<commit_before>from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Convolution2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense


# dimensions of our images.
img_width, img_height = 256, 256

train_data_dir = 'Data/big_pictures/train'
validation_data_dir = 'Data/big_pictures/validation'
nb_train_samples = 50
nb_validation_samples = 50
nb_epoch = 50


model = Sequential()
model.add(Convolution2D(32, 3, 3, input_shape=(3, img_width, img_height)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
<commit_msg>Test with Anaconda, Python 3.5 and Keras 2<commit_after>from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Convolution2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense
#bellow two line using for anaconda
#tested with CPU
from keras import backend as K
K.set_image_dim_ordering('th')

# dimensions of our images.
img_width, img_height = 256, 256

train_data_dir = 'Data/big_pictures/train'
validation_data_dir = 'Data/big_pictures/validation'
nb_train_samples = 50
nb_validation_samples = 50
nb_epoch = 50


model = Sequential()
model.add(Convolution2D(32, 3, 3, input_shape=(3, img_width, img_height)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

{'fraction_non_alphanumeric': 0.09520400858983537, 'fraction_numerical': 0.03507516105941303, 'mean_word_length': 6.988571428571428, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '4772002', 'n_tokens_mistral': 512, 'n_tokens_neox': 468, 'n_words': 121}