onnx_light.onnx.compose#

onnx_light.onnx.compose.add_prefix(model: ModelProto, prefix: str, rename_nodes: bool = True, rename_edges: bool = True, rename_inputs: bool = True, rename_outputs: bool = True, rename_initializers: bool = True, rename_value_infos: bool = True, rename_functions: bool = True, inplace: bool = False) → ModelProto#

Adds a prefix to names of elements in a model.

Applies prefix to graph nodes, edges, inputs, outputs, initializers, sparse initializers, value-infos and local functions as requested. Empty names are never prefixed.

Parameters:

  • model – The model to prefix.

  • prefix – Prefix string to prepend.

  • rename_nodes – Whether to prefix node names.

  • rename_edges – Whether to prefix node edge names.

  • rename_inputs – Whether to prefix input names.

  • rename_outputs – Whether to prefix output names.

  • rename_initializers – Whether to prefix initializer names.

  • rename_value_infos – Whether to prefix value-info names.

  • rename_functions – Whether to prefix local function names.

  • inplace – If True, mutates model in place; otherwise a copy is made.

Returns:

The (possibly new) ModelProto with prefixed names.

onnx_light.onnx.compose.add_prefix_graph(graph: GraphProto, prefix: str, rename_nodes: bool = True, rename_edges: bool = True, rename_inputs: bool = True, rename_outputs: bool = True, rename_initializers: bool = True, rename_value_infos: bool = True, inplace: bool = False, name_map: dict[str, str] | None = None) → GraphProto#

Adds a prefix to names of elements in a graph.

Applies prefix to nodes, edges, inputs, outputs, initializers, sparse initializers and value-infos as requested. Empty names are never prefixed.

Parameters:

  • graph – The graph to prefix.

  • prefix – Prefix string to prepend.

  • rename_nodes – Whether to prefix node names.

  • rename_edges – Whether to prefix node edge names.

  • rename_inputs – Whether to prefix input names.

  • rename_outputs – Whether to prefix output names.

  • rename_initializers – Whether to prefix initializer names.

  • rename_value_infos – Whether to prefix value-info names.

  • inplace – If True, mutates graph in place; otherwise a copy is made.

  • name_map – Ignored – kept for backward-compatibility with the old Python API.

Returns:

The (possibly new) GraphProto with prefixed names.

onnx_light.onnx.compose.check_overlapping_names(g1: GraphProto, g2: GraphProto, io_map: list[tuple[str, str]] | None = None) → list[tuple[str, list[str]]]#

Checks whether two graphs have overlapping names.

Returns a list of (category, names) pairs for each category where names appear in both g1 and g2. Recognised categories are "edge", "value_info", "initializer" and "sparse_initializer".

The optional io_map lists output/input pairs that are intentionally shared between the two graphs; those overlaps are excluded.

onnx_light.onnx.compose.expand_out_dim(model: ModelProto, dim_idx: int, inplace: bool = False) → ModelProto#

Inserts an extra dimension with extent 1 to each output in the model.

Parameters:

  • model – The model to modify.

  • dim_idx – Index at which the new dimension is inserted. Negative values count from the back of the existing dimension list.

  • inplace – If True, mutates model in place; otherwise a copy is made.

Returns:

The (possibly new) ModelProto with expanded output dimensions.

onnx_light.onnx.compose.expand_out_dim_graph(graph: GraphProto, dim_idx: int, inplace: bool = False) → GraphProto#

Inserts an extra dimension with extent 1 to each output in the graph.

Appends an Unsqueeze node for each output. Useful before merging graphs when the second graph expects a batch dimension.

Parameters:

  • graph – The graph to modify.

  • dim_idx – Index at which the new dimension is inserted. Negative values count from the back of the existing dimension list.

  • inplace – If True, mutates graph in place; otherwise a copy is made.

Returns:

The (possibly new) GraphProto with expanded output dimensions.

onnx_light.onnx.compose.merge_graphs(g1: GraphProto, g2: GraphProto, io_map: list[tuple[str, str]], inputs: list[str] | None = None, outputs: list[str] | None = None, prefix1: str = '', prefix2: str = '', name: str = '', doc_string: str = '') → GraphProto#

Combines two ONNX graphs into a single one.

Parameters:

  • g1 – First graph.

  • g2 – Second graph.

  • io_map – Pairs [(out_name, in_name), …] mapping outputs of g1 to inputs of g2.

  • inputs – Optional list of inputs to include.

  • outputs – Optional list of outputs to include.

  • prefix1 – Optional prefix for all names in g1.

  • prefix2 – Optional prefix for all names in g2.

  • name – Optional name for the combined graph.

  • doc_string – Optional doc-string for the combined graph.

Returns:

Combined GraphProto.

onnx_light.onnx.compose.merge_models(m1: ModelProto, m2: ModelProto, io_map: list[tuple[str, str]], inputs: list[str] | None = None, outputs: list[str] | None = None, prefix1: str = '', prefix2: str = '', name: str = '', doc_string: str = '', producer_name: str = 'onnx_light.onnx.compose.merge_models', producer_version: str = '1.0', domain: str = '', model_version: int | None = 1) → ModelProto#

Combines two ONNX models into a single one.

Both models must share the same IR version and operator sets.

Parameters:

  • m1 – First model.

  • m2 – Second model.

  • io_map – Pairs [(out_name, in_name), …] mapping outputs of m1 to inputs of m2.

  • inputs – Optional list of inputs for the combined model.

  • outputs – Optional list of outputs for the combined model.

  • prefix1 – Optional prefix for all names in m1.

  • prefix2 – Optional prefix for all names in m2.

  • name – Optional name for the combined graph.

  • doc_string – Optional doc-string for the combined graph.

  • producer_name – Producer name for the combined model.

  • producer_version – Producer version string.

  • domain – Domain of the combined model.

  • model_version – Version of the combined model. Pass None to leave the version unset.

Returns:

Combined ModelProto.