code: def _build_linear(n_in, n_out, name, init):
      return nn.Linear(
          n_in,
          n_out,
          weight_attr=P.ParamAttr(
              name="%s.w_0" % name if name is not None else None,
              initializer=init,
          ),
          bias_attr="%s.b_0" % name if name is not None else None,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import json
  import logging
  import math
  import six
  import numpy
  import paddle
  from paddle import nn
  from paddle.nn import functional
  from disco_diffusion_ernievil_base.vit_b_16x.ernievil2.transformers.file_utils import _fetch_from_remote, add_docstring
label_desc: Use image node_id 2 for calling a global function with example usage: _build_linear(n_in, n_out, name, init) and returns: nn