Question

我正在尝试在Keras中的虚拟数据上训练MobileNet，在多GPU机器上的Docker容器中。 Initially I was trying to train Xception，但我决定切换到一个较小的模型，这样即使是机器功能较弱的人也可以复制我的代码。我与ModelCheckpoint发生了一些我无法理解的冲突。

import tensorflow as tf
import keras.utils
from keras.applications import MobileNet
from keras.callbacks import ModelCheckpoint
from keras.optimizers import Adam
import numpy as np
import os


height = 224
width = 224
channels = 3
epochs = 10
num_classes = 10

# Generate dummy data
batch_size = 32  
n_train = 256
n_test = 64
x_train = np.random.random((n_train, height, width, channels))
y_train = keras.utils.to_categorical(np.random.randint(num_classes, size=(n_train, 1)), num_classes=num_classes)
x_test = np.random.random((n_train, height, width, channels))
y_test = keras.utils.to_categorical(np.random.randint(num_classes, size=(n_test, 1)), num_classes=num_classes)
# Get input shape
input_shape = x_train.shape[1:]

# Instantiate model 
model = MobileNet(weights=None,
                  input_shape=input_shape,
                  classes=num_classes)

model.compile(loss='categorical_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])
# Viewing Model Configuration
model.summary()

# Model file name
filepath = 'model_epoch_{epoch:02d}_loss_{loss:0.2f}_val_{val_loss:.2f}.hdf5'

# Define save_best_only checkpointer
checkpointer = ModelCheckpoint(filepath=filepath,
                             monitor='val_acc',
                             verbose=1,
                             save_best_only=True)

# Let's fit!
model.fit(x_train, y_train,
          batch_size=batch_size,
          epochs=epochs,
          validation_data=(x_test, y_test),
          callbacks=[checkpointer])

我得到的错误是

Traceback (most recent call last):
  File "very_basic_test.py", line 52, in <module>
    callbacks=[checkpointer])
  File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 1650, in fit
    batch_size=batch_size)
  File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 1490, in _standardize_user_data
    _check_array_lengths(x, y, sample_weights)
  File "/usr/local/lib/python2.7/dist-packages/keras/engine/training.py", line 220, in _check_array_lengths
    'and ' + str(list(set_y)[0]) + ' target samples.')
ValueError: Input arrays should have the same number of samples as target arrays. Found 256 input samples and 64 target samples.

Python，Keras和Tensorflow版本：

python -c 'import keras; import tensorflow; import sys; print(sys.version, 'keras.__version__', 'tensorflow.__version__')'
Using TensorFlow backend.
('2.7.12 (default, Dec  4 2017, 14:50:18) \n[GCC 5.4.0 20160609]', '2.1.6', '1.7.0')

Answer 1

问题与检查点回调无关，而是与您提供的数据有关。请查看x_train.shape和y_train.shape，以检查样本数量与第一维尺寸的不匹配情况。该错误似乎发生在该行上，因为这是.fit函数的调用。

在Keras中不能将ModelCheckpoint与MobileNet一起使用

1 个答案: