| | |
| | | #include <stdio.h> |
| | | #include <assert.h> |
| | | |
| | | softmax_layer *make_softmax_layer(int batch, int groups, int inputs) |
| | | softmax_layer make_softmax_layer(int batch, int inputs, int groups) |
| | | { |
| | | assert(inputs%groups == 0); |
| | | fprintf(stderr, "Softmax Layer: %d inputs\n", inputs); |
| | | softmax_layer *layer = calloc(1, sizeof(softmax_layer)); |
| | | layer->batch = batch; |
| | | layer->groups = groups; |
| | | layer->inputs = inputs; |
| | | layer->output = calloc(inputs*batch, sizeof(float)); |
| | | layer->delta = calloc(inputs*batch, sizeof(float)); |
| | | softmax_layer l = {0}; |
| | | l.type = SOFTMAX; |
| | | l.batch = batch; |
| | | l.groups = groups; |
| | | l.inputs = inputs; |
| | | l.outputs = inputs; |
| | | l.output = calloc(inputs*batch, sizeof(float)); |
| | | l.delta = calloc(inputs*batch, sizeof(float)); |
| | | #ifdef GPU |
| | | layer->output_gpu = cuda_make_array(layer->output, inputs*batch); |
| | | layer->delta_gpu = cuda_make_array(layer->delta, inputs*batch); |
| | | l.output_gpu = cuda_make_array(l.output, inputs*batch); |
| | | l.delta_gpu = cuda_make_array(l.delta, inputs*batch); |
| | | #endif |
| | | return layer; |
| | | return l; |
| | | } |
| | | |
| | | void softmax_array(float *input, int n, float *output) |
| | |
| | | } |
| | | } |
| | | |
| | | void forward_softmax_layer(const softmax_layer layer, float *input) |
| | | void forward_softmax_layer(const softmax_layer l, network_state state) |
| | | { |
| | | int b; |
| | | int inputs = layer.inputs / layer.groups; |
| | | int batch = layer.batch * layer.groups; |
| | | int inputs = l.inputs / l.groups; |
| | | int batch = l.batch * l.groups; |
| | | for(b = 0; b < batch; ++b){ |
| | | softmax_array(input+b*inputs, inputs, layer.output+b*inputs); |
| | | softmax_array(state.input+b*inputs, inputs, l.output+b*inputs); |
| | | } |
| | | } |
| | | |
| | | void backward_softmax_layer(const softmax_layer layer, float *delta) |
| | | void backward_softmax_layer(const softmax_layer l, network_state state) |
| | | { |
| | | int i; |
| | | for(i = 0; i < layer.inputs*layer.batch; ++i){ |
| | | delta[i] = layer.delta[i]; |
| | | for(i = 0; i < l.inputs*l.batch; ++i){ |
| | | state.delta[i] = l.delta[i]; |
| | | } |
| | | } |
| | | |