#include <algorithm>
#include <cmath>
#include <iostream>
#include <string>
#include <vector>
#include "example_utils.hpp"
N = 3,
C = 227;
std::vector<float> src_data(product(src_dims));
std::vector<float> scale_shift_data(product(scale_shift_dims));
std::generate(src_data.begin(), src_data.end(), []() {
static int i = 0;
return std::cos(i++ / 10.f);
});
auto mid = scale_shift_data.begin() + C;
std::generate(scale_shift_data.begin(), mid, []() {
static int i = 0;
return std::sin(i++ * 2.f);
});
std::generate(mid, scale_shift_data.end(), []() {
static int i = 0;
return std::tanh(i++);
});
auto src_md = memory::desc(src_dims, dt::f32, tag::tnc);
auto src_mem = memory(src_md, engine);
auto scale_shift_mem = memory({scale_shift_dims, dt::f32, tag::nc},
engine);
write_to_dnnl_memory(src_data.data(), src_mem);
write_to_dnnl_memory(scale_shift_data.data(), scale_shift_mem);
const float epsilon = 1.e-10f;
auto lnorm_desc
auto lnorm_pd
= layer_normalization_forward::primitive_desc(lnorm_desc, engine);
auto mean_mem = memory(lnorm_pd.mean_desc(), engine);
auto variance_mem = memory(lnorm_pd.variance_desc(), engine);
auto lnorm_prim = layer_normalization_forward(lnorm_pd);
std::unordered_map<int, memory> lnorm_args;
lnorm_prim.execute(engine_stream, lnorm_args);
engine_stream.wait();
read_from_dnnl_memory(src_data.data(), src_mem);
}
int main(int argc, char **argv) {
return handle_example_errors(
layer_normalization_example, parse_engine_kind(argc, argv));
}
@ forward_training
Forward data propagation (training mode).
#define DNNL_ARG_DST
A special mnemonic for destination argument for primitives that have a single destination.
Definition: dnnl_types.h:2422
#define DNNL_ARG_SCALE_SHIFT
A special mnemonic for scale and shift argument of normalization primitives.
Definition: dnnl_types.h:2448
#define DNNL_ARG_MEAN
Mean values tensor argument.
Definition: dnnl_types.h:2475
#define DNNL_ARG_VARIANCE
Variance values tensor argument.
Definition: dnnl_types.h:2477
#define DNNL_ARG_SRC
A special mnemonic for source argument for primitives that have a single source.
Definition: dnnl_types.h:2398
@ src_md
source memory desc
@ use_scale_shift
Use scale and shift parameters.
oneDNN namespace
Definition: dnnl.hpp:74
An execution engine.
Definition: dnnl.hpp:895
kind
Kinds of engines.
Definition: dnnl.hpp:900
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1138
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1237
data_type
Data type specification.
Definition: dnnl.hpp:1156
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1141
An execution stream.
Definition: dnnl.hpp:1011