下面是我的Tensorflow和Python代码，当准确率达到99%时会通过回调函数结束训练。但回调函数并未被调用。问题出在哪里？
def train_mnist(): class myCallback(tf.keras.callbacks.Callback): def on_epoc_end(self, epoch,logs={}): if (logs.get('accuracy')>0.99): print("Reached 99% accuracy so cancelling training!") self.model.stop_training=True mnist = tf.keras.datasets.mnist (x_train, y_train),(x_test, y_test) = mnist.load_data(path=path) x_train= x_train/255.0 x_test= x_test/255.0 callbacks=myCallback() model = tf.keras.models.Sequential([ # YOUR CODE SHOULD START HERE tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(256, activation=tf.nn.relu), tf.keras.layers.Dense(10, activation=tf.nn.softmax) ]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) # model fitting history = model.fit(x_train,y_train, epochs=10,callbacks=[callbacks]) # model fitting return history.epoch, history.history['acc'][-1]回答：
你拼错了epoch，而且你应该返回accuracy而不是acc。
from tensorflow.keras.layers import Input, Dense, Add, Activation, Flattenfrom tensorflow.keras.models import Model, Sequentialimport tensorflow as tfimport numpy as npimport randomfrom tensorflow.python.keras.layers import Input, GaussianNoise, BatchNormalizationdef train_mnist(): class myCallback(tf.keras.callbacks.Callback): def on_epoch_end(self, epoch,logs={}): print(logs.get('accuracy')) if (logs.get('accuracy')>0.9): print("Reached 90% accuracy so cancelling training!") self.model.stop_training=True mnist = tf.keras.datasets.mnist (x_train, y_train),(x_test, y_test) = mnist.load_data() x_train= x_train/255.0 x_test= x_test/255.0 callbacks=myCallback() model = tf.keras.models.Sequential([ # YOUR CODE SHOULD START HERE tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(256, activation=tf.nn.relu), tf.keras.layers.Dense(10, activation=tf.nn.softmax) ]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) # model fitting history = model.fit(x_train,y_train, epochs=10,callbacks=[callbacks]) # model fitting return history.epoch, history.history['accuracy'][-1]train_mnist()Epoch 1/101859/1875 [============================>.] - ETA: 0s - loss: 0.2273 - accuracy: 0.93580.93586665391922Reached 90% accuracy so cancelling training!1875/1875 [==============================] - 3s 2ms/step - loss: 0.2265 - accuracy: 0.9359([0], 0.93586665391922)