Global Namespace

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875
Date 2/28/2024
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Global Namespace

Overview

// namespaces

namespace dnnl;
    namespace dnnl::graph;
        namespace dnnl::graph::sycl_interop;
    namespace dnnl::ocl_interop;
    namespace dnnl::sycl_interop;
    namespace dnnl::threadpool_interop;
namespace oneapi;
namespace std;
namespace sycl;

// typedefs

typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef dnnl::memory::dim dim_t;
typedef dnnl::memory::dim dim_t;
typedef logical_tensor::data_type data_type;
typedef logical_tensor::layout_type layout_type;
typedef logical_tensor::dim dim;
typedef logical_tensor::dims dims;
typedef logical_tensor::data_type data_type;
typedef logical_tensor::layout_type layout_type;
typedef logical_tensor::property_type property_type;
typedef logical_tensor::dim dim;
typedef logical_tensor::dims dims;
typedef logical_tensor::data_type data_type;
typedef logical_tensor::layout_type layout_type;
typedef logical_tensor::dim dim;
typedef logical_tensor::dims dims;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef memory::format_tag tag;
typedef memory::data_type dt;
typedef struct dnnl_memory_desc* dnnl_memory_desc_t;
typedef const struct dnnl_memory_desc* const_dnnl_memory_desc_t;
typedef struct dnnl_memory* dnnl_memory_t;
typedef const struct dnnl_memory* const_dnnl_memory_t;
typedef struct dnnl_primitive_desc* dnnl_primitive_desc_t;
typedef const struct dnnl_primitive_desc* const_dnnl_primitive_desc_t;
typedef struct dnnl_primitive_attr* dnnl_primitive_attr_t;
typedef const struct dnnl_primitive_attr* const_dnnl_primitive_attr_t;
typedef struct dnnl_post_ops* dnnl_post_ops_t;
typedef const struct dnnl_post_ops* const_dnnl_post_ops_t;
typedef struct dnnl_primitive* dnnl_primitive_t;
typedef const struct dnnl_primitive* const_dnnl_primitive_t;
typedef int64_t dnnl_dim_t;
typedef dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS];
typedef struct dnnl_engine* dnnl_engine_t;
typedef struct dnnl_stream* dnnl_stream_t;
typedef const struct dnnl_stream* const_dnnl_stream_t;

typedef void* (*dnnl_graph_sycl_allocate_f)(
    size_t size,
    size_t alignment,
    const void *dev,
    const void *context
    );

typedef void (*dnnl_graph_sycl_deallocate_f)(
    void *buf,
    const void *dev,
    const void *context,
    void *event
    );

typedef struct dnnl_graph_partition* dnnl_graph_partition_t;
typedef const struct dnnl_graph_partition* const_dnnl_graph_partition_t;
typedef struct dnnl_graph_graph* dnnl_graph_graph_t;
typedef const struct dnnl_graph_graph* const_dnnl_graph_graph_t;
typedef struct dnnl_graph_op* dnnl_graph_op_t;
typedef const struct dnnl_graph_op* const_dnnl_graph_op_t;

typedef void* (*dnnl_graph_host_allocate_f)(
    size_t size,
    size_t alignment
    );

typedef void (*dnnl_graph_host_deallocate_f)(void *);
typedef struct dnnl_graph_allocator* dnnl_graph_allocator_t;
typedef const struct dnnl_graph_allocator* const_dnnl_graph_allocator_t;
typedef struct dnnl_graph_compiled_partition* dnnl_graph_compiled_partition_t;
typedef const struct dnnl_graph_compiled_partition* const_dnnl_graph_compiled_partition_t;
typedef struct dnnl_graph_tensor* dnnl_graph_tensor_t;
typedef const struct dnnl_graph_tensor* const_dnnl_graph_tensor_t;

// enums

enum dnnl_alg_kind_t;
enum dnnl_cpu_isa_hints_t;
enum dnnl_cpu_isa_t;
enum dnnl_data_type_t;
enum dnnl_engine_kind_t;
enum dnnl_format_kind_t;
enum dnnl_format_tag_t;
enum dnnl_fpmath_mode_t;
enum dnnl_graph_layout_type_t;
enum dnnl_graph_op_attr_t;
enum dnnl_graph_op_kind_t;
enum dnnl_graph_partition_policy_t;
enum dnnl_graph_tensor_property_t;
enum dnnl_normalization_flags_t;
enum dnnl_ocl_interop_memory_kind_t;
enum dnnl_primitive_kind_t;
enum dnnl_prop_kind_t;
enum dnnl_query_t;
enum dnnl_rnn_direction_t;
enum dnnl_rnn_flags_t;
enum dnnl_scratchpad_mode_t;
enum dnnl_status_t;
enum dnnl_stream_flags_t;
enum dnnl_sycl_interop_memory_kind_t;

// structs

struct args_t;
struct cpu_deletor;
struct dnnl_engine;
struct dnnl_exec_arg_t;
struct dnnl_graph_inplace_pair_t;
struct dnnl_graph_logical_tensor_t;
struct dnnl_memory;
struct dnnl_memory_desc;
struct dnnl_post_ops;
struct dnnl_primitive;
struct dnnl_primitive_attr;
struct dnnl_primitive_desc;
struct dnnl_stream;
struct dnnl_version_t;
struct example_allows_unimplemented;
struct gemm_dims_t;
struct sycl_deletor;

// global variables

const dim_t batch = 32;
const dim_t src_seq_length_max = 10;
const dim_t tgt_seq_length_max = 10;
const dim_t feature_size = 256;
const dim_t enc_bidir_n_layers = 1;
const dim_t enc_unidir_n_layers = 3;
const dim_t dec_n_layers = 4;
const int lstm_n_gates = 4;
const dim_t batch = 32;
const dim_t src_seq_length_max = 10;
const dim_t tgt_seq_length_max = 10;
const dim_t feature_size = 256;
const dim_t enc_bidir_n_layers = 1;
const dim_t enc_unidir_n_layers = 3;
const dim_t dec_n_layers = 4;
const int lstm_n_gates = 4;
static const int min_runs = 4;
const memory::dims strides = {4, 4};
const memory::dims padding = {0, 0};
const int N0 = 1 + rand() % 31;
const int N1 = 1 + rand() % 31;
const int T0 = 31 + 1 + rand() % 31;
const int T1 = 1 + rand() % 31;
const int leftmost_batch = N0 + N1;
const int rightmost_batch = N0;
const int leftmost_seq_length = T1;
const int rightmost_seq_length = T0 - T1;
const int common_feature_size = 1024;
const int common_n_layers = 1;
const int lstm_n_gates = 4;
engine eng(engine::kind::cpu, 0);
int number_of_runs = 1;
float fixed_beta = 0.f;
engine eng(engine::kind::cpu, 0);
int number_of_runs = 1;

// global functions

void bnorm_u8_via_binary_postops(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
static size_t product(dnnl_dim_t* arr, size_t size);
static void init_net_data(float* data, uint32_t dim, const dnnl_dim_t* dims);
static void prepare_arg_node(args_t* node, int nargs);
static void free_arg_node(args_t* node);
static void set_arg(dnnl_exec_arg_t* arg, int arg_idx, dnnl_memory_t memory);

static void init_data_memory(
    uint32_t dim,
    const dnnl_dim_t* dims,
    dnnl_format_tag_t user_tag,
    dnnl_engine_t engine,
    float* data,
    dnnl_memory_t* memory
    );

dnnl_status_t prepare_reorder(
    dnnl_memory_t* user_memory,
    const_dnnl_memory_desc_t prim_memory_md,
    dnnl_engine_t prim_engine,
    int dir_is_user_to_prim,
    dnnl_memory_t* prim_memory,
    dnnl_primitive_t* reorder,
    uint32_t* net_index,
    dnnl_primitive_t* net,
    args_t* net_args
    );

void simple_net(dnnl_engine_kind_t engine_kind);
int main(int argc, char** argv);
void cnn_inference_f32(engine::kind engine_kind);
int main(int argc, char** argv);
int main(int argc, char** argv);
void simple_net(engine::kind engine_kind);
int main(int argc, char** argv);
void simple_net(engine::kind engine_kind);
int main(int argc, char** argv);
static size_t product(dnnl_dim_t* arr, size_t size);
static void init_net_data(float* data, uint32_t dim, const dnnl_dim_t* dims);
static void prepare_arg_node(args_t* node, int nargs);
static void free_arg_node(args_t* node);
static void set_arg(dnnl_exec_arg_t* arg, int arg_idx, dnnl_memory_t memory);

static void init_data_memory(
    uint32_t dim,
    const dnnl_dim_t* dims,
    dnnl_format_tag_t user_tag,
    dnnl_engine_t engine,
    float* data,
    dnnl_memory_t* memory
    );

dnnl_status_t prepare_reorder(
    dnnl_memory_t* user_memory,
    const_dnnl_memory_desc_t prim_memory_md,
    dnnl_engine_t prim_engine,
    int dir_is_user_to_prim,
    dnnl_memory_t* prim_memory,
    dnnl_primitive_t* reorder,
    uint32_t* net_index,
    dnnl_primitive_t* net,
    args_t* net_args
    );

void simple_net();
int main(int argc, char** argv);
bool check_result(dnnl::memory dst_mem);
void sparse_matmul();
int main(int argc, char** argv);
std::vector<float> weighted_src_layer(batch* feature_size, 1. 0f);

std::vector<float> alignment_model(
    src_seq_length_max*batch* feature_size,
    1. 0f
    );

std::vector<float> alignments(src_seq_length_max* batch, 1. 0f);
std::vector<float> exp_sums(batch, 1. 0f);

void compute_weighted_annotations(
    float* weighted_annotations,
    dim_t src_seq_length_max,
    dim_t batch,
    dim_t feature_size,
    float* weights_annot,
    float* annotations
    );

void compute_attention(
    float* context_vectors,
    dim_t src_seq_length_max,
    dim_t batch,
    dim_t feature_size,
    float* weights_src_layer,
    float* dec_src_layer,
    float* annotations,
    float* weighted_annotations,
    float* weights_alignments
    );

void copy_context(
    float* src_iter,
    dim_t n_layers,
    dim_t batch,
    dim_t feature_size
    );

int main(int argc, char** argv);
std::vector<int32_t> weighted_src_layer(batch* feature_size, 1);

std::vector<float> alignment_model(
    src_seq_length_max*batch* feature_size,
    1. 0f
    );

std::vector<float> alignments(src_seq_length_max* batch, 1. 0f);
std::vector<float> exp_sums(batch, 1. 0f);

void compute_weighted_annotations(
    float* weighted_annotations,
    dim_t src_seq_length_max,
    dim_t batch,
    dim_t feature_size,
    float* weights_annot,
    float* annotations
    );

void compute_sum_of_rows(int8_t* a, dim_t rows, dim_t cols, int32_t* a_reduced);

void compute_attention(
    float* context_vectors,
    dim_t src_seq_length_max,
    dim_t batch,
    dim_t feature_size,
    int8_t* weights_src_layer,
    float weights_src_layer_scale,
    int32_t* compensation,
    uint8_t* dec_src_layer,
    float dec_src_layer_scale,
    float dec_src_layer_shift,
    uint8_t* annotations,
    float* weighted_annotations,
    float* weights_alignments
    );

void copy_context(
    float* src_iter,
    dim_t n_layers,
    dim_t batch,
    dim_t feature_size
    );

int main(int argc, char** argv);
size_t product(int n_dims, const dnnl_dim_t dims[]);
void fill(dnnl_memory_t mem, int n_dims, const dnnl_dim_t dims[]);
int find_negative(dnnl_memory_t mem, int n_dims, const dnnl_dim_t dims[]);
void cross_engine_reorder();
int main();
void fill(memory& mem, const memory::dims& adims);
int find_negative(memory& mem, const memory::dims& adims);
int main(int argc, char** argv);
static dnnl_engine_kind_t validate_engine_kind(dnnl_engine_kind_t akind);
static dnnl_engine_kind_t parse_engine_kind(int argc, char** argv);
static const char* engine_kind2str_upper(dnnl_engine_kind_t kind);
static void read_from_dnnl_memory(void* handle, dnnl_memory_t mem);
static void write_to_dnnl_memory(void* handle, dnnl_memory_t mem);
void finalize();
dnnl::engine::kind validate_engine_kind(dnnl::engine::kind akind);
const char* engine_kind2str_upper(dnnl::engine::kind kind);

int handle_example_errors(
    std::initializer_list<dnnl::engine::kind> engine_kinds,
    std::function<void()> example
    );

int handle_example_errors(
    std::function<void(dnnl::engine::kind, int, char**)> example,
    dnnl::engine::kind engine_kind,
    int argc,
    char** argv
    );

int handle_example_errors(
    std::function<void(dnnl::engine::kind)> example,
    dnnl::engine::kind engine_kind
    );

dnnl::engine::kind parse_engine_kind(int argc, char** argv, int extra_args = 0);
dnnl::memory::dim product(const dnnl::memory::dims& dims);
void read_from_dnnl_memory(void* handle, dnnl::memory& mem);
void write_to_dnnl_memory(void* handle, dnnl::memory& mem);
int main(int argc, char** argv);

cl_kernel create_init_opencl_kernel(
    cl_context ocl_ctx,
    const char* kernel_name,
    const char* ocl_code
    );

int main(int argc, char** argv);
int main(int argc, char** argv);
int main(int argc, char** argv);

void set_any_layout(
    const std::vector<dnnl::graph::partition>& partitions,
    std::unordered_set<size_t>& id_to_set_any_layout
    );

void* sycl_malloc_wrapper(
    size_t size,
    size_t alignment,
    const void* dev,
    const void* ctx
    );

void sycl_free_wrapper(
    void* ptr,
    const void* device,
    const void* context,
    void* event
    );

void allocate_graph_mem(
    std::vector<dnnl::graph::tensor>& tensors,
    const std::vector<dnnl::graph::logical_tensor>& lts,
    std::vector<std::shared_ptr<void>>& data_buffer,
    std::unordered_map<size_t, dnnl::graph::tensor>& global_outputs_ts_map,
    const dnnl::engine& eng,
    bool is_input
    );

void allocate_sycl_graph_mem(
    std::vector<dnnl::graph::tensor>& tensors,
    const std::vector<dnnl::graph::logical_tensor>& lts,
    std::vector<std::shared_ptr<void>>& data_buffer,
    std::unordered_map<size_t, dnnl::graph::tensor>& global_outputs_ts_map,
    sycl::queue& q,
    const dnnl::engine& eng,
    bool is_input
    );

int main(int argc, char** argv);
const char* get_type_string(dt type);
void print_test_case(dt type, gemm_dims_t dims);
void fill_random(std::vector<float>& out, bool is_integer);

double run_case(
    engine::kind engine_kind,
    dt type,
    gemm_dims_t dims,
    double time_limit = 0.
    );

void run(engine::kind engine_kind, dt type, gemm_dims_t dims, double time_limit);
void bad_args();
void matmul_perf(engine::kind engine_kind, int argc, char** argv);
int main(int argc, char** argv);
int main(int argc, char** argv);
void init_data(memory& m, float v);
void create_and_execute_relu(memory& data, engine& eng, stream& s);
primitive_attr create_attr_with_relu_post_op();
void performance_profiling(engine::kind engine_kind, int argc, char** argv);
int main(int argc, char** argv);
void augru_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void batch_normalization_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void binary_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void concat_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void convolution_example(dnnl::engine::kind engine_kind);
void depthwise_convolution_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void eltwise_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void group_normalization_example(engine::kind engine_kind);
int main(int argc, char** argv);
void inner_product_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void layer_normalization_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void lrn_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void lstm_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void matmul_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void pooling_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void prelu_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void reduction_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void reorder_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void resampling_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void shuffle_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void softmax_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void sum_example(dnnl::engine::kind engine_kind);
int main(int argc, char** argv);
void simple_net(engine::kind engine_kind);
int main(int argc, char** argv);
int main(int argc, char** argv);
void sycl_usm_tutorial(engine::kind engine_kind);
int main(int argc, char** argv);

void quantize(
    const std::vector<float>& X_f32,
    float scale_X,
    int32_t zp_X,
    memory& X_int_m
    );

void f32_matmul_compute(
    int64_t M,
    int64_t N,
    int64_t K,
    const std::vector<float>& A_f32,
    const std::vector<float>& B_f32,
    std::vector<float>& C_f32
    );

void dynamic_q10n_matmul(
    int64_t M,
    int64_t N,
    int64_t K,
    const std::vector<float>& A_f32,
    const std::vector<float>& B_f32,
    std::vector<uint8_t>& C_u8,
    float& scale_C,
    int32_t& zp_C
    );

void compare_f32_and_quantized_matmuls();
int main(int argc, char** argv);
matmul dynamic_matmul_create();

void dynamic_matmul_execute(
    matmul& matmul_p,
    char transA,
    char transB,
    int64_t M,
    int64_t N,
    int64_t K,
    float alpha,
    const float* A,
    int64_t lda,
    const float* B,
    int64_t ldb,
    float beta,
    float* C,
    int64_t ldc
    );

void sgemm_and_matmul_with_params(
    char transA,
    char transB,
    int64_t M,
    int64_t N,
    int64_t K,
    float alpha,
    float beta
    );

void sgemm_and_matmul();
int main(int argc, char** argv);
matmul::primitive_desc matmul_pd_create(int64_t K, int64_t N, const engine& eng);

void prepare_input(
    memory& A_u8_mem,
    memory& sc_A_mem,
    memory& sc_B_mem,
    memory& sc_C_mem,
    memory& zp_A_mem,
    memory& zp_C_mem
    );

void sanity_check(memory& C_u8_mem, memory& zp_C_mem);

void infer(
    const matmul& matmul_p,
    int64_t M,
    int64_t N,
    int64_t K,
    const memory& B_s8_mem,
    const engine& eng
    );

void inference_int8_matmul(engine::kind engine_kind);
int main(int argc, char** argv);
dnnl_status_t DNNL_API dnnl_primitive_desc_next_impl(dnnl_primitive_desc_t primitive_desc);

dnnl_status_t DNNL_API dnnl_primitive_desc_clone(
    dnnl_primitive_desc_t* primitive_desc,
    const_dnnl_primitive_desc_t existing_primitive_desc
    );

dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(
    const_dnnl_primitive_desc_t primitive_desc,
    const_dnnl_primitive_attr_t* attr
    );

dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc);

dnnl_status_t DNNL_API dnnl_primitive_desc_query(
    const_dnnl_primitive_desc_t primitive_desc,
    dnnl_query_t what,
    int index,
    void* result
    );

const_dnnl_memory_desc_t DNNL_API dnnl_primitive_desc_query_md(
    const_dnnl_primitive_desc_t primitive_desc,
    dnnl_query_t what,
    int index
    );

int DNNL_API dnnl_primitive_desc_query_s32(
    const_dnnl_primitive_desc_t primitive_desc,
    dnnl_query_t what,
    int index
    );

dnnl_status_t DNNL_API dnnl_primitive_create(
    dnnl_primitive_t* primitive,
    const_dnnl_primitive_desc_t primitive_desc
    );

dnnl_status_t DNNL_API dnnl_primitive_create_from_cache_blob(
    dnnl_primitive_t* primitive,
    const_dnnl_primitive_desc_t primitive_desc,
    size_t size,
    const uint8_t* cache_blob
    );

dnnl_status_t DNNL_API dnnl_primitive_execute(
    const_dnnl_primitive_t primitive,
    dnnl_stream_t stream,
    int nargs,
    const dnnl_exec_arg_t* args
    );

dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(
    const_dnnl_primitive_t primitive,
    const_dnnl_primitive_desc_t* primitive_desc
    );

dnnl_status_t DNNL_API dnnl_primitive_get_cache_blob(
    const_dnnl_primitive_t primitive,
    size_t* size,
    uint8_t* cache_blob
    );

dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive);
dnnl_status_t DNNL_API dnnl_primitive_attr_create(dnnl_primitive_attr_t* attr);

dnnl_status_t DNNL_API dnnl_primitive_attr_clone(
    dnnl_primitive_attr_t* attr,
    const_dnnl_primitive_attr_t existing_attr
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_destroy(dnnl_primitive_attr_t attr);

dnnl_status_t DNNL_API dnnl_primitive_attr_get_fpmath_mode(
    const_dnnl_primitive_attr_t attr,
    dnnl_fpmath_mode_t* mode
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_set_fpmath_mode(
    dnnl_primitive_attr_t attr,
    dnnl_fpmath_mode_t mode
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_get_scratchpad_mode(
    const_dnnl_primitive_attr_t attr,
    dnnl_scratchpad_mode_t* mode
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_set_scratchpad_mode(
    dnnl_primitive_attr_t attr,
    dnnl_scratchpad_mode_t mode
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_set_scales_mask(
    dnnl_primitive_attr_t attr,
    int arg,
    int mask
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_set_zero_points_mask(
    dnnl_primitive_attr_t attr,
    int arg,
    int mask
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_get_post_ops(
    const_dnnl_primitive_attr_t attr,
    const_dnnl_post_ops_t* post_ops
    );

dnnl_status_t DNNL_API dnnl_primitive_attr_set_post_ops(
    dnnl_primitive_attr_t attr,
    const_dnnl_post_ops_t post_ops
    );

dnnl_status_t DNNL_API dnnl_post_ops_create(dnnl_post_ops_t* post_ops);

dnnl_status_t DNNL_API dnnl_post_ops_clone(
    dnnl_post_ops_t* post_ops,
    const_dnnl_post_ops_t existing_post_ops
    );

dnnl_status_t DNNL_API dnnl_post_ops_destroy(dnnl_post_ops_t post_ops);
int DNNL_API dnnl_post_ops_len(const_dnnl_post_ops_t post_ops);

dnnl_primitive_kind_t DNNL_API dnnl_post_ops_get_kind(
    const_dnnl_post_ops_t post_ops,
    int index
    );

dnnl_status_t DNNL_API dnnl_post_ops_append_sum(
    dnnl_post_ops_t post_ops,
    float scale,
    int32_t zero_point,
    dnnl_data_type_t data_type
    );

dnnl_status_t DNNL_API dnnl_post_ops_get_params_sum(
    const_dnnl_post_ops_t post_ops,
    int index,
    float* scale,
    int32_t* zero_point,
    dnnl_data_type_t* data_type
    );

dnnl_status_t DNNL_API dnnl_post_ops_append_eltwise(
    dnnl_post_ops_t post_ops,
    dnnl_alg_kind_t alg_kind,
    float alpha,
    float beta
    );

dnnl_status_t DNNL_API dnnl_post_ops_get_params_eltwise(
    const_dnnl_post_ops_t post_ops,
    int index,
    dnnl_alg_kind_t* alg_kind,
    float* alpha,
    float* beta
    );

dnnl_status_t DNNL_API dnnl_post_ops_append_dw(
    dnnl_post_ops_t post_ops,
    dnnl_data_type_t weights_data_type,
    dnnl_data_type_t bias_data_type,
    dnnl_data_type_t dst_data_type,
    dnnl_dim_t kernel_size,
    dnnl_dim_t stride_size,
    dnnl_dim_t padding_l_size
    );

dnnl_status_t DNNL_API dnnl_post_ops_get_params_dw(
    const_dnnl_post_ops_t post_ops,
    int index,
    dnnl_data_type_t* weights_data_type,
    dnnl_data_type_t* bias_data_type,
    dnnl_data_type_t* dst_data_type,
    dnnl_dim_t* kernel_size,
    dnnl_dim_t* stride_size,
    dnnl_dim_t* padding_l_size
    );

dnnl_status_t DNNL_API dnnl_post_ops_append_binary(
    dnnl_post_ops_t post_ops,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t src1_desc
    );

dnnl_status_t DNNL_API dnnl_post_ops_get_params_binary(
    const_dnnl_post_ops_t post_ops,
    int index,
    dnnl_alg_kind_t* alg_kind,
    const_dnnl_memory_desc_t* src1_desc
    );

dnnl_status_t DNNL_API dnnl_post_ops_append_prelu(
    dnnl_post_ops_t post_ops,
    int mask
    );

dnnl_status_t DNNL_API dnnl_post_ops_get_params_prelu(
    const_dnnl_post_ops_t post_ops,
    int index,
    int* mask
    );

dnnl_status_t DNNL_API dnnl_memory_desc_destroy(dnnl_memory_desc_t memory_desc);

dnnl_status_t DNNL_API dnnl_memory_desc_clone(
    dnnl_memory_desc_t* memory_desc,
    const_dnnl_memory_desc_t existing_memory_desc
    );

dnnl_status_t DNNL_API dnnl_memory_desc_create_with_strides(
    dnnl_memory_desc_t* memory_desc,
    int ndims,
    const dnnl_dims_t dims,
    dnnl_data_type_t data_type,
    const dnnl_dims_t strides
    );

dnnl_status_t DNNL_API dnnl_memory_desc_create_with_tag(
    dnnl_memory_desc_t* memory_desc,
    int ndims,
    const dnnl_dims_t dims,
    dnnl_data_type_t data_type,
    dnnl_format_tag_t tag
    );

dnnl_status_t DNNL_API dnnl_memory_desc_create_submemory(
    dnnl_memory_desc_t* memory_desc,
    const_dnnl_memory_desc_t parent_memory_desc,
    const dnnl_dims_t dims,
    const dnnl_dims_t offsets
    );

dnnl_status_t DNNL_API dnnl_memory_desc_reshape(
    dnnl_memory_desc_t* out_memory_desc,
    const_dnnl_memory_desc_t in_memory_desc,
    int ndims,
    const dnnl_dims_t dims
    );

dnnl_status_t DNNL_API dnnl_memory_desc_permute_axes(
    dnnl_memory_desc_t* out_memory_desc,
    const_dnnl_memory_desc_t in_memory_desc,
    const int* permutation
    );

dnnl_status_t DNNL_API dnnl_memory_desc_query(
    const_dnnl_memory_desc_t memory_desc,
    dnnl_query_t what,
    void* result
    );

int DNNL_API dnnl_memory_desc_equal(
    const_dnnl_memory_desc_t lhs,
    const_dnnl_memory_desc_t rhs
    );

size_t DNNL_API dnnl_memory_desc_get_size(const_dnnl_memory_desc_t memory_desc);
size_t DNNL_API dnnl_data_type_size(dnnl_data_type_t data_type);

dnnl_status_t DNNL_API dnnl_memory_create(
    dnnl_memory_t* memory,
    const_dnnl_memory_desc_t memory_desc,
    dnnl_engine_t engine,
    void* handle
    );

dnnl_status_t DNNL_API dnnl_memory_get_memory_desc(
    const_dnnl_memory_t memory,
    const_dnnl_memory_desc_t* memory_desc
    );

dnnl_status_t DNNL_API dnnl_memory_get_engine(
    const_dnnl_memory_t memory,
    dnnl_engine_t* engine
    );

dnnl_status_t DNNL_API dnnl_memory_map_data(
    const_dnnl_memory_t memory,
    void** mapped_ptr
    );

dnnl_status_t DNNL_API dnnl_memory_unmap_data(
    const_dnnl_memory_t memory,
    void* mapped_ptr
    );

dnnl_status_t DNNL_API dnnl_memory_get_data_handle(
    const_dnnl_memory_t memory,
    void** handle
    );

dnnl_status_t DNNL_API dnnl_memory_set_data_handle(
    dnnl_memory_t memory,
    void* handle
    );

dnnl_status_t DNNL_API dnnl_memory_destroy(dnnl_memory_t memory);

dnnl_status_t DNNL_API dnnl_reorder_primitive_desc_create(
    dnnl_primitive_desc_t* reorder_primitive_desc,
    const_dnnl_memory_desc_t src_desc,
    dnnl_engine_t src_engine,
    const_dnnl_memory_desc_t dst_desc,
    dnnl_engine_t dst_engine,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_concat_primitive_desc_create(
    dnnl_primitive_desc_t* concat_primitive_desc,
    dnnl_engine_t engine,
    const_dnnl_memory_desc_t dst_desc,
    int n,
    int concat_dimension,
    const_dnnl_memory_desc_t const* src_descs,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_sum_primitive_desc_create(
    dnnl_primitive_desc_t* sum_primitive_desc,
    dnnl_engine_t engine,
    const_dnnl_memory_desc_t dst_desc,
    int n,
    const float* scales,
    const_dnnl_memory_desc_t const* src_descs,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_binary_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t src0_desc,
    const_dnnl_memory_desc_t src1_desc,
    const_dnnl_memory_desc_t dst_desc,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_convolution_forward_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_prop_kind_t prop_kind,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t src_desc,
    const_dnnl_memory_desc_t weights_desc,
    const_dnnl_memory_desc_t bias_desc,
    const_dnnl_memory_desc_t dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t dilates,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_attr_t attr
    );

dnnl_status_t DNNL_API dnnl_convolution_backward_data_primitive_desc_create(
    dnnl_primitive_desc_t* primitive_desc,
    dnnl_engine_t engine,
    dnnl_alg_kind_t alg_kind,
    const_dnnl_memory_desc_t diff_src_desc,
    const_dnnl_memory_desc_t weights_desc,
    const_dnnl_memory_desc_t diff_dst_desc,
    const dnnl_dims_t strides,
    const dnnl_dims_t dilates,
    const dnnl_dims_t padding_l,
    const dnnl_dims_t padding_r,
    const_dnnl_primitive_desc_t hint_fwd_pd,
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