code: def _convert_reshape(
      inexpr, keras_layer, etab, data_layout, input_shape=None
  ):  # pylint: disable=unused-argument
      _check_data_format(keras_layer)
      if input_shape is None:
          input_shape = keras_layer.input_shape
  
      inshape = input_shape  # includes batch
      tshape = keras_layer.target_shape  # no batch
      shape = (-1,) + tshape
  
      if data_layout == "NCHW" and (
          len(inshape) > 3 or len(tshape) > 2
      ):
          # Perform reshape in original NHWC format.
          inexpr = _op.transpose(
              inexpr, [0] + list(range(2, len(inshape))) + [1]
          )
          inexpr = _op.reshape(inexpr, newshape=shape)
          return _op.transpose(
              inexpr, axes=[0, -1] + list(range(1, len(shape) - 1))
          )
  
      return _op.reshape(inexpr, newshape=shape)
  
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 27 for calling a global function with example usage: _convert_reshape(inexpr, keras_layer, etab, data_layout, input_shape) and returns: _op, _op