fix(loss): update binary_cross_entropy loss implementation

Account for negation of targets, (1 - predictions), avg across batch.
TODO: Implement categorical cross-entropy loss / softmax cross-entropy for multiclass classification.

src/loss.rs

@@ -7,5 +7,12 @@ pub fn mean_squared_error(predictions: &Tensor, targets: &Tensor) -> f64 {
 
 /// Binary cross entropy loss.
 pub fn binary_cross_entropy(predictions: &Tensor, targets: &Tensor) -> f64 {
-    targets.mul(&predictions.ln()).sum()
+    let epsilon = 1e-8; // Small value to avoid taking the logarithm of zero
+    let loss = &(predictions.add_scalar(epsilon).ln().mul(&targets).add(
+        &targets
+            .sub_scalar(1.0)
+            .mul(&predictions.sub_scalar(1.0).add_scalar(epsilon).ln()),
+    ))
+    .mul_scalar(-1.0);
+    loss.mean()
 }