[upd] prototype to fluent interface

Context

The current prototype-style interface requires manual cloning and sequential mutation:

Tensor tmp = A.clone();
tmp.toDtype(Float32);
tmp.toBackend("cuda");
tmp.abs();
tmp.clip();

This is verbose, error-prone, and hard to chain.

Proposed Solution

Adopt a fluent interface:

Tensor B = A.toDtype(Float32).toBackend("cuda").abs().clip();

For in-place versions, use a trailing underscore (_): (see #294)

A.toDtype_().abs_().clip_(0, 1);  // Avoids allocating temporaries

This:

• Enables expressive, composable transformations
• Reduces boilerplate and memory overhead
• Follows familiar patterns from libraries like PyTorch (e.g. add_())