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_maxmin)]
mod tests {
    use super::*;
    use burn_tensor::TensorData;

    // NOTE: we use affine quantization to reduce quantization errors for range of input values
    #[test]
    fn test_max_dim_2d() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let output = tensor.max_dim(1);
        let expected = TensorData::from([[2.], [5.]]);

        output.dequantize().into_data().assert_eq(&expected, false);
    }

    #[test]
    fn test_max_dim_with_indices_2d_with_dim_0th() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let (output, index) = tensor.max_dim_with_indices(0);

        let output_expected = TensorData::from([[3., 4., 5.]]);
        let index_expected = TensorData::from([[1, 1, 1]]);

        output
            .dequantize()
            .into_data()
            .assert_eq(&output_expected, false);
        index.into_data().assert_eq(&index_expected, false);
    }

    #[test]
    fn test_max_dim_with_indices_2d() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let (output, index) = tensor.max_dim_with_indices(1);

        let output_expected = TensorData::from([[2.], [5.]]);
        let index_expected = TensorData::from([[2], [2]]);

        output
            .dequantize()
            .into_data()
            .assert_eq(&output_expected, false);
        index.into_data().assert_eq(&index_expected, false);
    }

    #[test]
    fn test_min_dim_2d() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let output = tensor.min_dim(1);

        let expected = TensorData::from([[0.], [3.]]);

        output.dequantize().into_data().assert_eq(&expected, false);
    }

    #[test]
    fn test_min_dim_with_indices_2d() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let (output, index) = tensor.min_dim_with_indices(1);

        let output_expected = TensorData::from([[0.], [3.]]);
        let index_expected = TensorData::from([[0], [0]]);

        output
            .dequantize()
            .into_data()
            .assert_eq(&output_expected, false);
        index.into_data().assert_eq(&index_expected, false);
    }

    #[test]
    fn test_min_dim_2d_with_0th_dim() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let output = tensor.min_dim(0);
        let expected = TensorData::from([[0., 1., 2.]]);

        output.dequantize().into_data().assert_eq(&expected, false);
    }

    #[test]
    fn test_max_dim_2d_with_0th_dim() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let output = tensor.max_dim(0);
        let expected = TensorData::from([[3., 4., 5.]]);

        output.dequantize().into_data().assert_eq(&expected, false);
    }

    #[test]
    fn test_min_dim_with_indices_2d_with_0th_dim() {
        let tensor = QTensor::<TestBackend, 2>::int8_affine([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

        let (output, index) = tensor.min_dim_with_indices(0);

        let output_expected = TensorData::from([[0., 1., 2.]]);
        let index_expected = TensorData::from([[0, 0, 0]]);

        output
            .dequantize()
            .into_data()
            .assert_eq(&output_expected, false);
        index.into_data().assert_eq(&index_expected, false);
    }

    #[test]
    fn test_maximum_pair() {
        let a = QTensor::<TestBackend, 1>::int8_affine([1.0, 5.0, 3.0, 4.0]);
        let b = QTensor::<TestBackend, 1>::int8_affine([2.0, 1.0, 4.0, 5.0]);

        let output = a.max_pair(b);
        let expected = TensorData::from([2.0, 5.0, 4.0, 5.0]);

        output
            .dequantize()
            .into_data()
            .assert_approx_eq(&expected, 1);
    }

    #[test]
    fn test_minimum_pair() {
        let a = QTensor::<TestBackend, 1>::int8_affine([1.0, 5.0, 3.0, 4.0]);
        let b = QTensor::<TestBackend, 1>::int8_affine([2.0, 1.0, 4.0, 5.0]);

        let output = a.min_pair(b);
        let expected = TensorData::from([1.0, 1.0, 3.0, 4.0]);

        output
            .dequantize()
            .into_data()
            .assert_approx_eq(&expected, 1);
    }
}