TorchLean

TorchLean is the runtime front-end for training and execution.

This module is the user-facing wrapper around the lower-level runtime session implementation:

• write a model/loss once over a small Ops interface,
• choose execution := .eager (dynamic tape) or execution := .typedGraph (typed SSA/DAG),
• run forward, backward, and step with the same call shape.

Runtime.Autograd.Model is the stable runtime namespace re-exported by NN.API.Runtime. Runtime.Autograd.Torch remains available as the lower-level session layer used internally by TorchLean and by typed graph sessions.

This umbrella does not own model catalogs or RL objectives. Runnable models live under TorchLean.nn.models, proof-oriented graph descriptions live under NN.GraphSpec.Models, and differentiable PPO / actor-critic loss helpers live under NN.Runtime.RL.PolicyGradient.Autograd. Keeping those out of the runtime core makes the dependency graph easier to audit: this folder should provide tensors, ops, modules, sessions, losses, optim/training glue, and executable autodiff utilities.

Training helpers

Optimizers