here last column is a output vector of size 1 and before that we have 5 unrolling pairs of data points, Can you pls point me how to write training routine for above example. I didn't understand much from your rnn-bit example is quite different use case and textgen is difficult to understand.
I tried like below, but i dont think its KANN_F_TRUTH array is correctly populated
for (int j = 0; j < num_rows - batch_size_; j += batch_size_) {
int k;
for (k = 0; k < ulen; ++k) {
for (int b = 0; b < batch_size_; ++b) {
int s = j + b;/// shuf[j + b];
for (int i = 0; i < input_; ++i)
x[k][b*input_ + i] = data.x[s][k][i];
for (int i = 0; i < output_; ++i)
y[k][b*output_ + i] = data.y[s][i]; // <--------------------------- some fix required here
}
}
cost += kann_cost(ua, 0, 1) * ulen * batch_size_;
n_cerr += kann_class_error(ua, &k);
tot_base += k;
//kad_check_grad(ua->n, ua->v, ua->n-1);
kann_RMSprop(n_var, error, NULL, 0.9f, ua->g, ua->x, r);
tot += ulen * batch_size_;
}
I have inputs (dimension 2) and outputs (1) sequence like below all numbers are normalized ( -1 to 1 )
below is copied 2 samples from training data
(-0.70,-0.23) (-0.70,-0.23) (-0.70,-0.23) (-0.70,-0.23) (-0.70,-0.23) 0.03 (-0.61,-0.26) (-0.61,-0.26) (-0.61,-0.26) (-0.61,-0.26) (-0.61,-0.26) -0.20
here last column is a output vector of size 1 and before that we have 5 unrolling pairs of data points, Can you pls point me how to write training routine for above example. I didn't understand much from your rnn-bit example is quite different use case and textgen is difficult to understand.
I tried like below, but i dont think its KANN_F_TRUTH array is correctly populated