Keras致密層形狀不匹配

Question

我正在嘗試在Keras中創建一個多類分類器，但是在Dense層中出現了尺寸不匹配的情況。

MAX_SENT_LENGTH = 100
MAX_SENTS = 15
EMBEDDING_DIM = 100

x_train = data[:-nb_validation_samples]
y_train = labels[:-nb_validation_samples]
x_val = data[-nb_validation_samples:]
y_val = labels[-nb_validation_samples:]

embedding_layer = Embedding(len(word_index) + 1,
                            EMBEDDING_DIM,
                            weights=[embedding_matrix],
                            input_length=MAX_SENT_LENGTH,
                            trainable=True)

sentence_input = Input(shape=(MAX_SENT_LENGTH,), dtype='int32')
embedded_sequences = embedding_layer(sentence_input)
l_lstm = Bidirectional(LSTM(100))(embedded_sequences)
sentEncoder = Model(sentence_input, l_lstm)

review_input = Input(shape=(MAX_SENTS,MAX_SENT_LENGTH), dtype='int32')
review_encoder = TimeDistributed(sentEncoder)(review_input)
l_lstm_sent = Bidirectional(LSTM(100))(review_encoder)
preds = Dense(7, activation='softmax')(l_lstm_sent)
model = Model(review_input, preds)

model.compile(loss='sparse_categorical_crossentropy',
              optimizer='rmsprop',
              metrics=['acc'])

model.fit(x_train, y_train, validation_data=(x_val, y_val), 
            epochs=10, batch_size=50)

類標簽正確地轉換為1-hot向量，但是在嘗試擬合模型時，出現此不匹配錯誤：

('Shape of data tensor:', (5327, 15, 100))
('Shape of label tensor:', (5327, 7))
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_2 (InputLayer)         (None, 15, 100)           0         
_________________________________________________________________
time_distributed_1 (TimeDist (None, 15, 200)           351500    
_________________________________________________________________
bidirectional_2 (Bidirection (None, 200)               240800    
_________________________________________________________________
dense_1 (Dense)              (None, 7)                 1407       
=================================================================
Total params: 592,501
Trainable params: 592,501
Non-trainable params: 0
_________________________________________________________________
None
ValueError: Error when checking target: expected dense_1 to have 
              shape (None, 1) but got array with shape (4262, 7)

（無，1）維來自何處？如何解決此錯誤？

Answer 1

如果您的標簽是一次性編碼，則應使用loss='categorical_crossentropy'而不是loss='sparse_categorical_crossentropy' 。 'sparse_categorical_crossentropy'采用整數標簽，這就是為什么需要(None,1)維的原因。