关于神经网络：ImportError：没有名为’tensorflow.python’的模块

ImportError: No module named 'tensorflow.python'

在这里，我想运行以下代码来尝试使用python的神经网络：

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from __future__ import print_function
from keras.datasets import mnist from
keras.models import Sequential from
keras.layers import Activation, Dense
from keras.utils import np_utils
import tensorflow as tf

batch_size = 128 nb_classes = 10 nb_epoch = 12

#input image dimensions img_row, img_cols = 28, 28

#the data, Shuffled and split between train and test sets (X_train, y_train), (X_test, y_test) = mnist.load_data()

X_train = X_train.reshape(X_train.shape[0], img_rows * img_cols)

X_test = X_test.reshape(X_test.shape[0], img_row * img_cols)

X_train = X_train.astype('float32') X_test = X_test.astype('float32') X_train /= 255 X_text /= 255

print('X_train shape:', X_train.shape) print(X_train_shape[0], 'train samples') print(X_test_shape[0], 'test samples')

#convert class vectors to binary category

Y_train = np_utils.to_categorical(y_train, nb_classes)

Y_test = np_utils.to_categorical(y_test, nb_classes)

model = Sequential()

model.add(Dense(output_dim = 800, input_dim=X_train.shape[1])) model.add(Activation('sigmoid')) model.add(Dense(nb_classes)) model.add(Actiovation('softmax'))

model.compile(loss = 'categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) #crossentropy fungsi galat atau fungsi error dipakai kalo class biner

#model.fit(X_train, Y_train, batch_size=batch_size, nb_epoch = nb_poch, verbose=1, validation_data=(X_test, Y_test))

score = model.evaluate(X_test, Y_test, verbose = 0) print('Test Score : ', score[0]) print('Test Accuracy : ', score[1])

一开始，它必须安装Keras，并取得成功。但是，当第一次尝试运行代码时，错误是：

ImportError : No Moduled Name"tensorflow"

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然后我使用pip安装：

pip install tensorflow

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安装后，我尝试再次运行代码，收到另一条这样的消息：

ImportError : No Moduled Name"tensorflow.python"

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消息错误我对这个错误一无所知