code: def _convert_upsample(
      inexpr, keras_layer, etab, data_layout, input_shape=None
  ):  # pylint: disable=unused-argument
      _check_data_format(keras_layer)
      upsample_type = type(keras_layer).__name__
      params = {}
      if upsample_type == "UpSampling1D":
          h = keras_layer.size
          params["scale_h"] = h
      elif upsample_type == "UpSampling2D":
          h, w = keras_layer.size
          params["scale_h"] = h
          params["scale_w"] = w
  
          if hasattr(keras_layer, "interpolation"):
              interpolation = keras_layer.interpolation
              if interpolation == "nearest":
                  params["method"] = "nearest_neighbor"
              else:
                  params["method"] = "bilinear"
      else:
          raise tvm.error.OpNotImplemented(
              f"Operator {upsample_type} is not supported for frontend Keras."
          )
      params["layout"] = data_layout
      out = _op.nn.upsampling(inexpr, **params)
      return out
  
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 20 for calling a global function with example usage: _convert_upsample(inexpr, keras_layer, etab, data_layout, input_shape) and returns: out