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

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

        let output = tensor.tanh();
        let expected = TensorData::from([[0.0, 0.7615, 0.9640], [0.9950, 0.9993, 0.9999]]);

        output
            .dequantize()
            .into_data()
            .assert_approx_eq(&expected, 3);
    }
}