Max_Title_Length= 50;
vector_size= 100;
Max_Content_Length= 50;
input_title = Input(shape = (Max_Title_Length,vector_size,), name = 'input_title')
input_content = Input(shape = (Max_Content_Length,vector_size,), name = 'input_content')
#x = Bidirectional(GRU(units = 100, return_sequences = True, kernel_initializer = keras.initializers.lecun_normal(seed = None), unit_forget_bias = True))(input_title)
x = Bidirectional(GRU(10, return_sequences=True))(input_title)
x_attention = Hierarchical_Attention(100)(x)
#y = Bidirectional(LSTM(units = 100, return_sequences = True, kernel_initializer = keras.initializers.lecun_normal(seed = None), unit_forget_bias = True))(input_content)
y = Bidirectional(GRU(10, return_sequences=True))(input_content)
y_attention = Hierarchical_Attention(100)(y)
z = concatenate([x_attention,y_attention])
z = Dense(units = 512, activation = 'relu')(z)
z = Dropout(0.2)(z)
z = Dense(units = 256, activation = 'relu')(z)
z = Dropout(0.2)(z)
z = Dense(units = 128, activation = 'relu')(z)
z = Dropout(0.2)(z)
z = Dense(units = 50, activation = 'relu')(z)
z = Dropout(0.2)(z)
z = Dense(units = 10, activation = 'relu')(z)
z = Dropout(0.2)(z)
output = Dense(units = 2, activation = 'softmax')(z)
model = Model(inputs = [input_title,input_content], outputs = output)
model.compile(optimizer= 'adam', loss= 'categorical_crossentropy', metrics=['acc'])
model.summary()
model.fit([X_train,X_train1], Y_train, batch_size=32, epochs=10)
Epoch 1/10
WARNING:tensorflow:Model was constructed with shape (None, 50, 100) for input KerasTensor(type_spec=TensorSpec(shape=(None, 50, 100), dtype=tf.float32, name='input_title'), name='input_title', description="created by layer 'input_title'"), but it was called on an input with incompatible shape (None, 50).
WARNING:tensorflow:Model was constructed with shape (None, 50, 100) for input KerasTensor(type_spec=TensorSpec(shape=(None, 50, 100), dtype=tf.float32, name='input_content'), name='input_content', description="created by layer 'input_content'"), but it was called on an input with incompatible shape (None, 50).
ValueError Traceback (most recent call last)
<ipython-input-293-42319c594972> in <module>()
----> 1 model.fit(X_train1,Y_train1,validation_data=(X_test1,Y_test1),epochs=10, batch_size=64)
9 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
975 except Exception as e: # pylint:disable=broad-except
976 if hasattr(e, "ag_error_metadata"):
--> 977 raise e.ag_error_metadata.to_exception(e)
978 else:
979 raise
ValueError: in user code:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:805 train_function *
return step_function(self, iterator)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:795 step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:1259 run
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2730 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica
return fn(*args, **kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:788 run_step **
outputs = model.train_step(data)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:754 train_step
y_pred = self(x, training=True)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py:998 __call__
input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/input_spec.py:207 assert_input_compatibility
' input tensors. Inputs received: ' + str(inputs))
ValueError: Layer model_18 expects 2 input(s), but it received 1 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, 50) dtype=int32>]
question from:
https://stackoverflow.com/questions/66048309/valueerror-layer-model-18-expects-2-inputs-but-it-received-1-input-tensors