code: def _Conv3DGrad(op: ops.Operation, grad):
      data_format = op.get_attr("data_format").decode()
      shape_0, shape_1 = array_ops.shape_n([op.inputs[0], op.inputs[1]])
      return [
          gen_nn_ops.conv3d_backprop_input_v2(
              shape_0,
              op.inputs[1],
              grad,
              dilations=op.get_attr("dilations"),
              strides=op.get_attr("strides"),
              padding=op.get_attr("padding"),
              data_format=data_format,
          ),
          gen_nn_ops.conv3d_backprop_filter_v2(
              op.inputs[0],
              shape_1,
              grad,
              dilations=op.get_attr("dilations"),
              strides=op.get_attr("strides"),
              padding=op.get_attr("padding"),
              data_format=data_format,
          ),
      ]
  
imports: import functools
  import itertools
  import operator
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 5 for calling a global function with example usage: _Conv3DGrad(op, grad) and returns: list