How to use multiple GPUs to train model in tensorflow - tensorflow

Question

I've read the keras official document and it says
To do single-host, multi-device synchronous training with a Keras model, you would use the tf.distribute.MirroredStrategy API. Here's how it works:
Instantiate a MirroredStrategy, optionally configuring which specific devices you want to use (by default the strategy will use all GPUs available).
Use the strategy object to open a scope, and within this scope, create all the Keras objects you need that contain variables. Typically, that means creating & compiling the model inside the distribution scope.
Train the model via fit() as usual.
Here is what I did. Basically, I have 8 GPUs but only 3 are available for the task (5, 6 & 7). I create a strategy using these 3 GPUs and compile the model inside the scope. However, each epoch in my training process takes as much time as using a single GPU, and nvidia also shows that only GPU 7 is in use when I do nvidia-smi in the terminal. Maybe the warning message shows the problem? But I am not an expert... If it is the issue, could someone translate it into plain English or provide a solution? Thanks a lot!!
strategy = tf.distribute.MirroredStrategy(["GPU:5", "GPU:6", "GPU:7"])
print('Number of devices: {}'.format(strategy.num_replicas_in_sync))
WARNING:tensorflow:Some requested devices in `tf.distribute.Strategy` are not visible to TensorFlow: /job:localhost/replica:0/task:0/device:GPU:6,/job:localhost/replica:0/task:0/device:GPU:5,/job:localhost/replica:0/task:0/device:GPU:7
INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:5', '/job:localhost/replica:0/task:0/device:GPU:6', '/job:localhost/replica:0/task:0/device:GPU:7')
Number of devices: 3
with strategy.scope():
model_test = model_unet
model_test.compile(loss=loss,
optimizer = adam_opt,
metrics=['accuracy',segmentation_models.metrics.IOUScore()],
)
model_test.fit(x_train,y_train,
validation_data=(x_val,y_val),
batch_size= 16,
epochs= 6, verbose=1, callbacks = callbacks
)
# an example of the first epoch
Train on 14400 samples, validate on 3600 samples
Epoch 1/6
6384/14400 [============>.................] - ETA: 5:35 - loss: 0.0045 - accuracy: 0.9833 - iou_score: 0.8918
Only GPU 7 is in use