
primitive_desc(const memory::desc &output, int concat_dimension, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1101
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1652
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:374
mkldnn_primitive_t get() const
Returns the value of the underlying C handle.
Definition: mkldnn.hpp:85
Definition: mkldnn.hpp:3094
blocked weights format
Definition: mkldnn_types.h:316
mkldnn_status_t MKLDNN_API mkldnn_primitive_attr_destroy(mkldnn_primitive_attr_t attr)
Deletes an attr.
Definition: mkldnn.hpp:702
Definition: mkldnn.hpp:650
blocked weights format
Definition: mkldnn_types.h:412
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
Definition: mkldnn.hpp:648
A Softmax primitive.
Definition: mkldnn_types.h:486
number of outputs expected
Definition: mkldnn_types.h:1211
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:3052
blocked weights format
Definition: mkldnn_types.h:415
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:1662
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:2522
REG_QUERY_MPD(src, src, 0)
stream & submit(std::vector< primitive > primitives)
Submits a vector of primitives to a stream for computations.
Definition: mkldnn.hpp:3318
A base class for all primitive descriptors.
Definition: mkldnn.hpp:1258
Definition: mkldnn.hpp:598
Definition: mkldnn.hpp:2235
mkldnn_status_t
Status values returned by Intel(R) MKL-DNN functions.
Definition: mkldnn_types.h:47
stream & rerun()
Definition: mkldnn.hpp:3356
Definition: mkldnn.hpp:2198
A descriptor of a convolution operation.
Definition: mkldnn_types.h:733
Definition: mkldnn.hpp:300
desc(prop_kind aprop_kind, const memory::desc &data_desc, int axis, int group_size)
Definition: mkldnn.hpp:3217
Definition: mkldnn.hpp:2173
The operation failed and should be retried.
Definition: mkldnn_types.h:53
memory null_memory(engine eng)
Definition: mkldnn.hpp:905
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:680
Definition: mkldnn.hpp:1982
blocked weights format
Definition: mkldnn_types.h:279
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:654
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:1602
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:253
4D data tensor with the physical layout chwn, used in Neon.
Definition: mkldnn_types.h:171
Definition: mkldnn.hpp:265
padding_kind
Definition: mkldnn.hpp:232
The operation failed because of incorrect function arguments.
Definition: mkldnn_types.h:55
Definition: mkldnn.hpp:695
Forward data propagation (alias for mkldnn_forward_inference)
Definition: mkldnn_types.h:447
Definition: mkldnn.hpp:2036
Definition: mkldnn.hpp:1898
Definition: mkldnn.hpp:671
An opaque structure to describe an engine.
Definition: mkldnn.hpp:737
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:1564
Definition: mkldnn.hpp:2820
Backward data propagation.
Definition: mkldnn_types.h:453
Definition: mkldnn.hpp:2434
Definition: mkldnn.hpp:703
static void validate_dims(std::vector< T > v)
Definition: mkldnn.hpp:586
Definition: mkldnn.hpp:3257
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:3247
Definition: mkldnn.hpp:641
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...
Definition: mkldnn.hpp:712
desc(prop_kind aprop_kind, const memory::desc &data_desc, int softmax_axis)
Definition: mkldnn.hpp:2400
Definition: mkldnn.hpp:274
blocked weights format
Definition: mkldnn_types.h:310
blocked weights format
Definition: mkldnn_types.h:383
Definition: mkldnn.hpp:722
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:145
Definition: mkldnn.hpp:679
concat(const primitive_desc &concat_pd, std::vector< primitive::at > &inputs, const memory &output)
Definition: mkldnn.hpp:1142
memory::desc desc()
Returns the memory primitive descriptor.
Definition: mkldnn.hpp:799
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:1997
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...
Definition: mkldnn.hpp:644
float alpha
alpha is a negative slope parameter (used only if (flags & mkldnn_rnn_cell_with_relu) != 0) ...
Definition: mkldnn_types.h:984
Definition: mkldnn.hpp:607
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:607
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:192
algorithm get_activation() const
Definition: mkldnn.hpp:2999
A descriptor of a Softmax operation.
Definition: mkldnn_types.h:830
blocked weights format
Definition: mkldnn_types.h:416
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.
Definition: mkldnn.hpp:658
softmax_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2420
blocked weights format
Definition: mkldnn_types.h:417
blocked data format
Definition: mkldnn_types.h:262
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
Definition: mkldnn.hpp:659
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:938
Definition: mkldnn.hpp:728
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:229
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:3227
An opaque structure for a chain of post operations.
An opaque structure to describe a primitive descriptor.
batch normalization descriptor
Definition: mkldnn_types.h:1231
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:1721
mkldnn_rnn_direction_t
A direction of RNN primitive execution.
Definition: mkldnn_types.h:991
Definition: mkldnn.hpp:655
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:480
primitive_desc(const desc &desc, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1869
mkldnn_lrn_desc_t data
Definition: mkldnn.hpp:2099
mkldnn_status_t MKLDNN_API mkldnn_memory_set_data_handle(mkldnn_primitive_t memory, void *handle)
For a memory primitive, sets the data handle.
Definition: mkldnn.hpp:637
engine(const mkldnn_engine_t &aengine)
Definition: mkldnn.hpp:538
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:287
size_t get_size() const
Returns the number of bytes required to allocate the memory described including the padding area...
Definition: mkldnn.hpp:805
engine(const handle< mkldnn_primitive_desc_t > &pd)
Definition: mkldnn.hpp:541
Definition: mkldnn.hpp:738
engine get_engine()
Definition: mkldnn.hpp:1271
desc(dims adims, data_type adata_type, format aformat)
Constructs a memory descriptor.
Definition: mkldnn.hpp:765
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1044
blocked data format
Definition: mkldnn_types.h:263
const char * impl_info_str() const
Returns implementation name.
Definition: mkldnn.hpp:1287
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 (possi...
Definition: mkldnn.hpp:225
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2797
sum(const primitive_desc &sum_pd, std::vector< primitive::at > &inputs, const memory &output)
Definition: mkldnn.hpp:1231
An execution engine.
Definition: mkldnn.hpp:503
memory(const primitive_desc &adesc, void *ahandle)
Definition: mkldnn.hpp:855
blocked weights format
Definition: mkldnn_types.h:408
Definition: mkldnn.hpp:751
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2865
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 (...
Definition: mkldnn.hpp:615
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
Definition: mkldnn.hpp:714
mkldnn_pooling_desc_t data
Definition: mkldnn.hpp:2237
REG_QUERY_MPD(src, src, 0)
blocked weights format
Definition: mkldnn_types.h:323
int len() const
Definition: mkldnn.hpp:375
Undefined primitive (XXX: why do we have it?).
Definition: mkldnn_types.h:464
Definition: mkldnn.hpp:690
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:494
Packed weights format used in RNN.
Definition: mkldnn_types.h:421
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:910
Definition: mkldnn.hpp:749
Round down.
Definition: mkldnn_types.h:90
4D grouped weights tensor with the physical layout goiw.
Definition: mkldnn_types.h:210
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const softmax_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2449
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:1739
Definition: mkldnn.hpp:696
Definition: mkldnn.hpp:264
Definition: mkldnn.hpp:700
primitive_attr()
Definition: mkldnn.hpp:419
Definition: mkldnn_types.h:538
Definition: mkldnn.hpp:2346
Definition: mkldnn.hpp:633
An unspecified engine.
Definition: mkldnn.hpp:510
Definition: mkldnn.hpp:713
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.
Definition: mkldnn.hpp:596
primitive_desc(const desc &desc, const engine &e, const softmax_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2445
Definition: mkldnn.hpp:677
mkldnn_softmax_desc_t data
Definition: mkldnn.hpp:2435
float get_clipping() const
Definition: mkldnn.hpp:3008
Definition: mkldnn.hpp:2409
Definition: mkldnn.hpp:247
32-bit signed integer.
Definition: mkldnn_types.h:76
memory::primitive_desc query_mpd(query what, int idx=0) const
Queries and returns requested memory primitive descriptor.
Definition: mkldnn.hpp:1312
Definition: mkldnn.hpp:706
primitive_desc(const desc &desc, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2878
Max pooling.
Definition: mkldnn_types.h:533
Definition: mkldnn.hpp:724
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:1423
memory::desc zero_md()
Definition: mkldnn.hpp:899
Definition: mkldnn.hpp:336
primitive_desc(const memory::primitive_desc &input, memory::dims dims, memory::dims offsets)
Definition: mkldnn.hpp:1034
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 values are mkldnn_forwar...
blocked weights format
Definition: mkldnn_types.h:300
blocked weights format
Definition: mkldnn_types.h:322
REG_QUERY_MPD(src, src, 0)
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:2175
Definition: mkldnn.hpp:628
execution engine
Definition: mkldnn_types.h:1207
stream(kind akind)
Constructs a stream.
Definition: mkldnn.hpp:3306
Definition: mkldnn.hpp:1033
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:2866
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 the spatial domain: strides, kernel sizes, padding_l, padding_r, and padding_kind.
Definition: mkldnn.hpp:2172
blocked weights format
Definition: mkldnn_types.h:307
static mkldnn_memory_format_t convert_to_c(format aformat)
Definition: mkldnn.hpp:894
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const eltwise_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2366
Definition: mkldnn.hpp:2690
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:969
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:1237
blocked weights format
Definition: mkldnn_types.h:325
Definition: mkldnn.hpp:744
mkldnn_shuffle_desc_t data
Definition: mkldnn.hpp:3216
5D grouped weights tensor with the physical layout goihw, used in Caffe.
Definition: mkldnn_types.h:214
REG_QUERY_MPD(dst, dst, 0)
const_mkldnn_primitive_t primitive
Primitive to specify the output for.
Definition: mkldnn_types.h:1167
Definition: mkldnn.hpp:289
blocked weights format
Definition: mkldnn_types.h:336
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:3065
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:795
Definition: mkldnn.hpp:699
rnn descriptor
Definition: mkldnn_types.h:1233
An element-wise primitive.
Definition: mkldnn_types.h:484
Definition: mkldnn.hpp:2877
Definition: mkldnn.hpp:2433
REG_QUERY_MPD(src_layer, src, 0)
blocked weights format
Definition: mkldnn_types.h:315
destination grad.
Definition: mkldnn_types.h:1244
Definition: mkldnn.hpp:745
engine get_engine()
Definition: mkldnn.hpp:1228
Definition: mkldnn.hpp:2347
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:979
blocked weights format
Definition: mkldnn_types.h:328
A descriptor for an RNN operation.
Definition: mkldnn_types.h:1006
Definition: mkldnn.hpp:620
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:1400
Definition: mkldnn.hpp:1089
Definition: mkldnn.hpp:277
Definition: mkldnn.hpp:259
eltwise descriptor
Definition: mkldnn_types.h:1227
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:2616
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:1448
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:2753
lrn_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2084
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:2909
batch_normalization_flag
Definition: mkldnn.hpp:288
A memory primitive.
Definition: mkldnn_types.h:466
float clipping
clipping parameter (used only if (flags & mkldnn_rnn_cell_with_clipping) != 0)
Definition: mkldnn_types.h:987
Definition: mkldnn.hpp:697
blocked weights format
Definition: mkldnn_types.h:297
blocked weights format
Definition: mkldnn_types.h:309
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:3097
Eltwise: soft_relu.
Definition: mkldnn_types.h:529
Definition: mkldnn.hpp:1532
Definition: mkldnn.hpp:675
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:2833
Definition: mkldnn.hpp:341
Definition: mkldnn.hpp:709
Definition: mkldnn.hpp:645
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.
Definition: mkldnn.hpp:599
RNN cell.
Definition: mkldnn_types.h:544
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2199
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:1760
const post_ops get_post_ops() const
Definition: mkldnn.hpp:460
bool is_null_memory(const const_mkldnn_primitive_t &aprimitive)
Definition: mkldnn.hpp:930
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2882
Definition: mkldnn.hpp:367
Definition: mkldnn.hpp:2864
blocked weights format
Definition: mkldnn_types.h:344
Definition: mkldnn.hpp:1360
Backward weights propagation.
Definition: mkldnn_types.h:455
void set_int_output_round_mode(round_mode mode)
Definition: mkldnn.hpp:433
mkldnn_rnn_desc_t data
Definition: mkldnn.hpp:3025
blocked weights format
Definition: mkldnn_types.h:411
Definition: mkldnn.hpp:669
32-bit/single-precision floating point.
Definition: mkldnn_types.h:74
Definition: mkldnn.hpp:743
blocked weights format
Definition: mkldnn_types.h:275
blocked data format
Definition: mkldnn_types.h:260
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:1584
pooling_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2210
2D weights tensor with physical layout oi.
Definition: mkldnn_types.h:180
Just a sentinel, not real memory format.
Definition: mkldnn_types.h:425
Memory descriptor.
Definition: mkldnn_types.h:692
Definition: mkldnn.hpp:719
Definition: mkldnn.hpp:2796
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:3234
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve.
Definition: mkldnn_types.h:561
void set_clipping(float clipping)
Definition: mkldnn.hpp:3009
convolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights)
Definition: mkldnn.hpp:1676
mkldnn_lrn_desc_t data
Definition: mkldnn.hpp:2037
Definition: mkldnn.hpp:2795
desc(prop_kind aprop_kind, const memory::desc &src_desc, T epsilon, unsigned flags)
Definition: mkldnn.hpp:2484
Definition: mkldnn.hpp:280
Definition: mkldnn.hpp:608
pooling descriptor
Definition: mkldnn_types.h:1229
Definition: mkldnn.hpp:2236
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
Definition: mkldnn.hpp:631
REG_QUERY_MPD(src, src, 0)
mkldnn_pooling_desc_t data
Definition: mkldnn.hpp:2174
Definition: mkldnn.hpp:267
blocked weights format
Definition: mkldnn_types.h:274
blocked data format
Definition: mkldnn_types.h:264
3D weights tensor with physical layout wio.
Definition: mkldnn_types.h:189
Definition: mkldnn.hpp:701
blocked weights format
Definition: mkldnn_types.h:393
blocked weights format
Definition: mkldnn_types.h:343
Definition: mkldnn.hpp:630
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...
memory::primitive_desc mean_primitive_desc() const
Definition: mkldnn.hpp:2506
Definition: mkldnn.hpp:725
unsigned int flags
RNN cell flags.
Definition: mkldnn_types.h:981
Definition: mkldnn.hpp:647
3D data tensor with the physical layout ncw.
Definition: mkldnn_types.h:159
blocked weights format
Definition: mkldnn_types.h:313
bool operator!=(const primitive_desc &other) const
Definition: mkldnn.hpp:814
convolution_backward_data(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &weights, const memory &diff_src)
Definition: mkldnn.hpp:1546
The operation was successful.
Definition: mkldnn_types.h:49
Definition: mkldnn.hpp:632
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:403
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:367
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2935
primitive_desc(const desc &desc, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1648
desc(algorithm kind, algorithm activation_f)
Definition: mkldnn.hpp:2987
blocked weights format
Definition: mkldnn_types.h:381
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:1259
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:409
mkldnn_rnn_desc_t data
Definition: mkldnn.hpp:3096
Definition: mkldnn.hpp:653
bool operator==(const primitive_desc &other) const
Definition: mkldnn.hpp:809
Backward propagation (with respect to all parameters.
Definition: mkldnn_types.h:451
5D data tensor with the physical layout ndhwc, used in TensorFlow.
Definition: mkldnn_types.h:177
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:2959
softmax descriptor
Definition: mkldnn_types.h:1228
mkldnn_round_mode_t
Rounding mode.
Definition: mkldnn_types.h:86
A deconvolution primitive.
Definition: mkldnn_types.h:482
Definition: mkldnn.hpp:330
Definition: mkldnn.hpp:275
primitive_desc(const desc &adesc, const engine &aengine)
Constructs a memory primitive descriptor.
Definition: mkldnn.hpp:789
Use global statistics.
Definition: mkldnn_types.h:574
primitive_desc(int concat_dimension, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1114
Definition: mkldnn.hpp:668
blocked weights format
Definition: mkldnn_types.h:314
Definition: mkldnn.hpp:636
no query
Definition: mkldnn_types.h:1205
Definition: mkldnn.hpp:2907
int get_gates_count() const
Definition: mkldnn.hpp:3014
Definition: mkldnn.hpp:1700
blocked weights format
Definition: mkldnn_types.h:395
blocked weights format
Definition: mkldnn_types.h:330
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 offsets offsets...
8-bit unsigned integer.
Definition: mkldnn_types.h:82
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1127
REG_QUERY_MPD(src, src, 0)
bool operator==(const T other) const
Definition: mkldnn.hpp:61
Definition: mkldnn.hpp:664
blocked weights format
Definition: mkldnn_types.h:407
Definition: mkldnn.hpp:346
Average pooling include padding.
Definition: mkldnn_types.h:535
Unspecified format.
Definition: mkldnn_types.h:148
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:2891
Definition: mkldnn.hpp:2058
destination memory primitive desc
Definition: mkldnn_types.h:1243
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: mkldnn_types.h:239
GRU cell with linear before reset.
Definition: mkldnn_types.h:557
memory(const primitive_desc &adesc)
Constructs a memory primitive.
Definition: mkldnn.hpp:828
Definition: mkldnn.hpp:649
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:2136
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:540
Definition: mkldnn.hpp:698
REG_QUERY_MPD(src, src, 0)
blocked weights format
Definition: mkldnn_types.h:296
GRU cell.
Definition: mkldnn_types.h:548
Eager stream.
Definition: mkldnn_types.h:1258
primitive_desc(const memory::primitive_desc &input, const memory::primitive_desc &output, const primitive_attr &aattr)
Definition: mkldnn.hpp:984
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:1218
CPU engine.
Definition: mkldnn.hpp:512
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:1938
Definition: mkldnn.hpp:1361
desc(const memory::desc &diff_data_desc, int axis, int group_size)
Definition: mkldnn.hpp:3250
Definition: mkldnn.hpp:3248
Definition: mkldnn.hpp:256
pooling_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2274
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 a pointer to a constant floating point array of output ...
3D weights tensor with physical layout oiw.
Definition: mkldnn_types.h:186
Eltwise: parametric exponential linear unit (elu)
Definition: mkldnn_types.h:517
void set_data_handle(void *handle) const
Definition: mkldnn.hpp:885
REG_QUERY_MPD(src, src, 0)
kind
Kinds of engines.
Definition: mkldnn.hpp:508
Definition: mkldnn.hpp:2098
Definition: mkldnn.hpp:2863
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2413
Definition: mkldnn.hpp:693
Intel(R) MKL-DNN exception class.
Definition: mkldnn.hpp:161
round_mode
Definition: mkldnn.hpp:223
Definition: mkldnn.hpp:747
bool operator==(mkldnn_data_type_t a, memory::data_type b)
Definition: mkldnn.hpp:939
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1827
Eltwise: ReLU.
Definition: mkldnn_types.h:513
Definition: mkldnn.hpp:2397
mkldnn_convolution_desc_t data
Definition: mkldnn.hpp:1362
Definition: mkldnn.hpp:233
1D data tensor.
Definition: mkldnn_types.h:154
REG_QUERY_MPD(diff_src, diff_src, 0)
REG_QUERY_MPD(src, src, 0)
mkldnn_primitive_at_t data
The underlying C API structure.
Definition: mkldnn.hpp:136
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const batch_normalization_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2695
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:3134
Definition: mkldnn.hpp:705
primitive_desc(const desc &desc, const engine &e, const shuffle_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:3258
4D weights tensor with physical layout ihwo.
Definition: mkldnn_types.h:198
mkldnn_eltwise_desc_t data
Definition: mkldnn.hpp:2348
mkldnn_memory_format_t
Memory format specification.
Definition: mkldnn_types.h:143
Definition: mkldnn.hpp:1032
Eltwise: square.
Definition: mkldnn_types.h:519
Definition: mkldnn.hpp:609
Definition: mkldnn.hpp:1166
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:1382
REG_QUERY_MPD(src_layer, src, 0)
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 an eltwise_desc for forward propagation using prop_kind (possible values are mkldnn_forwa...
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:891
4D data tensor with the physical layout nhwc, used in TensorFlow.
Definition: mkldnn_types.h:168
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst, const memory &mean, const memory &variance)
Definition: mkldnn.hpp:2591
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:2100
Definition: mkldnn.hpp:616
Backward bias propagation.
Definition: mkldnn_types.h:457
Definition: mkldnn.hpp:973
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, int local_size, float alpha, float beta)
Definition: mkldnn.hpp:2047
blocked weights format
Definition: mkldnn_types.h:404
Use scale and shift parameters.
Definition: mkldnn_types.h:587
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:1702
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:365
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.
Definition: mkldnn.hpp:661
blocked weights format
Definition: mkldnn_types.h:295
blocked weights format
Definition: mkldnn_types.h:382
A descriptor of a shuffle operation.
Definition: mkldnn_types.h:778
Definition: mkldnn_types.h:1001
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...
memory::primitive_desc dst_primitive_desc() const
Definition: mkldnn.hpp:1215
mkldnn_eltwise_desc_t data
Definition: mkldnn.hpp:2310
primitive_desc(const desc &desc, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1983
Definition: mkldnn.hpp:418
blocked weights format
Definition: mkldnn_types.h:398
REG_QUERY_MPD(diff_src, diff_src, 0)
blocked weights format
Definition: mkldnn_types.h:339
Definition: mkldnn.hpp:1868
Definition: mkldnn.hpp:688
REG_QUERY_MPD(src, src, 0)
int ndims
Number of dimensions.
Definition: mkldnn_types.h:697
reorder(const primitive_desc &aprimitive_desc, const primitive::at &input, const memory &output)
Definition: mkldnn.hpp:997
Definition: mkldnn.hpp:2035
Definition: mkldnn.hpp:1090
kind
A proxy to C primitive kind enum.
Definition: mkldnn.hpp:113
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:358
5D grouped weights tensor with the physical layout giohw.
Definition: mkldnn_types.h:221
An opaque structure to describe an execution stream.
void set_alpha(float alpha)
Definition: mkldnn.hpp:3003
bool operator!=(const T other) const
Definition: mkldnn.hpp:62
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 an 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:2110
Definition: mkldnn.hpp:656
5D data tensor with the physical layout ncdhw.
Definition: mkldnn_types.h:174
Definition: mkldnn.hpp:3215
Definition: mkldnn.hpp:621
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:232
Definition: mkldnn.hpp:2122
Definition: mkldnn.hpp:741
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:1561
Definition: mkldnn.hpp:667
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:1795
REG_QUERY_MPD(diff_src, diff_src, 0)
A rnn primitive.
Definition: mkldnn_types.h:496
Definition: mkldnn.hpp:685
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.
REG_QUERY_MPD(diff_src, diff_src, 0)
blocked weights format
Definition: mkldnn_types.h:324
blocked weights format
Definition: mkldnn_types.h:270
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_size.
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1899
Definition: mkldnn.hpp:623
Definition: mkldnn.hpp:2984
eltwise_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2375
mkldnn_prop_kind_t
Kinds of propagation.
Definition: mkldnn_types.h:435
Definition: mkldnn.hpp:683
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn.hpp:134
CPU engine.
Definition: mkldnn_types.h:1057
Definition: mkldnn.hpp:291
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:878
desc(algorithm alg_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, T alpha=0, T beta=0)
Definition: mkldnn.hpp:2351
Eltwise: square root.
Definition: mkldnn_types.h:523
Definition: mkldnn.hpp:731
Definition: mkldnn.hpp:739
Definition: mkldnn.hpp:692
blocked weights format
Definition: mkldnn_types.h:277
mkldnn_stream_kind_t
Kinds of streams.
Definition: mkldnn_types.h:1254
REG_QUERY_MPD(src, src, 0)
Definition: mkldnn.hpp:271
Definition: mkldnn.hpp:681
Definition: mkldnn.hpp:610
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:195
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn_types.h:1165
Winograd convolution.
Definition: mkldnn_types.h:505
Definition: mkldnn.hpp:638
Definition: mkldnn.hpp:246
Definition: mkldnn.hpp:343
Eltwise: linear.
Definition: mkldnn_types.h:525
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:1828
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:1900
reorder(const primitive::at &input, const memory &output)
Definition: mkldnn.hpp:1008
Eltwise: logistic.
Definition: mkldnn_types.h:531
Definition: mkldnn.hpp:2675
Direct convolution.
Definition: mkldnn_types.h:503
Primitive iterator passed over last primitive descriptor.
Definition: mkldnn_types.h:62
Definition: mkldnn.hpp:338
Definition: mkldnn.hpp:270
Definition: mkldnn.hpp:721
lrn_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &workspace, const memory &dst)
Definition: mkldnn.hpp:2070
source gradient memory primitive desc
Definition: mkldnn_types.h:1240
mkldnn_alg_kind_t cell_kind
RNN cell kind.
Definition: mkldnn_types.h:976
Definition: mkldnn.hpp:1489
mkldnn_batch_normalization_desc_t data
Definition: mkldnn.hpp:2677
Definition: mkldnn_types.h:993
An opaque structure for primitive descriptor attributes.
Definition: mkldnn.hpp:312
blocked data format
Definition: mkldnn_types.h:266
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...
blocked weights format
Definition: mkldnn_types.h:329
desc(prop_kind aprop_kind, algorithm aalgorithm, const memory::desc &src_desc, int local_size, float alpha, float beta, float k)
Definition: mkldnn.hpp:2038
void get_output_scales(int &mask, std::vector< float > &scales) const
Definition: mkldnn.hpp:439
batch_normalization_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:2647
Definition: mkldnn.hpp:3299
Definition: mkldnn.hpp:748
mkldnn_rnn_cell_desc_t c_rnn_cell_
Definition: mkldnn.hpp:2985
runtime estimation (seconds)
Definition: mkldnn_types.h:1213
blocked weights format
Definition: mkldnn_types.h:397
Definition: mkldnn.hpp:1647
A (in-place) concat primitive.
Definition: mkldnn_types.h:476
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.
Definition: mkldnn.hpp:660
blocked weights format
Definition: mkldnn_types.h:298
Definition: mkldnn.hpp:673
LSTM cell.
Definition: mkldnn_types.h:546
blocked weights format
Definition: mkldnn_types.h:280
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.hpp:740
Definition: mkldnn_types.h:1002
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2495
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2821
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2824
Undefined data type, used for empty memory descriptors.
Definition: mkldnn_types.h:72
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:353
Definition: mkldnn.hpp:1825
16-bit signed integer.
Definition: mkldnn_types.h:78
Definition: mkldnn.hpp:2309
A shuffle primitive.
Definition: mkldnn_types.h:472
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:305
Definition: mkldnn.hpp:624
mkldnn_shuffle_desc_t data
Definition: mkldnn.hpp:3249
primitive_desc()
Definition: mkldnn.hpp:786
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.
blocked weights format
Definition: mkldnn_types.h:312
primitive_desc(const memory::desc &output, const std::vector< float > &scales, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1178
desc(prop_kind aprop_kind, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc)
Definition: mkldnn.hpp:2809
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...
blocked data format
Definition: mkldnn_types.h:258
Definition: mkldnn.hpp:1782
Definition: mkldnn.hpp:242
blocked weights format
Definition: mkldnn_types.h:331
Definition: mkldnn.hpp:2930
Definition: mkldnn.hpp:676
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:1490
REG_QUERY_MPD(diff_src, diff_src, 0)
blocked weights format
Definition: mkldnn_types.h:321
A (out-of-place) concat primitive.
Definition: mkldnn_types.h:474
REG_QUERY_MPD(src, src, 0)
blocked weights format
Definition: mkldnn_types.h:340
Definition: mkldnn.hpp:629
Fuse with ReLU.
Definition: mkldnn_types.h:596
Definition: mkldnn.hpp:746
Definition: mkldnn.hpp:678
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:1204
A descriptor of a Batch Normalization operation.
Definition: mkldnn_types.h:907
Definition: mkldnn.hpp:691
static engine query(const primitive_desc &pd)
Definition: mkldnn.hpp:551
Definition: mkldnn.hpp:3023
blocked weights format
Definition: mkldnn_types.h:354
deconvolution_backward_weights(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_weights)
Definition: mkldnn.hpp:2011
blocked data format
Definition: mkldnn_types.h:265
blocked weights format
Definition: mkldnn_types.h:276
A sum primitive.
Definition: mkldnn_types.h:478
blocked weights format
Definition: mkldnn_types.h:342
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:2770
Definition: mkldnn.hpp:302
Definition: mkldnn.hpp:627
blocked weights format
Definition: mkldnn_types.h:392
eltwise_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst)
Definition: mkldnn.hpp:2333
blocked weights format
Definition: mkldnn_types.h:282
Definition: mkldnn.hpp:727
unsigned flags
Definition: mkldnn_types.h:934
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:281
blocked weights format
Definition: mkldnn_types.h:345
Definition: mkldnn.hpp:2983
Definition: mkldnn.hpp:595
memory::primitive_desc variance_primitive_desc() const
Definition: mkldnn.hpp:2508
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: mkldnn_types.h:507
softmax_backward(const primitive_desc &aprimitive_desc, const primitive::at &dst, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2459
blocked weights format
Definition: mkldnn_types.h:271
Definition: mkldnn.hpp:3024
Definition: mkldnn.hpp:258
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2323
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:399
mkldnn_status_t MKLDNN_API mkldnn_stream_rerun(mkldnn_stream_t stream, mkldnn_primitive_t *error_primitive)
Reruns all the primitives within the stream.
float get_alpha() const
Definition: mkldnn.hpp:3002
2D weights tensor with physical layout io.
Definition: mkldnn_types.h:183
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:1214
blocked weights format
Definition: mkldnn_types.h:335
An batch normalization primitive.
Definition: mkldnn_types.h:492
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:501
engine(kind akind, size_t index)
Constructs an engine.
Definition: mkldnn.hpp:529
Definition: mkldnn.hpp:2308
A descriptor of a pooling operation.
Definition: mkldnn_types.h:846
Definition: mkldnn.hpp:639
Definition: mkldnn.hpp:3295
Definition: mkldnn.hpp:272
Definition: mkldnn.hpp:273
engine get_engine()
Definition: mkldnn.hpp:818
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:1987
const_mkldnn_primitive_desc_t get_primitive_desc() const
Returns the descriptor of the underlying C API primitive.
Definition: mkldnn.hpp:210
deconvolution descriptor
Definition: mkldnn_types.h:1225
std::vector< const_mkldnn_primitive_desc_t > cpp_to_c(std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1168
blocked weights format
Definition: mkldnn_types.h:347
shuffle_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:3266
primitive_desc(const memory::primitive_desc &input, const memory::primitive_desc &output)
Definition: mkldnn.hpp:975
void get_params_eltwise(int index, float &scale, algorithm &alg, float &alpha, float &beta) const
Definition: mkldnn.hpp:402
primitive_desc(const desc &desc, const engine &e, const pooling_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2261
mkldnn_memory_desc_t data
The underlying C API data structure.
Definition: mkldnn.hpp:758
mkldnn_primitive_desc_t MKLDNN_API mkldnn_primitive_desc_iterator_fetch(const_mkldnn_primitive_desc_iterator_t iterator)
Fetches the current primitive descriptor.
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:1451
engine get_engine()
Definition: mkldnn.hpp:994
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:80
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:431
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:2322
friend struct error
Definition: mkldnn.hpp:107
desc(const memory::desc &src_desc, const memory::desc &diff_weights_desc, const memory::desc &diff_dst_desc)
Definition: mkldnn.hpp:2919
Definition: mkldnn.hpp:729
source memory primitive desc
Definition: mkldnn_types.h:1239
mkldnn_primitive_kind_t
Kinds of primitives.
Definition: mkldnn_types.h:462
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const deconvolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1873
Definition: mkldnn.hpp:711
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:1960
REG_QUERY_MPD(diff_src, diff_src, 0)
Definition: mkldnn.hpp:3226
Winograd deconvolution.
Definition: mkldnn_types.h:511
Definition: mkldnn.hpp:3300
Definition: mkldnn.hpp:248
number of inputs expected
Definition: mkldnn_types.h:1210
mkldnn_softmax_desc_t data
Definition: mkldnn.hpp:2399
Definition: mkldnn.hpp:345
Definition: mkldnn.hpp:657
Definition: mkldnn.hpp:3048
Definition: mkldnn.hpp:2676
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2498
Definition: mkldnn.hpp:2481
desc(prop_kind aprop_kind, algorithm alg_kind, const memory::desc &src_desc, T alpha=0, T beta=0)
Definition: mkldnn.hpp:2312
An unspecified engine.
Definition: mkldnn_types.h:1256
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:1783
A view primitive.
Definition: mkldnn_types.h:468
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:3095
Definition: mkldnn.hpp:262
Definition: mkldnn.hpp:666
Definition: mkldnn.hpp:328
Definition: mkldnn.hpp:750
Definition: mkldnn.hpp:622
Definition: mkldnn.hpp:3129
Definition: mkldnn.hpp:742
blocked weights format
Definition: mkldnn_types.h:311
mkldnn_primitive_kind_t convert_to_c(primitive::kind akind)
Definition: mkldnn.hpp:154
Definition: mkldnn.hpp:718
Definition: mkldnn.hpp:734
Definition: mkldnn.hpp:704
Definition: mkldnn.hpp:1562
blocked data format
Definition: mkldnn_types.h:261
Definition: mkldnn.hpp:340
Definition: mkldnn.hpp:717
Definition: mkldnn.hpp:331
Definition: mkldnn.hpp:323
Definition: mkldnn.hpp:333
Average pooling exclude padding.
Definition: mkldnn_types.h:537
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.
Definition: mkldnn_types.h:972
Forward data propagation (inference mode).
Definition: mkldnn_types.h:445
6D grouped weights tensor with the physical layout goidhw, used in Caffe.
Definition: mkldnn_types.h:225
Definition: mkldnn.hpp:687
5D weights tensor with physical layout iodhw, used in Caffe.
Definition: mkldnn_types.h:204
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:2538
Direct deconvolution.
Definition: mkldnn_types.h:509
Eltwise: abs.
Definition: mkldnn_types.h:521
int get_state_count() const
Definition: mkldnn.hpp:3017
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:2560
blocked weights format
Definition: mkldnn_types.h:369
pooling_backward(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &workspace, const memory &diff_src)
Definition: mkldnn.hpp:2286
bool operator==(const handle &other) const
Definition: mkldnn.hpp:87
blocked weights format
Definition: mkldnn_types.h:299
A memory descriptor.
Definition: mkldnn.hpp:755
deconvolution_backward_data(const primitive_desc &aprimitive_desc, const primitive::at &diff_dst, const primitive::at &weights, const memory &diff_src)
Definition: mkldnn.hpp:1882
5D grouped weights tensor with the physical layout hwigo, used in TensorFlow.
Definition: mkldnn_types.h:218
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2326
blocked weights format
Definition: mkldnn_types.h:389
bool operator!=(mkldnn_data_type_t a, memory::data_type b)
Definition: mkldnn.hpp:942
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:515
algorithm get_cell_kind() const
Definition: mkldnn.hpp:2997
mkldnn_inner_product_desc_t data
Definition: mkldnn.hpp:2908
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:1810
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:388
Definition: mkldnn.hpp:646
mkldnn_status_t MKLDNN_API mkldnn_engine_destroy(mkldnn_engine_t engine)
Destroys an engine.
Definition: mkldnn.hpp:682
view(const primitive_desc &view_pd, primitive::at input)
Definition: mkldnn.hpp:1060
blocked weights format
Definition: mkldnn_types.h:348
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:1920
Definition: mkldnn.hpp:663
blocked weights format
Definition: mkldnn_types.h:346
2D data tensor.
Definition: mkldnn_types.h:156
primitive_desc(const desc &desc, const engine &e, const batch_normalization_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2691
Definition: mkldnn.hpp:625
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:2798
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:3345
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 and dif...
Primitive or engine failed on execution.
Definition: mkldnn_types.h:64
memory descriptor for memory and view
Definition: mkldnn_types.h:1223
Definition: mkldnn.hpp:710
view(memory input, memory::dims dims, memory::dims offsets)
Definition: mkldnn.hpp:1069
Definition: mkldnn.hpp:1447
Definition: mkldnn.hpp:266
Definition: mkldnn.hpp:674
An LRN primitive.
Definition: mkldnn_types.h:490
Definition: mkldnn_types.h:998
mkldnn_padding_kind_t
Kinds of padding.
Definition: mkldnn_types.h:429
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:3157
Lazy stream.
Definition: mkldnn_types.h:1260
Definition: mkldnn.hpp:332
desc(const memory::desc &diff_desc, const memory::desc &data_desc, int softmax_axis)
Definition: mkldnn.hpp:2436
blocked weights format
Definition: mkldnn_types.h:394
Definition: mkldnn.hpp:304
Definition: mkldnn.hpp:726
blocked weights format
Definition: mkldnn_types.h:273
desc(algorithm kind)
Definition: mkldnn.hpp:2993
Definition: mkldnn.hpp:689
primitive_desc(const desc &desc, const engine &e, const rnn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:3130
Definition: mkldnn.hpp:1826
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: mkldnn_types.h:246
blocked weights format
Definition: mkldnn_types.h:338
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:612
Definition: mkldnn.hpp:640
REG_QUERY_MPD(src, src, 0)
Definition: mkldnn.hpp:2906
Definition: mkldnn.hpp:708
shuffle descriptor
Definition: mkldnn_types.h:1226
Forward data propagation (training mode).
Definition: mkldnn_types.h:441
Definition: mkldnn.hpp:733
Definition: mkldnn.hpp:665
Definition: mkldnn.hpp:344
primitive_desc(const desc &desc, const engine &e, const lrn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2123
Definition: mkldnn.hpp:626
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:2945
mkldnn_convolution_desc_t data
Definition: mkldnn.hpp:1563
memory(const primitive &aprimitive)
Constructs a memory primitive from a generic primitive.
Definition: mkldnn.hpp:824
3D data tensor with the physical layout nwc.
Definition: mkldnn_types.h:162
engine get_engine()
Definition: mkldnn.hpp:1139
Definition: mkldnn.hpp:613
post_ops()
Definition: mkldnn.hpp:368
An opaque structure to describe a primitive.
Definition: mkldnn.hpp:715
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:2731
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: mkldnn_types.h:152
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:1363
mkldnn_data_type_t
Data type specification.
Definition: mkldnn_types.h:70
primitive::kind kind(int index) const
Definition: mkldnn.hpp:377
Definition: mkldnn.hpp:1488
Definition: mkldnn.hpp:600
Definition: mkldnn.hpp:662
Definition: mkldnn.hpp:643
Definition: mkldnn.hpp:611
Definition: mkldnn.hpp:325
Definition: mkldnn.hpp:318
convolution descriptor
Definition: mkldnn_types.h:1224
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1537
Definition: mkldnn.hpp:707
Definition: mkldnn.hpp:606
A memory primitive descriptor.
Definition: mkldnn.hpp:782
Definition: mkldnn.hpp:314
Definition: mkldnn.hpp:2444
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:326
primitive_desc(const desc &desc, const engine &e, const convolution_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:1533
blocked weights format
Definition: mkldnn_types.h:317
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:2661
Eltwise: bounded_relu.
Definition: mkldnn_types.h:527
Definition: mkldnn.hpp:2398
Definition: mkldnn_types.h:995
convolution_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &weights, const memory &dst)
Definition: mkldnn.hpp:1473
Definition: mkldnn.hpp:735
Definition: mkldnn.hpp:694
Definition: mkldnn.hpp:617
mkldnn_engine_kind_t
Kinds of engines.
Definition: mkldnn_types.h:1053
Definition: mkldnn_types.h:968
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:66
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:3049
blocked weights format
Definition: mkldnn_types.h:414
blocked weights format
Definition: mkldnn_types.h:366
Memory primitive that describes the data.
Definition: mkldnn.hpp:579
Weights format used in 8bit Winograd convolution.
Definition: mkldnn_types.h:419
Definition: mkldnn.hpp:327
primitive_desc(const desc &desc, const engine &e)
Definition: mkldnn.hpp:2059
Definition: mkldnn.hpp:2097
Definition: mkldnn.hpp:301
Round nearest.
Definition: mkldnn_types.h:88
blocked weights format
Definition: mkldnn_types.h:413
Definition: mkldnn.hpp:243
Definition: mkldnn.hpp:3298
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:2712
Definition: mkldnn.hpp:1699
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: mkldnn_types.h:686
static mkldnn_stream_kind_t convert_to_c(kind akind)
Definition: mkldnn.hpp:3302
blocked weights format
Definition: mkldnn_types.h:272
blocked weights format
Definition: mkldnn_types.h:410
Definition: mkldnn.hpp:1897
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:2480
pooling_forward(const primitive_desc &aprimitive_desc, const primitive::at &src, const memory &dst, const memory &workspace)
Definition: mkldnn.hpp:2222
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:1460
4D weights tensor with physical layout iohw.
Definition: mkldnn_types.h:201
A reorder primitive.
Definition: mkldnn_types.h:470
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:1786
rnn_direction
Definition: mkldnn.hpp:299
primitive_attr get_primitive_attr() const
Definition: mkldnn.hpp:1273
Definition: mkldnn.hpp:672
primitive_desc(const std::vector< float > &scales, std::vector< memory::primitive_desc > inputs)
Definition: mkldnn.hpp:1197
blocked weights format
Definition: mkldnn_types.h:390
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:380
blocked weights format
Definition: mkldnn_types.h:320
Definition: mkldnn.hpp:635
An unspecified engine.
Definition: mkldnn_types.h:1055
desc(const mkldnn_memory_desc_t &adata)
Constructs a memory descriptor from a C API data structure.
Definition: mkldnn.hpp:778
blocked weights format
Definition: mkldnn_types.h:341
Definition: mkldnn.hpp:597
Definition: mkldnn.hpp:1167
int MKLDNN_API mkldnn_post_ops_len(const_mkldnn_post_ops_t post_ops)
Returns the length of post operations for given post_ops.
primitive_desc get_primitive_desc() const
Returns the descriptor of the memory primitive.
Definition: mkldnn.hpp:865
engine get_engine()
Definition: mkldnn.hpp:1057
Definition: mkldnn.hpp:684
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const pooling_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2265
friend class primitive_at
Definition: mkldnn.hpp:109
blocked weights format
Definition: mkldnn_types.h:391
Definition: mkldnn.hpp:720
blocked weights format
Definition: mkldnn_types.h:368
mkldnn_alg_kind_t
Kinds of algorithms.
Definition: mkldnn_types.h:500
Definition: mkldnn.hpp:716
primitive_desc(const desc &desc, const engine &e, const inner_product_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2931
Definition: mkldnn.hpp:263
inner product descriptor
Definition: mkldnn_types.h:1232
blocked weights format
Definition: mkldnn_types.h:375
void get_params_sum(int index, float &scale) const
Definition: mkldnn.hpp:390
A pooling primitive.
Definition: mkldnn_types.h:488
Definition: mkldnn.hpp:723
REG_QUERY_MPD(src, src, 0)
weights memory primitive descriptor desc
Definition: mkldnn_types.h:1241
output memory primitive desc
Definition: mkldnn_types.h:1238
Definition: mkldnn.hpp:2260
blocked weights format
Definition: mkldnn_types.h:396
5D weights tensor with physical layout dhwio, used in TensorFlow.
Definition: mkldnn_types.h:207
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e)
Definition: mkldnn.hpp:2062
mkldnn_batch_normalization_desc_t data
Definition: mkldnn.hpp:2482
Definition: mkldnn.hpp:974
mkldnn_status_t MKLDNN_API mkldnn_primitive_destroy(mkldnn_primitive_t primitive)
Deletes a primitive.
Definition: mkldnn.hpp:334
Definition: mkldnn.hpp:634
std::string message
Definition: mkldnn.hpp:163
Definition: mkldnn.hpp:3214
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.
Definition: mkldnn.hpp:651
primitive_desc(const desc &desc, const engine &e, const eltwise_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2362
Definition: mkldnn.hpp:2494
Definition: mkldnn.hpp:315
blocked weights format
Definition: mkldnn_types.h:308
handle(const handle &other)
Definition: mkldnn.hpp:71
Forward data propagation (alias for mkldnn_forward_training)
Definition: mkldnn_types.h:449
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: mkldnn_types.h:227
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:1230
Definition: mkldnn.hpp:670
workspace memory primitive desc
Definition: mkldnn_types.h:1245
lrn_backward(const primitive_desc &aprimitive_desc, const primitive::at &src, const primitive::at &diff_dst, const memory &diff_src)
Definition: mkldnn.hpp:2150
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:1624
bool next_impl()
Advances the next implementation for the given op descriptor.
Definition: mkldnn.hpp:1301
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...
Definition: mkldnn.hpp:619
blocked weights format
Definition: mkldnn_types.h:269
blocked weights format
Definition: mkldnn_types.h:278
mkldnn_deconvolution_desc_t data
Definition: mkldnn.hpp:1701
Definition: mkldnn.hpp:642
desc(prop_kind aprop_kind, const memory::desc &diff_data_desc, const memory::desc &data_desc, T epsilon, unsigned flags)
Definition: mkldnn.hpp:2679
REG_QUERY_MPD(src, src, 0)
blocked weights format
Definition: mkldnn_types.h:327
Definition: mkldnn.hpp:224
weights format with additional buffer size equal to the number of output channels and containing the ...
Definition: mkldnn_types.h:294
Definition: mkldnn.hpp:736
Definition: mkldnn.hpp:614
Definition: mkldnn.hpp:686
round_mode get_int_output_round_mode() const
Definition: mkldnn.hpp:426
primitive_desc(const desc &desc, const primitive_attr &attr, const engine &e, const lrn_forward::primitive_desc &hint_fwd_pd)
Definition: mkldnn.hpp:2127
weights grad.
Definition: mkldnn_types.h:1242
4D data tensor with the physical layout nchw, used in Caffe.
Definition: mkldnn_types.h:165
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.
Definition: mkldnn.hpp:618
void append_eltwise(float scale, algorithm alg, float alpha, float beta)
Definition: mkldnn.hpp:395
primitive kind
Definition: mkldnn_types.h:1208
blocked data format
Definition: mkldnn_types.h:259
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:1846
blocked weights format
Definition: mkldnn_types.h:306
Definition: mkldnn.hpp:317
Definition: mkldnn.hpp:652
An opaque structure to describe a primitive descriptor iterator.
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:2238
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:2575
Definition: mkldnn.hpp:732
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:1491
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:3026
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...