code: def _make_ind(dim, shape):
      m = np.empty(shape, dtype=np.int64)
      ind = [slice(0, shape[i]) for i in range(len(shape))]
      new_shape = [1] * len(shape)
      new_shape[dim] = shape[dim]
      first = np.arange(shape[dim]).reshape(new_shape)
      m[tuple(ind)] = first
      return m
  
file_path: onnx/onnx/reference/ops_optimized/op_conv_optimized.py
imports: import numpy
  from onnx.reference.op_run import OpRun
label_desc: Use image node_id 1 for calling a global function with example usage: _make_ind(dim, shape) and returns: m