提交 4d2a2e75 编写于 作者: B baiyfbupt

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into develop

......@@ -24,7 +24,7 @@ set(BOOST_PROJECT "extern_boost")
# So we use 1.41.0 here.
set(BOOST_VER "1.41.0")
set(BOOST_TAR "boost_1_41_0")
set(BOOST_URL "http://paddlepaddledeps.bj.bcebos.com/${BOOST_TAR}.tar.gz")
set(BOOST_URL "http://paddlepaddledeps.cdn.bcebos.com/${BOOST_TAR}.tar.gz")
set(BOOST_SOURCES_DIR ${THIRD_PARTY_PATH}/boost)
set(BOOST_DOWNLOAD_DIR "${BOOST_SOURCES_DIR}/src/${BOOST_PROJECT}")
set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}/${BOOST_TAR}" CACHE PATH "boost include directory." FORCE)
......
......@@ -21,11 +21,12 @@ else()
ExternalProject_Add(
extern_eigen3
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/RLovelett/eigen.git"
GIT_REPOSITORY "https://github.com/eigenteam/eigen-git-mirror"
# eigen on cuda9.1 missing header of math_funtions.hpp
# https://stackoverflow.com/questions/43113508/math-functions-hpp-not-found-when-using-cuda-with-eigen
GIT_TAG 917060c364181f33a735dc023818d5a54f60e54c
PREFIX ${EIGEN_SOURCE_DIR}
DOWNLOAD_NAME "eigen"
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
......
......@@ -53,11 +53,9 @@ ExternalProject_Add(
${EXTERNAL_PROJECT_LOG_ARGS}
DEPENDS ${MKLDNN_DEPENDS}
GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git"
GIT_TAG "v0.14"
GIT_TAG "db3424ad44901513c03a1ea31ccaacdf633fbe9f"
PREFIX ${MKLDNN_SOURCES_DIR}
UPDATE_COMMAND ""
# Patch MKLDNN to compile with gcc 4.8, the related issue is in intel/mkl-dnn#237.
PATCH_COMMAND ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/patches/mkldnn.hpp ${MKLDNN_SOURCES_DIR}/src/extern_mkldnn/include/mkldnn.hpp
CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
CMAKE_ARGS -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
CMAKE_ARGS -DMKLROOT=${MKLML_ROOT}
......
......@@ -28,7 +28,7 @@ INCLUDE(ExternalProject)
SET(MKLML_PROJECT "extern_mklml")
SET(MKLML_VER "mklml_lnx_2018.0.3.20180406")
SET(MKLML_URL "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz")
SET(MKLML_URL "http://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.tgz")
SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml")
SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")
SET(MKLML_DST_DIR "mklml")
......
......@@ -98,6 +98,14 @@ elseif (WITH_MKLML)
)
endif()
if(WITH_MKLDNN)
set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/mkldnn")
copy(mkldnn_lib
SRCS ${MKLDNN_INC_DIR} ${MKLDNN_SHARED_LIB}
DSTS ${dst_dir} ${dst_dir}/lib
)
endif()
if(NOT MOBILE_INFERENCE AND NOT RPI)
set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/snappy")
copy(snappy_lib
......
......@@ -186,11 +186,7 @@ endif()
add_subdirectory(detail)
if(WITH_DISTRIBUTE)
if(WITH_GPU)
op_library(gen_nccl_id_op DEPS nccl_common)
else()
set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
endif()
set(DISTRIBUTE_DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
op_library(send_op DEPS ${DISTRIBUTE_DEPS})
......@@ -208,6 +204,12 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
if(WITH_GPU)
op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc)
set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else()
set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
endif()
else()
set(DEPS_OPS ${DEPS_OPS} send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op gen_nccl_id_op)
endif()
......
......@@ -20,19 +20,15 @@
#=================================================
function print_usage() {
RED='\033[0;31m'
BLUE='\033[0;34m'
BOLD='\033[1m'
NONE='\033[0m'
echo -e "\n${RED}Usage${NONE}:
${BOLD}$0${NONE} [OPTION]"
${BOLD}${SCRIPT_NAME}${NONE} [OPTION]"
echo -e "\n${RED}Options${NONE}:
${BLUE}build${NONE}: run build for x86 platform
${BLUE}build_android${NONE}: run build for android platform
${BLUE}build_ios${NONE}: run build for ios platform
${BLUE}test${NONE}: run all unit tests
${BLUE}single_test${NONE}: run a single unit test
${BLUE}bind_test${NONE}: parallel tests bind to different GPU
${BLUE}doc${NONE}: generate paddle documents
${BLUE}html${NONE}: convert C++ source code into HTML
......@@ -45,7 +41,15 @@ function print_usage() {
}
function init() {
RED='\033[0;31m'
BLUE='\033[0;34m'
BOLD='\033[1m'
NONE='\033[0m'
PADDLE_ROOT="$( cd "$( dirname "${BASH_SOURCE[0]}")/../../" && pwd )"
if [ -z "${SCRIPT_NAME}" ]; then
SCRIPT_NAME=$0
fi
}
function cmake_gen() {
......@@ -91,7 +95,6 @@ function cmake_gen() {
-DWITH_AVX=${WITH_AVX:-OFF}
-DWITH_GOLANG=${WITH_GOLANG:-OFF}
-DCUDA_ARCH_NAME=${CUDA_ARCH_NAME:-All}
-DWITH_SWIG_PY=ON
-DWITH_C_API=${WITH_C_API:-OFF}
-DWITH_PYTHON=${WITH_PYTHON:-ON}
-DWITH_SWIG_PY=${WITH_SWIG_PY:-ON}
......@@ -309,6 +312,25 @@ EOF
fi
}
function single_test() {
TEST_NAME=$1
if [ -z "${TEST_NAME}" ]; then
echo -e "${RED}Usage:${NONE}"
echo -e "${BOLD}${SCRIPT_NAME}${NONE} ${BLUE}single_test${NONE} [test_name]"
exit 1
fi
mkdir -p ${PADDLE_ROOT}/build
cd ${PADDLE_ROOT}/build
if [ ${WITH_TESTING:-ON} == "ON" ] ; then
cat <<EOF
========================================
Running ${TEST_NAME} ...
========================================
EOF
ctest --output-on-failure -R ${TEST_NAME}
fi
}
function bind_test() {
# the number of process to run tests
NUM_PROC=6
......@@ -491,6 +513,9 @@ function main() {
test)
run_test
;;
single_test)
single_test $2
;;
bind_test)
bind_test
;;
......
......@@ -63,6 +63,7 @@ EOL
${DOCKER_CMD} run -it \
--name $CONTAINER_ID \
${DOCKER_ENV} \
-e SCRIPT_NAME=$0 \
-v $PADDLE_ROOT:/paddle \
-v ${HOME}/.ccache:/root/.ccache \
-w /paddle \
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
/*******************************************************************************
* Copyright 2016-2018 Intel Corporation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
#ifndef MKLDNN_HPP
#define MKLDNN_HPP
#ifndef DOXYGEN_SHOULD_SKIP_THIS
#include <stdlib.h>
#include <algorithm>
#include <iterator>
#include <memory>
#include <string>
#include <vector>
#include "mkldnn.h"
#endif
namespace mkldnn {
/// @addtogroup cpp_api C++ API
/// @{
/// @addtogroup cpp_api_utils Utils
/// @{
/// A class that provides the destructor for an Intel(R) MKL-DNN C handle
template <typename T>
class handle_traits {};
/// A class for wrapping an Intel(R) MKL-DNN handle. It is used as the base
/// class for primitive (#mkldnn_primitive_t), engine (#mkldnn_engine_t), and
/// stream (#mkldnn_stream_t) handles. An object of the #mkldnn::handle class
/// can be passed by value. This class enables wrapping:
/// - Newly constructed handles.
/// @n In this case, the constructed handle uses reference counting provided
/// by @p std::shared_ptr with a proper deleter function specified through
/// the @p handle_traits class.
/// - Pre-existing handles returned by the Intel(R) MKL-DNN C API (for
/// example, through #mkldnn_primitive_get_output()).
/// @n In this case, an Intel(R) MKL-DNN C API handle is wrapped without a
/// deleter because it is assumed that the handle wrapper for the original
/// object deletes the handle (this model is similar to @p std::weak_ptr).
template <typename T, typename traits = handle_traits<T>>
class handle {
private:
std::shared_ptr<typename std::remove_pointer<T>::type> _data;
handle(const handle &&) = delete;
handle &operator=(const handle &&other) = delete;
protected:
/// Constructs a C handle wrapper.
/// @param t The C handle to wrap.
/// @param weak A flag to specify whether to construct a weak wrapper.
handle(T t = 0, bool weak = false) : _data(0) { reset(t, weak); }
bool operator==(const T other) const { return other == _data.get(); }
bool operator!=(const T other) const { return !(*this == other); }
public:
handle(const handle &other) : _data(other._data) {}
handle &operator=(const handle &other) {
_data = other._data;
return *this;
}
/// Resets the value of a C handle.
/// @param t The new value of the C handle.
/// @param weak A flag to specify whether the wrapper should be weak.
void reset(T t, bool weak = false) {
auto dummy_destructor = [](T) {
return decltype(traits::destructor(0))(0);
};
_data.reset(t, weak ? dummy_destructor : traits::destructor);
}
/// Returns the value of the underlying C handle.
T get() const { return _data.get(); }
bool operator==(const handle &other) const {
return other._data.get() == _data.get();
}
bool operator!=(const handle &other) const { return !(*this == other); }
};
#ifndef DOXYGEN_SHOULD_SKIP_THIS
template <>
struct handle_traits<mkldnn_primitive_desc_t> {
static constexpr auto destructor = &mkldnn_primitive_desc_destroy;
};
template <>
struct handle_traits<mkldnn_primitive_t> {
static constexpr auto destructor = &mkldnn_primitive_destroy;
};
#endif
/// Base class for all computational primitives.
class primitive : public handle<mkldnn_primitive_t> {
friend struct error;
friend struct stream;
friend class primitive_at;
using handle::handle;
public:
/// A proxy to C primitive kind enum
enum class kind {
undefined_primitive = mkldnn_undefined_primitive,
memory = mkldnn_memory,
view = mkldnn_view,
reorder = mkldnn_reorder,
concat = mkldnn_concat,
concat_inplace = mkldnn_concat_inplace,
sum = mkldnn_sum,
convolution = mkldnn_convolution,
deconvolution = mkldnn_deconvolution,
eltwise = mkldnn_eltwise,
relu = mkldnn_relu,
softmax = mkldnn_softmax,
pooling = mkldnn_pooling,
lrn = mkldnn_lrn,
batch_normalization = mkldnn_batch_normalization,
inner_product = mkldnn_inner_product,
convolution_relu = mkldnn_convolution_relu,
rnn = mkldnn_rnn,
};
/// A wrapper structure to specify a particular output of a primitive.
struct at {
/// The underlying C API structure.
mkldnn_primitive_at_t data;
/// Constructs a wrapper specifying @p aprimitive output with index @p
/// at.
///
/// @param aprimitive The target primitive.
/// @param at The output index.
at(const primitive &aprimitive, size_t at = 0)
: data(mkldnn_primitive_at(aprimitive.get(), at)) {}
/// Returns the specified output.
inline operator primitive() const;
};
/// Returns the descriptor of the underlying C API primitive
inline const_mkldnn_primitive_desc_t get_primitive_desc() const;
// TODO: use the C++ API wrapper structure.
};
inline mkldnn_primitive_kind_t convert_to_c(primitive::kind akind) {
return static_cast<mkldnn_primitive_kind_t>(akind);
}
/// Intel(R) MKL-DNN exception class.
///
/// This class captures the status returned by the failed C API function, error
/// message, and, optionally, handle of the primitive that caused the error.
struct error : public std::exception {
mkldnn_status_t status;
std::string message;
primitive error_primitive;
/// Constructs an error instance.
///
/// @param astatus The error status returned by the C API.
/// @param amessage The error message.
/// @param aerror_primitive (optional) A C handle of the primitive that
/// caused the error.
error(mkldnn_status_t astatus,
std::string amessage,
mkldnn_primitive_t aerror_primitive = 0)
: status(astatus),
message(amessage),
error_primitive(aerror_primitive, true) {}
/// A convenience function for wrapping calls to the C API. Checks the
/// return status and throws an #error in case of failure.
///
/// @param status The error status returned by the C API.
/// @param message The error message.
/// @param error_primitive (optional) A C handle of the primitive that
/// caused the error.
static void wrap_c_api(mkldnn_status_t status,
std::string message,
mkldnn_primitive_t *error_primitive = 0) {
if (status != mkldnn_success) {
if (nullptr != error_primitive)
throw error(status, message, *error_primitive);
else
throw error(status, message, nullptr);
}
}
};
inline primitive::at::operator primitive() const {
const_mkldnn_primitive_t output;
error::wrap_c_api(
mkldnn_primitive_get_output(data.primitive, data.output_index, &output),
"could not get an output primitive");
return primitive(const_cast<mkldnn_primitive_t>(output), true);
}
const_mkldnn_primitive_desc_t primitive::get_primitive_desc() const {
const_mkldnn_primitive_desc_t pd;
error::wrap_c_api(mkldnn_primitive_get_primitive_desc(get(), &pd),
"could not get primitive descriptor by primitive");
return pd;
}
/// @}
/// @addtogroup cpp_api_enums Common data types and enumerations
/// @{
enum round_mode {
round_nearest = mkldnn_round_nearest,
round_down = mkldnn_round_down,
};
inline mkldnn_round_mode_t convert_to_c(round_mode mode) {
return static_cast<mkldnn_round_mode_t>(mode);
}
enum padding_kind { zero = mkldnn_padding_zero };
inline mkldnn_padding_kind_t convert_to_c(padding_kind kind) {
return static_cast<mkldnn_padding_kind_t>(kind);
}
enum prop_kind {
forward_training = mkldnn_forward_training,
forward_scoring = mkldnn_forward_scoring,
forward_inference = mkldnn_forward_inference,
forward = mkldnn_forward,
backward = mkldnn_backward,
backward_data = mkldnn_backward_data,
backward_weights = mkldnn_backward_weights,
backward_bias = mkldnn_backward_bias
};
inline mkldnn_prop_kind_t convert_to_c(prop_kind kind) {
return static_cast<mkldnn_prop_kind_t>(kind);
}
enum algorithm {
algorithm_undef = mkldnn_alg_kind_undef,
convolution_direct = mkldnn_convolution_direct,
convolution_winograd = mkldnn_convolution_winograd,
deconvolution_direct = mkldnn_deconvolution_direct,
deconvolution_winograd = mkldnn_deconvolution_winograd,
eltwise_relu = mkldnn_eltwise_relu,
eltwise_tanh = mkldnn_eltwise_tanh,
eltwise_elu = mkldnn_eltwise_elu,
eltwise_square = mkldnn_eltwise_square,
eltwise_abs = mkldnn_eltwise_abs,
eltwise_sqrt = mkldnn_eltwise_sqrt,
eltwise_linear = mkldnn_eltwise_linear,
eltwise_bounded_relu = mkldnn_eltwise_bounded_relu,
eltwise_soft_relu = mkldnn_eltwise_soft_relu,
eltwise_logistic = mkldnn_eltwise_logistic,
lrn_across_channels = mkldnn_lrn_across_channels,
lrn_within_channel = mkldnn_lrn_within_channel,
pooling_max = mkldnn_pooling_max,
pooling_avg = mkldnn_pooling_avg,
pooling_avg_include_padding = mkldnn_pooling_avg_include_padding,
pooling_avg_exclude_padding = mkldnn_pooling_avg_exclude_padding,
vanilla_rnn = mkldnn_vanilla_rnn,
vanilla_lstm = mkldnn_vanilla_lstm,
vanilla_gru = mkldnn_vanilla_gru,
};
inline mkldnn_alg_kind_t convert_to_c(algorithm aalgorithm) {
return static_cast<mkldnn_alg_kind_t>(aalgorithm);
}
enum batch_normalization_flag {
use_global_stats = mkldnn_use_global_stats,
use_scale_shift = mkldnn_use_scaleshift,
omit_stats = mkldnn_omit_stats,
fuse_bn_relu = mkldnn_fuse_bn_relu
};
inline mkldnn_batch_normalization_flag_t convert_to_c(
batch_normalization_flag aflag) {
return static_cast<mkldnn_batch_normalization_flag_t>(aflag);
}
enum rnn_direction {
unidirectional_left2right = mkldnn_unidirectional_left2right,
unidirectional_right2left = mkldnn_unidirectional_right2left,
unidirectional = mkldnn_unidirectional,
bidirectional_concat = mkldnn_bidirectional_concat,
bidirectional_sum = mkldnn_bidirectional_sum,
};
inline mkldnn_rnn_direction_t convert_to_c(rnn_direction adir) {
return static_cast<mkldnn_rnn_direction_t>(adir);
}
enum query {
undef = mkldnn_query_undef,
eengine = mkldnn_query_engine,
primitive_kind = mkldnn_query_primitive_kind,
num_of_inputs_s32 = mkldnn_query_num_of_inputs_s32,
num_of_outputs_s32 = mkldnn_query_num_of_outputs_s32,
time_estimate_f64 = mkldnn_query_time_estimate_f64,
memory_consumption_s64 = mkldnn_query_memory_consumption_s64,
impl_info_str = mkldnn_query_impl_info_str,
memory_d = mkldnn_query_memory_d,
convolution_d = mkldnn_query_convolution_d,
deconvolution_d = mkldnn_query_deconvolution_d,
eltwise_d = mkldnn_query_eltwise_d,
relu_d = mkldnn_query_relu_d,
softmax_d = mkldnn_query_softmax_d,
pooling_d = mkldnn_query_pooling_d,
lrn_d = mkldnn_query_lrn_d,
batch_normalization_d = mkldnn_query_batch_normalization_d,
inner_product_d = mkldnn_query_inner_product_d,
convolution_relu_d = mkldnn_query_convolution_relu_d,
rnn_d = mkldnn_query_rnn_d,
input_pd = mkldnn_query_input_pd,
output_pd = mkldnn_query_output_pd,
src_pd = mkldnn_query_src_pd,
diff_src_pd = mkldnn_query_diff_src_pd,
weights_pd = mkldnn_query_weights_pd,
diff_weights_pd = mkldnn_query_diff_weights_pd,
dst_pd = mkldnn_query_dst_pd,
diff_dst_pd = mkldnn_query_diff_dst_pd,
workspace_pd = mkldnn_query_workspace_pd,
};
inline mkldnn_query_t convert_to_c(query aquery) {
return static_cast<mkldnn_query_t>(aquery);
}
/// @}
/// @addtogroup cpp_api_attr Attributes
/// @{
#ifndef DOXYGEN_SHOULD_SKIP_THIS
template <>
struct handle_traits<mkldnn_post_ops_t> {
static constexpr auto destructor = &mkldnn_post_ops_destroy;
};
#endif
struct post_ops : public handle<mkldnn_post_ops_t> {
post_ops() {
mkldnn_post_ops_t result;
error::wrap_c_api(mkldnn_post_ops_create(&result),
"could not create post operation sequence");
reset(result);
}
int len() const { return mkldnn_post_ops_len(get()); }
primitive::kind kind(int index) const {
error::wrap_c_api(index < len() ? mkldnn_success : mkldnn_invalid_arguments,
"post_ops index is out of range");
return static_cast<primitive::kind>(mkldnn_post_ops_get_kind(get(), index));
}
void append_sum(float scale = 1.) {
error::wrap_c_api(mkldnn_post_ops_append_sum(get(), scale),
"could not append sum");
}
void get_params_sum(int index, float &scale) const {
error::wrap_c_api(mkldnn_post_ops_get_params_sum(get(), index, &scale),
"could not get sum params");
}
void append_eltwise(float scale, algorithm alg, float alpha, float beta) {
error::wrap_c_api(mkldnn_post_ops_append_eltwise(
get(), scale, convert_to_c(alg), alpha, beta),
"could not append eltwise");
}
void get_params_eltwise(int index,
float &scale,
algorithm &alg,
float &alpha,
float &beta) const {
mkldnn_alg_kind_t c_alg;
error::wrap_c_api(mkldnn_post_ops_get_params_eltwise(
get(), index, &scale, &c_alg, &alpha, &beta),
"could not get eltwise params");
alg = static_cast<algorithm>(c_alg);
}
};
#ifndef DOXYGEN_SHOULD_SKIP_THIS
template <>
struct handle_traits<mkldnn_primitive_attr_t> {
static constexpr auto destructor = &mkldnn_primitive_attr_destroy;
};
#endif
struct primitive_attr : public handle<mkldnn_primitive_attr_t> {
primitive_attr() {
mkldnn_primitive_attr_t result;
error::wrap_c_api(mkldnn_primitive_attr_create(&result),
"could not create a primitive attr");
reset(result);
}
round_mode get_int_output_round_mode() const {
mkldnn_round_mode_t result;
error::wrap_c_api(
mkldnn_primitive_attr_get_int_output_round_mode(get(), &result),
"could not get int output round mode");
return round_mode(result);
}
void set_int_output_round_mode(round_mode mode) {
error::wrap_c_api(mkldnn_primitive_attr_set_int_output_round_mode(
get(), mkldnn::convert_to_c(mode)),
"could not set int output round mode");
}
void get_output_scales(int &mask, std::vector<float> &scales) const {
int count, c_mask;
const float *c_scales;
error::wrap_c_api(mkldnn_primitive_attr_get_output_scales(
get(), &count, &c_mask, &c_scales),
"could not get int output scales");
scales.resize(count);
mask = c_mask;
for (int c = 0; c < count; ++c) scales[c] = c_scales[c];
}
void set_output_scales(int mask, const std::vector<float> &scales) {
error::wrap_c_api(mkldnn_primitive_attr_set_output_scales(
get(), (int)scales.size(), mask, &scales[0]),
"could not set int output scales");
}
const post_ops get_post_ops() const {
post_ops result;
const_mkldnn_post_ops_t c_result;
error::wrap_c_api(mkldnn_primitive_attr_get_post_ops(get(), &c_result),
"could not get post operation sequence");
result.reset(const_cast<mkldnn_post_ops_t>(c_result), true);
return result;
}
void set_post_ops(post_ops ops) {
error::wrap_c_api(mkldnn_primitive_attr_set_post_ops(get(), ops.get()),
"could not set post operation sequence");
}
};
/// @}
/// @addtogroup cpp_api_engine Engine
/// @{
#ifndef DOXYGEN_SHOULD_SKIP_THIS
template <>
struct handle_traits<mkldnn_engine_t> {
static constexpr auto destructor = &mkldnn_engine_destroy;
};
#endif
/// An execution engine.
struct engine : public handle<mkldnn_engine_t> {
friend class primitive;
// gcc bug??? using handle::handle;
/// Kinds of engines
enum kind {
/// An unspecified engine
any = mkldnn_any_engine,
/// CPU engine
cpu = mkldnn_cpu,
};
/// Returns the number of engines of a certain kind.
///
/// @param akind The kind of engines to count.
static size_t get_count(kind akind) {
return mkldnn_engine_get_count(convert_to_c(akind));
}
/// Constructs an engine.
///
/// @param akind The kind of engine to construct.
/// @param index The index of the engine. Must be less than the value
/// returned by #get_count() for this particular kind of engine.
engine(kind akind, size_t index) {
mkldnn_engine_t aengine;
error::wrap_c_api(
mkldnn_engine_create(&aengine, convert_to_c(akind), index),
"could not create an engine");
reset(aengine);
}
explicit engine(const mkldnn_engine_t &aengine) : handle(aengine, true) {}
engine(const handle<mkldnn_primitive_desc_t> &pd) {
mkldnn_engine_t engine_q;
error::wrap_c_api(
mkldnn_primitive_desc_query(
pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
"could not get engine from primitive_desc");
reset(engine_q, true);
}
template <class primitive_desc>
static engine query(const primitive_desc &pd) {
mkldnn_engine_t engine_q;
error::wrap_c_api(
mkldnn_primitive_desc_query(
pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
"could not get engine from primitive_desc");
return engine(engine_q);
}
private:
static mkldnn_engine_kind_t convert_to_c(kind akind) {
return static_cast<mkldnn_engine_kind_t>(akind);
}
};
/// @}
/// @addtogroup cpp_api_primitives Primitives
/// @{
/// @addtogroup cpp_api_memory Memory
/// @{
/// Memory primitive that describes the data.
struct memory : public primitive {
private:
std::shared_ptr<char> _handle;
public:
typedef std::vector<std::remove_extent<mkldnn_dims_t>::type> dims;
template <typename T>
static void validate_dims(std::vector<T> v) {
if (v.size() > TENSOR_MAX_DIMS)
throw error(mkldnn_invalid_arguments, "invalid dimensions");
}
/// Data type specification. See #mkldnn_data_type_t for a detailed
/// description.
enum data_type {
data_undef = mkldnn_data_type_undef,
f32 = mkldnn_f32,
s32 = mkldnn_s32,
s16 = mkldnn_s16,
s8 = mkldnn_s8,
u8 = mkldnn_u8,
};
/// Memory format specification. See #mkldnn_memory_format_t
/// for a detailed description.
enum format {
format_undef = mkldnn_format_undef,
any = mkldnn_any,
blocked = mkldnn_blocked,
x = mkldnn_x,
nc = mkldnn_nc,
nchw = mkldnn_nchw,
nhwc = mkldnn_nhwc,
chwn = mkldnn_chwn,
nChw8c = mkldnn_nChw8c,
nChw16c = mkldnn_nChw16c,
ncdhw = mkldnn_ncdhw,
ndhwc = mkldnn_ndhwc,
nCdhw16c = mkldnn_nCdhw16c,
oi = mkldnn_oi,
io = mkldnn_io,
oihw = mkldnn_oihw,
ihwo = mkldnn_ihwo,
hwio = mkldnn_hwio,
oidhw = mkldnn_oidhw,
OIdhw16i16o = mkldnn_OIdhw16i16o,
OIdhw16o16i = mkldnn_OIdhw16o16i,
Oidhw16o = mkldnn_Oidhw16o,
Odhwi16o = mkldnn_Odhwi16o,
oIhw8i = mkldnn_oIhw8i,
oIhw16i = mkldnn_oIhw16i,
OIhw8i8o = mkldnn_OIhw8i8o,
OIhw16i16o = mkldnn_OIhw16i16o,
OIhw8o8i = mkldnn_OIhw8o8i,
OIhw16o16i = mkldnn_OIhw16o16i,
IOhw16o16i = mkldnn_IOhw16o16i,
OIhw8i16o2i = mkldnn_OIhw8i16o2i,
OIhw8o16i2o = mkldnn_OIhw8o16i2o,
OIhw4i16o4i = mkldnn_OIhw4i16o4i,
Oihw8o = mkldnn_Oihw8o,
Oihw16o = mkldnn_Oihw16o,
Ohwi8o = mkldnn_Ohwi8o,
Ohwi16o = mkldnn_Ohwi16o,
OhIw16o4i = mkldnn_OhIw16o4i,
goihw = mkldnn_goihw,
hwigo = mkldnn_hwigo,
gOIhw8i8o = mkldnn_gOIhw8i8o,
gOIhw16i16o = mkldnn_gOIhw16i16o,
gOIhw8i16o2i = mkldnn_gOIhw8i16o2i,
gOIhw8o16i2o = mkldnn_gOIhw8o16i2o,
gOIhw4i16o4i = mkldnn_gOIhw4i16o4i,
gOihw8o = mkldnn_gOihw8o,
gOihw16o = mkldnn_gOihw16o,
gOhwi8o = mkldnn_gOhwi8o,
gOhwi16o = mkldnn_gOhwi16o,
Goihw8g = mkldnn_Goihw8g,
Goihw16g = mkldnn_Goihw16g,
gOIhw8o8i = mkldnn_gOIhw8o8i,
gOIhw16o16i = mkldnn_gOIhw16o16i,
gIOhw16o16i = mkldnn_gIOhw16o16i,
gOhIw16o4i = mkldnn_gOhIw16o4i,
goidhw = mkldnn_goidhw,
gOIdhw16i16o = mkldnn_gOIdhw16i16o,
gOIdhw16o16i = mkldnn_gOIdhw16o16i,
gOidhw16o = mkldnn_gOidhw16o,
gOdhwi16o = mkldnn_gOdhwi16o,
ntc = mkldnn_ntc,
tnc = mkldnn_tnc,
ldsnc = mkldnn_ldsnc,
ldigo = mkldnn_ldigo,
ldigo_p = mkldnn_ldigo_p,
ldgoi = mkldnn_ldgoi,
ldgoi_p = mkldnn_ldgoi_p,
ldgo = mkldnn_ldgo,
wino_fmt = mkldnn_wino_fmt,
format_last = mkldnn_format_last,
};
/// A memory descriptor.
struct desc {
friend struct memory;
/// The underlying C API data structure.
mkldnn_memory_desc_t data;
/// Constructs a memory descriptor.
///
/// @param adims Data dimensions
/// @param adata_type Data precision/type.
/// @param aformat Data layout format.
desc(dims adims, data_type adata_type, format aformat) {
validate_dims(adims);
error::wrap_c_api(
mkldnn_memory_desc_init(&data,
(int)adims.size(),
adims.size() == 0 ? nullptr : &adims[0],
convert_to_c(adata_type),
convert_to_c(aformat)),
"could not initialize a memory descriptor");
}
/// Constructs a memory descriptor from a C API data structure.
///
/// @param adata A C API #mkldnn_memory_desc_t structure.
desc(const mkldnn_memory_desc_t &adata) : data(adata) {}
};
/// A memory primitive descriptor.
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
friend struct memory;
// TODO: make private
primitive_desc() {}
/// Constructs a memory primitive descriptor.
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_memory_primitive_desc_create(
&result, &adesc.data, aengine.get()),
"could not initialize a memory primitive descriptor");
reset(result);
}
/// Returns the memory primitive descriptor.
memory::desc desc() {
auto memory_d = mkldnn_primitive_desc_query_memory_d(get());
return memory::desc(*memory_d);
}
/// Returns the number of bytes required to allocate the memory described
/// including the padding area.
size_t get_size() const {
return mkldnn_memory_primitive_desc_get_size(get());
}
bool operator==(const primitive_desc &other) const {
return mkldnn_memory_primitive_desc_equal(get(), other.get());
}
bool operator!=(const primitive_desc &other) const {
return !operator==(other);
}
engine get_engine() { return engine::query(*this); }
};
/// Constructs a memory primitive from a generic primitive.
///
/// @param aprimitive The primitive to treat as memory.
memory(const primitive &aprimitive) : primitive(aprimitive) {}
/// Constructs a memory primitive.
///
/// @param adesc Memory primitive descriptor.
memory(const primitive_desc &adesc) {
mkldnn_primitive_t result;
error::wrap_c_api(
mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
"could not create a memory primitive");
reset(result);
auto _malloc = [](size_t size, int alignment) {
void *ptr;
#ifdef _WIN32
ptr = _aligned_malloc(size, alignment);
int rc = ((ptr) ? 0 : errno);
#else
int rc = ::posix_memalign(&ptr, alignment, size);
#endif /* _WIN32 */
return (rc == 0) ? (char *)ptr : nullptr;
};
auto _free = [](char *p) {
#ifdef _WIN32
_aligned_free((void *)p);
#else
::free((void *)p);
#endif /* _WIN32 */
};
_handle.reset(_malloc(adesc.get_size(), 4096), _free);
set_data_handle(_handle.get());
}
memory(const primitive_desc &adesc, void *ahandle) {
mkldnn_primitive_t result;
error::wrap_c_api(
mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
"could not create a memory primitive");
reset(result);
set_data_handle(ahandle);
}
/// Returns the descriptor of the memory primitive.
primitive_desc get_primitive_desc() const {
primitive_desc adesc;
const_mkldnn_primitive_desc_t cdesc;
error::wrap_c_api(
mkldnn_primitive_get_primitive_desc(get(), &cdesc),
"could not get primitive descriptor from a memory primitive");
/* FIXME: no const_cast should be here */
adesc.reset(const_cast<mkldnn_primitive_desc_t>(cdesc), true);
return adesc;
}
/// Returns a handle of the data contained in the memory primitive. On
/// the CPU engine, this is a pointer to the allocated memory.
inline void *get_data_handle() const {
void *handle;
error::wrap_c_api(mkldnn_memory_get_data_handle(get(), &handle),
"could not get native handle");
return handle;
}
inline void set_data_handle(void *handle) const {
error::wrap_c_api(mkldnn_memory_set_data_handle(get(), handle),
"could not set native handle");
}
// Must go away or be private:
static mkldnn_data_type_t convert_to_c(data_type adata_type) {
return static_cast<mkldnn_data_type_t>(adata_type);
}
static mkldnn_memory_format_t convert_to_c(format aformat) {
return static_cast<mkldnn_memory_format_t>(aformat);
}
};
inline memory::desc zero_md() {
mkldnn_memory_desc_t zero;
zero.primitive_kind = mkldnn_memory;
return memory::desc(zero);
}
inline memory null_memory(engine eng) {
mkldnn::memory::desc zero = zero_md();
return memory({zero, eng}, nullptr);
}
inline bool is_null_memory(const const_mkldnn_primitive_t &aprimitive) {
const_mkldnn_primitive_desc_t aprimitive_pd;
mkldnn_primitive_get_primitive_desc(aprimitive, &aprimitive_pd);
const mkldnn_memory_desc_t *aprimitive_md =
mkldnn_primitive_desc_query_memory_d(aprimitive_pd);
return ((aprimitive_md != nullptr) && (aprimitive_md->ndims == 0));
}
inline bool operator==(mkldnn_data_type_t a, memory::data_type b) {
return a == memory::convert_to_c(b);
}
inline bool operator!=(mkldnn_data_type_t a, memory::data_type b) {
return !(a == b);
}
inline bool operator==(memory::data_type a, mkldnn_data_type_t b) {
return b == a;
}
inline bool operator!=(memory::data_type a, mkldnn_data_type_t b) {
return !(a == b);
}
inline bool operator==(mkldnn_memory_format_t a, memory::format b) {
return a == memory::convert_to_c(b);
}
inline bool operator!=(mkldnn_memory_format_t a, memory::format b) {
return !(a == b);
}
inline bool operator==(memory::format a, mkldnn_memory_format_t b) {
return b == a;
}
inline bool operator!=(memory::format a, mkldnn_memory_format_t b) {
return !(a == b);
}
/// @}
/// @addtogroup cpp_api_reorder Reorder
/// @{
struct reorder : public primitive {
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const memory::primitive_desc &input,
const memory::primitive_desc &output) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_reorder_primitive_desc_create(
&result, input.get(), output.get()),
"could not create a reorder primitive descriptor");
reset(result);
}
primitive_desc(const memory::primitive_desc &input,
const memory::primitive_desc &output,
const primitive_attr &aattr) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_reorder_primitive_desc_create_v2(
&result, input.get(), output.get(), aattr.get()),
"could not create a reorder primitive descriptor");
reset(result);
}
engine get_engine() { return engine::query(*this); }
};
reorder(const primitive_desc &aprimitive_desc,
const primitive::at &input,
const memory &output) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {input.data};
const_mkldnn_primitive_t outputs[] = {output.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a reorder primitive");
reset(result);
}
reorder(const primitive::at &input, const memory &output) {
auto input_mpd = memory(input).get_primitive_desc();
auto output_mpd = output.get_primitive_desc();
auto reorder_d = primitive_desc(input_mpd, output_mpd);
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {input.data};
const_mkldnn_primitive_t outputs[] = {output.get()};
error::wrap_c_api(
mkldnn_primitive_create(&result, reorder_d.get(), inputs, outputs),
"could not create a reorder primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_view View
/// @{
struct view : public primitive {
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const memory::primitive_desc &input,
memory::dims dims,
memory::dims offsets) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_view_primitive_desc_create(
&result, input.get(), &dims[0], &offsets[0]),
"could not create a view primitive descriptor");
reset(result);
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
view(const primitive_desc &view_pd, primitive::at input) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {input.data};
error::wrap_c_api(
mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
"could not create a view primitive");
reset(result);
}
view(memory input, memory::dims dims, memory::dims offsets) {
mkldnn_primitive_t result;
primitive_desc view_pd(input.get_primitive_desc(), dims, offsets);
mkldnn_primitive_at_t inputs[] = {primitive::at(input).data};
error::wrap_c_api(
mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
"could not create a view primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_concat Concat
/// @{
struct concat : public primitive {
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
std::vector<memory::primitive_desc> inputs) {
std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
c_api_inputs.reserve(inputs.size());
auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
std::transform(inputs.begin(),
inputs.end(),
std::back_inserter(c_api_inputs),
convert_to_c);
return c_api_inputs;
}
primitive_desc(const memory::desc &output,
int concat_dimension,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
error::wrap_c_api(
mkldnn_concat_primitive_desc_create(&result,
&output.data,
(int)c_api_inputs.size(),
concat_dimension,
&c_api_inputs[0]),
"could not create a concat primitive descriptor");
reset(result);
}
primitive_desc(int concat_dimension,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
error::wrap_c_api(
mkldnn_concat_primitive_desc_create(&result,
nullptr,
(int)c_api_inputs.size(),
concat_dimension,
&c_api_inputs[0]),
"could not create a concat primitive descriptor");
reset(result);
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
concat(const primitive_desc &concat_pd,
std::vector<primitive::at> &inputs,
const memory &output) {
mkldnn_primitive_t result;
std::vector<mkldnn_primitive_at_t> p_inputs;
for (size_t i = 0; i < inputs.size(); i++)
p_inputs.push_back(inputs[i].data);
const_mkldnn_primitive_t outputs[] = {output.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, concat_pd.get(), &p_inputs[0], outputs),
"could not create a concat primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_sum Sum
/// @{
struct sum : public primitive {
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
std::vector<memory::primitive_desc> inputs) {
std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
c_api_inputs.reserve(inputs.size());
auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
std::transform(inputs.begin(),
inputs.end(),
std::back_inserter(c_api_inputs),
convert_to_c);
return c_api_inputs;
}
primitive_desc(const memory::desc &output,
const std::vector<float> &scales,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
error::wrap_c_api(
mkldnn_sum_primitive_desc_create(&result,
&output.data,
(int)c_api_inputs.size(),
&scales[0],
&c_api_inputs[0]),
"could not create a sum primitive descriptor");
reset(result);
}
primitive_desc(const std::vector<float> &scales,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
error::wrap_c_api(
mkldnn_sum_primitive_desc_create(&result,
nullptr,
(int)c_api_inputs.size(),
&scales[0],
&c_api_inputs[0]),
"could not create a sum primitive descriptor");
reset(result);
}
/** @deprecated: api backwards compatibility for double scales type */
MKLDNN_DEPRECATED
primitive_desc(const memory::desc &output,
std::vector<double> scale,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
auto scale_f = scale_to_float(scale);
error::wrap_c_api(
mkldnn_sum_primitive_desc_create(&result,
&output.data,
(int)c_api_inputs.size(),
&scale_f[0],
&c_api_inputs[0]),
"could not create a sum primitive descriptor");
reset(result);
}
/** @deprecated: api backwards compatibility for double scales type */
MKLDNN_DEPRECATED
primitive_desc(std::vector<double> scale,
std::vector<memory::primitive_desc> inputs) {
mkldnn_primitive_desc_t result;
auto c_api_inputs = cpp_to_c(inputs);
auto scale_f = scale_to_float(scale);
error::wrap_c_api(
mkldnn_sum_primitive_desc_create(&result,
nullptr,
(int)c_api_inputs.size(),
&scale_f[0],
&c_api_inputs[0]),
"could not create a sum primitive descriptor");
reset(result);
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
sum(const primitive_desc &sum_pd,
std::vector<primitive::at> &inputs,
const memory &output) {
mkldnn_primitive_t result;
std::vector<mkldnn_primitive_at_t> p_inputs;
for (size_t i = 0; i < inputs.size(); i++)
p_inputs.push_back(inputs[i].data);
const_mkldnn_primitive_t outputs[] = {output.get()};
error::wrap_c_api(
mkldnn_primitive_create(&result, sum_pd.get(), &p_inputs[0], outputs),
"could not create a sum primitive");
reset(result);
}
private:
static std::vector<float> scale_to_float(const std::vector<double> &vd) {
std::vector<float> vf(vd.size());
std::transform(
vd.begin(), vd.end(), vf.begin(), [=](double x) { return (float)x; });
return vf;
}
};
/// @}
/// @addtogroup cpp_api_convolution Convolution
/// @{
struct convolution_forward : public primitive {
struct desc {
mkldnn_convolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(mkldnn_convolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
&bias_desc.data,
&dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution forward descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(mkldnn_convolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
nullptr,
&dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution forward descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(dilates);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_dilated_convolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
&bias_desc.data,
&dst_desc.data,
&strides[0],
&dilates[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a dilated convolution forward descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(dilates);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_dilated_convolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
nullptr,
&dst_desc.data,
&strides[0],
&dilates[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a dilated convolution forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a convolution forward primitive descriptor");
reset(result);
}
primitive_desc(const desc &adesc,
const primitive_attr &aattr,
const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create_v2(
&result, &adesc.data, aattr.get(), aengine.get(), nullptr),
"could not create a convolution forward primitive descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
convolution_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const primitive::at &bias,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution forward bias primitive");
reset(result);
}
convolution_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution forward primitive");
reset(result);
}
};
struct convolution_backward_data : public primitive {
struct desc {
mkldnn_convolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_convolution_backward_data_desc_init(
&data,
convert_to_c(aalgorithm),
&diff_src_desc.data,
&weights_desc.data,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward data descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(dilates);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_dilated_convolution_backward_data_desc_init(
&data,
convert_to_c(aalgorithm),
&diff_src_desc.data,
&weights_desc.data,
&diff_dst_desc.data,
&strides[0],
&dilates[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward data descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a convolution backward data primitive descriptor");
reset(result);
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
convolution_backward_data(const primitive_desc &aprimitive_desc,
const primitive::at &diff_dst,
const primitive::at &weights,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution backward data primitive");
reset(result);
}
};
struct convolution_backward_weights : public primitive {
struct desc {
mkldnn_convolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_convolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
&diff_bias_desc.data,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward weights descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_convolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
nullptr,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward weights descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(dilates);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_dilated_convolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
&diff_bias_desc.data,
&diff_dst_desc.data,
&strides[0],
&dilates[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward weights descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(dilates);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_dilated_convolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
nullptr,
&diff_dst_desc.data,
&strides[0],
&dilates[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a convolution backward weights descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a convolution backward weights primitive "
"descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution backward weights primitive");
reset(result);
}
convolution_backward_weights(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &diff_dst,
const memory &diff_weights) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution backward weights primitive");
reset(result);
}
};
struct convolution_relu_forward : public primitive {
struct desc {
mkldnn_convolution_relu_desc_t data;
desc(const convolution_forward::desc conv_desc,
const float negative_slope) {
error::wrap_c_api(
mkldnn_convolution_relu_desc_init(
&data, &conv_desc.data, negative_slope),
"could not create a convolution_relu_forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a convolution relu forward descriptor");
reset(result);
}
engine get_engine() { return engine::query(*this); }
};
convolution_relu_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const primitive::at &bias,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution relu forward primitive");
reset(result);
}
convolution_relu_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a convolution relu forward primitive");
reset(result);
}
};
/// @}
//
/// @addtogroup cpp_api_deconvolution Deconvolution
/// @{
struct deconvolution_forward : public primitive {
struct desc {
mkldnn_deconvolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
&bias_desc.data,
&dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a deconvolution forward descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&weights_desc.data,
nullptr,
&dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a deconvolution forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a deconvolution forward primitive descriptor");
reset(result);
}
primitive_desc(const desc &adesc,
const primitive_attr &aattr,
const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create_v2(
&result, &adesc.data, aattr.get(), aengine.get(), nullptr),
"could not create a deconvolution forward primitive descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
deconvolution_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const primitive::at &bias,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a deconvolution forward bias primitive");
reset(result);
}
deconvolution_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a deconvolution forward primitive");
reset(result);
}
};
struct deconvolution_backward_data : public primitive {
struct desc {
mkldnn_deconvolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_deconvolution_backward_data_desc_init(
&data,
convert_to_c(aalgorithm),
&diff_src_desc.data,
&weights_desc.data,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a deconvolution backward data descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a deconvolution backward data primitive "
"descriptor");
reset(result);
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
deconvolution_backward_data(const primitive_desc &aprimitive_desc,
const primitive::at &diff_dst,
const primitive::at &weights,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a deconvolution backward data primitive");
reset(result);
}
};
struct deconvolution_backward_weights : public primitive {
struct desc {
mkldnn_deconvolution_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_deconvolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
&diff_bias_desc.data,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a deconvolution backward weights descriptor");
}
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) {
memory::validate_dims(strides);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_deconvolution_backward_weights_desc_init(
&data,
convert_to_c(aalgorithm),
&src_desc.data,
&diff_weights_desc.data,
nullptr,
&diff_dst_desc.data,
&strides[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not create a deconvolution backward weights descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a deconvolution backward weights primitive "
"descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a deconvolution backward weights primitive");
reset(result);
}
deconvolution_backward_weights(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &diff_dst,
const memory &diff_weights) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a deconvolution backward weights primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_lrn LRN
/// @{
struct lrn_forward : public primitive {
struct desc {
mkldnn_lrn_desc_t data;
desc(prop_kind aprop_kind,
algorithm aalgorithm,
const memory::desc &src_desc,
int local_size,
float alpha,
float beta,
float k) {
error::wrap_c_api(
mkldnn_lrn_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
local_size,
alpha,
beta,
k),
"could not create a lrn forward descriptor");
}
desc(prop_kind aprop_kind,
algorithm aalgorithm,
const memory::desc &src_desc,
int local_size,
float alpha,
float beta) {
error::wrap_c_api(
mkldnn_lrn_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
local_size,
alpha,
beta,
float(1.0)),
"could not create a lrn forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a lrn forward primitive descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t ldesc;
const_mkldnn_primitive_desc_t const_ldesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
"could not clone a workspace primitive descriptor");
adesc.reset(ldesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
lrn_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &workspace,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a lrn forward primitive");
reset(result);
}
lrn_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a lrn forward primitive");
reset(result);
}
};
struct lrn_backward : public primitive {
struct desc {
mkldnn_lrn_desc_t data;
desc(algorithm aalgorithm,
const memory::desc &data_desc,
const memory::desc &diff_data_desc,
int local_size,
float alpha,
float beta,
float k) {
error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
convert_to_c(aalgorithm),
&diff_data_desc.data,
&data_desc.data,
local_size,
alpha,
beta,
k),
"could not create a lrn backward descriptor");
}
desc(algorithm aalgorithm,
const memory::desc &data_desc,
const memory::desc &diff_data_desc,
int local_size,
float alpha,
float beta) {
error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
convert_to_c(aalgorithm),
&diff_data_desc.data,
&data_desc.data,
local_size,
alpha,
beta,
float(1.0)),
"could not create a lrn backward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc,
const engine &aengine,
const lrn_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a backward lrn primitive descriptor");
reset(result);
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t ldesc;
const_mkldnn_primitive_desc_t const_ldesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
"could not clone a workspace primitive descriptor");
adesc.reset(ldesc);
return adesc;
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff_dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
lrn_backward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &diff_dst,
const primitive::at &workspace,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data, workspace.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a lrn backward primitive");
reset(result);
}
lrn_backward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &diff_dst,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a lrn backward primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_pooling Pooling
/// @{
struct pooling_forward : public primitive {
struct desc {
mkldnn_pooling_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(kernel);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(
mkldnn_pooling_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
convert_to_c(aalgorithm),
&src_desc.data,
&dst_desc.data,
&strides[0],
&kernel[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not init a forward pooling descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a forward pooling primitive descriptor");
reset(result);
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a workspace primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
pooling_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get(), nullptr};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a pooling forward primitive");
reset(result);
}
pooling_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst,
const memory &workspace) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a pooling forward primitive");
reset(result);
}
};
struct pooling_backward : public primitive {
struct desc {
mkldnn_pooling_desc_t data;
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) {
memory::validate_dims(strides);
memory::validate_dims(kernel);
memory::validate_dims(padding_l);
memory::validate_dims(padding_r);
error::wrap_c_api(mkldnn_pooling_backward_desc_init(
&data,
convert_to_c(aalgorithm),
&diff_src_desc.data,
&diff_dst_desc.data,
&strides[0],
&kernel[0],
&padding_l[0],
&padding_r[0],
mkldnn::convert_to_c(apadding_kind)),
"could not init a backward pooling descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const pooling_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a backward pooling primitive descriptor");
reset(result);
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
pooling_backward(const primitive_desc &aprimitive_desc,
const primitive::at &diff_dst,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a pooling backward primitive");
reset(result);
}
pooling_backward(const primitive_desc &aprimitive_desc,
const primitive::at &diff_dst,
const primitive::at &workspace,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {diff_dst.data, workspace.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a pooling backward primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_eltwise Eltwise
/// @{
struct eltwise_forward : public primitive {
struct desc {
mkldnn_eltwise_desc_t data;
template <typename T>
desc(prop_kind aprop_kind,
algorithm alg_kind,
const memory::desc &src_desc,
T alpha = 0,
T beta = 0) {
error::wrap_c_api(
mkldnn_eltwise_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
mkldnn::convert_to_c(alg_kind),
&src_desc.data,
static_cast<float>(alpha),
static_cast<float>(beta)),
"could not create a eltwise forward descriptor");
}
/** @deprecated: api backward compatibility for relu */
template <typename T>
MKLDNN_DEPRECATED desc(prop_kind aprop_kind,
const memory::desc &src_desc,
T negative_slope)
: desc(aprop_kind, eltwise_relu, src_desc, negative_slope) {}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a eltwise forward primitive descriptor");
reset(result);
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
eltwise_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a eltwise forward primitive");
reset(result);
}
};
typedef eltwise_forward relu_forward;
struct eltwise_backward : public primitive {
struct desc {
mkldnn_eltwise_desc_t data;
template <typename T>
desc(algorithm alg_kind,
const memory::desc &diff_data_desc,
const memory::desc &data_desc,
T alpha = 0,
T beta = 0) {
error::wrap_c_api(
mkldnn_eltwise_backward_desc_init(&data,
mkldnn::convert_to_c(alg_kind),
&diff_data_desc.data,
&data_desc.data,
static_cast<float>(alpha),
static_cast<float>(beta)),
"could not create a eltwise backward descriptor");
}
/** @deprecated: api backward compatibility for relu */
template <typename T>
MKLDNN_DEPRECATED desc(const memory::desc &diff_data_desc,
const memory::desc &data_desc,
T negative_slope)
: desc(eltwise_relu, diff_data_desc, data_desc, negative_slope) {}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const eltwise_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a eltwise backward primitive descriptor");
reset(result);
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
eltwise_backward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &diff_dst,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a eltwise backward primitive");
reset(result);
}
};
typedef eltwise_backward relu_backward;
/// @}
/// @addtogroup cpp_api_softmax Softmax
/// @{
struct softmax_forward : public primitive {
struct desc {
mkldnn_softmax_desc_t data;
desc(prop_kind aprop_kind,
const memory::desc &data_desc,
int softmax_axis) {
error::wrap_c_api(
mkldnn_softmax_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
&data_desc.data,
softmax_axis),
"could not create a softmax forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a softmax forward primitive descriptor");
reset(result);
}
engine get_engine() { return engine::query(*this); }
};
softmax_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a softmax forward primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_batch_norm Batch normalization
/// @{
struct batch_normalization_forward : public primitive {
struct desc {
mkldnn_batch_normalization_desc_t data;
template <typename T>
desc(prop_kind aprop_kind,
const memory::desc &src_desc,
T epsilon,
unsigned flags) {
error::wrap_c_api(
mkldnn_batch_normalization_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
&src_desc.data,
static_cast<float>(epsilon),
flags),
"could not create a batch normalization forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a batch normalization forward "
"primitive descriptor");
reset(result);
}
primitive_desc(const desc &adesc,
const primitive_attr &aattr,
const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create_v2(
&result, &adesc.data, aattr.get(), aengine.get(), nullptr),
"could not create a batch normalization forward "
"primitive descriptor");
reset(result);
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t bndesc;
const_mkldnn_primitive_desc_t const_bndesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a weights primitive descriptor");
adesc.reset(bndesc);
return adesc;
}
memory::primitive_desc mean_primitive_desc() const {
memory::primitive_desc aprimitive_desc;
mkldnn_primitive_desc_t bndesc;
mkldnn_batch_normalization_desc_t *p;
error::wrap_c_api(
mkldnn_primitive_desc_query(
get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
"could not get a batch-normalization descriptor");
const_mkldnn_primitive_desc_t const_bndesc =
(p->flags & use_global_stats)
? mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 1)
: mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a mean primitive descriptor");
aprimitive_desc.reset(bndesc);
return aprimitive_desc;
}
memory::primitive_desc variance_primitive_desc() const {
memory::primitive_desc aprimitive_desc;
mkldnn_primitive_desc_t bndesc;
mkldnn_batch_normalization_desc_t *p;
error::wrap_c_api(
mkldnn_primitive_desc_query(
get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
"could not get a batch-normalization descriptor");
const_mkldnn_primitive_desc_t const_bndesc =
(p->flags & use_global_stats)
? mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 2)
: mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 2);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a variance primitive descriptor");
aprimitive_desc.reset(bndesc);
return aprimitive_desc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a workspace primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {
src.data, mean.data, variance.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
batch_normalization_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &mean,
const primitive::at &variance,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, mean.data, variance.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
/// @warning batch_normalization_forward has 2 constructors with very
/// similar signatures:
/// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
/// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
/// The only way to distinguish between those is to explicitly
/// cast all input parameters to their type, i.e. to
/// const primitive:at &.
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {
dst.get(), mean.get(), variance.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {
dst.get(), mean.get(), variance.get(), workspace.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
batch_normalization_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst,
const memory &mean,
const memory &variance) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {
dst.get(), mean.get(), variance.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
/// @warning batch_normalization_forward has 2 constructors with very
/// similar signatures:
/// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
/// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
/// The only way to distinguish between those is to explicitly
/// cast all input parameters to their type, i.e. to
/// const primitive:at &.
/// @note to make users' experience a little bit better this constructor
/// checks if whether parameters match corresponding primitive
/// descriptor, and if they are not -- call the other (proper)
/// constructor. Yeah, this is still very ugly...
batch_normalization_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst,
const memory &mean,
const memory &variance,
const memory &workspace) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[2] = {src.data};
const_mkldnn_primitive_t outputs[4] = {
dst.get(), mean.get(), variance.get(), workspace.get()};
if (1) { // check whether this is the `wrong` constructor
const int n_inputs_expected = mkldnn_primitive_desc_query_s32(
aprimitive_desc.get(), mkldnn_query_num_of_inputs_s32, 0);
const int n_outputs_expected = mkldnn_primitive_desc_query_s32(
aprimitive_desc.get(), mkldnn_query_num_of_outputs_s32, 0);
if (n_inputs_expected == 2 && n_outputs_expected == 3) {
// shift parameters, get rid of workspace, and add weights...
auto _weights = dst;
inputs[1] = {_weights.get(), 0};
auto _dst = mean, _mean = variance, _variance = workspace;
outputs[0] = _dst.get();
outputs[1] = _mean.get();
outputs[2] = _variance.get();
outputs[3] = nullptr;
}
}
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
batch_normalization_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at &weights,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
batch_normalization_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization forward primitive");
reset(result);
}
};
struct batch_normalization_backward : public primitive {
struct desc {
mkldnn_batch_normalization_desc_t data;
template <typename T>
desc(prop_kind aprop_kind,
const memory::desc &diff_data_desc,
const memory::desc &data_desc,
T epsilon,
unsigned flags) {
error::wrap_c_api(
mkldnn_batch_normalization_backward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
&diff_data_desc.data,
&data_desc.data,
static_cast<float>(epsilon),
flags),
"could not create a batch normalization backward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc,
const engine &aengine,
const batch_normalization_forward::primitive_desc
&hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a batch normalization backward primitive "
"descriptor");
reset(result);
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t bndesc;
const_mkldnn_primitive_desc_t const_bndesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a weights primitive descriptor");
adesc.reset(bndesc);
return adesc;
}
memory::primitive_desc diff_weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t bndesc;
const_mkldnn_primitive_desc_t const_bndesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a diff_weights primitive descriptor");
adesc.reset(bndesc);
return adesc;
}
memory::primitive_desc mean_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t bndesc;
const_mkldnn_primitive_desc_t const_bndesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a mean primitive descriptor");
adesc.reset(bndesc);
return adesc;
}
memory::primitive_desc variance_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t bndesc;
const_mkldnn_primitive_desc_t const_bndesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 2);
error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
"could not clone a variance primitive descriptor");
adesc.reset(bndesc);
return adesc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a workspace primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
// Prop_kind == backward
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {
src.data, mean.data, variance.data, diff_dst.data, weights.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization backward primitive");
reset(result);
}
// Prop_kind == backward (+ws)
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data,
mean.data,
variance.data,
diff_dst.data,
weights.data,
workspace.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization backward primitive");
reset(result);
}
// Prop_kind == backward_data (+ws or +weights)
/// @warning This constructor works for backward_data propagation
/// - w/ weights but w/o workspace, or
/// - w/ workspace but w/o weights
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data,
mean.data,
variance.data,
diff_dst.data,
weights_or_workspace.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization backward primitive");
reset(result);
}
// Prop_kind == backward_data
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {
src.data, mean.data, variance.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a batch normalization backward primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_inner_product Inner Product
/// @{
struct inner_product_forward : public primitive {
struct desc {
mkldnn_inner_product_desc_t data;
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) {
error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
&src_desc.data,
&weights_desc.data,
&bias_desc.data,
&dst_desc.data),
"could not create a inner product forward descriptor");
}
desc(prop_kind aprop_kind,
const memory::desc &src_desc,
const memory::desc &weights_desc,
const memory::desc &dst_desc) {
error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
&data,
mkldnn::convert_to_c(aprop_kind),
&src_desc.data,
&weights_desc.data,
nullptr,
&dst_desc.data),
"could not create a inner product forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create a inner product forward primitive descriptor");
reset(result);
}
primitive_desc(const desc &adesc,
const primitive_attr &aattr,
const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create_v2(
&result, &adesc.data, aattr.get(), aengine.get(), nullptr),
"could not create a inner product "
"forward primitive descriptor");
reset(result);
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
inner_product_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at weights,
const primitive::at &bias,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a inner product forward primitive");
reset(result);
}
inner_product_forward(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at weights,
const memory &dst) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
const_mkldnn_primitive_t outputs[] = {dst.get()};
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a inner product forward primitive");
reset(result);
}
};
struct inner_product_backward_data : public primitive {
struct desc {
mkldnn_inner_product_desc_t data;
desc(const memory::desc &diff_src_desc,
const memory::desc &weights_desc,
const memory::desc &diff_dst_desc) {
error::wrap_c_api(
mkldnn_inner_product_backward_data_desc_init(&data,
&diff_src_desc.data,
&weights_desc.data,
&diff_dst_desc.data),
"could not create a inner product backward data descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a inner product backward data primitive "
"descriptor");
reset(result);
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff dst primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
inner_product_backward_data(const primitive_desc &aprimitive_desc,
const primitive::at &diff_dst,
const primitive::at weights,
const memory &diff_src) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
const_mkldnn_primitive_t outputs[] = {diff_src.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a inner product backward data primitive");
reset(result);
}
};
struct inner_product_backward_weights : public primitive {
struct desc {
mkldnn_inner_product_desc_t data;
desc(const memory::desc &src_desc,
const memory::desc &diff_weights_desc,
const memory::desc &diff_bias_desc,
const memory::desc &diff_dst_desc) {
error::wrap_c_api(
mkldnn_inner_product_backward_weights_desc_init(
&data,
&src_desc.data,
&diff_weights_desc.data,
&diff_bias_desc.data,
&diff_dst_desc.data),
"could not create a inner product backward weights descriptor");
}
desc(const memory::desc &src_desc,
const memory::desc &diff_weights_desc,
const memory::desc &diff_dst_desc) {
error::wrap_c_api(
mkldnn_inner_product_backward_weights_desc_init(
&data,
&src_desc.data,
&diff_weights_desc.data,
nullptr,
&diff_dst_desc.data),
"could not create a inner product backward weights descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(
const desc &adesc,
const engine &aengine,
const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(&result,
&adesc.data,
aengine.get(),
hint_fwd_primitive_desc.get()),
"could not create a inner product backward weights primitive "
"descriptor");
reset(result);
}
memory::primitive_desc diff_dst_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff dst primititve descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_weights_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a diff bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc src_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
inner_product_backward_weights(const primitive_desc &aprimitive_desc,
const primitive::at &src,
const primitive::at diff_dst,
const memory &diff_weights) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a inner product backward weights primitive");
reset(result);
}
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
error::wrap_c_api(
mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create a inner product backward weights primitive");
reset(result);
}
};
/// @}
/// @addtogroup cpp_api_rnn RNN
/// @{
struct rnn_cell {
struct desc {
mkldnn_rnn_cell_desc_t c_rnn_cell_;
desc(algorithm kind, algorithm activation_f) {
error::wrap_c_api(
mkldnn_rnn_cell_desc_init(&c_rnn_cell_,
mkldnn::convert_to_c(kind),
mkldnn::convert_to_c(activation_f),
0U,
0,
0),
"could not init an rnn cell descriptor");
}
desc(algorithm kind) : desc(kind, algorithm::algorithm_undef) {}
operator const mkldnn_rnn_cell_desc_t *() const { return &c_rnn_cell_; }
algorithm get_cell_kind() const { return algorithm(c_rnn_cell_.cell_kind); }
algorithm get_activation() const {
return algorithm(c_rnn_cell_.activation_kind);
}
float get_alpha() const { return c_rnn_cell_.alpha; }
void set_alpha(float alpha) {
c_rnn_cell_.flags |= mkldnn_rnn_cell_with_relu;
c_rnn_cell_.alpha = alpha;
}
float get_clipping() const { return c_rnn_cell_.clipping; }
void set_clipping(float clipping) {
c_rnn_cell_.flags |= mkldnn_rnn_cell_with_clipping;
c_rnn_cell_.clipping = clipping;
}
int get_gates_count() const {
return mkldnn_rnn_cell_get_gates_count(&c_rnn_cell_);
}
int get_state_count() const {
return mkldnn_rnn_cell_get_states_count(&c_rnn_cell_);
}
};
};
struct rnn_forward : public primitive {
struct desc {
mkldnn_rnn_desc_t data;
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) {
error::wrap_c_api(
mkldnn_rnn_forward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
cell,
mkldnn::convert_to_c(direction),
&src_layer_desc.data,
&src_iter_desc.data,
&weights_layer_desc.data,
&weights_iter_desc.data,
&bias_desc.data,
&dst_layer_desc.data,
&dst_iter_desc.data),
"could not create an RNN forward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create an RNN forward primitive descriptor");
reset(result);
}
memory::primitive_desc src_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone an src layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc src_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src iter primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_src_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 2);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t ldesc;
const_mkldnn_primitive_desc_t const_ldesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
"could not clone a workspace primitive descriptor");
adesc.reset(ldesc);
return adesc;
}
memory::primitive_desc dst_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 1);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last iteration primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[5];
const_mkldnn_primitive_t outputs[3];
int idx = 0;
inputs[idx++] = src_layer.data;
if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
inputs[idx++] = weights_layer.data;
inputs[idx++] = weights_iter.data;
if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
idx = 0;
outputs[idx++] = dst_layer.get();
if (!is_null_memory(dst_iter.get())) outputs[idx++] = dst_iter.get();
if (!is_null_memory(workspace.get())) outputs[idx++] = workspace.get();
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create an RNN forward primitive");
reset(result);
}
};
struct rnn_backward : public primitive {
struct desc {
mkldnn_rnn_desc_t data;
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) {
error::wrap_c_api(
mkldnn_rnn_backward_desc_init(&data,
mkldnn::convert_to_c(aprop_kind),
cell,
mkldnn::convert_to_c(direction),
&src_layer_desc.data,
&src_iter_desc.data,
&weights_layer_desc.data,
&weights_iter_desc.data,
&bias_desc.data,
&dst_layer_desc.data,
&dst_iter_desc.data,
&diff_src_layer_desc.data,
&diff_src_iter_desc.data,
&diff_weights_layer_desc.data,
&diff_weights_iter_desc.data,
&diff_bias_desc.data,
&diff_dst_layer_desc.data,
&diff_dst_iter_desc.data),
"could not create an RNN backward descriptor");
}
};
struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
primitive_desc(const desc &adesc, const engine &aengine) {
mkldnn_primitive_desc_t result;
error::wrap_c_api(
mkldnn_primitive_desc_create(
&result, &adesc.data, aengine.get(), nullptr),
"could not create an RNN backward primitive descriptor");
reset(result);
}
memory::primitive_desc src_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone an src layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc src_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(src_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src iter primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc weights_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(weights_pd), 2);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 0);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc dst_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(dst_pd), 1);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last iteration primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_src_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone an src_layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_src_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_src_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a src iter primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_weights_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_weights_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 1);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a weights primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_bias_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_weights_pd), 2);
error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a bias primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_layer_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 0);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last layer primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc diff_dst_iter_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t cdesc;
const_mkldnn_primitive_desc_t const_cdesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(diff_dst_pd), 1);
error::wrap_c_api(
mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
"could not clone a dst last iteration primitive descriptor");
adesc.reset(cdesc);
return adesc;
}
memory::primitive_desc workspace_primitive_desc() const {
memory::primitive_desc adesc;
mkldnn_primitive_desc_t ldesc;
const_mkldnn_primitive_desc_t const_ldesc =
mkldnn_primitive_desc_query_pd(
get(), mkldnn::convert_to_c(workspace_pd), 0);
error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
"could not clone a workspace primitive descriptor");
adesc.reset(ldesc);
return adesc;
}
engine get_engine() { return engine::query(*this); }
};
// With last iteration (with and without input src_iter)
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) {
mkldnn_primitive_t result;
mkldnn_primitive_at_t inputs[10];
const_mkldnn_primitive_t outputs[5];
int idx = 0;
inputs[idx] = src_layer.data;
if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
inputs[idx++] = weights_layer.data;
inputs[idx++] = weights_iter.data;
if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
inputs[idx] = dst_layer.data;
if (!is_null_memory(dst_iter.data.primitive)) inputs[idx++] = dst_iter.data;
inputs[idx] = diff_dst_layer.data;
if (!is_null_memory(diff_dst_iter.data.primitive))
inputs[idx++] = diff_dst_iter.data;
inputs[idx] = workspace.data;
idx = 0;
outputs[idx] = diff_src_layer.get();
if (!is_null_memory(diff_src_iter.get()))
outputs[idx++] = diff_src_iter.get();
outputs[idx] = diff_weights_layer.get();
outputs[idx] = diff_weights_iter.get();
if (!is_null_memory(diff_bias.get())) outputs[idx] = diff_bias.get();
error::wrap_c_api(mkldnn_primitive_create(
&result, aprimitive_desc.get(), inputs, outputs),
"could not create an RNN backward primitive");
reset(result);
}
};
/// @}
/// @} Primitives
/// @addtogroup cpp_api_stream Stream
/// @{
#ifndef DOXYGEN_SHOULD_SKIP_THIS
template <>
struct handle_traits<mkldnn_stream_t> {
static constexpr auto destructor = &mkldnn_stream_destroy;
};
#endif
struct stream : public handle<mkldnn_stream_t> {
using handle::handle;
enum kind {
any = mkldnn_stream_kind_t::mkldnn_any_stream,
eager = mkldnn_stream_kind_t::mkldnn_eager,
lazy = mkldnn_stream_kind_t::mkldnn_lazy
};
static mkldnn_stream_kind_t convert_to_c(kind akind) {
return static_cast<mkldnn_stream_kind_t>(akind);
}
/// Constructs a stream.
stream(kind akind) {
mkldnn_stream_t astream;
error::wrap_c_api(mkldnn_stream_create(&astream, convert_to_c(akind)),
"could not create a stream");
reset(astream);
}
/// Submits a vector of primitives to a stream for computations.
///
/// @param primitives The vector of primitives to submit.
/// @returns The stream.
stream &submit(std::vector<primitive> primitives) {
// TODO: find a proper way to convert vector<primitive> to
// vector<mkldnn_primitive_t>
if (primitives.size() == 0) return *this;
std::vector<mkldnn_primitive_t> c_api_primitives;
c_api_primitives.reserve(primitives.size());
auto convert_to_c = [](primitive p) { return p.get(); };
std::transform(primitives.begin(),
primitives.end(),
std::back_inserter(c_api_primitives),
convert_to_c);
mkldnn_primitive_t c_api_error_primitive;
error::wrap_c_api(mkldnn_stream_submit(get(),
c_api_primitives.size(),
&c_api_primitives[0],
&c_api_error_primitive),
"could not submit primitives to a stream",
&c_api_error_primitive);
return *this;
}
/// Waits for all computations submitted to the stream to complete.
///
/// @param block Specifies whether the operation should wait indefinitely or
/// return
/// immediately.
/// @returns @c true if all computations completed.
/// @returns @c false if not all computations completed.
bool wait(bool block = true) {
mkldnn_primitive_t c_api_error_primitive;
mkldnn_status_t status =
mkldnn_stream_wait(get(), block, &c_api_error_primitive);
if (status != mkldnn_success && status != mkldnn_try_again)
error::wrap_c_api(
status, "could not wait on a stream", &c_api_error_primitive);
return (status == mkldnn_success);
}
stream &rerun() {
mkldnn_primitive_t c_api_error_primitive;
error::wrap_c_api(mkldnn_stream_rerun(get(), &c_api_error_primitive),
"could not rerun a stream",
&c_api_error_primitive);
return *this;
}
};
/// @}
/// @} C++ API
} // namespace mkldnn
#endif
......@@ -62,31 +62,31 @@ def train(use_cuda, train_program, save_dirname):
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
trainer = fluid.Trainer(
train_func=train_program, place=place, optimizer=optimizer)
train_func=train_program,
place=place,
optimizer=optimizer,
parallel=True)
def event_handler(event):
if isinstance(event, fluid.EndEpochEvent):
test_reader = paddle.batch(
paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
test_metrics = trainer.test(
avg_cost, acc = trainer.test(
reader=test_reader, feed_order=['img', 'label'])
avg_cost_set = test_metrics[0]
acc_set = test_metrics[1]
# get test acc and loss
acc = numpy.array(acc_set).mean()
avg_cost = numpy.array(avg_cost_set).mean()
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
if float(acc) > 0.2: # Smaller value to increase CI speed
if acc > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
event.epoch + 1, float(avg_cost), float(acc)))
if math.isnan(float(avg_cost)):
event.epoch + 1, avg_cost, acc))
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
elif isinstance(event, fluid.EndStepEvent):
print("Step {0}, Epoch {1} Metrics {2}".format(
event.step, event.epoch, map(numpy.array, event.metrics)))
train_reader = paddle.batch(
paddle.reader.shuffle(
......@@ -131,4 +131,4 @@ def main(use_cuda):
if __name__ == '__main__':
# for use_cuda in (False, True):
main(use_cuda=False)
main(use_cuda=True)
......@@ -55,24 +55,18 @@ def train(use_cuda, train_program, save_dirname):
if isinstance(event, fluid.EndEpochEvent):
test_reader = paddle.batch(
paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
test_metrics = trainer.test(
avg_cost, acc = trainer.test(
reader=test_reader, feed_order=['img', 'label'])
avg_cost_set = test_metrics[0]
acc_set = test_metrics[1]
# get test acc and loss
acc = numpy.array(acc_set).mean()
avg_cost = numpy.array(avg_cost_set).mean()
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
if float(acc) > 0.2: # Smaller value to increase CI speed
if acc > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
event.epoch + 1, float(avg_cost), float(acc)))
if math.isnan(float(avg_cost)):
event.epoch + 1, avg_cost, acc))
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
......
......@@ -20,6 +20,7 @@ import data_feeder
import contextlib
import io
import unique_name
import parallel_executor
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
import optimizer as opt_module
......@@ -48,12 +49,14 @@ class BeginStepEvent(object):
def __init__(self, epoch_id, step_id):
self.epoch = epoch_id
self.step = step_id
self.fetch_metrics = True
class EndStepEvent(object):
def __init__(self, epoch_id, step_id):
def __init__(self, epoch_id, step_id, metrics):
self.epoch = epoch_id
self.step = step_id
self.metrics = metrics
def check_and_get_place(place):
......@@ -87,12 +90,17 @@ class Trainer(object):
Args:
train_func(callable): A function which will return loss. The loss must be a scalar.
infer_func(callable): A function which will return predict, used to save inference model
optimizer(optimizer.Optimizer): The optimizer should be an instance of Optimizer
place: The device place of this trainer.
"""
def __init__(self, train_func, optimizer, param_path=None, place=None):
def __init__(self,
train_func,
optimizer,
param_path=None,
place=None,
parallel=False):
self.parallel = parallel
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
# test_word2vec.py
......@@ -106,14 +114,14 @@ class Trainer(object):
with framework.program_guard(self.train_program, self.startup_program):
program_func_outs = train_func()
self.test_outputs = program_func_outs if isinstance(
self.train_func_outputs = program_func_outs if isinstance(
program_func_outs, list) else [program_func_outs]
self.test_program = self.train_program.clone()
if not isinstance(optimizer, opt_module.Optimizer):
raise TypeError(
"The optimizer should be an instance of Optimizer")
# The fisrt element of program_func_outs is loss.
loss = self.test_outputs[0]
loss = self.train_func_outputs[0]
optimize_ops, params_grads = optimizer.minimize(loss)
self.place = check_and_get_place(place)
......@@ -202,12 +210,7 @@ class Trainer(object):
'TRAINING_ROLE environment variable must be either TRAINER or PSERVER'
)
def train(self,
num_epochs,
event_handler,
reader,
feed_order,
parallel=False):
def train(self, num_epochs, event_handler, reader=None, feed_order=None):
"""
Train the model.
......@@ -215,25 +218,24 @@ class Trainer(object):
num_epochs: The number of epoch. An epoch will process all data in reader
event_handler: The event handler. A function with type (ev:Event)->void
reader:
parallel: True if use multi-CPUs or multi-GPUs
feed_order: Feeding order of reader. None will following the defining
order in program
Returns:
"""
if parallel:
raise NotImplementedError(
"Parallel Executor version of trainer is not implemented")
training_role = os.getenv("PADDLE_TRAINING_ROLE", "")
if training_role == "PSERVER":
with self._prog_and_scope_guard():
exe = executor.Executor(self.place)
exe.run()
return
self._train_by_executor(num_epochs, event_handler, reader, feed_order)
if self.parallel:
self._train_by_parallel_executor(num_epochs, event_handler, reader,
feed_order)
else:
self._train_by_executor(num_epochs, event_handler, reader,
feed_order)
def test(self, reader, feed_order):
"""
......@@ -245,7 +247,8 @@ class Trainer(object):
order in program
"""
return self._test_by_executor(reader, feed_order, self.test_outputs)
return self._test_by_executor(reader, feed_order,
self.train_func_outputs)
def save_params(self, param_path):
# reference: save_persistables in io.py
......@@ -279,13 +282,25 @@ class Trainer(object):
feeder = data_feeder.DataFeeder(
feed_list=feed_var_list, place=self.place)
exe = executor.Executor(self.place)
for epoch_id in range(num_epochs):
event_handler(BeginEpochEvent(epoch_id))
for step_id, data in enumerate(reader()):
event_handler(BeginStepEvent(epoch_id, step_id))
exe.run(feed=feeder.feed(data), fetch_list=[])
event_handler(EndStepEvent(epoch_id, step_id))
event_handler(EndEpochEvent(epoch_id))
reader = feeder.decorate_reader(reader, multi_devices=False)
self._train_by_any_executor(event_handler, exe, num_epochs, reader)
def _train_by_any_executor(self, event_handler, exe, num_epochs, reader):
for epoch_id in range(num_epochs):
event_handler(BeginEpochEvent(epoch_id))
for step_id, data in enumerate(reader()):
begin_event = BeginStepEvent(epoch_id, step_id)
event_handler(begin_event)
if begin_event.fetch_metrics:
metrics = exe.run(feed=data,
fetch_list=[
var.name
for var in self.train_func_outputs
])
else:
metrics = exe.run(feed=data, fetch_list=[])
event_handler(EndStepEvent(epoch_id, step_id, metrics))
event_handler(EndEpochEvent(epoch_id))
def _test_by_executor(self, reader, feed_order, fetch_list):
with executor.scope_guard(self.scope):
......@@ -304,6 +319,28 @@ class Trainer(object):
return [x / count for x in accumulated]
def _train_by_parallel_executor(self, num_epochs, event_handler, reader,
feed_order):
with self._prog_and_scope_guard():
pe = self._get_or_create_parallel_executor()
feed_var_list = build_feed_var_list(self.train_program, feed_order)
feeder = data_feeder.DataFeeder(
feed_list=feed_var_list, place=self.place)
reader = feeder.decorate_reader(reader, multi_devices=True)
for epoch_id in range(num_epochs):
self._train_by_any_executor(event_handler, pe, num_epochs,
reader)
def _get_parallel_executor(self):
return getattr(self, 'parallel_executor', None)
def _get_or_create_parallel_executor(self):
if self._get_parallel_executor() is None:
self.parallel_executor = parallel_executor.ParallelExecutor(
use_cuda=isinstance(self.place, core.CUDAPlace),
loss_name=self.train_func_outputs[0].name)
return self._get_parallel_executor()
def build_feed_var_list(program, feed_order):
if not isinstance(program, framework.Program):
......
......@@ -171,7 +171,7 @@ if args.timeline_path:
profile_paths = profile_path.split(',')
profile_dict = dict()
if len(profile_path) == 1:
if len(profile_paths) == 1:
with open(profile_path, 'r') as f:
profile_s = f.read()
profile_pb = profiler_pb2.Profile()
......
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