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vx_khr_nn.h File Reference
The Khronos Extension for Deep Convolutional Networks Functions. More...
#include <VX/vx.h>Go to the source code of this file.
Data Structures | |
| struct | _vx_nn_convolution_params_t |
| Input parameters for a convolution operation. More... | |
| struct | _vx_nn_deconvolution_params_t |
| Input parameters for a deconvolution operation. More... | |
| struct | _vx_nn_roi_pool_params_t |
| Input parameters for ROI pooling operation. More... | |
Macros | |
| #define | OPENVX_KHR_NN "vx_khr_nn" |
| #define | VX_LIBRARY_KHR_NN_EXTENSION (0x1) |
| The Neural Network Extension Library Set. | |
Typedefs | |
| typedef struct _vx_nn_convolution_params_t | vx_nn_convolution_params_t |
| Input parameters for a convolution operation. | |
| typedef struct _vx_nn_deconvolution_params_t | vx_nn_deconvolution_params_t |
| Input parameters for a deconvolution operation. | |
| typedef struct _vx_nn_roi_pool_params_t | vx_nn_roi_pool_params_t |
| Input parameters for ROI pooling operation. | |
Enumerations | |
| enum | vx_kernel_nn_ext_e { VX_KERNEL_CONVOLUTION_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x0 , VX_KERNEL_FULLY_CONNECTED_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x1 , VX_KERNEL_POOLING_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x2 , VX_KERNEL_SOFTMAX_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x3 , VX_KERNEL_ACTIVATION_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x5 , VX_KERNEL_ROI_POOLING_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x6 , VX_KERNEL_DECONVOLUTION_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x7 , VX_KERNEL_LOCAL_RESPONSE_NORMALIZATION_LAYER = VX_KERNEL_BASE(VX_ID_KHRONOS, VX_LIBRARY_KHR_NN_EXTENSION) + 0x8 } |
| The list of Neural Network Extension Kernels. More... | |
| enum | vx_nn_enum_e { VX_ENUM_NN_ROUNDING_TYPE = 0x1A , VX_ENUM_NN_POOLING_TYPE = 0x1B , VX_ENUM_NN_NORMALIZATION_TYPE = 0x1C , VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE = 0x1D } |
| NN extension type enums. | |
| enum | vx_nn_rounding_type_e { VX_NN_DS_SIZE_ROUNDING_FLOOR = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ROUNDING_TYPE) + 0x0 , VX_NN_DS_SIZE_ROUNDING_CEILING = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ROUNDING_TYPE) + 0x1 } |
| down scale rounding. More... | |
| enum | vx_nn_pooling_type_e { VX_NN_POOLING_MAX = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_POOLING_TYPE) + 0x0 , VX_NN_POOLING_AVG = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_POOLING_TYPE) + 0x1 } |
| The Neural Network pooling type list. More... | |
| enum | vx_nn_norm_type_e { VX_NN_NORMALIZATION_SAME_MAP = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_NORMALIZATION_TYPE) + 0x0 , VX_NN_NORMALIZATION_ACROSS_MAPS = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_NORMALIZATION_TYPE) + 0x1 } |
| The Neural Network normalization type list. More... | |
| enum | vx_nn_activation_function_e { VX_NN_ACTIVATION_LOGISTIC = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x0 , VX_NN_ACTIVATION_HYPERBOLIC_TAN = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x1 , VX_NN_ACTIVATION_RELU = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x2 , VX_NN_ACTIVATION_BRELU = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x3 , VX_NN_ACTIVATION_SOFTRELU = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x4 , VX_NN_ACTIVATION_ABS = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x5 , VX_NN_ACTIVATION_SQUARE = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x6 , VX_NN_ACTIVATION_SQRT = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x7 , VX_NN_ACTIVATION_LINEAR = VX_ENUM_BASE(VX_ID_KHRONOS, VX_ENUM_NN_ACTIVATION_FUNCTION_TYPE) + 0x8 } |
| The Neural Network activation functions list. More... | |
| enum | vx_nn_type_e { VX_TYPE_NN_CONVOLUTION_PARAMS = 0x025 , VX_TYPE_NN_DECONVOLUTION_PARAMS = 0x026 , VX_TYPE_NN_ROI_POOL_PARAMS = 0x027 } |
| The type enumeration lists all NN extension types. More... | |
Functions | |
| VX_API_ENTRY vx_node VX_API_CALL | vxConvolutionLayer (vx_graph graph, vx_tensor inputs, vx_tensor weights, vx_tensor biases, const vx_nn_convolution_params_t *convolution_params, vx_size size_of_convolution_params, vx_tensor outputs) |
| [Graph] Creates a Convolutional Network Convolution Layer Node. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxFullyConnectedLayer (vx_graph graph, vx_tensor inputs, vx_tensor weights, vx_tensor biases, vx_enum overflow_policy, vx_enum rounding_policy, vx_tensor outputs) |
| [Graph] Creates a Fully connected Convolutional Network Layer Node. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxPoolingLayer (vx_graph graph, vx_tensor inputs, vx_enum pooling_type, vx_size pooling_size_x, vx_size pooling_size_y, vx_size pooling_padding_x, vx_size pooling_padding_y, vx_enum rounding, vx_tensor outputs) |
| [Graph] Creates a Convolutional Network Pooling Layer Node. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxSoftmaxLayer (vx_graph graph, vx_tensor inputs, vx_tensor outputs) |
| [Graph] Creates a Convolutional Network Softmax Layer Node. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxLocalResponseNormalizationLayer (vx_graph graph, vx_tensor inputs, vx_enum type, vx_size normalization_size, vx_float32 alpha, vx_float32 beta, vx_float32 bias, vx_tensor outputs) |
| [Graph] Creates a Convolutional Network Local Response Normalization Layer Node. This function is optional for 8-bit extension with the extension string 'KHR_NN_8'. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxActivationLayer (vx_graph graph, vx_tensor inputs, vx_enum function, vx_float32 a, vx_float32 b, vx_tensor outputs) |
[Graph] Creates a Convolutional Network Activation Layer Node. The function operate a specific function (Specified in vx_nn_activation_function_e), On the input data. the equation for the layer is: \( outputs(i,j,k,l) = function(inputs(i,j,k,l), a, b) \) for all i,j,k,l. More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxROIPoolingLayer (vx_graph graph, vx_tensor input_data, vx_tensor input_rois, const vx_nn_roi_pool_params_t *roi_pool_params, vx_size size_of_roi_params, vx_tensor output_arr) |
| [Graph] Creates a Convolutional Network ROI pooling node More... | |
| VX_API_ENTRY vx_node VX_API_CALL | vxDeconvolutionLayer (vx_graph graph, vx_tensor inputs, vx_tensor weights, vx_tensor biases, const vx_nn_deconvolution_params_t *deconvolution_params, vx_size size_of_deconv_params, vx_tensor outputs) |
| [Graph] Creates a Convolutional Network Deconvolution Layer Node. More... | |
Detailed Description
The Khronos Extension for Deep Convolutional Networks Functions.