code: def _convert_lambda(inexpr, keras_layer, _, data_layout):
      fcode = keras_layer.function.__code__
      # Convert l2_normalize
      if (
          fcode.co_name == "<lambda>"
          and len(fcode.co_names) > 0
          and fcode.co_names[-1] == "l2_normalize"
      ):
          return _convert_l2_normalize(inexpr, keras_layer, data_layout)
      raise tvm.error.OpNotImplemented(
          f"Function {fcode.co_names} used in Lambda layer is not supported in frontend Keras."
      )
  
imports: import dis
  import sys
  import numpy
  import tvm
  from tvm.ir import IRModule, TensorType, TupleType
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from ..None import op
  from ...None import nd
  from .common import ExprTable, new_var
label_desc: Use image node_id 33 for calling a global function with example usage: _convert_lambda(inexpr, keras_layer, _, data_layout) and returns: _convert_l2_normalize