ظهور الخطأ ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type list). أثناء محاولة تدريب شبكة عصبية

أحاول تدريب شبكة عصبية لتحليل المشاعر، لكن يظهر لي الخطأ التالي:

from keras.datasets import imdb
from keras.layers import Embedding, SimpleRNN
from keras.models import Sequential
(input_train, y_train), (input_test, y_test) = imdb.load_data(
num_words=max_features)
print(len(input_train), 'train sequences')
print(len(input_test), 'test sequences')
print('input_train shape:', input_train.shape)
print('input_test shape:', input_test.shape)
from keras.layers import Dense
model = Sequential()
model.add(Embedding(10000, 32))
model.add(SimpleRNN(32))
model.add(Dense(1, activation='sigmoid'))
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['acc'])
history = model.fit(input_train, y_train,
epochs=2,
batch_size=32,
validation_split=0.2)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-53-0d042e98c73b> in <module>
     17 epochs=2,
     18 batch_size=32,
---> 19 validation_split=0.2)

~\anaconda3\lib\site-packages\tensorflow\python\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, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
   1062           use_multiprocessing=use_multiprocessing,
   1063           model=self,
-> 1064           steps_per_execution=self._steps_per_execution)
   1065 
   1066       # Container that configures and calls `tf.keras.Callback`s.

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in __init__(self, x, y, sample_weight, batch_size, steps_per_epoch, initial_epoch, epochs, shuffle, class_weight, max_queue_size, workers, use_multiprocessing, model, steps_per_execution)
   1110         use_multiprocessing=use_multiprocessing,
   1111         distribution_strategy=ds_context.get_strategy(),
-> 1112         model=model)
   1113 
   1114     strategy = ds_context.get_strategy()

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in __init__(self, x, y, sample_weights, sample_weight_modes, batch_size, epochs, steps, shuffle, **kwargs)
    261                **kwargs):
    262     super(TensorLikeDataAdapter, self).__init__(x, y, **kwargs)
--> 263     x, y, sample_weights = _process_tensorlike((x, y, sample_weights))
    264     sample_weight_modes = broadcast_sample_weight_modes(
    265         sample_weights, sample_weight_modes)

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in _process_tensorlike(inputs)
   1014     return x
   1015 
-> 1016   inputs = nest.map_structure(_convert_numpy_and_scipy, inputs)
   1017   return nest.list_to_tuple(inputs)
   1018 

~\anaconda3\lib\site-packages\tensorflow\python\util\nest.py in map_structure(func, *structure, **kwargs)
    657 
    658   return pack_sequence_as(
--> 659       structure[0], [func(*x) for x in entries],
    660       expand_composites=expand_composites)
    661 

~\anaconda3\lib\site-packages\tensorflow\python\util\nest.py in <listcomp>(.0)
    657 
    658   return pack_sequence_as(
--> 659       structure[0], [func(*x) for x in entries],
    660       expand_composites=expand_composites)
    661 

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py in _convert_numpy_and_scipy(x)
   1009       if issubclass(x.dtype.type, np.floating):
   1010         dtype = backend.floatx()
-> 1011       return ops.convert_to_tensor_v2_with_dispatch(x, dtype=dtype)
   1012     elif scipy_sparse and scipy_sparse.issparse(x):
   1013       return _scipy_sparse_to_sparse_tensor(x)

~\anaconda3\lib\site-packages\tensorflow\python\util\dispatch.py in wrapper(*args, **kwargs)
    199     """Call target, and fall back on dispatchers if there is a TypeError."""
    200     try:
--> 201       return target(*args, **kwargs)
    202     except (TypeError, ValueError):
    203       # Note: convert_to_eager_tensor currently raises a ValueError, not a

~\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in convert_to_tensor_v2_with_dispatch(value, dtype, dtype_hint, name)
   1403   """
   1404   return convert_to_tensor_v2(
-> 1405       value, dtype=dtype, dtype_hint=dtype_hint, name=name)
   1406 
   1407 

~\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in convert_to_tensor_v2(value, dtype, dtype_hint, name)
   1413       name=name,
   1414       preferred_dtype=dtype_hint,
-> 1415       as_ref=False)
   1416 
   1417 

~\anaconda3\lib\site-packages\tensorflow\python\profiler\trace.py in wrapped(*args, **kwargs)
    161         with Trace(trace_name, **trace_kwargs):
    162           return func(*args, **kwargs)
--> 163       return func(*args, **kwargs)
    164 
    165     return wrapped

~\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
   1538 
   1539     if ret is None:
-> 1540       ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
   1541 
   1542     if ret is NotImplemented:

~\anaconda3\lib\site-packages\tensorflow\python\framework\tensor_conversion_registry.py in _default_conversion_function(***failed resolving arguments***)
     50 def _default_conversion_function(value, dtype, name, as_ref):
     51   del as_ref  # Unused.
---> 52   return constant_op.constant(value, dtype, name=name)
     53 
     54 

~\anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in constant(value, dtype, shape, name)
    263   """
    264   return _constant_impl(value, dtype, shape, name, verify_shape=False,
--> 265                         allow_broadcast=True)
    266 
    267 

~\anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
    274       with trace.Trace("tf.constant"):
    275         return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
--> 276     return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
    277 
    278   g = ops.get_default_graph()

~\anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
    299 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
    300   """Implementation of eager constant."""
--> 301   t = convert_to_eager_tensor(value, ctx, dtype)
    302   if shape is None:
    303     return t

~\anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
     96       dtype = dtypes.as_dtype(dtype).as_datatype_enum
     97   ctx.ensure_initialized()
---> 98   return ops.EagerTensor(value, ctx.device_name, dtype)
     99 
    100 

ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type list).