Update execute.rs

src/execute.rs

@@ -19,6 +19,7 @@ use crate::pfsys::{
 };
 use crate::pfsys::{create_proof_circuit_kzg, verify_proof_circuit_kzg};
 use crate::pfsys::{save_vk, srs::*};
+use crate::tensor::TensorError;
 use crate::RunArgs;
 #[cfg(not(target_arch = "wasm32"))]
 use ethers::types::H160;
@@ -605,6 +606,8 @@ pub struct AccuracyResults {
     max_abs_error: f32,
     min_abs_error: f32,
     mean_squared_error: f32,
+    mean_percent_error: f32,
+    mean_abs_percent_error: f32,
 }
 
 impl AccuracyResults {
@@ -616,19 +619,30 @@ impl AccuracyResults {
         let mut errors = vec![];
         let mut abs_errors = vec![];
         let mut squared_errors = vec![];
+        let mut percentage_errors = vec![];
+        let mut abs_percentage_errors = vec![];
 
         for (original, calibrated) in original_preds.iter_mut().zip(calibrated_preds.iter_mut()) {
             original.flatten();
             calibrated.flatten();
             let error = (original.clone() - calibrated.clone())?;
             let abs_error = error.map(|x| x.abs());
             let squared_error = error.map(|x| x.powi(2));
+            let percentage_error =
+                error.enum_map(|i, x| Ok::<_, TensorError>(x / original[i].clone()))?;
+            let abs_percentage_error = percentage_error.map(|x| x.abs());
 
             errors.extend(error.into_iter());
             abs_errors.extend(abs_error.into_iter());
             squared_errors.extend(squared_error.into_iter());
+            percentage_errors.extend(percentage_error.into_iter());
+            abs_percentage_errors.extend(abs_percentage_error.into_iter());
         }
 
+        let mean_percent_error =
+            percentage_errors.iter().sum::<f32>() / percentage_errors.len() as f32;
+        let mean_abs_percent_error =
+            abs_percentage_errors.iter().sum::<f32>() / abs_percentage_errors.len() as f32;
         let mean_error = errors.iter().sum::<f32>() / errors.len() as f32;
         let median_error = errors[errors.len() / 2];
         let max_error = errors
@@ -667,6 +681,8 @@ impl AccuracyResults {
             max_abs_error,
             min_abs_error,
             mean_squared_error,
+            mean_percent_error,
+            mean_abs_percent_error,
         })
     }
 }