Keras 2.0.4@OSX 10.12.5(Python 3.6.1)

環境

$ sw_vers
ProductName:	Mac OS X
ProductVersion:	10.12.5
BuildVersion:	16F73
$ pyenv versions
  system
* 3.6.1 (set by /Users/dela/.pyenv/version)
$ pip freeze | grep Keras
Keras==2.0.4

セットアップ

pip install -U tensorflow
pip install -U keras
pip install h5py
pip install matplotlib

コード

from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import Dense, Activation
from keras.utils import np_utils
import matplotlib.pyplot as plt

#ValueError: Error when checking target: expected activation_2 to have shape (None, 10) but got array with shape (60000, 1)
(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = x_train.reshape(60000, 784) / 255
x_test = x_test.reshape(10000, 784) / 255

model = Sequential([
    Dense(512, input_shape=(784,)),
    Activation('sigmoid'),
    Dense(10),
    Activation('softmax')
])

model.compile(loss='sparse_categorical_crossentropy', optimizer='sgd', metrics=['accuracy'])

hist = model.fit(x_train, y_train, batch_size=200, verbose=1, epochs=20, validation_split=0.1)

score = model.evaluate(x_test, y_test, verbose=1)
print("\ntest accuracy : ", score[1])

loss = hist.history['loss']
val_loss = hist.history['val_loss']
plt.plot(range(20), loss, marker = '.', label = 'loss')
plt.plot(range(20), val_loss, marker = '.', label = 'val_loss')
plt.legend(loc  = 'best', fontsize = 10)
plt.grid()
plt.xlabel('epoch')
plt.ylabel('loss')
plt.show()

acc = hist.history['acc']
val_acc = hist.history['val_acc']
plt.plot(range(20), acc, marker = '.', label = 'acc')
plt.plot(range(20), val_acc, marker = '.', label = 'val_acc')
plt.legend(loc  = 'best', fontsize = 10)
plt.grid()
plt.xlabel('epoch')
plt.ylabel('acc')
plt.show()

実行ログ

python multi_layer_perceptron.py
Using TensorFlow backend.
Train on 54000 samples, validate on 6000 samples
Epoch 1/20
2017-06-11 09:45:37.849024: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-11 09:45:37.849085: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-11 09:45:37.849100: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
54000/54000 [==============================] - 5s - loss: 2.0821 - acc: 0.4838 - val_loss: 1.8598 - val_acc: 0.6797
Epoch 2/20
54000/54000 [==============================] - 4s - loss: 1.7041 - acc: 0.7005 - val_loss: 1.5052 - val_acc: 0.7832
Epoch 3/20
54000/54000 [==============================] - 4s - loss: 1.4035 - acc: 0.7591 - val_loss: 1.2284 - val_acc: 0.8223
Epoch 4/20
54000/54000 [==============================] - 4s - loss: 1.1764 - acc: 0.7901 - val_loss: 1.0275 - val_acc: 0.8498
Epoch 5/20
54000/54000 [==============================] - 4s - loss: 1.0121 - acc: 0.8095 - val_loss: 0.8814 - val_acc: 0.8563
Epoch 6/20
54000/54000 [==============================] - 4s - loss: 0.8931 - acc: 0.8239 - val_loss: 0.7762 - val_acc: 0.8685
Epoch 7/20
54000/54000 [==============================] - 4s - loss: 0.8052 - acc: 0.8338 - val_loss: 0.6971 - val_acc: 0.8773
Epoch 8/20
54000/54000 [==============================] - 4s - loss: 0.7386 - acc: 0.8405 - val_loss: 0.6370 - val_acc: 0.8825
Epoch 9/20
54000/54000 [==============================] - 4s - loss: 0.6867 - acc: 0.8474 - val_loss: 0.5895 - val_acc: 0.8853
Epoch 10/20
54000/54000 [==============================] - 4s - loss: 0.6451 - acc: 0.8526 - val_loss: 0.5518 - val_acc: 0.8870
Epoch 11/20
54000/54000 [==============================] - 5s - loss: 0.6113 - acc: 0.8565 - val_loss: 0.5204 - val_acc: 0.8915
Epoch 12/20
54000/54000 [==============================] - 4s - loss: 0.5832 - acc: 0.8602 - val_loss: 0.4947 - val_acc: 0.8942
Epoch 13/20
54000/54000 [==============================] - 4s - loss: 0.5595 - acc: 0.8637 - val_loss: 0.4726 - val_acc: 0.8958
Epoch 14/20
54000/54000 [==============================] - 5s - loss: 0.5393 - acc: 0.8668 - val_loss: 0.4542 - val_acc: 0.8985
Epoch 15/20
54000/54000 [==============================] - 4s - loss: 0.5218 - acc: 0.8697 - val_loss: 0.4383 - val_acc: 0.8995
Epoch 16/20
54000/54000 [==============================] - 4s - loss: 0.5066 - acc: 0.8720 - val_loss: 0.4245 - val_acc: 0.8998
Epoch 17/20
54000/54000 [==============================] - 5s - loss: 0.4931 - acc: 0.8737 - val_loss: 0.4119 - val_acc: 0.9013
Epoch 18/20
54000/54000 [==============================] - 4s - loss: 0.4813 - acc: 0.8748 - val_loss: 0.4010 - val_acc: 0.9028
Epoch 19/20
54000/54000 [==============================] - 4s - loss: 0.4705 - acc: 0.8772 - val_loss: 0.3921 - val_acc: 0.9038
Epoch 20/20
54000/54000 [==============================] - 6s - loss: 0.4610 - acc: 0.8788 - val_loss: 0.3831 - val_acc: 0.9052
 9984/10000 [============================>.] - ETA: 0s
test accuracy :  0.8905

グラフ描画

以下のエラーが発生するので、対応が必要

エラー

Fontconfig warning: line 146: blank doesn't take any effect anymore. please remove it from your fonts.conf
/Users/dela/.pyenv/versions/3.6.1/lib/python3.6/site-packages/matplotlib/font_manager.py:280: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
  'Matplotlib is building the font cache using fc-list. '
Traceback (most recent call last):
  File "multi_layer_perceptron.py", line 5, in <module>
    import matplotlib.pyplot as plt
  File "/Users/dela/.pyenv/versions/3.6.1/lib/python3.6/site-packages/matplotlib/pyplot.py", line 115, in <module>
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
  File "/Users/dela/.pyenv/versions/3.6.1/lib/python3.6/site-packages/matplotlib/backends/__init__.py", line 32, in pylab_setup
    globals(),locals(),[backend_name],0)
  File "/Users/dela/.pyenv/versions/3.6.1/lib/python3.6/site-packages/matplotlib/backends/backend_macosx.py", line 19, in <module>
    from matplotlib.backends import _macosx
RuntimeError: Python is not installed as a framework. The Mac OS X backend will not be able to function correctly if Python is not installed as a framework. See the Python documentation for more information on installing Python as a framework on Mac OS X. Please either reinstall Python as a framework, or try one of the other backends. If you are using (Ana)Conda please install python.app and replace the use of 'python' with 'pythonw'. See 'Working with Matplotlib on OSX' in the Matplotlib FAQ for more information.

対応

$ python -c "import matplotlib;print(matplotlib.matplotlib_fname())"
$ vim /Users/dela/.pyenv/versions/3.6.1/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
line:38 #backend      : macosx
line:39 backend      : Tkagg

グラフ