class_docstr: A helper class for handling relay functions from darknet model.
docstr: Parse the weights and biases for fully connected or dense layer.
docstr_tok: ["Parse","the","weights","and","biases","for","fully","connected","or","dense","layer","."]
code: def _get_connected_weights(self, layer, opname):
      """Parse the weights and biases for fully connected or dense layer."""
      size = layer.outputs * layer.inputs
      if size == 0:
          return None
  
      weights = self._read_memory_buffer(
          (layer.outputs, layer.inputs), layer.weights
      )
      biases = self._read_memory_buffer((layer.outputs,), layer.biases)
  
      params = {}
      k = _get_params_name(opname, "weight")
      params[k] = tvm.nd.array(weights)
  
      if layer.batch_normalize == 1 and layer.dontloadscales != 1:
          params.update(
              self._get_batchnorm_weights(layer, opname, layer.outputs)
          )
          k = _get_params_name(opname, "beta")
          params[k] = tvm.nd.array(biases)
      else:
          k = _get_params_name(opname, "bias")
          params[k] = tvm.nd.array(biases)
      return params
  
imports: from enum import Enum
  import numpy
  import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from .common import get_relay_op, new_var
label_desc: Use image node_id 4 for calling the GraphProto obj's underlying member method code with example usage: obj._get_connected_weights(layer, opname) and returns: params, None