TorchLean API

NN.Runtime.PyTorch.Wire

Graph wire format #

NN.IR.OpTag identifies semantic operators. This module assigns each identity its fixed spelling in torchlean.ir.v1: for example, .mulElem is written as "mul_elem". Keeping this table separate from diagnostic names lets us improve an error message while keeping existing graphs readable. Exporters and importers use the same table.

The tag round trip is proved for every constructor. Static attributes are parsed separately; parseOpKind? constructs only operations that need none. Tuple projections and supported container nodes belong to the external value graph, not the tensor graph's semantic operator vocabulary.

Format marker written to the root format field.

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    Projection of one component out of a tuple-valued FX node.

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      Container-valued nn.MultiheadAttention call kept in the value graph.

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        Legacy marker for a tuple producer without a lowering rule; the importer reports its limits.

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          Fixed constructor spelling in the torchlean.ir.v1 artifact.

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            Parse a v1 constructor spelling into its semantic identity.

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              Parse an attribute-free operation; attributed operators need their separate fields.

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                JSON or Python "kind": "<wire>" field for an operator identity.

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                  JSON or Python object holding only the kind field.

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                    The wire string as a quoted JSON or Python literal.

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                      Python set literal of quoted wire strings.

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                        Every v1 tag parses back to its identity: the codec is complete and collision free.

                        Serializing and parsing an operation preserves its identity, regardless of its attributes.

                        The attribute-free v1 round trip reconstructs the original operation.