AttributeError: 'NoneType' object has no attribute 'dtype'

 

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/tmp/ipykernel_23207/4182898696.py in <module>
     45                                                  monitor='loss')  # 由于 
     46 
---> 47 history = model.fit(x_train, y_train, batch_size=32, epochs=100, callbacks=[cp_callback])
     48 
     49 model.summary()

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/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_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
    725         max_queue_size=max_queue_size,
    726         workers=workers,
--> 727         use_multiprocessing=use_multiprocessing)
    728 
    729   def evaluate(self,

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_arrays.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, **kwargs)
    641         steps=steps_per_epoch,
    642         validation_split=validation_split,
--> 643         shuffle=shuffle)
    644 
    645     if validation_data:

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, batch_size, check_steps, steps_name, steps, validation_split, shuffle, extract_tensors_from_dataset)
   2430     is_compile_called = False
   2431     if not self._is_compiled and self.optimizer:
-> 2432       self._compile_from_inputs(all_inputs, y_input, x, y)
   2433       is_compile_called = True
   2434 

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py in _compile_from_inputs(self, all_inputs, target, orig_inputs, orig_target)
   2665         sample_weight_mode=self.sample_weight_mode,
   2666         run_eagerly=self.run_eagerly,
-> 2667         experimental_run_tf_function=self._experimental_run_tf_function)
   2668 
   2669   # TODO(omalleyt): Consider changing to a more descriptive function name.

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
    455     self._self_setattr_tracking = False  # pylint: disable=protected-access
    456     try:
--> 457       result = method(self, *args, **kwargs)
    458     finally:
    459       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py in compile(self, optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors, distribute, **kwargs)
    341                           self.loss_functions, target_tensors):
    342       endpoint = _TrainingEndpoint(o, n, l)
--> 343       endpoint.create_training_target(t, run_eagerly=self.run_eagerly)
    344       self._training_endpoints.append(endpoint)
    345 

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py in create_training_target(self, target, run_eagerly)
   3060       if target is None:
   3061         target_dtype = losses.LABEL_DTYPES_FOR_LOSSES.get(
-> 3062             self.loss_fn, K.dtype(self.output))
   3063 
   3064         target = K.placeholder(

/home/software/anaconda3/envs/tf115/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py in dtype(x)
   1241   ```
   1242   """
-> 1243   return x.dtype.base_dtype.name
   1244 
   1245 

AttributeError: 'NoneType' object has no attribute 'dtype'
AttributeError：“ NoneType”对象没有属性“ dtype”

 可能是Numpy和TensorFlow兼容性问题。

 目前使用的是TensorFlow2.1版本，于是将Numpy版本修改为1.18.5，发现问题得到解决