Record-syntax-based inline definitions; NN building blocks

[lukstafi]

This is a rushed release. CUDA backend regressions. The next release 0.6.2 should come at the 0.6 -> 0.6.1 cadence (that is relatively soon).

Highlights:

• Record-based syntax for inline definitions, with the first field being the defined identifier, it's value being the parameter initialization (prevented for %cd syntax) -- punning means using a default, the following fields being the labeled arguments passed to the initialization expression.
• Shape allows injecting shape equality constraints via set_dim and set_equal, and capturing shape (dim, row) variables via einsum variable capture syntax. set_dim takes a variable reference and a number. "Equaling" a dimension and a row creates a Total_elems constraint (dimension vs. product of dimensions), otherwise it's strict equality e.g. between rows.
• Split the sources of neural_nets_lib into two directories, tensor/ with the core implementation and lib/ with user-land code.
• Fleshed-out Nn_blocks with components for tensors and convolutional nets. The tensor components are already validated but not yet sufficient for full-blown GPT-style network (e.g. missing fixed positional encodings). The convolution components are not validated and do not work yet.
• Introduced truly heterogeneous precision primitive ops, operations like where and Uint4x32_to_prec_uniform were previously buggy.
• Migrated documentation to docs/ directory with pandoc rendering support.

Many more changes, see the datailed CHANGES.md compiled by Claude Code.

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