报错TypeError:怎么解决？具体报错信息如下

Question

在运行以下代码时

model = load_model('unet_brain_mri_seg.hdf5', custom_objects={'dice_coef_loss': dice_coef_loss, 'iou': iou, 'dice_coef': dice_coef})


test_gen = train_generator(df_test, BATCH_SIZE,
                           dict(),
                           target_size=(im_height, im_width))
results = model.evaluate(test_gen, steps=len(df_test) / BATCH_SIZE)
print("Test lost: ",results[0])
print("Test IOU: ",results[1])
print("Test Dice Coefficent: ",results[2])

报错

TypeError                                 Traceback (most recent call last)
<ipython-input-23-9684583ed357> in <module>()
      2                                 dict(),
      3                                 target_size=(im_height, im_width))
----> 4 results = model.evaluate(test_gen, steps=len(df_test) / BATCH_SIZE)
      5 print("Test lost: ",results[0])
      6 print("Test IOU: ",results[1])

9 frames
/usr/local/lib/python3.7/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

TypeError: in user code:

    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1233 test_function  *
        return step_function(self, iterator)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1224 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /usr/local/lib/python3.7/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/python3.7/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/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica
        return fn(*args, **kwargs)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:1219 run_step  **
        with ops.control_dependencies(_minimum_control_deps(outputs)):
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py:2793 _minimum_control_deps
        outputs = nest.flatten(outputs, expand_composites=True)
    /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py:341 flatten
        return _pywrap_utils.Flatten(structure, expand_composites)

    TypeError: '<' not supported between instances of 'function' and 'str'

但是在model.evaluate之前运行model.fit没有报错，具体代码如下

EPOCHS = 150
BATCH_SIZE = 32
learning_rate = 1e-4


train_generator_args = dict(rotation_range=0.2,
                            width_shift_range=0.05,
                            height_shift_range=0.05,
                            shear_range=0.05,
                            zoom_range=0.05,
                            horizontal_flip=True,
                            fill_mode='nearest')
train_gen = train_generator(df_train, BATCH_SIZE,
                                train_generator_args,
                                target_size=(im_height, im_width))
    
test_gener = train_generator(df_val, BATCH_SIZE,
                                dict(),
                                target_size=(im_height, im_width))
    
model = unet(input_size=(im_height, im_width, 3))



decay_rate = learning_rate / EPOCHS
opt = Adam(lr=learning_rate, beta_1=0.9, beta_2=0.999, epsilon=None, decay=decay_rate, amsgrad=False)
model.compile(optimizer=opt, loss=dice_coef_loss, metrics=["binary_accuracy", iou, dice_coef])

callbacks = [ModelCheckpoint('unet_brain_mri_seg.hdf5', verbose=1, save_best_only=True)]

history = model.fit(train_gen,
                    steps_per_epoch=len(df_train) / BATCH_SIZE, 
                    epochs=EPOCHS, 
                    callbacks=callbacks,
                    validation_data = test_gener,
                    validation_steps=len(df_val) / BATCH_SIZE)

Answer 1

数据类型错误，检查一下BATCH_SIZE是不是int类型，如果是的话，再使用steps= int(len(df_test) / BATCH_SIZE),转换数据类型试试看。