}
		mappings[m.ID] = m
	}
	functions := make(map[uint64]*Function, len(p.Function))
	for _, f := range p.Function {
		if f == nil {
			return fmt.Errorf("profile has nil function")
		}
		if f.ID == 0 {
			return fmt.Errorf("found function with reserved ID=0")
		}
		if functions[f.ID] != nil {
			return fmt.Errorf("multiple functions with same id: %d", f.ID)
		}
		functions[f.ID] = f
	}

	}
	f := &Function{
		ID:         uint64(len(pm.p.Function) + 1),
		Name:       src.Name,
		SystemName: src.SystemName,
		Filename:   src.Filename,
		StartLine:  src.StartLine,
	}
	pm.functions[k] = f
	pm.functionsByID[src.ID] = f
	pm.p.Function = append(pm.p.Function, f)
	return f
}

// key generates a struct to be used as a key for maps.
func (f *Function) key() functionKey {
	return functionKey{

#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace tensorflow::quantization {

// Declares pure virtual member functions for a python-side derived class to
// override. This allows calling python implementations from the C++ layer.
// Member functions should be pure not stateful; they should not access or rely
// on member fields.
class PyFunctionLibrary {
 public:
  virtual ~PyFunctionLibrary() = default;

	HasAES    bool // KM-AES{128,192,256} functions
	HasAESCBC bool // KMC-AES{128,192,256} functions
	HasAESCTR bool // KMCTR-AES{128,192,256} functions
	HasAESGCM bool // KMA-GCM-AES{128,192,256} functions
	HasGHASH  bool // KIMD-GHASH function
	HasSHA1   bool // K{I,L}MD-SHA-1 functions
	HasSHA256 bool // K{I,L}MD-SHA-256 functions
	HasSHA512 bool // K{I,L}MD-SHA-512 functions

}

// pstate records package-level coverage data state:
// - a table of functions (file/fname/literal)
// - a map recording the index/ID of each func encountered so far
// - a table storing execution count for the coverable units in each func
type pstate struct {
	// slice of unique functions
	funcs []fnfile
	// maps function to index in slice above (index acts as function ID)
	funcTable map[fnfile]uint32

C.sizeof_struct_stat.

A C function may be declared in the Go file with a parameter type of
the special name _GoString_. This function may be called with an
ordinary Go string value. The string length, and a pointer to the
string contents, may be accessed by calling the C functions

	size_t _GoStringLen(_GoString_ s);
	const char *_GoStringPtr(_GoString_ s);

These functions are only available in the preamble, not in other C

				d.pred.add(n)
			}
		}
	}

	var G, funcG []*graphNode // separate non-functions and functions
	for _, n := range M {
		if _, ok := n.obj.(*Func); ok {
			funcG = append(funcG, n)
		} else {
			G = append(G, n)
		}
	}

	// remove function nodes and collect remaining graph nodes in G
	// (Mutually recursive functions may introduce cycles among themselves

				d.pred.add(n)
			}
		}
	}

	var G, funcG []*graphNode // separate non-functions and functions
	for _, n := range M {
		if _, ok := n.obj.(*Func); ok {
			funcG = append(funcG, n)
		} else {
			G = append(G, n)
		}
	}

	// remove function nodes and collect remaining graph nodes in G
	// (Mutually recursive functions may introduce cycles among themselves

        signature_def_map,
    const tensorflow::quantization::PyFunctionLibrary& py_function_library);

// Function used by the pywrap_quantization module to mirror
// `::stablehlo::quantization::PopulateDefaults`.
QuantizationConfig PywrapPopulateDefaults(
    const QuantizationConfig& user_provided_config);

// Function used by the pywrap_quantization module to mirror
// `::stablehlo::quantization::ExpandPresets`.

// example function, at least one other function, type, variable, or constant
// declaration, and no test or benchmark functions.
//
// # Fuzzing
//
// 'go test' and the testing package support fuzzing, a testing technique where
// a function is called with randomly generated inputs to find bugs not
// anticipated by unit tests.
//
// Functions of the form
//
//	func FuzzXxx(*testing.F)