From 4be324efc36f5f0cd66ba2f6d81bb39fef258e3e Mon Sep 17 00:00:00 2001
From: old-bear <jrjbear@gmail.com>
Date: Thu, 23 Aug 2018 04:09:14 +0800
Subject: [PATCH] [tune] Support infinity value in report result (#2693)

* + Compatibility fix under py2 on ray.tune

* + Revert changes on master branch

* + Use default JsonEncoder in ray.tune.logger

* + Add UT for infinity support
---
 python/ray/tune/logger.py                 | 15 ---------------
 python/ray/tune/test/trial_runner_test.py | 17 +++++++++++++++++
 2 files changed, 17 insertions(+), 15 deletions(-)

diff --git a/python/ray/tune/logger.py b/python/ray/tune/logger.py
index 2ce7ca2cf..c1ffbcafe 100644
--- a/python/ray/tune/logger.py
+++ b/python/ray/tune/logger.py
@@ -170,21 +170,6 @@ class _SafeFallbackEncoder(json.JSONEncoder):
         super(_SafeFallbackEncoder, self).__init__(**kwargs)
         self.nan_str = nan_str
 
-    def iterencode(self, o, _one_shot=False):
-        if self.ensure_ascii:
-            _encoder = json.encoder.encode_basestring_ascii
-        else:
-            _encoder = json.encoder.encode_basestring
-
-        def floatstr(o, allow_nan=self.allow_nan, nan_str=self.nan_str):
-            return repr(o) if not np.isnan(o) else nan_str
-
-        _iterencode = json.encoder._make_iterencode(
-            None, self.default, _encoder, self.indent, floatstr,
-            self.key_separator, self.item_separator, self.sort_keys,
-            self.skipkeys, _one_shot)
-        return _iterencode(o, 0)
-
     def default(self, value):
         try:
             if np.isnan(value):
diff --git a/python/ray/tune/test/trial_runner_test.py b/python/ray/tune/test/trial_runner_test.py
index abfe9e97e..e7814a20c 100644
--- a/python/ray/tune/test/trial_runner_test.py
+++ b/python/ray/tune/test/trial_runner_test.py
@@ -366,6 +366,23 @@ class TrainableFunctionApiTest(unittest.TestCase):
         self.assertEqual(trial.status, Trial.TERMINATED)
         self.assertEqual(trial.last_result[TIMESTEPS_TOTAL], 99)
 
+    def testReportInfinity(self):
+        def train(config, reporter):
+            for i in range(100):
+                reporter(mean_accuracy=float('inf'))
+
+        register_trainable("f1", train)
+        [trial] = run_experiments({
+            "foo": {
+                "run": "f1",
+                "config": {
+                    "script_min_iter_time_s": 0,
+                },
+            }
+        })
+        self.assertEqual(trial.status, Trial.TERMINATED)
+        self.assertEqual(trial.last_result['mean_accuracy'], float('inf'))
+
 
 class RunExperimentTest(unittest.TestCase):
     def setUp(self):