UnimplementedError Traceback(最近一次调用最后一次)
UnimplementedError:发现 2 个根本错误。(0) 未实现:不支持将字符串转换为浮点数 [[node functional_11/Cast (defined at :1)]] (1) 已取消:函数在启动前已取消 0 次成功操作。0 派生错误被忽略。[操作:__inference_train_function_47870]
函数调用栈:train_function -> train_function
这是我的代码。知道我在做什么错吗?
lstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(lstm_units, dropout=0.2, recurrent_dropout=0.2))
# loading our matrix
emb = tf.keras.layers.Embedding(max_words, embedding_dim, input_length=300, weights=[embedding_matrix],trainable=False)
input1 = tf.keras.Input(shape=(300,))
e1 = emb(input1)
x1 = lstm_layer(e1)
input2 = tf.keras.Input(shape=(300,))
e2 = emb(input2)
x2 = lstm_layer(e2)
mhd = lambda x: tf.keras.backend.abs(x[0] - x[1])
merged = tf.keras.layers.Lambda(function=mhd, output_shape=lambda x: x[0],name='L1_distance')([x1, x2])
preds = tf.keras.layers.Dense(1, activation='sigmoid')(merged)
model = tf.keras.Model(inputs=[input1, input2], outputs=preds)
model.compile(loss='mse', optimizer='adam')
model.summary()
history = model.fit([X_train[:,0], X_train[:,1]], y_train, epochs=100, validation_data=([X_valid[:,0], X_valid[:,1]], y_valid))```