Using an example of TPU usage on a pod v3.32 with software "tpu-vm-tf-2.11.0-pod" is always giving the same error when initializing TF's TPUStrategy:
RuntimeError: TPU cores on each host is not same. This should not happen!. devices: [_DeviceAttributes(/job:localhost/replica:0/task:0/device:CPU:0, CPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU_SYSTEM:0, TPU_SYSTEM, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:0, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:1, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:2, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:3, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:4, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:5, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:6, TPU, 0, 0), _DeviceAttributes(/job:localhost/replica:0/task:0/device:TPU:7, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:CPU:0, CPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU_SYSTEM:0, TPU_SYSTEM, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:0, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:1, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:2, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:3, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:4, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:5, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:6, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:0/device:TPU:7, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:CPU:0, CPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU_SYSTEM:0, TPU_SYSTEM, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:0, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:1, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:2, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:3, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:4, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:5, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:6, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:3/device:TPU:7, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:CPU:0, CPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU_SYSTEM:0, TPU_SYSTEM, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:0, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:1, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:2, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:3, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:4, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:5, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:6, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:1/device:TPU:7, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:CPU:0, CPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU_SYSTEM:0, TPU_SYSTEM, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:0, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:1, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:2, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:3, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:4, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:5, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:6, TPU, 0, 0), _DeviceAttributes(/job:worker/replica:0/task:2/device:TPU:7, TPU, 0, 0)]
Here is the minimal example script I'm executing:
import tensorflow as tf
print("Tensorflow version " + tf.__version__)
cluster_resolver = tf.distribute.cluster_resolver.TPUClusterResolver()
print('Running on TPU ', cluster_resolver.cluster_spec().as_dict()['worker'])
tf.config.experimental_connect_to_cluster(cluster_resolver)
tf.tpu.experimental.initialize_tpu_system(cluster_resolver)
strategy = tf.distribute.TPUStrategy(cluster_resolver)
@tf.function
def add_fn(x,y):
z = x + y
return z
x = tf.constant(1.)
y = tf.constant(1.)
z = strategy.run(add_fn, args=(x,y))
print(z)
And the command used, where tpu-test-pod is the name of the tpu:
TPU_NAME=tpu-test-pod python3 tpu-test.py
Tried recreating the TPU but is still getting the same error. Anyone can help me? Thx
you are getting this error because you are missing one more important env variable. You need to also
export TPU_LOAD_LIBRARY=0 for pods. If you do this, your code should be running. For more details please follow this guide step by step https://cloud.google.com/tpu/docs/tensorflow-pods#set_up_a_tpu_vm_pod_running_tensorflow_and_run_a_calculation