code: def reshape(inputs, prev_modules, attrs, outputs):
      # extract inputs
      _, data_tensor_shape = inputs[0]
      shape_tensor_val, _ = inputs[1]
      shape_arry = None
      if shape_tensor_val is not None:
          shape_arry = np.squeeze(shape_tensor_val).astype(int).tolist()
      # create module node
      module = Reshape(shape_arry)(prev_modules)
      return module, [shape_tensor_val]
  
file_path: BigDL/python/dllib/src/bigdl/dllib/contrib/onnx/ops_converter.py
imports: from bigdl.dllib.nn.layer import SpatialAveragePooling, SpatialBatchNormalization
  from bigdl.dllib.nn.layer import SpatialConvolution, SpatialMaxPooling, JoinTable
  from bigdl.dllib.nn.layer import ReLU, SoftMax, CAddTable, Unsqueeze
  from bigdl.dllib.nn.onnx.layer import Constant, Gather, Gemm, Shape, Reshape
  from .converter_utils import *
label_desc: Use image node_id 10 for calling a global function with example usage: reshape(inputs, prev_modules, attrs, outputs) and returns: module,  list