Traceback (most recent call last): File "C:\Users\gutolinPC\Desktop\tensorflow.py", line 3, in from keras.datasets import mnist File "C:\Program Files\Python37\lib\site-packages\keras__init__.py", line 3,in from . import utils File "C:\Program Files\Python37\lib\site-packages\keras\utils__init__.py", line 6, in from . import conv_utils File "C:\Program Files\Python37\lib\site-packages\keras\utils\conv_utils.py", line 9, in from .. import backend as K File "C:\Program Files\Python37\lib\site-packages\keras\backend__init__.py", line 89, in from .tensorflow_backend import * File "C:\Program Files\Python37\lib\site- packages\keras\backend\tensorflow_backend.py", line 5, in import tensorflow as tf File "C:\Users\gutolinPC\Desktop\tensorflow.py", line 3, in from keras.datasets import mnist File "C:\Program Files\Python37\lib\site- packages\keras\datasets__init__.py", line 4, in from . import imdb File "C:\Program Files\Python37\lib\site-packages\keras\datasets\imdb.py", line 8, in from ..preprocessing.sequence import _remove_long_seq File "C:\Program Files\Python37\lib\site- packages\keras\preprocessing__init__.py", line 12, in from . import image File "C:\Program Files\Python37\lib\site- packages\keras\preprocessing\image.py", line 11, in from keras_preprocessing import image File "C:\Program Files\Python37\lib\site- packages\keras_preprocessing\image__init__.py", line 6, in from .dataframe_iterator import DataFrameIterator File "C:\Program Files\Python37\lib\site- packages\keras_preprocessing\image\dataframe_iterator.py", line 10, in from .iterator import BatchFromFilesMixin, Iterator File "C:\Program Files\Python37\lib\site-packages\keras_preprocessing\image\iterator.py", line 13, in IteratorType = get_keras_submodule('utils').Sequence AttributeError: module 'keras.utils' has no attribute 'Sequence'
Win 10
python 3.7.0
Keras 2.2.4
Keras-Applications 1.0.7
Keras-Preprocessing 1.0.9
tensorboard 1.13.1
tensorflow 1.13.1
tensorflow-estimator 1.13.0
Full code
import numpy
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense
from keras.utils import np_utils
numpy.random.seed(42)
(X_train, y_train), (X_test, y_test) = mnist.load_data()
X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)
X_train = X_train.astype('float32')
X_test = X_test.astype('float32')
X_train /= 255
X_test /= 255
Y_train = np_utils.to_categorical(y_train, 10)
Y_test = np_utils.to_categorical(y_test, 10)
model = Sequential()
model.add(Dense(800, input_dim=784, activation="relu",
kernel_initializer="normal"))
model.add(Dense(10, activation="softmax", kernel_initializer="normal"))
model.compile(loss="categorical_crossentropy", optimizer="SGD", metrics=["accuracy"])
print(model.summary())
model.fit(X_train, Y_train, batch_size=200, epochs=25, validation_split=0.2, verbose=2)
scores = model.evaluate(X_test, Y_test, verbose=0)
print("Точность работы на тестовых данных: %.2f%%" % (scores[1]*100))