ValueError: Input 0 is incompatible with layer model

[Huii]

I'm attempting to use your work in my time series classsification pipeline. First of all: Thank you very much for providing the source code under an open source license!

I'm trying to train the model, save it to disk and load it again from another method. This is my code:

x_trainScaledNPArray = np.array(x_trainScaled)
x_testScaledNPArray = np.array(x_testScaled)
y_trainNPArray = np.array(y_train)
y_testNPArray = np.array(y_test)

batch_size = 16
nb_epochs = 1 # 2000
verbose = True
    
pathToModelCheckpoints = 'myPath/'
pathToModel = 'myPathToModel/'
reduce_lr = keras.callbacks.ReduceLROnPlateau(monitor='loss', factor=0.5, patience=50,min_lr=0.0001)
# model checkpoint
model_checkpoint = keras.callbacks.ModelCheckpoint(filepath=pathToModelCheckpoints, monitor='loss',save_best_only=True)
callbacks=[reduce_lr,model_checkpoint]
input_shape = x_trainScaledNPArray.shape
nb_classes = len(np.unique(y_train))
model = TransferLearningMain.build_model(input_shape, nb_classes, pre_model=None)
TransferLearningMain.train(x_trainScaledNPArray,y_trainNPArray,x_testScaledNPArray,y_testNPArray,batch_size,verbose,nb_epochs,callbacks,pathToModelCheckpoints,pre_model=None)
model.save(pathToModel)

print(x_trainScaledNPArray.shape)
print(x_testScaledNPArray.shape)

model = keras.models.load_model(model_path)
y_pred = model.predict(x_test,batch_size=4)

The output is:

(18287, 2048)
(347, 2048)

Traceback (most recent call last):
 [...]
    y_pred = model.predict(x_test,batch_size=4)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py", line 1727, in predict
    tmp_batch_outputs = self.predict_function(iterator)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\def_function.py", line 889, in __call__
    result = self._call(*args, **kwds)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\def_function.py", line 933, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\def_function.py", line 764, in _initialize
    *args, **kwds))
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\function.py", line 3050, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\function.py", line 3444, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\function.py", line 3289, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\framework\func_graph.py", line 999, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\eager\def_function.py", line 672, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\framework\func_graph.py", line 986, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py:1569 predict_function  *
        return step_function(self, iterator)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py:1559 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\distribute\distribute_lib.py:1285 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\distribute\distribute_lib.py:2833 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\distribute\distribute_lib.py:3608 _call_for_each_replica
        return fn(*args, **kwargs)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py:1552 run_step  **
        outputs = model.predict_step(data)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\training.py:1525 predict_step
        return self(x, training=False)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\base_layer.py:1013 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
    C:\Users\myUser\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\engine\input_spec.py:270 assert_input_compatibility
        ', found shape=' + display_shape(x.shape))

    ValueError: Input 0 is incompatible with layer model: expected shape=(None, 18287, 2048), found shape=(None, 2048)

Any ideas to solve this issue are highly appreciated.