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Shape inference, jitted routines, gccjit backend
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@lukstafi lukstafi released this 01 Apr 16:49
· 505 commits to master since this release
0.3.0
fc4ae7b

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.

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