在 Keras 中构建数据时如何使用 repeat() 函数? [英] How to use repeat() function when building data in Keras?
问题描述
我正在用猫和狗的数据集训练一个二元分类器:
总数据集:10000 张图像
训练数据集:8000张图片
验证/测试数据集:2000 张图像
I am training a binary classifier on a dataset of cats and dogs:
Total Dataset: 10000 images
Training Dataset: 8000 images
Validation/Test Dataset: 2000 images
Jupyter 笔记本代码:
The Jupyter notebook code:
# Part 2 - Fitting the CNN to the images
train_datagen = ImageDataGenerator(rescale = 1./255,
shear_range = 0.2,
zoom_range = 0.2,
horizontal_flip = True)
test_datagen = ImageDataGenerator(rescale = 1./255)
training_set = train_datagen.flow_from_directory('dataset/training_set',
target_size = (64, 64),
batch_size = 32,
class_mode = 'binary')
test_set = test_datagen.flow_from_directory('dataset/test_set',
target_size = (64, 64),
batch_size = 32,
class_mode = 'binary')
history = model.fit_generator(training_set,
steps_per_epoch=8000,
epochs=25,
validation_data=test_set,
validation_steps=2000)
我在 CPU 上训练它没有问题,但是当我在 GPU 上运行时,它抛出了这个错误:
I trained it on a CPU without a problem but when I run on GPU it throws me this error:
Found 8000 images belonging to 2 classes.
Found 2000 images belonging to 2 classes.
WARNING:tensorflow:From <ipython-input-8-140743827a71>:23: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
Please use Model.fit, which supports generators.
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
Train for 8000 steps, validate for 2000 steps
Epoch 1/25
250/8000 [..............................] - ETA: 21:50 - loss: 7.6246 - accuracy: 0.5000
WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 200000 batches). You may need to use the repeat() function when building your dataset.
250/8000 [..............................] - ETA: 21:52 - loss: 7.6246 - accuracy: 0.5000
我想知道如何在使用 Tensorflow 2.0 的 keras 中使用 repeat() 函数?
I would like to know how to use the repeat() function in keras using Tensorflow 2.0?
推荐答案
你的问题源于参数steps_per_epoch
和 validation_steps
需要等于总和划分为 batch_size
的数据点数.
Your problem stems from the fact that the parameters steps_per_epoch
and validation_steps
need to be equal to the total number of data points divided to the batch_size
.
您的代码可以在 2017 年 8 月之前在 Keras 1.X
中运行.
Your code would work in Keras 1.X
, prior to August 2017.
将您的 model.fit()
函数更改为:
Change your model.fit()
function to:
history = model.fit_generator(training_set,
steps_per_epoch=int(8000/batch_size),
epochs=25,
validation_data=test_set,
validation_steps=int(2000/batch_size))
从 TensorFlow 2.1
开始,fit_generator()
已被弃用.您也可以在生成器上使用 .fit()
方法.
As of TensorFlow 2.1
, fit_generator()
is being deprecated. You can use .fit()
method also on generators.
TensorFlow >= 2.1
代码:
history = model.fit(training_set.repeat(),
steps_per_epoch=int(8000/batch_size),
epochs=25,
validation_data=test_set.repeat(),
validation_steps=int(2000/batch_size))
注意int(8000/batch_size)
等价于8000//batch_size
(整数除法)
Notice that int(8000/batch_size)
is equivalent to 8000 // batch_size
(integer division)
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