diff --git a/src/compute/models/dense_nn.rs b/src/compute/models/dense_nn.rs index 930dcc3..b9f5a00 100644 --- a/src/compute/models/dense_nn.rs +++ b/src/compute/models/dense_nn.rs @@ -264,10 +264,8 @@ mod tests { for i in 0..before.rows() { for j in 0..before.cols() { - assert!( - (before[(i, j)] - after[(i, j)]).abs() < 1e-12, - "prediction changed despite 0 epochs" - ); + // "prediction changed despite 0 epochs" + assert!((before[(i, j)] - after[(i, j)]).abs() < 1e-12); } } } @@ -330,12 +328,8 @@ mod tests { let after_preds = model.predict(&x); let after_loss = mse_loss(&after_preds, &y); - assert!( - after_loss < before_loss, - "MSE did not decrease (before: {}, after: {})", - before_loss, - after_loss - ); + // MSE did not decrease (before: {}, after: {}) + assert!(after_loss < before_loss); } #[test] @@ -346,12 +340,8 @@ mod tests { for i in 0..input.rows() { for j in 0..input.cols() { - assert!( - (output[(i, j)] - expected[(i, j)]).abs() < 1e-9, - "Tanh forward output mismatch at ({}, {})", - i, - j - ); + // Tanh forward output mismatch at ({}, {}) + assert!((output[(i, j)] - expected[(i, j)]).abs() < 1e-9); } } } @@ -364,12 +354,8 @@ mod tests { for i in 0..input.rows() { for j in 0..input.cols() { - assert!( - (output[(i, j)] - expected[(i, j)]).abs() < 1e-9, - "ReLU derivative output mismatch at ({}, {})", - i, - j - ); + // "ReLU derivative output mismatch at ({}, {})" + assert!((output[(i, j)] - expected[(i, j)]).abs() < 1e-9); } } } @@ -382,12 +368,8 @@ mod tests { for i in 0..input.rows() { for j in 0..input.cols() { - assert!( - (output[(i, j)] - expected[(i, j)]).abs() < 1e-9, - "Tanh derivative output mismatch at ({}, {})", - i, - j - ); + // "Tanh derivative output mismatch at ({}, {})" + assert!((output[(i, j)] - expected[(i, j)]).abs() < 1e-9); } } } @@ -404,10 +386,8 @@ mod tests { assert_eq!(matrix.cols(), cols); for val in matrix.data() { - assert!( - *val >= -limit && *val <= limit, - "Xavier initialized value out of range" - ); + // Xavier initialized value out of range + assert!(*val >= -limit && *val <= limit); } } @@ -423,10 +403,8 @@ mod tests { assert_eq!(matrix.cols(), cols); for val in matrix.data() { - assert!( - *val >= -limit && *val <= limit, - "He initialized value out of range" - ); + // He initialized value out of range + assert!(*val >= -limit && *val <= limit); } } @@ -442,12 +420,8 @@ mod tests { for i in 0..output_gradient.rows() { for j in 0..output_gradient.cols() { - assert!( - (output_gradient[(i, j)] - expected_gradient[(i, j)]).abs() < 1e-9, - "BCE gradient output mismatch at ({}, {})", - i, - j - ); + // BCE gradient output mismatch at ({}, {}) + assert!((output_gradient[(i, j)] - expected_gradient[(i, j)]).abs() < 1e-9); } } } @@ -489,12 +463,8 @@ mod tests { .iter() .sum::(); - assert!( - after_loss < before_loss, - "BCE did not decrease (before: {}, after: {})", - before_loss, - after_loss - ); + // BCE did not decrease (before: {}, after: {}) + assert!(after_loss < before_loss,); } #[test] @@ -525,21 +495,15 @@ mod tests { // Verify that weights and biases of both layers have changed, // implying delta propagation occurred for l > 0 - assert!( - model.weights[0] != initial_weights_l0, - "Weights of first layer did not change, delta propagation might not have occurred" - ); - assert!( - model.biases[0] != initial_biases_l0, - "Biases of first layer did not change, delta propagation might not have occurred" - ); - assert!( - model.weights[1] != initial_weights_l1, - "Weights of second layer did not change" - ); - assert!( - model.biases[1] != initial_biases_l1, - "Biases of second layer did not change" - ); + + + // Weights of first layer did not change, delta propagation might not have occurred + assert!(model.weights[0] != initial_weights_l0); + // Biases of first layer did not change, delta propagation might not have occurred + assert!(model.biases[0] != initial_biases_l0); + // Weights of second layer did not change + assert!(model.weights[1] != initial_weights_l1); + // Biases of second layer did not change + assert!(model.biases[1] != initial_biases_l1); } }