cc6085567559b008c831d07fcb7c1f53bea9a699,coremltools/converters/nnssa/frontend/tensorflow/load.py,,load,#Any#Any#,13

Before Change

    ssa = graphdef_to_ssa(gd)

    placeholder_shape = kwargs.get("placeholder_shape", {})
    for k, v in placeholder_shape.items():
        assert (k in ssa.functions["main"].graph)
        ssa.functions["main"].graph[k].tfattr["_output_shapes"] = [v]

    passes = [
        delete_asserts, functionalize_loops, constant_propagation, cond_to_where,
        remove_variable_nodes, fusedbatchnorm_rewrite, lstmblockcell_rewrite
    ]

After Change

    placeholder_shape = kwargs.get("inputs", {})
    if len(placeholder_shape) > 0:
        graph = ssa.functions["main"].graph
        required_plhd_nodes = [node for node in graph if 
            graph[node].op == "Placeholder"]
        for name in required_plhd_nodes:
            if name not in placeholder_shape:
                raise ValueError("Shape of required input {} is not provided.".format(name))
            graph[name].attr["_output_shapes"] = [placeholder_shape[name]]

    passes = [
        delete_asserts, functionalize_loops, constant_propagation,
        cond_to_where, remove_variable_nodes, fusedbatchnorm_rewrite,
        lstmblockcell_rewrite

Instances