本文整理汇总了Python中keras.models.Sequential.predictions_and_gradient方法的典型用法代码示例。如果您正苦于以下问题：Python Sequential.predictions_and_gradient方法的具体用法？Python Sequential.predictions_and_gradient怎么用？Python Sequential.predictions_and_gradient使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类keras.models.Sequential的用法示例。
在下文中一共展示了Sequential.predictions_and_gradient方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_keras_model
# 需要导入模块: from keras.models import Sequential [as 别名]
# 或者: from keras.models.Sequential import predictions_and_gradient [as 别名]
def test_keras_model(num_classes):
bounds = (0, 255)
channels = num_classes
model = Sequential()
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
model.add(GlobalAveragePooling2D(
data_format='channels_last', input_shape=(5, 5, channels)))
model = KerasModel(
model,
bounds=bounds,
predicts='logits')
test_images = np.random.rand(2, 5, 5, channels).astype(np.float32)
test_label = 7
assert model.batch_predictions(test_images).shape \
== (2, num_classes)
test_logits = model.predictions(test_images[0])
assert test_logits.shape == (num_classes,)
test_gradient = model.gradient(test_images[0], test_label)
assert test_gradient.shape == test_images[0].shape
np.testing.assert_almost_equal(
model.predictions_and_gradient(test_images[0], test_label)[0],
test_logits)
np.testing.assert_almost_equal(
model.predictions_and_gradient(test_images[0], test_label)[1],
test_gradient)
assert model.num_classes() == num_classes