jpeg画像をＡ．Ｂファイルにいれて画像データをpythonデータ型に変更しました。
次にCNNの実装を行いましたが下記エラーが出ました。解決の方法をお願いします。
コードとエラーは下記です。よろしくお願いします。

from keras.models import Sequential
from keras.layers.convolutional import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense
import numpy as np

# カテゴリの指定
categories = ["A","B"]
nb_classes = len(categories)
# 画像サイズを指定
image_w = 64 
image_h = 64

# データをロード --- (※1)
X_train, X_test, y_train, y_test = np.load("./image/data.npy")
# データを正規化する
X_train = X_train.astype("float32") / 256
X_test  = X_test.astype("float32")  / 256
print('X_train shape:', X_train.shape)

# モデルを構築 --- (※2)
model = Sequential()
model.add(Conv2D(32, 3, 3, padding='same', input_shape=X_train.shape[1:]))
model.add(Activation('relu'))
model.add(Conv2D(32,3))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Conv2D(64, 3, 3, padding='same'))
model.add(Activation('relu'))
model.add(Conv2D(64, 3, 3))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Flatten()) # --- (※3) 
model.add(Dense(512))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(nb_classes)) # ---- (*3a)
model.add(Activation('softmax'))

model.compile(loss='binary_crossentropy',
    optimizer='rmsprop',
    metrics=['accuracy'])

# モデルを訓練する --- (※4)
model.fit(X_train, y_train, batch_size=32, nb_epoch=50)

# モデルを評価する --- (※5)
score = model.evaluate(X_test, y_test)
print('loss=', score[0])
print('accuracy=', score[1])

ValueError                                Traceback (most recent call last)
<ipython-input-1-c8df3491520e> in <module>()
     20 # モデルを構築 --- (※2)
     21 model = Sequential()
---> 22 model.add(Conv2D(32, 3, 3, padding='same', input_shape=X_train.shape[1:]))
     23 model.add(Activation('relu'))
     24 model.add(Conv2D(32,3))

/anaconda/lib/python2.7/site-packages/keras/legacy/interfaces.pyc in wrapper(*args, **kwargs)
     32                 object_name = func.__name__
     33             if preprocessor:
---> 34                 args, kwargs, converted = preprocessor(args, kwargs)
     35             else:
     36                 converted = []

/anaconda/lib/python2.7/site-packages/keras/legacy/interfaces.pyc in conv2d_args_preprocessor(args, kwargs)
    276                 if kwd in kwargs:
    277                     raise ValueError(
--> 278                         'It seems that you are using the Keras 2 '
    279                         'and you are passing both `kernel_size` and `strides` '
    280                         'as integer positional arguments. For safety reasons, '

ValueError: It seems that you are using the Keras 2 and you are passing both `kernel_size` and `strides` as integer positional arguments. For safety reasons, this is disallowed. Pass `strides` as a keyword argument instead.