数据分批读取训练问题

[shuDaoNan9]

大数据场景下全量加载到显卡训练显然不现实，鄙人在TF2.4.0中试了下将数据处理好后分批给到DeepMatch模型，发现有以下问题：
1. 通过tf.data.Dataset.from_tensor_slices将数据分批后训练，却发现在tf.compat.v1.disable_eager_execution()后无法使用，报错如下：
D:\Anaconda3\envs\TF2GPU\lib\site-packages\tensorflow\python\keras\backend.py:434: UserWarning: tf.keras.backend.set_learning_phase is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the training argument of the __call__ method of your layer or model.
warnings.warn('tf.keras.backend.set_learning_phase is deprecated and '
Traceback (most recent call last):
File "F:/python/DeepMatch-master/examples/bp_mind_emr_distr_index_batch.py", line 77, in
for batch_train_model_input,batch_train_label in tf.data.Dataset.from_tensor_slices((test_model_input)).batch(2): #.shuffle(1000):
File "D:\Anaconda3\envs\TF2GPU\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 424, in iter
raise RuntimeError("iter() is only supported inside of tf.function "
RuntimeError: iter() is only supported inside of tf.function or when eager execution is enabled.

2. 通过继承class DataGenerator(keras.utils.Sequence)方式分批读取数据，目前跑单机模式，CPU和GPU利用率上不去

3. 然后尝试了generate_arrays_from_file(data,batch_size=256)分批读取训练，Linux服务器单机正常运行，但CPU和GPU利用率上不去，但win10 GPU运行不行（WIN10报错，后来了解到win10上不能workers=4,use_multiprocessing=True这样多进程）

然后我又看了下DeepCtr那边的code写法，几乎也都是全量数据加载的，没看到分批给到GPU训练，不知路过的各位如何解决此类问题的？

谢谢！