| | |
| | | #define CONVOLUTIONAL_LAYER_H |
| | | |
| | | #include "cuda.h" |
| | | #include "params.h" |
| | | #include "image.h" |
| | | #include "activations.h" |
| | | #include "layer.h" |
| | | #include "network.h" |
| | | |
| | | typedef layer convolutional_layer; |
| | | |
| | |
| | | void push_convolutional_layer(convolutional_layer layer); |
| | | void pull_convolutional_layer(convolutional_layer layer); |
| | | |
| | | void bias_output_gpu(float *output, float *biases, int batch, int n, int size); |
| | | void add_bias_gpu(float *output, float *biases, int batch, int n, int size); |
| | | void backward_bias_gpu(float *bias_updates, float *delta, int batch, int n, int size); |
| | | #ifdef CUDNN |
| | | void cudnn_convolutional_setup(layer *l, int cudnn_preference); |
| | | void cuda_convert_f32_to_f16(float* input_f32, size_t size, float *output_f16); |
| | | #endif |
| | | #endif |
| | | |
| | | convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation); |
| | | convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int padding, ACTIVATION activation, int batch_normalize, int binary, int xnor, int adam); |
| | | void denormalize_convolutional_layer(convolutional_layer l); |
| | | void resize_convolutional_layer(convolutional_layer *layer, int w, int h); |
| | | void forward_convolutional_layer(const convolutional_layer layer, network_state state); |
| | | void update_convolutional_layer(convolutional_layer layer, int batch, float learning_rate, float momentum, float decay); |
| | | image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_filters); |
| | | image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_weights); |
| | | void binarize_weights(float *weights, int n, int size, float *binary); |
| | | void swap_binary(convolutional_layer *l); |
| | | void binarize_weights2(float *weights, int n, int size, char *binary, float *scales); |
| | | |
| | | void backward_convolutional_layer(convolutional_layer layer, network_state state); |
| | | |
| | | void bias_output(float *output, float *biases, int batch, int n, int size); |
| | | void add_bias(float *output, float *biases, int batch, int n, int size); |
| | | void backward_bias(float *bias_updates, float *delta, int batch, int n, int size); |
| | | |
| | | image get_convolutional_image(convolutional_layer layer); |
| | | image get_convolutional_delta(convolutional_layer layer); |
| | | image get_convolutional_filter(convolutional_layer layer, int i); |
| | | image get_convolutional_weight(convolutional_layer layer, int i); |
| | | |
| | | int convolutional_out_height(convolutional_layer layer); |
| | | int convolutional_out_width(convolutional_layer layer); |
| | | void rescale_filters(convolutional_layer l, float scale, float trans); |
| | | void rgbgr_filters(convolutional_layer l); |
| | | void rescale_weights(convolutional_layer l, float scale, float trans); |
| | | void rgbgr_weights(convolutional_layer l); |
| | | |
| | | #endif |
| | | |