burn-tensor 0.16.1

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

    #[test]
    fn clamp_min() {
        let device = Default::default();
        // test float tensor
        let data = TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
        let tensor = TestTensor::<2>::from_data(data, &device);

        let output = tensor.clamp_min(2.0);

        output
            .into_data()
            .assert_eq(&TensorData::from([[2.0, 2.0, 2.0], [3.0, 4.0, 5.0]]), false);

        // test int tensor
        let data = TensorData::from([[0, 1, 2], [3, 4, 5]]);
        let tensor = TestTensorInt::<2>::from_data(data, &device);
        let output = tensor.clamp_min(2);

        output
            .into_data()
            .assert_eq(&TensorData::from([[2, 2, 2], [3, 4, 5]]), false);
    }

    #[test]
    fn clamp_max() {
        let device = Default::default();
        // test float tensor
        let data = TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
        let tensor = TestTensor::<2>::from_data(data, &device);

        let output = tensor.clamp_max(2.0);

        output
            .into_data()
            .assert_eq(&TensorData::from([[0.0, 1.0, 2.0], [2.0, 2.0, 2.0]]), false);

        // test int tensor
        let data = TensorData::from([[0, 1, 2], [3, 4, 5]]);
        let tensor = TestTensorInt::<2>::from_data(data, &device);
        let output = tensor.clamp_max(4);

        output
            .into_data()
            .assert_eq(&TensorData::from([[0, 1, 2], [3, 4, 4]]), false);
    }

    #[test]
    fn clamp_min_max() {
        let device = Default::default();
        // test float tensor
        let data = TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
        let tensor = TestTensor::<2>::from_data(data, &device);
        let output = tensor.clamp(1.0, 4.0);

        output
            .into_data()
            .assert_eq(&TensorData::from([[1.0, 1.0, 2.0], [3.0, 4.0, 4.0]]), false);

        // test int tensor
        let data = TensorData::from([[0, 1, 2], [3, 4, 5]]);
        let tensor = TestTensorInt::<2>::from_data(data, &device);
        let output = tensor.clamp(1, 4);

        output
            .into_data()
            .assert_eq(&TensorData::from([[1, 1, 2], [3, 4, 4]]), false);
    }
}