我在代码结尾处遇到麻烦，如下所示。 我想该错误消息表示数据的形状，但我不知道。
from keras.layers import SimpleRNN, Embedding, Dense, LSTM
from keras.models import Sequential
from keras.preprocessing.sequence import pad_sequences
vocab_size = len(word_index)+1 # number of words
max_len = 157
data = pad_sequences(x, maxlen=max_len)
print("data shape: ", data.shape)
data shape: (3012, 157)
data
array([[ 0, 0, 0, ..., 51, 10, 36],
[ 0, 0, 0, ..., 1129, 4994, 920],
[ 0, 0, 0, ..., 5004, 5005, 364],
...,
[ 0, 0, 0, ..., 17364, 17365, 17366],
[ 0, 0, 0, ..., 114, 176, 54],
[ 0, 0, 0, ..., 17371, 17372, 1227]])
x_test = data[n_of_train:]
y_test = y[n_of_train:]
x_train = data[:n_of_train]
y_train = y[:n_of_train]
print(x_test.shape)
print(y_test.shape)
print(x_train.shape)
print(y_train.shape)
print(type(x_test))
print(type(y_test))
print(type(x_train))
print(type(y_train))
(603, 157)
(603,)
(2409, 157)
(2409,)
<class 'numpy.ndarray'>
<class 'pandas.core.series.Series'>
<class 'numpy.ndarray'>
<class 'pandas.core.series.Series'>
model = Sequential()
model.add(Embedding(vocab_size,32))
model.add(SimpleRNN(32))
# model.add(Dense(7, input_dim=3, init='uniform', activation='softmax'))
model.add(Dense(5, activation='softmax'))
model.compile(optimizer='adam',loss='categorical_crossentropy', metrics=['accuracy'])
history = model.fit(x_train, y_train, epochs=2, batch_size=32, validation_data=(x_test,y_test),verbose=1)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-20-1b1364437bdb> in <module>
----> 1 history = model.fit(x_train, y_train, epochs=2, batch_size=32, validation_data=(x_test,y_test),verbose=1)
C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
950 sample_weight=sample_weight,
951 class_weight=class_weight,
--> 952 batch_size=batch_size)
953 # Prepare validation data.
954 do_validation = False
C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, check_array_lengths, batch_size)
787 feed_output_shapes,
788 check_batch_axis=False, # Don't enforce the batch size.
--> 789 exception_prefix='target')
790
791 # Generate sample-wise weight values given the `sample_weight` and
C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training_utils.py in standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)
136 ': expected ' + names[i] + ' to have shape ' +
137 str(shape) + ' but got array with shape ' +
--> 138 str(data_shape))
139 return data
140
ValueError: Error when checking target: expected dense_1 to have shape (5,) but got array with shape (1,)