class_docstr: Adapt Caffe prototxt and weights into uniform format
class_docstr_tok: ["Adapt","Caffe","prototxt","and","weights","into","uniform","format"]
code: def _adapt_data_provider(self):
      if not self._raw_net:
          raise KeyError("Invalid net structure\n")
      raw_layers = self._raw_net.layer or self._raw_net.layers
      for raw_layer in raw_layers:
          if raw_layer.type != "Input":
              continue
          if not self._inclusive_layer(raw_layer):
              continue
  
          for i in range(0, len(raw_layer.top)):
              data_provider = cntkmodel.CntkLayersDefinition()
              data_provider.op_name = raw_layer.top[i]
              data_provider.tensor = raw_layer.input_param.shape[i].dim[
                  1:
              ]  # cancel mini-batch
              self._uni_model.data_provider.append(data_provider)
  
imports: import sys
  import os
  import time
  import math
  from cntk.contrib.crosstalkcaffe.unimodel import cntkmodel
  from cntk.contrib.crosstalkcaffe.adapter import baseadapter
  from .None import caffeimpl
label_desc: Use image node_id 4 for calling the CaffeAdapter obj's underlying member method code with example usage: obj._adapt_data_provider() without return types