Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)
0.10
Performance library for Deep Learning
|
Memory descriptor. More...
#include <mkldnn_types.h>
Public Attributes | |
mkldnn_primitive_kind_t | primitive_kind |
The kind of primitive. More... | |
int | ndims |
Number of dimensions. More... | |
mkldnn_dims_t | dims |
Dimensions in the following order: mini-batch, channel, spatial. More... | |
mkldnn_data_type_t | data_type |
Data type of the tensor elements. More... | |
mkldnn_memory_format_t | format |
Memory format. More... | |
union { | |
mkldnn_blocking_desc_t blocking | |
Description of the data layout for memory formats that use blocking. More... | |
} | layout_desc |
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.
mkldnn_blocking_desc_t mkldnn_memory_desc_t::blocking |
Description of the data layout for memory formats that use blocking.
mkldnn_data_type_t mkldnn_memory_desc_t::data_type |
Data type of the tensor elements.
mkldnn_dims_t mkldnn_memory_desc_t::dims |
Dimensions in the following order: mini-batch, channel, spatial.
For example: {N, C, H, W}
.
mkldnn_memory_format_t mkldnn_memory_desc_t::format |
Memory format.
union { ... } mkldnn_memory_desc_t::layout_desc |
int mkldnn_memory_desc_t::ndims |
Number of dimensions.
mkldnn_primitive_kind_t mkldnn_memory_desc_t::primitive_kind |
The kind of primitive.
Used for self identifying the primitive descriptor. Must be mkldnn_memory.