我遇到了一个从未有过的奇怪问题：我建立了一个简单的模型：

merged = Concatenate()(model_inputs)
merged = Dense(50,activation='relu')(merged)
merged = Dense(30,activation='relu')(merged)
merged = Dense(1,activation='sigmoid')(merged)
model = Model(inputs=model_inputs,outputs=merged)

model_inputs是：

[<KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'CryoSleep')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'RoomService')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'Spa')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'VRDeck')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'Deck')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'Side')>,
 <KerasTensor: shape=(None, 1) dtype=float32 (created by layer 'AllSpending')>]

现在我编译并想适合模型：

X_Train_nn = create_input_values(X_Train)
y_Train_nn = create_label_values(y_Train)
X_Val_nn = create_input_values(X_Val)
y_Val_nn = create_label_values(y_Val)
model.compile(loss='binary_crossentropy',optimizer='nadam',metrics=['acc'])
model.fit(X_Train_nn,y_Train_nn,epochs=50,batch_size=32,validation_data=(X_Val_nn , y_Val_nn ),verbose=1)

该模型训练一个epoch，但在尝试验证时失败。如果我删除验证部分，它就能成功工作。否则，我会收到以下错误消息：

ValueError: Layer "model_1" expects 7 input(s), but it received 1 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, 7) dtype=float64>]

但事实并非如此。验证集的长度正确。为什么？我可以用X_Val_nn训练模型，它训练正确。我使用X_Val_nn和evaluate函数，它工作正常。
我甚至将训练集作为训练和验证数据传递，并显示相同的错误。因此，它能够使用X_Train_nn进行训练，但验证失败。并且它总是显示上面显示的错误消息。
你知道这是怎么回事吗？
PS：整个traceback如下：

Epoch 1/50

Exception ignored in: <function _xla_gc_callback at 0x7f601ee392d0>
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/jax/_src/lib/__init__.py", line 103, in _xla_gc_callback
    def _xla_gc_callback(*args):
KeyboardInterrupt: 

26/28 [==========================>...] - ETA: 0s - loss: 0.4339 - acc: 0.7849

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-195-c3a76520886a> in <cell line: 6>()
      4 y_Val_nn = create_label_values(y_Val)
      5 model.compile(loss='binary_crossentropy',optimizer='nadam',metrics=['acc'])
----> 6 model.fit(X_Val_nn,y_Val_nn,epochs=50,batch_size=32,validation_data=(range(100), y_Train_nn),verbose=1)

33 frames

/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     59     def error_handler(*args, **kwargs):
     60         if not tf.debugging.is_traceback_filtering_enabled():
---> 61             return fn(*args, **kwargs)
     62 
     63         filtered_tb = None

/usr/local/lib/python3.10/dist-packages/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)
   1727                             steps_per_execution=self._steps_per_execution,
   1728                         )
-> 1729                     val_logs = self.evaluate(
   1730                         x=val_x,
   1731                         y=val_y,

/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     59     def error_handler(*args, **kwargs):
     60         if not tf.debugging.is_traceback_filtering_enabled():
---> 61             return fn(*args, **kwargs)
     62 
     63         filtered_tb = None

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in evaluate(self, x, y, batch_size, verbose, sample_weight, steps, callbacks, max_queue_size, workers, use_multiprocessing, return_dict, **kwargs)
   2070                         ):
   2071                             callbacks.on_test_batch_begin(step)
-> 2072                             tmp_logs = self.test_function(iterator)
   2073                             if data_handler.should_sync:
   2074                                 context.async_wait()

/usr/local/lib/python3.10/dist-packages/tensorflow/python/util/traceback_utils.py in error_handler(*args, **kwargs)
    139     try:
    140       if not is_traceback_filtering_enabled():
--> 141         return fn(*args, **kwargs)
    142     except NameError:
    143       # In some very rare cases,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py in __call__(self, *args, **kwds)
    892 
    893       with OptionalXlaContext(self._jit_compile):
--> 894         result = self._call(*args, **kwds)
    895 
    896       new_tracing_count = self.experimental_get_tracing_count()

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py in _call(self, *args, **kwds)
    940       # This is the first call of __call__, so we have to initialize.
    941       initializers = []
--> 942       self._initialize(args, kwds, add_initializers_to=initializers)
    943     finally:
    944       # At this point we know that the initialization is complete (or less

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py in _initialize(self, args, kwds, add_initializers_to)
    761     self._graph_deleter = FunctionDeleter(self._lifted_initializer_graph)
    762     self._concrete_variable_creation_fn = (
--> 763         self._variable_creation_fn    # pylint: disable=protected-access
    764         ._get_concrete_function_internal_garbage_collected(
    765             *args, **kwds))

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/tracing_compiler.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
    169     """Returns a concrete function which cleans up its graph function."""
    170     with self._lock:
--> 171       concrete_function, _ = self._maybe_define_concrete_function(args, kwargs)
    172     return concrete_function
    173 

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/tracing_compiler.py in _maybe_define_concrete_function(self, args, kwargs)
    164       kwargs = {}
    165 
--> 166     return self._maybe_define_function(args, kwargs)
    167 
    168   def _get_concrete_function_internal_garbage_collected(self, *args, **kwargs):

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/tracing_compiler.py in _maybe_define_function(self, args, kwargs)
    394           kwargs = placeholder_bound_args.kwargs
    395 
--> 396           concrete_function = self._create_concrete_function(
    397               args, kwargs, func_graph)
    398 

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/tracing_compiler.py in _create_concrete_function(self, args, kwargs, func_graph)
    298 
    299     concrete_function = monomorphic_function.ConcreteFunction(
--> 300         func_graph_module.func_graph_from_py_func(
    301             self._name,
    302             self._python_function,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, create_placeholders, acd_record_initial_resource_uses)
   1212         _, original_func = tf_decorator.unwrap(python_func)
   1213 
-> 1214       func_outputs = python_func(*func_args, **func_kwargs)
   1215 
   1216       # invariant: `func_outputs` contains only Tensors, CompositeTensors,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py in wrapped_fn(*args, **kwds)
    665         # the function a weak reference to itself to avoid a reference cycle.
    666         with OptionalXlaContext(compile_with_xla):
--> 667           out = weak_wrapped_fn().__wrapped__(*args, **kwds)
    668         return out
    669 

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs)
   1198           except Exception as e:  # pylint:disable=broad-except
   1199             if hasattr(e, "ag_error_metadata"):
-> 1200               raise e.ag_error_metadata.to_exception(e)
   1201             else:
   1202               raise

/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs)
   1187           # TODO(mdan): Push this block higher in tf.function's call stack.
   1188           try:
-> 1189             return autograph.converted_call(
   1190                 original_func,
   1191                 args,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in converted_call(f, args, kwargs, caller_fn_scope, options)
    437     try:
    438       if kwargs is not None:
--> 439         result = converted_f(*effective_args, **kwargs)
    440       else:
    441         result = converted_f(*effective_args)

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in tf__test_function(iterator)
     13                 try:
     14                     do_return = True
---> 15                     retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
     16                 except:
     17                     do_return = False

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in converted_call(f, args, kwargs, caller_fn_scope, options)
    375 
    376   if not options.user_requested and conversion.is_allowlisted(f):
--> 377     return _call_unconverted(f, args, kwargs, options)
    378 
    379   # internal_convert_user_code is for example turned off when issuing a dynamic

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in _call_unconverted(f, args, kwargs, options, update_cache)
    457   if kwargs is not None:
    458     return f(*args, **kwargs)
--> 459   return f(*args)
    460 
    461 

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in step_function(model, iterator)
   1834 
   1835             data = next(iterator)
-> 1836             outputs = model.distribute_strategy.run(run_step, args=(data,))
   1837             outputs = reduce_per_replica(
   1838                 outputs,

/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py in run(***failed resolving arguments***)
   1314       fn = autograph.tf_convert(
   1315           fn, autograph_ctx.control_status_ctx(), convert_by_default=False)
-> 1316       return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
   1317 
   1318   def reduce(self, reduce_op, value, axis):

/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py in call_for_each_replica(self, fn, args, kwargs)
   2893       kwargs = {}
   2894     with self._container_strategy().scope():
-> 2895       return self._call_for_each_replica(fn, args, kwargs)
   2896 
   2897   def _call_for_each_replica(self, fn, args, kwargs):

/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py in _call_for_each_replica(self, fn, args, kwargs)
   3694   def _call_for_each_replica(self, fn, args, kwargs):
   3695     with ReplicaContext(self._container_strategy(), replica_id_in_sync_group=0):
-> 3696       return fn(*args, **kwargs)
   3697 
   3698   def _reduce_to(self, reduce_op, value, destinations, options):

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
    687       try:
    688         with conversion_ctx:
--> 689           return converted_call(f, args, kwargs, options=options)
    690       except Exception as e:  # pylint:disable=broad-except
    691         if hasattr(e, 'ag_error_metadata'):

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in converted_call(f, args, kwargs, caller_fn_scope, options)
    375 
    376   if not options.user_requested and conversion.is_allowlisted(f):
--> 377     return _call_unconverted(f, args, kwargs, options)
    378 
    379   # internal_convert_user_code is for example turned off when issuing a dynamic

/usr/local/lib/python3.10/dist-packages/tensorflow/python/autograph/impl/api.py in _call_unconverted(f, args, kwargs, options, update_cache)
    456 
    457   if kwargs is not None:
--> 458     return f(*args, **kwargs)
    459   return f(*args)
    460 

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in run_step(data)
   1822 
   1823             def run_step(data):
-> 1824                 outputs = model.test_step(data)
   1825                 # Ensure counter is updated only if `test_step` succeeds.
   1826                 with tf.control_dependencies(_minimum_control_deps(outputs)):

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in test_step(self, data)
   1786         x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data)
   1787 
-> 1788         y_pred = self(x, training=False)
   1789         # Updates stateful loss metrics.
   1790         self.compute_loss(x, y, y_pred, sample_weight)

/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     59     def error_handler(*args, **kwargs):
     60         if not tf.debugging.is_traceback_filtering_enabled():
---> 61             return fn(*args, **kwargs)
     62 
     63         filtered_tb = None

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in __call__(self, *args, **kwargs)
    556             layout_map_lib._map_subclass_model_variable(self, self._layout_map)
    557 
--> 558         return super().__call__(*args, **kwargs)
    559 
    560     @doc_controls.doc_in_current_and_subclasses

/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     59     def error_handler(*args, **kwargs):
     60         if not tf.debugging.is_traceback_filtering_enabled():
---> 61             return fn(*args, **kwargs)
     62 
     63         filtered_tb = None

/usr/local/lib/python3.10/dist-packages/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
   1110         ):
   1111 
-> 1112             input_spec.assert_input_compatibility(
   1113                 self.input_spec, inputs, self.name
   1114             )

/usr/local/lib/python3.10/dist-packages/keras/engine/input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
    217 
    218     if len(inputs) != len(input_spec):
--> 219         raise ValueError(
    220             f'Layer "{layer_name}" expects {len(input_spec)} input(s),'
    221             f" but it received {len(inputs)} input tensors. "

ValueError: in user code:

    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1852, in test_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1836, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 1316, in run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 2895, in call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 3696, in _call_for_each_replica
        return fn(*args, **kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1824, in run_step  **
        outputs = model.test_step(data)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1788, in test_step
        y_pred = self(x, training=False)
    File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 61, in error_handler
        return fn(*args, **kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 558, in __call__
        return super().__call__(*args, **kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 61, in error_handler
        return fn(*args, **kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/base_layer.py", line 1112, in __call__
        input_spec.assert_input_compatibility(
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/input_spec.py", line 219, in assert_input_compatibility
        raise ValueError(

    ValueError: Layer "model_1" expects 7 input(s), but it received 1 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, 7) dtype=float64>]