backprop.c

足球机器人仿真组CMU97的源码

  epoch_error = 0.0;
  epoch_error_num = 0;
  for (p=0; p<n_pat; p++) {
    for (i=0;i<NN_n_inp;i++) inp[i] = train_in[p][i]; /* set input vector */
    forward_pass();
    for (o=0;o<NN_n_out;o++) target[o] = train_out[p][o]; /* set target vector */
    backward_pass();
  }
  update_weights ();
/*my_error("1epoch");*/
}

#endif  /* Need actfn for forward_pass which is needed for use*/

/* applies an activation function of type g to a value */
float actfn(enum actfntype g, float value)
{
  if (g==line) return value;
  if (g==sigm) return 1.0 / (1.0+exp(-value));
  if (g==gauss) return exp(-sqr(value));
}

/* computes the deriv. of an act.fn. g at a value, possibly using g(value) */
float actfnprime(enum actfntype g,float value,float g_value)
{
  if (g==line) return 1.0;
  if (g==sigm) return g_value*(1.0-g_value) + .1;  /* .1 is Fahlman's suggestion */
/*  if (g==sigm) return g_value*(1.0-g_value);*/
  if (g==gauss) return -2.0*value*g_value;
}

/* assume the inp[] array has already been set with the desired input */
void forward_pass ()
{
  int i,h,o;
  /* propagate inputs to hidden layer */
  for (h=0; h<NN_n_hid; h++) {
    hid0[h]=0.0;
    for (i=0; i<NN_n_inp+1; i++) {
      hid0[h] += inp[i] * w1[i][h];
    }
    hid[h] = actfn(h_actfn, hid0[h]);
  }
  /* propagate hidden layer to outputs */
  for (o=0; o<NN_n_out; o++) {
    out0[o]=0.0;
    for (h=0; h<NN_n_hid+1; h++) {
      out0[o] += hid[h] * w2[h][o];
    }
    out[o] = actfn(o_actfn, out0[o]);
  }
/*  my_error("forward");*/
}

#ifndef FOR_USE  

/* assume the inp[] array has been set, forward_pass() has already been called
   to propagate forward those inputs, and the target[] array is also set.   */
void backward_pass ()
{
  float error,delta;
  int i,h,o;
  /* compute error at outputs */
  for (o=0; o<NN_n_out; o++) {
    error = target[o]-out[o];
    epoch_error += sqr(error);
    if ( fabs(error) > .4 ) epoch_error_num++;
    dout[o] = error * actfnprime(o_actfn,out0[o],out[o]);
  }
  /* backpropagate error signal to the hidden layer */
  for (h=0; h<NN_n_hid; h++) {
    delta=0.0;
    for (o=0; o<NN_n_out; o++) {
      delta += dout[o] * w2[h][o];
    }
    dhid[h] = delta * actfnprime(h_actfn,hid0[h],hid[h]);
  }
  /* Now that we've got an error signal for each unit in the network,
     we can determine the weight changes & accumulate them in dw1 and dw2. */
  for (o=0; o<NN_n_out; o++) {
    for (h=0; h<NN_n_hid+1; h++) {
      dw2[h][o] += eta2 * dout[o] * hid[h];
    }
  }
  for (h=0; h<NN_n_hid; h++) {
    for (i=0; i<NN_n_inp+1; i++) {
      dw1[i][h] += eta1 * dhid[h] * inp[i];
    }
  }
/*  my_error("backward");*/
}

/* update the w1 and w2 weights using the accumulated changes in dw1 and dw2
   as well as a momentum term involving the last epoch's total weight change.*/
void update_weights()
{
  int i,h,o;
  for (i=0; i<NN_n_inp+1; i++) {
    for (h=0; h<NN_n_hid; h++) {
      w1[i][h] += ( prev_dw1[i][h] = dw1[i][h] + alpha*prev_dw1[i][h] );
      w1[i][h] *= beta;
    }
  }
  for (h=0; h<NN_n_hid+1; h++) {
    for (o=0; o<NN_n_out; o++) {
      w2[h][o] += ( prev_dw2[h][o] = dw2[h][o] + alpha*prev_dw2[h][o] );
      w2[h][o] *= beta;
    }
  }
}

/* Write the weights to a file  */
void write_weights(char *source)
{
  FILE *weightFile;
  int i,j;

  weightFile = fopen(source,"w");
  if ( !weightFile ) 
    my_error("couldn't open weightFile");

/* The weights */
  fprintf(weightFile,"{");
  for (i=0; i<NN_n_inp+1; i++){
    fprintf(weightFile,"{");
    for (j=0; j<NN_n_hid; j++)
      fprintf(weightFile,"%f ",w1[i][j]);
    fprintf(weightFile,"} ");
  }
  fprintf(weightFile,"}\n");

  fprintf(weightFile,"{");
  for (i=0; i<NN_n_hid+1; i++){
    fprintf(weightFile,"{");
    for (j=0; j<NN_n_out; j++)
      fprintf(weightFile,"%f ",w2[i][j]);
    fprintf(weightFile,"} ");
  }
  fprintf(weightFile,"}\n\n");

  fprintf(weightFile,"Last changes in weights:\n");
  fprintf(weightFile,"{");
  for (i=0; i<NN_n_inp+1; i++){
    fprintf(weightFile,"{");
    for (j=0; j<NN_n_hid; j++)
      fprintf(weightFile,"%f ",dw1[i][j]);
    fprintf(weightFile,"} ");
  }
  fprintf(weightFile,"}\n");

  fprintf(weightFile,"{");
  for (i=0; i<NN_n_hid+1; i++){
    fprintf(weightFile,"{");
    for (j=0; j<NN_n_out; j++)
      fprintf(weightFile,"%f ",dw2[i][j]);
    fprintf(weightFile,"} ");
  }
  fprintf(weightFile,"}\n\n");

  fprintf(weightFile,"The last forward pass, followed by target (epoch %d):\n",
	  epoch_counter);
  for (i=0; i<NN_n_inp+1; i++)
    fprintf(weightFile,"%f ",inp[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_hid; i++)
    fprintf(weightFile,"%f ",hid0[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_hid+1; i++)
    fprintf(weightFile,"%f ",hid[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_out; i++)
    fprintf(weightFile,"%f ",out0[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_out; i++)
    fprintf(weightFile,"%f ",out[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_out; i++)
    fprintf(weightFile,"%f ",target[i]);
  fprintf(weightFile,"\n\n");

  fprintf(weightFile,"dhid and dout from last pass:\n");
  for (i=0; i<NN_n_hid; i++)
    fprintf(weightFile,"%f ",dhid[i]);
  fprintf(weightFile,"\n");

  for (i=0; i<NN_n_out; i++)
    fprintf(weightFile,"%f ",dout[i]);
  fprintf(weightFile,"\n\n");

  fprintf(weightFile,"%d->%d->%d network:\n", NN_n_inp,NN_n_hid,NN_n_out);
  fprintf(weightFile,"\teta = (%f,%f), alpha = %f, beta = %f, randmax = %f\n",
	 eta1,eta2,alpha,beta,randmax);
  fprintf(weightFile,"\t%d training patterns from %s\n", n_pat, TRAIN_FILE);
  if ( strcmp(INITIALIZE_FILE,"none") )
    fprintf(weightFile,"Weights initialized from %s\n",INITIALIZE_FILE);

  fprintf(weightFile,"Epoch %d:  tot err = %7.4f, avg err = %7.4f, num wrong = %d\n",
	 epoch_counter, epoch_error, 
	 epoch_error/(n_pat*NN_n_out), epoch_error_num);

  fclose(weightFile);
}

#endif

/* Load the weights from a file  */
void load_weights(char *source)
{
  FILE *weightFile;
  int i,j;

  weightFile = fopen(source,"r");
  if ( !weightFile ) 
    my_error("couldn't open weightFile");
  
/* The weights */
  fscanf(weightFile,"{");
  for (i=0; i<NN_n_inp+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_hid; j++)
      fscanf(weightFile,"%f ",&(w1[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n");
  
  fscanf(weightFile,"{");
  for (i=0; i<NN_n_hid+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_out; j++)
      fscanf(weightFile,"%f ",&(w2[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n\n");

  fclose(weightFile);
/*  my_error("load_weights");*/
}

#ifndef FOR_USE

/* Load the weights from a file called */
void initialize_from_file(char *source)
{
  FILE *weightFile;
  int i,j;

  printf("Initializing %d->%d->%d network:\n", NN_n_inp,NN_n_hid,NN_n_out);
  printf("\teta = (%f,%f), alpha = %f\n",
	 eta1,eta2,alpha);
  printf("\t%d training patterns\n", n_pat);
  printf("Initializing weights from %s\n", source);

  weightFile = fopen(source,"r");
  if ( !weightFile ) 
    my_error("couldn't open weightFile");

  /* initialize bias units */
  inp[NN_n_inp] = 1.0;
  hid[NN_n_hid] = 1.0;
  
/* The weights */
  fscanf(weightFile,"{");
  for (i=0; i<NN_n_inp+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_hid; j++)
      fscanf(weightFile,"%f ",&(w1[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n");
  
  fscanf(weightFile,"{");
  for (i=0; i<NN_n_hid+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_out; j++)
      fscanf(weightFile,"%f ",&(w2[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n\n");

  fscanf(weightFile,"Last changes in weights:\n");
  fscanf(weightFile,"{");
  for (i=0; i<NN_n_inp+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_hid; j++)
      fscanf(weightFile,"%f ",&(dw1[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n");

  fscanf(weightFile,"{");
  for (i=0; i<NN_n_hid+1; i++){
    fscanf(weightFile,"{");
    for (j=0; j<NN_n_out; j++)
      fscanf(weightFile,"%f ",&(dw2[i][j]));
    fscanf(weightFile,"} ");
  }
  fscanf(weightFile,"}\n\n");


  fclose(weightFile);
}

#endif