0.3: Shape inference, jitted routines, gccjit backend

Major rewrite. Abandoning the design choices of 0.1 and 0.2.

Added:

• Optionally, inferring or checking tensor (batch) sizes from data (e.g. file) sizes.
• Static indexing. A "slice" operator to select individual batches.
• Established the backends API with first-class modules.
• The Train module as an optimization "frontend".
• Parallel optimization across devices.
• Global settings configurable via config files, environment variables, and commandline flags.
• Integration of backend logging with ppx_minidebug (the debug_log_from_routines setting).

Changed:

• The Cuda backend is not supported for now. It is (optionally) buildable to reduce code rot.
• Dynamic indexing is not supported anymore (to reduce complexity). It might be reintroduced if needed.
• Factored out the arrayjit library / package containing compilation (former Ndarray, Node, Code).
• Renamed Formula -> Tensor
• No more "form vs. non-form" formulas / tensors.
• Formula/tensor roots are split into forward roots and backprop roots.
• No more %nn_rs, %nn_dt syntaxes and Synthetic fetch primitive.
• Renamed %nn_op to %op and %nn_cd to %cd.
• Migrated gccjit into a separate repository.
• Migrated cudajit into a separate repository.
• Massive rewrite of shape inference in a declarative style.
• Generalize zero_out to initialize_neutral to prepare arbitrary accumulation operation.
• Renamed Node -> Lazy_array -> Tnode (tensor node).

And more.