neuralqx.experimental.operators.symbolic.compiler.compiler module

Symbolic operator compiler orchestrator.

class SymbolicCompiler(*, pipeline=None, lowerer_registry=None, artifact_store=None, options=None)

Bases: object

Orchestrates the symbolic operator compilation pipeline.

The compiler accepts a symbolic operator (an AbstractSymbolicOperator), runs it through the registered pass pipeline, optionally resolves a cache hit, and, on a miss, invokes the appropriate lowerer to produce a concrete ComputationalJaxOperator.

Typical usage:

from neuralqx.experimental.operators.symbolic import SymbolicCompiler

compiler = SymbolicCompiler()
compiled_op = compiler.compile_operator(my_symbolic_op)
xp, mels = compiled_op.get_conn_padded(x_batch)

Parameters:

• pipeline (SymbolicPassPipeline | None) – Pass pipeline to use. Defaults to default_symbolic_pass_pipeline().

• lowerer_registry (SymbolicLowererRegistry | None) – Lowerer registry. Defaults to default_symbolic_lowerer_registry().

• artifact_store (AbstractSymbolicArtifactStore | None) – Artifact cache store. Defaults to the module-level shared default_symbolic_artifact_store().

• options (SymbolicCompilerOptions | None) – Compiler options. Defaults to SymbolicCompilerOptions with all defaults.

compile_symbolic_operator(operator, *, options=None, metadata=None)

Module-level convenience function for one-shot symbolic compilation.

Uses the module-level shared SymbolicCompiler instance (lazily created). The shared compiler reuses the global in-process artifact cache.

Parameters:

• operator (Any) – Symbolic operator with a to_ir() method.

• options (SymbolicCompilerOptions | None) – Override compiler options.

• metadata (dict[str, Any] | None) – Extra metadata for the context.

Return type:

ComputationalJaxOperator

Returns:

Executable ComputationalJaxOperator.

Example:

from neuralqx.experimental.operators.symbolic import compile_symbolic_operator

compiled_op = compile_symbolic_operator(my_symbolic_op)
xp, mels = compiled_op.get_conn_padded(x_batch)