implemented staircase approach for TrainingsData

src/data/generation.rs

@@ -70,10 +70,31 @@ pub fn example_gen() {
         println!("Input: {:?}\nTarget: {:?}\n", input, target);
     }
     for (input, target) in pairs {
-        println!(
-            "Input: {:?}\nTarget: {:?}\n",
-            tokenizer.detokenize(input),
-            tokenizer.detokenize(target)
-        );
+
+
+        let staircase_pairs = generate_staircase_pairs(&input, &target);
+
+        for (staircase_input, staircase_target) in staircase_pairs {
+            println!(
+                "Input: {:?}\nTarget: {:?}\n",
+                tokenizer.detokenize(staircase_input),
+                tokenizer.detokenize(staircase_target)
+            );
+        }
     }
 }
+fn generate_staircase_pairs(input: &Vec<usize>, target: &Vec<usize>) -> Vec<(Vec<usize>, Vec<usize>)> {
+    let mut staircase_pairs = Vec::new();
+
+    // The number of steps will be the length of the target sequence
+    for i in 1..=target.len() {
+        // Slice input and target incrementally
+        let staircase_input = input.iter().take(i).cloned().collect::<Vec<usize>>();
+        let staircase_target = target.iter().take(i).cloned().collect::<Vec<usize>>();
+
+        // Add this pair to the staircase pairs vector
+        staircase_pairs.push((staircase_input, staircase_target));
+    }
+
+    staircase_pairs
+}