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Some fixes to momentum

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This commit is contained in:
Joseph Redmon
2014-12-07 20:16:21 -08:00
parent 28e2115272
commit a99050f0c8
5 changed files with 27 additions and 26 deletions
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28
src/connected_layer.c
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@ -24,22 +24,20 @@ connected_layer *make_connected_layer(int batch, int inputs, int outputs, ACTIVA
layer->delta = calloc(batch*outputs, sizeof(float*));
layer->weight_updates = calloc(inputs*outputs, sizeof(float));
//layer->weight_adapt = calloc(inputs*outputs, sizeof(float));
layer->weights = calloc(inputs*outputs, sizeof(float));
float scale = 1./inputs;
scale = .01;
for(i = 0; i < inputs*outputs; ++i)
layer->weights[i] = scale*2*(rand_uniform()-.5);
layer->bias_updates = calloc(outputs, sizeof(float));
//layer->bias_adapt = calloc(outputs, sizeof(float));
layer->biases = calloc(outputs, sizeof(float));
for(i = 0; i < outputs; ++i){
//layer->biases[i] = rand_normal()*scale + scale;
layer->biases[i] = 1;
for(i = 0; i < inputs*outputs; ++i){
layer->weights[i] = scale*rand_normal();
}
#ifdef GPU
layer->bias_updates = calloc(outputs, sizeof(float));
layer->biases = calloc(outputs, sizeof(float));
for(i = 0; i < outputs; ++i){
layer->biases[i] = .01;
}
#ifdef GPU
layer->weights_cl = cl_make_array(layer->weights, inputs*outputs);
layer->biases_cl = cl_make_array(layer->biases, outputs);
@ -48,7 +46,7 @@ connected_layer *make_connected_layer(int batch, int inputs, int outputs, ACTIVA
layer->output_cl = cl_make_array(layer->output, outputs*batch);
layer->delta_cl = cl_make_array(layer->delta, outputs*batch);
#endif
#endif
layer->activation = activation;
fprintf(stderr, "Connected Layer: %d inputs, %d outputs\n", inputs, outputs);
return layer;
@ -59,7 +57,7 @@ void update_connected_layer(connected_layer layer)
axpy_cpu(layer.outputs, layer.learning_rate, layer.bias_updates, 1, layer.biases, 1);
scal_cpu(layer.outputs, layer.momentum, layer.bias_updates, 1);
scal_cpu(layer.inputs*layer.outputs, 1.-layer.learning_rate*layer.decay, layer.weights, 1);
axpy_cpu(layer.inputs*layer.outputs, -layer.decay, layer.weights, 1, layer.weight_updates, 1);
axpy_cpu(layer.inputs*layer.outputs, layer.learning_rate, layer.weight_updates, 1, layer.weights, 1);
scal_cpu(layer.inputs*layer.outputs, layer.momentum, layer.weight_updates, 1);
}
@ -129,7 +127,7 @@ void update_connected_layer_gpu(connected_layer layer)
axpy_ongpu(layer.outputs, layer.learning_rate, layer.bias_updates_cl, 1, layer.biases_cl, 1);
scal_ongpu(layer.outputs, layer.momentum, layer.bias_updates_cl, 1);
scal_ongpu(layer.inputs*layer.outputs, 1.-layer.learning_rate*layer.decay, layer.weights_cl, 1);
axpy_ongpu(layer.inputs*layer.outputs, -layer.decay, layer.weights_cl, 1, layer.weight_updates_cl, 1);
axpy_ongpu(layer.inputs*layer.outputs, layer.learning_rate, layer.weight_updates_cl, 1, layer.weights_cl, 1);
scal_ongpu(layer.inputs*layer.outputs, layer.momentum, layer.weight_updates_cl, 1);
pull_connected_layer(layer);
@ -176,4 +174,4 @@ void backward_connected_layer_gpu(connected_layer layer, cl_mem input, cl_mem de
if(c) gemm_ongpu(0,1,m,n,k,1,a,k,b,k,0,c,n);
}
#endif
#endif