img_classifier.py 文件源码

def build_model(self, inputs, learner_type=commons.LearnerType.Classifier):
    _, endpoints = self.incep4_model.build_model(inputs)
    # get feature output.
    basenet_output = endpoints[self.incep4_model.net_params.output_layer_name]
    if len(basenet_output.get_shape()) > 2:
      basenet_output_flat = slim.flatten(
          basenet_output, scope="baseoutput_flatten")
    else:
      basenet_output_flat = basenet_output
    # add ft layer.
    new_logits = slim.fully_connected(
        basenet_output_flat,
        self.net_params.cls_num,
        activation_fn=None,
        scope="ft/logits")
    # monitor ft layer output.
    base_model.add_tensor_summary(
        new_logits.name, new_logits, use_histogram=True, use_sparsity=True)
    return new_logits, endpoints