| backward() | mic::mlnn::fully_connected::Linear< eT > | inlinevirtual |
| mic::mlnn::Layer::backward(mic::types::MatrixPtr< eT > dy_) | mic::mlnn::Layer< eT > | inline |
| batch_size | mic::mlnn::Layer< eT > | protected |
| batchSize() | mic::mlnn::Layer< eT > | inline |
| calculateMeanReconstructionError() | mic::mlnn::fully_connected::Linear< eT > | inline |
| calculateNumericalGradient(mic::types::MatrixPtr< eT > x_, mic::types::MatrixPtr< eT > target_y_, mic::types::MatrixPtr< eT > param_, loss loss_, eT delta_) | mic::mlnn::Layer< eT > | inline |
| dw_activations | mic::mlnn::fully_connected::Linear< eT > | private |
| dx_activations | mic::mlnn::Layer< eT > | protected |
| dy_activations | mic::mlnn::Layer< eT > | protected |
| forward(bool test_=false) | mic::mlnn::fully_connected::Linear< eT > | inlinevirtual |
| mic::mlnn::Layer::forward(mic::types::MatrixPtr< eT > x_, bool test=false) | mic::mlnn::Layer< eT > | inline |
| g | mic::mlnn::Layer< eT > | protected |
| getGradient(std::string name_) | mic::mlnn::Layer< eT > | inline |
| getInputActivations() | mic::mlnn::Layer< eT > | inlinevirtual |
| getInputGradientActivations() | mic::mlnn::Layer< eT > | inlinevirtual |
| getInverseOutputActivations() | mic::mlnn::fully_connected::Linear< eT > | inline |
| getInverseWeightActivations() | mic::mlnn::fully_connected::Linear< eT > | inline |
| getOutputActivations() | mic::mlnn::Layer< eT > | inlinevirtual |
| getOutputGradientActivations() | mic::mlnn::Layer< eT > | inlinevirtual |
| getParam(std::string name_) | mic::mlnn::Layer< eT > | inline |
| getState(std::string name_) | mic::mlnn::Layer< eT > | inline |
| getWeightActivations() | mic::mlnn::fully_connected::Linear< eT > | inline |
| getWeightGradientActivations() | mic::mlnn::fully_connected::Linear< eT > | inline |
| input_depth | mic::mlnn::Layer< eT > | protected |
| input_height | mic::mlnn::Layer< eT > | protected |
| input_width | mic::mlnn::Layer< eT > | protected |
| inputSize() | mic::mlnn::Layer< eT > | inline |
| inverse_w_activations | mic::mlnn::fully_connected::Linear< eT > | private |
| inverse_y_activations | mic::mlnn::fully_connected::Linear< eT > | private |
| Layer(size_t input_height_, size_t input_width_, size_t input_depth_, size_t output_height_, size_t output_width_, size_t output_depth_, LayerTypes layer_type_, std::string name_="layer") | mic::mlnn::Layer< eT > | inline |
| Layer() | mic::mlnn::Layer< eT > | inlineprotected |
| layer_name | mic::mlnn::Layer< eT > | protected |
| layer_type | mic::mlnn::Layer< eT > | protected |
| lazyAllocateMatrixVector(std::vector< std::shared_ptr< mic::types::Matrix< eT > > > &vector_, size_t vector_size_, size_t matrix_height_, size_t matrix_width_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnChannelFromSample(mic::types::MatrixPtr< eT > sample_ptr_, mic::types::MatrixArray< eT > &array_, std::string id_, size_t sample_number_, size_t channel_number_, size_t height_, size_t width_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnInputChannel(mic::types::MatrixPtr< eT > sample_ptr_, size_t sample_number_, size_t channel_number_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnInputSample(mic::types::MatrixPtr< eT > batch_ptr_, size_t sample_number_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnOutputChannel(mic::types::MatrixPtr< eT > sample_ptr_, size_t sample_number_, size_t channel_number_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnOutputSample(mic::types::MatrixPtr< eT > batch_ptr_, size_t sample_number_) | mic::mlnn::Layer< eT > | inline |
| lazyReturnSampleFromBatch(mic::types::MatrixPtr< eT > batch_ptr_, mic::types::MatrixArray< eT > &array_, std::string id_, size_t sample_number_, size_t sample_size_) | mic::mlnn::Layer< eT > | inline |
| Linear(size_t inputs_, size_t outputs_, std::string name_="Linear") | mic::mlnn::fully_connected::Linear< eT > | inline |
| Linear(size_t input_height_, size_t input_width_, size_t input_depth_, size_t output_height_, size_t output_width_, size_t output_depth_, std::string name_="Linear") | mic::mlnn::fully_connected::Linear< eT > | inline |
| Linear() | mic::mlnn::fully_connected::Linear< eT > | inlineprivate |
| m | mic::mlnn::Layer< eT > | protected |
| mic::mlnn::fully_connected::SparseLinear class | mic::mlnn::fully_connected::Linear< eT > | friend |
| mic::mlnn::MultiLayerNeuralNetwork class | mic::mlnn::fully_connected::Linear< eT > | friend |
| name() const | mic::mlnn::Layer< eT > | inline |
| opt | mic::mlnn::Layer< eT > | protected |
| output_depth | mic::mlnn::Layer< eT > | protected |
| output_height | mic::mlnn::Layer< eT > | protected |
| output_width | mic::mlnn::Layer< eT > | protected |
| outputSize() | mic::mlnn::Layer< eT > | inline |
| p | mic::mlnn::Layer< eT > | protected |
| resetGrads() | mic::mlnn::fully_connected::Linear< eT > | inlinevirtual |
| resizeBatch(size_t batch_size_) | mic::mlnn::Layer< eT > | inlinevirtual |
| s | mic::mlnn::Layer< eT > | protected |
| setOptimization() | mic::mlnn::Layer< eT > | inline |
| setState(std::string name_, mic::types::MatrixPtr< eT > mat_ptr_) | mic::mlnn::Layer< eT > | inline |
| streamLayerParameters() | mic::mlnn::Layer< eT > | inlinevirtual |
| type() const | mic::mlnn::Layer< eT > | inline |
| update(eT alpha_, eT decay_=0.0f) | mic::mlnn::fully_connected::Linear< eT > | inlinevirtual |
| w_activations | mic::mlnn::fully_connected::Linear< eT > | private |
| x_activations | mic::mlnn::Layer< eT > | protected |
| y_activations | mic::mlnn::Layer< eT > | protected |
| ~Layer() | mic::mlnn::Layer< eT > | inlinevirtual |
| ~Linear() | mic::mlnn::fully_connected::Linear< eT > | inlinevirtual |
1.8.6 
