[tune] Test TF2.0, TF1.14, TF1.12 Tensorboard support (#5931)

python/ray/tune/examples/pbt_memnn_example.py

@@ -14,12 +14,16 @@ from tensorflow.keras.layers import LSTM
 from tensorflow.keras.optimizers import RMSprop
 from tensorflow.keras.utils import get_file
 from tensorflow.keras.preprocessing.sequence import pad_sequences
-from ray.tune import Trainable
+
+from filelock import FileLock
+import os
 import argparse
 import tarfile
 import numpy as np
 import re
 
+from ray.tune import Trainable
+
 
 def tokenize(sent):
     """Return the tokens of a sentence including punctuation.
@@ -211,7 +215,8 @@ class MemNNModel(Trainable):
         return model
 
     def _setup(self, config):
-        self.train_stories, self.test_stories = read_data()
+        with FileLock(os.path.expanduser("~/.tune.lock")):
+            self.train_stories, self.test_stories = read_data()
         model = self.build_model()
         rmsprop = RMSprop(
             lr=self.config.get("lr", 1e-3), rho=self.config.get("rho", 0.9))

python/ray/tune/logger.py

@@ -146,7 +146,7 @@ def tf2_compat_logger(config, logdir, trial=None):
     else:
         import tensorflow as tf
         use_tf2_api = (distutils.version.LooseVersion(tf.__version__) >=
-                       distutils.version.LooseVersion("2.0.0"))
+                       distutils.version.LooseVersion("1.15.0"))
         if use_tf2_api:
             tf = tf.compat.v2  # setting this for TF2.0
             return TF2Logger(config, logdir, trial)
@@ -238,7 +238,7 @@ class TFLogger(Logger):
 
     def _init(self):
         logger.debug("Initializing TFLogger instead of TF2Logger.")
-        self._file_writer = tf.compat.v1.summary.FileWriter(self.logdir)
+        self._file_writer = tf.summary.FileWriter(self.logdir)
 
     def on_result(self, result):
         tmp = result.copy()

python/ray/tune/tests/test_logger.py

@@ -0,0 +1,59 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from collections import namedtuple
+import unittest
+import tempfile
+import shutil
+
+from ray.tune.logger import tf2_compat_logger, JsonLogger, CSVLogger
+
+Trial = namedtuple("MockTrial", ["evaluated_params", "trial_id"])
+
+
+def result(t, rew):
+    return dict(
+        time_total_s=t,
+        episode_reward_mean=rew,
+        mean_accuracy=rew * 2,
+        training_iteration=int(t))
+
+
+class LoggerSuite(unittest.TestCase):
+    """Test built-in loggers."""
+
+    def setUp(self):
+        self.test_dir = tempfile.mkdtemp()
+
+    def tearDown(self):
+        shutil.rmtree(self.test_dir, ignore_errors=True)
+
+    def testTensorBoardLogger(self):
+        config = {"a": 2, "b": 5}
+        t = Trial(evaluated_params=config, trial_id=5342)
+        logger = tf2_compat_logger(
+            config=config, logdir=self.test_dir, trial=t)
+        logger.on_result(result(2, 4))
+        logger.on_result(result(2, 4))
+        logger.close()
+
+    def testCSV(self):
+        config = {"a": 2, "b": 5}
+        t = Trial(evaluated_params=config, trial_id="csv")
+        logger = CSVLogger(config=config, logdir=self.test_dir, trial=t)
+        logger.on_result(result(2, 4))
+        logger.on_result(result(2, 4))
+        logger.close()
+
+    def testJSON(self):
+        config = {"a": 2, "b": 5}
+        t = Trial(evaluated_params=config, trial_id="json")
+        logger = JsonLogger(config=config, logdir=self.test_dir, trial=t)
+        logger.on_result(result(2, 4))
+        logger.on_result(result(2, 4))
+        logger.close()
+
+
+if __name__ == "__main__":
+    unittest.main(verbosity=2)