code: def forward_pass(self, inputs, param_vector):
      params = self.parser.get(param_vector, "params")
      biases = self.parser.get(param_vector, "biases")
      if inputs.ndim > 2:
          inputs = inputs.reshape(
              (inputs.shape[0], np.prod(inputs.shape[1:]))
          )
      return self.nonlinearity(np.dot(inputs[:, :], params) + biases)
  
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  import autograd.numpy
  import autograd.numpy.random
  import autograd.scipy.signal
  from autograd import grad
  import data_mnist
label_desc: Use image node_id 3 for calling the full_layer obj's underlying member method code with example usage: obj.forward_pass(inputs, param_vector) and returns: self