Documentation
Rate This Document
Findability
Accuracy
Completeness
Readability
SubmitClose

Feature Scope

Data Types

Table 1 Parameter data types

Input Data (src) Type

Output Data (dst) Type

Scale and Shift Data Type

f32

f32

f32

f16

f16

f16

bf16

bf16

bf16

Propagation Directions and Flags

Flag

Propagation Direction

dnnl_normalization_flags_none (default normalization)
  • Forward:
    • dnnl_forward_training
    • dnnl_forward_inference
  • Backward:
    • dnnl_backward_data
    • dnnl_backward

dnnl_use_global_stats (global statistics)

dnnl_use_scale (enabling the scale parameter)

Forward:

  • dnnl_forward_training
  • dnnl_forward_inference

dnnl_use_shift (enabling the shift parameter)

dnnl_use_global_stats | dnnl_use_scale | dnnl_use_shift

Data Layout

Table 2 Mapping between each tensor dimension and parameter data layout

Tensor Dimension

Input Tensor (src) Data Layout

Output Tensor (dst) Data Layout

Data Layout of Divided Difference and Variance Tensors

2D

dnnl_ab

dnnl_ab

dnnl_a

3D

dnnl_abc

dnnl_abc

dnnl_ab

4D

dnnl_abcd

dnnl_abcd

dnnl_abc

5D

dnnl_abcde

dnnl_abcde

dnnl_abcd
Parent topic: Layer Normalization