[add] in-place operation for Tensor

Context

Some Tensor member functions are in-place and mutate the object (e.g setDataType()), others are out-of-place and create a new object (e.g copyTranspose() or add())

Most of this methods could benefit from having two versions: out-of-place and in-place.

Moreover, which member function is in place or not is not clear. It does not appear in parameters nor in the syntax. This informations only come from the non-complete documentation.

On the path to consistent syntax, I suggest to use the trailing underscore syntax for in-place member function transformations. Similar to PyTorch, this syntax is known to many users and is very visual.

Hense, we would have:

    Tensor abs() const;
    Tensor& abs_();

    Tensor sqrt() const;
    Tensor& sqrt_();

    Tensor clip(float min = std::numeric_limits<float>::lowest(),
                float max = std::numeric_limits<float>::max()) const;
    Tensor& clip_(float min = std::numeric_limits<float>::lowest(),
                  float max = std::numeric_limits<float>::max());

as an example