burn-tensor 0.18.0

Tensor library with user-friendly APIs and automatic differentiation support
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#[burn_tensor_testgen::testgen(q_add)]
mod tests {
    use super::*;
    use burn_tensor::TensorData;
    use burn_tensor::{Tolerance, ops::FloatElem};
    type FT = FloatElem<TestBackend>;

    #[test]
    fn test_add_d2() {
        let tensor_1 = QTensor::<TestBackend, 2>::int8([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
        let tensor_2 = QTensor::<TestBackend, 2>::int8([[6.0, 7.0, 8.0], [9.0, 10.0, 11.0]]);

        let output = tensor_1 + tensor_2;

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[6.0, 8.0, 10.0], [12.0, 14.0, 16.0]]),
            Tolerance::absolute(1e-1),
        );
    }

    #[test]
    fn test_add_broadcast() {
        let tensor_1 = QTensor::<TestBackend, 2>::int8([[0.0, 1.0, 2.0]]);
        let tensor_2 = QTensor::<TestBackend, 2>::int8([[3.0, 4.0, 5.0], [6.0, 7.0, 8.0]]);

        let output = tensor_1 + tensor_2;

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[3.0, 5.0, 7.0], [6.0, 8.0, 10.0]]),
            Tolerance::absolute(1e-1),
        );
    }

    #[test]
    fn test_add_different_strides_rhs() {
        // We need to execute an operation after `from data` to trigger inplace in some backends.
        // Which is the operation that might be problematic in this case.
        let tensor_1 = QTensor::<TestBackend, 2>::int8([[0.0, 1.0], [2.0, 3.0]]) * 1;
        let tensor_2 = QTensor::<TestBackend, 2>::int8([[4.0, 5.0], [6.0, 7.0]]) * 1;

        let output = tensor_1 + tensor_2.transpose();

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[4.0, 7.0], [7.0, 10.0]]),
            Tolerance::absolute(1e-1),
        );
    }

    #[test]
    fn test_add_different_strides_lhs() {
        // We need to execute an operation after `from data` to trigger inplace in some backends.
        // Which is the operation that might be problematic in this case.
        let tensor_1 = QTensor::<TestBackend, 2>::int8([[0.0, 1.0], [2.0, 3.0]]) * 1;
        let tensor_2 = QTensor::<TestBackend, 2>::int8([[4.0, 5.0], [6.0, 7.0]]) * 1;

        let output = tensor_1.transpose() + tensor_2;

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[4.0, 7.0], [7.0, 10.0]]),
            Tolerance::absolute(1e-1),
        );
    }

    #[test]
    fn test_add_different_strides_broadcast() {
        // We need to execute an operation after `from data` to trigger inplace in some backends.
        // Which is the operation that might be problematic in this case.
        let tensor_1 = QTensor::<TestBackend, 2>::int8([[0.0, 1.0], [2.0, 3.0]]) * 1;
        let tensor_2 = QTensor::<TestBackend, 2>::int8([[4.0, 5.0]]) * 1;

        let output = tensor_1.transpose() + tensor_2;

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[4.0, 7.0], [5.0, 8.0]]),
            Tolerance::absolute(1e-1),
        );
    }

    #[test]
    fn should_support_add_scalar_ops() {
        let scalar = 2.0;
        let tensor = QTensor::<TestBackend, 2>::int8([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let output = tensor + scalar;

        // Precision 1 to approximate de/quantization errors
        output.dequantize().into_data().assert_approx_eq::<FT>(
            &TensorData::from([[2.0, 3.0, 4.0], [5.0, 6.0, 7.0]]),
            Tolerance::absolute(1e-1),
        );
    }
}