Keras 在 1 個完成的 epoch 后停止

Question

嘗試使用簡單的 CNN 在 CIFAR-10 數據集上運行分類。 但是，模型在完成第一個 epoch 后停止，並且不會繼續完成所有五個。 請幫忙。

輸入：

cifar10 = tf.keras.datasets.cifar10
(train_images, train_labels), (test_images, test_labels) = cifar10.load_data()

import os
import matplotlib.pyplot as plt
import numpy as np
import time
import tensorflow as tf
from tensorflow import keras 
from tensorflow.keras import layers
from tensorflow.keras import models
from tensorflow.keras import optimizers
from tensorflow.keras.applications import VGG16
from tensorflow.keras.preprocessing.image import ImageDataGenerator

model = models.Sequential()

# Convolutional base (feature extractor)
model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))
model.add(layers.MaxPooling2D((2, 2)))

model.add(layers.Conv2D(64, (3, 3), activation='relu'))
model.add(layers.MaxPooling2D((2, 2)))

# Deep feed-forward classifier
model.add(layers.Flatten())
model.add(layers.Dense(64, activation='relu'))
model.add(layers.Dense(10, activation='softmax'))

model.compile(loss='sparse_categorical_crossentropy', optimizer=optimizers.RMSprop(lr=1e-4), metrics=['acc'])

history = model.fit(
    x=train_images,
    y=train_labels,
    steps_per_epoch=100,
    epochs=5,
    verbose=1,
    validation_data=(test_images, test_labels),
    validation_steps=50)

輸出：

Train on 50000 samples, validate on 10000 samples
Epoch 1/5
50000/50000 [==============================] - 28s 564us/sample - loss: 2.1455 - acc: 0.2945 - val_loss: 2.0011 - val_acc: 0.3038

Answer 1

您應該刪除 steps_per_epoh 和 validation_steps 並使用 batch_size 參數。