问Tensorflow MNIST import input_data run error？

Traceback (most recent call last):

File "/home/steven/idea/project/tensorflow/study01/testMinst.py", line 6, in <module>

from tensorflow.examples.tutorials.mnist import input_data

File "/usr/local/lib/python2.7/dist-packages/tensorflow/examples/tutorials/mnist/__init__.py", line 21, in <module>

from tensorflow.examples.tutorials.mnist import input_data

File "/usr/local/lib/python2.7/dist-packages/tensorflow/examples/tutorials/mnist/input_data.py", line 30, in <module>

from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/__init__.py", line 48, in <module>

from tensorflow.contrib import distribute

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/distribute/__init__.py", line 34, in <module>

from tensorflow.contrib.distribute.python.tpu_strategy import TPUStrategy

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/distribute/python/tpu_strategy.py", line 27, in <module>

from tensorflow.contrib.tpu.python.ops import tpu_ops

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/__init__.py", line 69, in <module>

from tensorflow.contrib.tpu.python.ops.tpu_ops import *

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/ops/tpu_ops.py", line 39, in <module>

resource_loader.get_path_to_datafile("_tpu_ops.so"))

File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/util/loader.py", line 56, in load_op_library

ret = load_library.load_op_library(path)

File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/load_library.py", line 60, in load_op_library

lib_handle = py_tf.TF_LoadLibrary(library_filename)

tensorflow.python.framework.errors_impl.InvalidArgumentError: Invalid name:

An op that loads optimization parameters into HBM for embedding. Must be

preceded by a ConfigureTPUEmbeddingHost op that sets up the correct

embedding table configuration. For example, this op is used to install

parameters that are loaded from a checkpoint before a training loop is

executed.