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| author |  weidankong <kongweidan84@gmail.com> | 2018-08-15 10:05:31 -0700 |
|---|---|---|
| committer | weidankong <kongweidan84@gmail.com> | 2018-08-15 10:05:31 -0700 |
| commit | 5b2ac79e45dd217fd2954e6b170b569c42162f3f (patch) | |
| tree | a295a42792b975e71bd72e53504c653ccef2b05e /tensorflow/contrib/opt | |
| parent | fae346fb4b745cac4f93f503ed51a1debf48de41 (diff) | |
fix Ubuntu Sanity check failure
Diffstat (limited to 'tensorflow/contrib/opt')
| -rw-r--r-- | tensorflow/contrib/opt/python/training/elastic_average_optimizer_test.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/opt/python/training/elastic_average_optimizer_test.py b/tensorflow/contrib/opt/python/training/elastic_average_optimizer_test.py index c2a680edd1..0db368cc4e 100644 --- a/tensorflow/contrib/opt/python/training/elastic_average_optimizer_test.py +++ b/tensorflow/contrib/opt/python/training/elastic_average_optimizer_test.py @@ -117,7 +117,7 @@ def _get_workers(num_workers, period, workers, moving_rate, num_ps=1): if num_ps == 1: train_op = [ opt.apply_gradients(([grads_0, var_0], [grads_1, var_1]), - global_step) + global_step) ] else: train_op = [ @@ -125,7 +125,7 @@ def _get_workers(num_workers, period, workers, moving_rate, num_ps=1): [grads_1, var_1], [grads_part_0, part_0], [grads_part_1, part_1]), - global_step) + global_step) ] easgd_hook = opt.make_session_run_hook(is_chief, worker_id) saver = opt.swapping_saver() @@ -197,7 +197,7 @@ class ElasticAverageOptimizerTest(test.TestCase): # save, data will be global value savers[0].save(sessions[0]._sess._sess._sess._sess, - save_path='./model/model') + save_path='./model/model') ops.reset_default_graph() # restore on a new graph with session.Session() as sess: v0 = variable_scope.get_variable(initializer=0.0, name="v0") @@ -250,7 +250,7 @@ class ElasticAverageOptimizerTest(test.TestCase): part_0_g = sessions[0].run(part_0_g) savers[0].save(sessions[0]._sess._sess._sess._sess, - save_path='./model/model') + save_path='./model/model') # verify restore of partitioned_variables ops.reset_default_graph() # restore on a new graph |