struct dnnl_memory_desc_t¶
Overview¶
Memory descriptor. More…
#include <dnnl_types.h> struct dnnl_memory_desc_t { // fields int ndims; dnnl_dims_t dims; dnnl_data_type_t data_type; dnnl_dims_t padded_dims; dnnl_dims_t padded_offsets; dnnl_dim_t offset0; dnnl_format_kind_t format_kind; dnnl_blocking_desc_t blocking; dnnl_wino_desc_t wino_desc; dnnl_rnn_packed_desc_t rnn_packed_desc; union dnnl_memory_desc_t::@2 format_desc; dnnl_memory_extra_desc_t extra; };
Detailed Documentation¶
Memory descriptor.
The description is based on a number of dimensions, dimensions themselves, plus information about elements type and memory format. Additionally, contains format-specific descriptions of the data layout.
Fields¶
int ndims
Number of dimensions.
dnnl_dims_t dims
Dimensions in the following order:
CNN data tensors: mini-batch, channel, spatial (
{N, C, [[D,] H,] W}
)CNN weight tensors: group (optional), output channel, input channel, spatial (
{[G,] O, I, [[D,] H,] W}
)RNN data tensors: time, mini-batch, channels (
{T, N, C}
) or layers, directions, states, mini-batch, channels ({L, D, S, N, C}
)RNN weight tensor: layers, directions, input channel, gates, output channels (
{L, D, I, G, O}
).
Note
The order of dimensions does not depend on the memory format, so whether the data is laid out in dnnl_nchw or dnnl_nhwc the dims for 4D CN data tensor would be {N, C, H, W}
.
dnnl_data_type_t data_type
Data type of the tensor elements.
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
dnnl_dims_t padded_offsets
Per-dimension offset from the padding to actual data, the top-level tensor with offsets applied must lie within the padding area.
dnnl_dim_t offset0
Offset from memory origin to the current block, non-zero only in a description of a memory sub-block.
dnnl_format_kind_t format_kind
Memory format kind.
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.