def testNoShuffleDeterministic(self):
problem = algorithmic.TinyAlgo()
dataset = problem.dataset(mode=tf.estimator.ModeKeys.TRAIN,
data_dir=algorithmic.TinyAlgo.data_dir,
shuffle_files=False)
tensor1 = dataset.make_one_shot_iterator().get_next()["targets"]
tensor2 = dataset.make_one_shot_iterator().get_next()["targets"]
with tf.Session() as sess:
self.assertTrue(assert_tensors_equal(sess, tensor1, tensor2, 20))
def testExperimentWithClass(self):
exp_fn = trainer_lib.create_experiment_fn(
"transformer",
algorithmic.TinyAlgo(),
algorithmic.TinyAlgo.data_dir,
train_steps=1,
eval_steps=1,
min_eval_frequency=1,
use_tpu=False)
run_config = trainer_lib.create_run_config(
model_dir=algorithmic.TinyAlgo.data_dir, num_gpus=0, use_tpu=False)
hparams = registry.hparams("transformer_tiny_tpu")
exp = exp_fn(run_config, hparams)
exp.test()
def testDataFilenames(self):
problem = algorithmic.TinyAlgo()
num_shards = 10
shuffled = False
data_dir = "/tmp"
# Test training_filepaths and data_filepaths give the same list on
# appropriate arguments.
self.assertAllEqual(
problem.training_filepaths(data_dir, num_shards, shuffled),
problem.data_filepaths(problem_module.DatasetSplit.TRAIN, data_dir,
num_shards, shuffled))
self.assertAllEqual(
problem.dev_filepaths(data_dir, num_shards, shuffled),
problem.data_filepaths(problem_module.DatasetSplit.EVAL, data_dir,
num_shards, shuffled))
self.assertAllEqual(
problem.test_filepaths(data_dir, num_shards, shuffled),
problem.data_filepaths(problem_module.DatasetSplit.TEST, data_dir,
num_shards, shuffled))
