# Data Model¶

oneDNN Graph uses logical tensor to describe data type, shape, and layout. The data type could be FP32, INT8, BF16, FP16, and future extension. The shape contains multiple dimensions, and the total dimension and the size of the dimension could be set as unknown.

oneDNN Graph supports both public layout and opaque layout. When the layout_type of logical tensor is strided, it means that the tensor layout is public which the user can identify each tensor element in the physical memory.

For example, for $$dims[][][] = {x, y, z}$$, $$strides[][][] = {s0, s1, s2}$$, the physical memory location should be in $$s0*x+s1*y+s2*z$$.

When the layout_type of logical tensor is opaque, users are not supposed to interpret the memory buffer directly. An opaque tensor can only be output from oneDNN Graph’s compiled partition and can only be fed to another compile partition as an input tensor.