code: def _convert_pooling3d(
      inexpr, keras_layer, etab, data_layout, input_shape=None
  ):  # pylint: disable=unused-argument
      _check_data_format(keras_layer)
      pool_type = type(keras_layer).__name__
      if input_shape is None:
          input_shape = keras_layer.input_shape
  
      if pool_type not in ["MaxPooling3D", "AveragePooling3D"]:
          raise tvm.error.OpNotImplemented(
              f"Operator {keras_layer} is not supported for frontend Keras."
          )
  
      pool_d1, pool_d2, pool_d3 = keras_layer.pool_size
      stride_d1, stride_d2, stride_d3 = keras_layer.strides
      params = {
          "pool_size": [pool_d1, pool_d2, pool_d3],
          "strides": [stride_d1, stride_d2, stride_d3],
          "padding": [0, 0, 0],
          "layout": data_layout,
      }
  
      if keras_layer.padding == "valid":
          pass
      elif keras_layer.padding == "same":
          in_d1 = input_shape[1]
          in_d2 = input_shape[2]
          in_d3 = input_shape[3]
          pad_d1 = _get_pad_pair(in_d1, pool_d1, stride_d1)
          pad_d2 = _get_pad_pair(in_d2, pool_d2, stride_d2)
          pad_d3 = _get_pad_pair(in_d3, pool_d3, stride_d3)
          params["padding"] = [
              pad_d1[0],
              pad_d2[0],
              pad_d3[0],
              pad_d1[1],
              pad_d2[1],
              pad_d3[1],
          ]
      else:
          raise tvm.error.OpAttributeUnImplemented(
              f"Padding with {keras_layer.padding} is not supported in operator Pooling3D."
          )
  
      out = _op.transpose(inexpr, axes=(0, 4, 1, 2, 3))
      params["layout"] = "NCDHW"
      if pool_type == "MaxPooling3D":
          out = _op.nn.max_pool3d(out, **params)
      elif pool_type == "AveragePooling3D":
          out = _op.nn.avg_pool3d(out, **params)
  
      return _op.transpose(out, axes=(0, 2, 3, 4, 1))
  
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 18 for calling a global function with example usage: _convert_pooling3d(inexpr, keras_layer, etab, data_layout, input_shape) and returns: _op