fn test_serialization_forced_alignement()

in safetensors/src/tensor.rs [1106:1137]

• 28 lines of code
• 1 McCabe index (conditional complexity)

    fn test_serialization_forced_alignement() {
        let data: Vec<u8> = vec![0.0f32, 1.0, 2.0, 3.0, 4.0, 5.0]
            .into_iter()
            .flat_map(|f| f.to_le_bytes())
            .collect();
        let shape = vec![1, 1, 2, 3];
        let attn_0 = TensorView::new(Dtype::F32, shape, &data).unwrap();
        let metadata: HashMap<String, TensorView> =
            // Smaller string to force misalignment compared to previous test.
            [("attn0".to_string(), attn_0)].into_iter().collect();

        let out = serialize(&metadata, None).unwrap();
        assert_eq!(
            out,
            [
                72, 0, 0, 0, 0, 0, 0, 0, 123, 34, 97, 116, 116, 110, 48, 34, 58, 123, 34, 100, 116,
                121, 112, 101, 34, 58, 34, 70, 51, 50, 34, 44, 34, 115, 104, 97, 112, 101, 34, 58,
                91, 49, 44, 49, 44, 50, 44, 51, 93, 44, 34, 100, 97, 116, 97, 95, 111, 102, 102,
                // All the 32 are forcing alignement of the tensor data for casting to f32, f64
                // etc..
                115, 101, 116, 115, 34, 58, 91, 48, 44, 50, 52, 93, 125, 125, 32, 32, 32, 32, 32,
                32, 32, 0, 0, 0, 0, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0,
                160, 64
            ],
        );
        let parsed = SafeTensors::deserialize(&out).unwrap();
        let tensor = parsed.tensor("attn0").unwrap();
        assert_eq!(
            tensor.data().as_ptr() as usize % tensor.dtype().bitsize().div_ceil(8),
            0
        );
    }