class_docstr: Associates parameters loaded from a .caffemodel file with their corresponding nodes.
class_docstr_tok: ["Associates","parameters","loaded","from","a",".caffemodel","file","with","their","corresponding","nodes","."]
code: def load_using_caffe(self):
      caffe = get_caffe_resolver().caffe
      net = caffe.Net(
          str(self.def_path), str(self.data_path), caffe.TEST
      )
      data = lambda blob: blob.data
      self.params = [
          (k, list(map(data, v))) for k, v in net.params.items()
      ]
  
imports: from __future__ import unicode_literals
  from google.protobuf import text_format
  import numpy
  from mmdnn.conversion.caffe.graph import GraphBuilder, NodeKind, LAYER_IN_TRAIN_PROTO
  from mmdnn.conversion.caffe.mapper import NodeMapper, get_handler_name
  from mmdnn.conversion.caffe.resolver import get_caffe_resolver, has_pycaffe
  from mmdnn.conversion.caffe.errors import print_stderr, ConversionError
  from mmdnn.conversion.caffe.common_graph import Graph
  from mmdnn.conversion.caffe.utils import get_lower_case, get_upper_case
label_desc: Use image node_id 2 for calling the DataInjector obj's underlying member method code with example usage: obj.load_using_caffe() without return types