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Refactor test assertions to improve readability by removing error messages from assert macros

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This commit is contained in:
Palash Tyagi 2025-07-12 01:06:02 +01:00
parent 9182ab9fca
commit 7b0d34384a
1 changed files with 28 additions and 64 deletions
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92
src/compute/models/dense_nn.rs
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@ -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::<f64>();
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);
}
}