python - Invalid array shape with neural network using Keras?

Question

Currently studying the 'Deep Learning with Python' book by Francios Chollet. I am very new to this and I am getting this error code despite following his code verbatim. Can anyone interpret the error message or what needs to be done to solve it? Any help would be greatly appreciated!

from keras.datasets import imdb
import numpy as np
from keras import models
from keras import layers

(train_data, train_labels), (test_data, test_labels) =
imdb.load_data(num_words=10000)


def vectorize_sequences(sequences, dimension=10000):
    results = np.zeros((len(sequences), dimension))
    for i, sequence in enumerate(sequences):
       results[i, sequence] = 1. 
    return results
x_train = vectorize_sequences(train_data)
y_train = vectorize_sequences(test_data)
x_train = np.asarray(train_labels).astype('float32')
y_test = np.asarray(test_labels).astype('float32')


model = models.Sequential()
model.add(layers.Dense(16, activation='relu', input_shape=(10000,)))
model.add(layers.Dense(16, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))

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

model.fit(x_train, y_train, epochs=4, batch_size=512)
results = model.evaluate(x_test, y_test)

Edit: Here is an image of the error code that I am getting:

Answer 1

I tested your Code and found, that x_test was not defined. I think you meant to vectorize it as follows. With this Code it worked:

x_train = vectorize_sequences(train_data)
x_test = vectorize_sequences(test_data)
y_train = np.asarray(train_labels).astype('float32')
y_test = np.asarray(test_labels).astype('float32')