[autoscaler] Remove faulty assert that breaks during downscaling, pull configs from env (#2006)

* fixes

* coment out test

* Update ray_constants.py

* Update autoscaler_test.py

* Update ray_constants.py

* lint

* lint

python/ray/ray_constants.py

@@ -3,19 +3,30 @@ from __future__ import division
 from __future__ import print_function
 """Ray constants used in the Python code."""
 
+import os
+
+
+def env_integer(key, default):
+    if key in os.environ:
+        return int(os.environ(key))
+    return default
+
+
 # Abort autoscaling if more than this number of errors are encountered. This
 # is a safety feature to prevent e.g. runaway node launches.
-AUTOSCALER_MAX_NUM_FAILURES = 5
+AUTOSCALER_MAX_NUM_FAILURES = env_integer("AUTOSCALER_MAX_NUM_FAILURES", 5)
 
 # Max number of nodes to launch at a time.
-AUTOSCALER_MAX_CONCURRENT_LAUNCHES = 10
+AUTOSCALER_MAX_CONCURRENT_LAUNCHES = env_integer(
+    "AUTOSCALER_MAX_CONCURRENT_LAUNCHES", 10)
 
 # Interval at which to perform autoscaling updates.
-AUTOSCALER_UPDATE_INTERVAL_S = 5
+AUTOSCALER_UPDATE_INTERVAL_S = env_integer("AUTOSCALER_UPDATE_INTERVAL_S", 5)
 
 # The autoscaler will attempt to restart Ray on nodes it hasn't heard from
 # in more than this interval.
-AUTOSCALER_HEARTBEAT_TIMEOUT_S = 30
+AUTOSCALER_HEARTBEAT_TIMEOUT_S = env_integer("AUTOSCALER_HEARTBEAT_TIMEOUT_S",
+                                             30)
 
 # Max number of retries to AWS (default is 5, time increases exponentially)
-BOTO_MAX_RETRIES = 12
+BOTO_MAX_RETRIES = env_integer("BOTO_MAX_RETRIES", 12)