burn-tensor 0.16.1

Tensor library with user-friendly APIs and automatic differentiation support
Documentation 
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#[burn_tensor_testgen::testgen(q_mask)]
mod tests {
    use super::*;
    use burn_tensor::TensorData;

    #[test]
    fn should_support_mask_where_ops() {
        let tensor = QTensor::<TestBackend, 2>::int8([[1.0, 7.0], [2.0, 3.0]]);
        let mask = TestTensorBool::<2>::from_bool(
            TensorData::from([[true, false], [false, true]]),
            &Default::default(),
        );
        let value = QTensor::<TestBackend, 2>::int8([[1.8, 2.8], [3.8, 4.8]]);

        let output = tensor.mask_where(mask, value);
        let expected = TensorData::from([[1.8, 7.0], [2.0, 4.8]]);

        // Precision 1 to approximate de/quantization errors
        output
            .dequantize()
            .into_data()
            .assert_approx_eq(&expected, 1);
    }

    #[test]
    fn should_support_mask_fill_ops() {
        let tensor = QTensor::<TestBackend, 2>::int8([[1.0, 7.0], [2.0, 3.0]]);
        let mask = TestTensorBool::<2>::from_bool(
            TensorData::from([[true, false], [false, true]]),
            &Default::default(),
        );

        let output = tensor.mask_fill(mask, 2.0);
        let expected = TensorData::from([[2.0, 7.0], [2.0, 2.0]]);

        // Precision 1 to approximate de/quantization errors
        output
            .dequantize()
            .into_data()
            .assert_approx_eq(&expected, 1);
    }
}