dnn.py 文件源码

def _predictions(logits, n_classes):
  """Returns predictions for the given logits and n_classes."""
  predictions = {}
  if n_classes == 2:
    predictions[_LOGISTIC] = math_ops.sigmoid(logits)
    logits = array_ops.concat(1, [array_ops.zeros_like(logits), logits])
  predictions[_PROBABILITIES] = nn.softmax(logits)
  predictions[_CLASSES] = array_ops.reshape(
      math_ops.argmax(logits, 1), shape=(-1, 1))
  return predictions