我想利用多个GPU使用 tf.distribute.MirroredStrategy() 方法。
下面是我的代码片段：

# Imports

import tensorflow as tf
import model # Module of functions for building the model

# Check GPU availability

devices = tf.config.list_physical_devices('GPU')
print('Num GPUs:', len(devices))
print(devices)

# Prepare dataset (Xtrain/Xtest are Numpy arrays with shape, (None, 600, 23))

Xtrain, Xtest = models.get_dataset() 

# Datasets as tf.data.dataset objects

batch_size = 256
train_dataset = tf.data.Dataset.from_tensor_slices((Xtrain, Xtrain)).batch(batch_size)
test_dataset = tf.data.Dataset.from_tensor_slices((Xtest, Xtest)).batch(batch_size)

# Build model for synchronous multi-GPU training

strategy = tf.distribute.MirroredStrategy()
print('Number of devices in strategy: {}'.format(strategy.num_replicas_in_sync))

with strategy.scope():
    # Define model hyperparameters                                                                                                              
    input_dim = Xtrain.shape[1:]
    clipnorm = 100
    learning_rate = 1e-4
    latent_dim = 50
    dropout = 0.33

    # Compile model                                                                                                                       
    encoder = models.Encoder(input_dim=input_dim, latent_dim=latent_dim,
                             dropout=dropout)
    decoder = models.Decoder(input_dim=input_dim, latent_dim=latent_dim,
                             dropout=dropout)
    m1vae = models.ProtVAE(encoder=encoder, decoder=decoder, name='m1vae')
    m1vae.compileVAE(input_dim=input_dim, latent_dim=latent_dim,
                     learning_rate=learning_rate, clipnorm=clipnorm)

运行代码时，if在编译步骤中失败，并显示以下错误消息：

Num GPUs: 2

[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:1', device_type='GPU')]

Number of devices in strategy: 2

Traceback (most recent call last):
  File "work_python_scripts/test_m1vae_gpu.py", line 114, in <module>
    m1vae.compileVAE(input_dim=input_dim, latent_dim=latent_dim, learning_rate=learning_rate,
  File "/home/jgado/condaenvs/tfgpu/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py", line 332, in __ex\
it__
    _pop_per_thread_mode()
  File "/home/jgado/condaenvs/tfgpu/lib/python3.8/site-packages/tensorflow/python/distribute/distribution_strategy_context.py", li\
ne 65, in _pop_per_thread_mode
    ops.get_default_graph()._distribution_strategy_stack.pop(-1)  # pylint: disable=protected-access
IndexError: pop from empty list

我不知道这是不是因为我的功能( Encoder , Decoder , ProtVAE ，及 CompileVAE )在单独的模块中定义( models.py ). 但是我觉得这不应该是个问题，因为这些函数是在strategy.scope（）块中调用的。