models.py 文件源码

def create_model(self, model_input, num_classes=10, l2_penalty=1e-8, **unused_params):
    """Creates a logistic model.

    Args:
      model_input: 'batch' x 'num_features' matrix of input features.
      num_classes: The number of classes in the dataset.

    Returns:
      A dictionary with a tensor containing the probability predictions of the
      model in the 'predictions' key. The dimensions of the tensor are
      batch_size x num_classes."""
    net = slim.flatten(model_input)
    output = slim.fully_connected(
        net, num_classes, activation_fn=None,
        weights_regularizer=slim.l2_regularizer(l2_penalty))
    return {"predictions": output}