►Ndcnnasgn | |
Caggregate_ik_map_functor | Functor to cast input to kernel indexes (without any change in value) |
Cas_kernel | Retag input dimension policy as kernel dimension policy |
Cbatch_tag | Tag: Images within a minibatch |
Cchannel_selector | Tag: Channel dimension |
Cchannel_size_policy | Channel size policy |
Ccombined_data | Input data, forward-propagated activations, and loss of the complete network |
Ccombined_model | Model data (weights and biases) of the complete network |
Ccombined_policy | Policy: The complete network |
Cconv_ik_range_functor | Functor: Input index to kernel index range |
Cconv_iko_map_functor | Functor: Input index to neg_delta_functor |
Cconv_kernel_size_policy | Policy class: Convolution kernel dimensions |
Cconv_ko_range_functor | Functor: Kernel index to output index range |
Cconv_koi_map_functor | Functor: Kernel index to delta_functor |
Cconv_ok_range_functor | Functor: Output index to kernel index range |
Cconv_oki_map_functor | Functor: Output index to delta_functor |
Cconv_weight_policy | Policy class: Model weight data types for convolutional layers |
Cconv_weight_size_policy | Policy class: Model weight dimensions for convolutional layers |
Cdelta_functor | Functor to add a fixed value |
Ce_channel_policy | Policy: Internal activation channels |
Cf_channel_policy | Policy: Internal activation channels |
Cfeature_bias_policy | |
Cfeature_conv_layer_base | Utility base class for the fully connected layer |
Cfeature_data_policy | Final layer activation data policy |
Cfeature_multiplier_policy | |
Cfeature_shift_layer_base | |
Cfeature_weight_policy | Policy class: Model weight data types for fully connected layers |
Cfeature_weight_size_policy | Policy class: Model weight dimensions for fully connected layers |
Cfinal_maxpool_layer_base | |
Cfirst_data_policy | |
Cfirst_normalize_layer_base | Utility base class for the first normalizing layer |
Cg_channel_policy | Policy: Internal activation channels |
Cglobal_state | The global state, shared by all threads |
Ch_channel_policy | Policy: Internal activation channels |
Cheight_selector | Tag: Height dimension of an image |
Cimage_data_policy | Internal layer activation data policy |
Cimage_data_size_policy | Combined image and channel size policy |
Cimage_maxpool_layer_base | |
Cimage_multiply_layer_base | Utility base class for the image multiply layer |
Cimage_normalize_layer_base | Utility base class for a normalizing layer |
Cimage_relu_layer_base | |
Cimage_shift_layer_base | Utility base class for the image shift layer |
Cimage_size_policy | Image size policy |
Cj_channel_policy | Policy: Internal activation channels |
Ckernel_height_selector | Tag: Kernel height dimension |
Ckernel_width_selector | Tag: Kernel width dimension |
Cl_f_data_policy | |
Cl_image_policy | Policy: Image after the third strided convolution layer (12) |
Clabels_channel_policy | Policy: Final linear layer channels |
Closs_data | Loss data class |
Closs_data_policy | Loss data policy |
Closs_layer_base | |
Cm_f_data_policy | |
Cm_g_data_policy | |
Cm_h_data_policy | |
Cm_image_policy | Policy: Image after the first MaxPool layer (24) |
Cmaxpool_height_selector | |
Cmaxpool_height_stag | |
Cmaxpool_koi_map_functor | |
Cmaxpool_width_selector | |
Cmaxpool_width_stag | |
Cmonochrome_channel_policy | Policy: Input image channels |
Cmul_delta_functor | Functor to multiply by a constant and add a fixed value |
Cneg_delta_functor | Functor to subtract from a fixed value |
Cno_kernel_policy | |
Cnonstrided_conv_layer_base | Utility base class for the convolutional layer |
Crgb_channel_policy | Policy: Input image channels |
Cs_g_data_policy | |
Cs_h_data_policy | |
Cs_image_policy | Policy: Image after the second MaxPool layer (42) |
Cs_j_data_policy | |
Cstandard_kernel_policy | Policy: Convolution kernel size |
Cstrided_conv_layer_base | Utility base class for the convolutional layer |
Cthread_state | The thread-related state |
Cwidth_selector | Tag: Width dimension of an image |
Cxl_f_data_policy | |
Cxl_image_policy | Policy: Image after the second strided convolution layer (04) |
Cxxl_e_data_policy | |
Cxxl_image_policy | Policy: Image after the first strided convolution layer (00) |
Cxxxl_image_policy | Policy: Input image size |
►Ndcnnsol | |
Cbatch_tag | Tag: Images within a minibatch |
Cchannel_selector | Tag: Channel dimension |
Ccomplete_cnn_internal< SPI, SPO, permutation_policy > | Internal activation and normalization-state data of a complete layer |
Ccomplete_cnn_layer< SPI, SPO, KSP, permutation_policy > | A complete layer |
Ccomplete_cnn_model< CSPI, CSPO, KSP, permutation_policy > | Model data of a complete layer |
Cconv_weight_policy | Policy class: Model weight data types for convolutional layers |
Cconv_weights< KSP, CSPI, CSPO, permutation_policy > | Convolution or Aggregate layer model |
Cfeature_bias< CSP, permutation_policy > | Shift layer model |
Cfeature_bias_policy | |
Cfeature_conv_layer< CSPI, CSPO, permutation_policy > | A fully-connected layer |
Cfeature_conv_layer_base | Utility base class for the fully connected layer |
Cfeature_data< CSP, permutation_policy > | Output of the final Aggregate layer |
Cfeature_data_policy | Final layer activation data policy |
Cfeature_multiplier< CSP, permutation_policy > | Multiplier layer model |
Cfeature_multiplier_policy | |
Cfeature_shift_layer< CSP, permutation_policy > | Final shift layer |
Cfeature_shift_layer_base | |
Cfeature_weight_policy | Policy class: Model weight data types for fully connected layers |
Cfeature_weights< CSPI, CSPO, permutation_policy > | Fully connected layer model |
Cfinal_maxpool_layer< SPI, CSPO, permutation_policy > | A MaxPool layer |
Cfinal_maxpool_layer_base | |
Cfirst_normalize_layer< SP, permutation_policy > | The first Normalizing layer |
Cfirst_normalize_layer_base | Utility base class for the first normalizing layer |
Cheight_selector | Tag: Height dimension of an image |
Cimage_data< SP, permutation_policy > | Forward-propagated data between layers |
Cimage_data_policy | Internal layer activation data policy |
Cimage_maxpool_layer< SPI, SPO, permutation_policy > | A MaxPool layer |
Cimage_maxpool_layer_base | |
Cimage_multiply_layer< SP, permutation_policy > | Multiply layer |
Cimage_multiply_layer_base | Utility base class for the image multiply layer |
Cimage_normalize_layer< SP, permutation_policy > | A normalizing layer |
Cimage_normalize_layer_base | Utility base class for a normalizing layer |
Cimage_relu_layer< SP, permutation_policy > | A ReLU layer |
Cimage_relu_layer_base | |
Cimage_shift_layer< SP, permutation_policy > | Shift layer |
Cimage_shift_layer_base | Utility base class for the image shift layer |
Ckernel_height_selector | Tag: Kernel height dimension |
Ckernel_width_selector | Tag: Kernel width dimension |
Closs_layer< CSP, permutation_policy > | The loss layer |
Closs_layer_base | |
Cnonstrided_conv_layer< SPI, SPO, KSP, permutation_policy > | A convolutional layer, non-strided case |
Cnonstrided_conv_layer_base | Utility base class for the convolutional layer |
Cpermutation_policy | Policy class defining the layout of all major data |
Cstrided_conv_layer< SPI, SPO, KSP, permutation_policy > | A convolutional layer, strided case |
Cstrided_conv_layer_base | Utility base class for the convolutional layer |
Ctag_list | A wrapped list of tags |
Ctensor_class | A tensor - a multi-dimensional tagged generalization of vector/matrix |
Cwidth_selector | Tag: Width dimension of an image |
►Ntagged | |
Cindex_class | A list of tagged indexes (a position in an N-dimensional space) |
Cindex_class< T > | A tagged index |
Crange_class | A list of tagged ranges (an N-dimensional box) |
Crange_class< T > | A range generating tagged index values |
Ctag_list | A wrapped list of tags |
Ctensor_class | A tensor - a multi-dimensional tagged generalization of vector/matrix |
Ctensor_view | A reference to a sub-space of a tensor |