Fix bug in MujocoModelGenerator

Before this commit, when there is an error raised when loading the xml
object, only the worker_thread terminates. This commit fixes this bug by
terminating all the processes.

Fix some typo in the last commit.

rllab/dynamics_randomization/mujoco_model_gen.py

@@ -1,14 +1,15 @@
-from lxml import etree
-from mujoco_py import load_model_from_xml
-from rllab.dynamics_randomization import VariationMethod
-from rllab.dynamics_randomization import VariationDistribution
+import atexit
+import sys
 from threading import Event
-from threading import RLock
 from threading import Thread
 
-import atexit
+from lxml import etree
+from mujoco_py import load_model_from_xml
 import numpy as np
 
+from rllab.dynamics_randomization import VariationDistribution
+from rllab.dynamics_randomization import VariationMethod
+
 
 class MujocoModelGenerator:
     """
@@ -33,7 +34,7 @@ def __init__(self, file_path, variations):
         self._file_path = file_path
         # Worker Thread
         self._worker_thread = Thread(
-            target=self._generator_routine, daemon=True)
+            target=self._generator_routine, daemon=True, name="Worker-Thread")
         # Reference to the generated model
         self._mujoco_model = None
         # Communicates the calling thread with the worker thread by awaking
@@ -58,6 +59,10 @@ def get_model(self):
             A MuJoCo model with randomized dynamic parameters specified by the
             user in this class.
         """
+        if not self._worker_thread.is_alive():
+            # If worker thread is dead because of an error, raise an error in main thread
+            raise ChildProcessError("Error raised in Worker-Thread")
+
         if not self._model_ready.is_set():
             # If the model is not ready yet, wait for it to be finished.
             self._model_ready.wait()
@@ -101,7 +106,7 @@ def _generator_routine(self):
                 raise AttributeError("Range shape != default value shape")
 
         # Generate model with randomized dynamic parameters
-        while (not self._stop_event.is_set()):
+        while not self._stop_event.is_set():
             for v in self._variations.get_list():
                 e = v.elem
                 if v.distribution == VariationDistribution.GAUSSIAN:
@@ -111,7 +116,7 @@ def _generator_routine(self):
                     c = np.random.uniform(
                         low=v.var_range[0], high=v.var_range[1])
                 else:
-                    raise NotImplementedError("Unkown distribution")
+                    raise NotImplementedError("Unknown distribution")
                 if v.method == VariationMethod.COEFFICIENT:
                     e.attrib[v.attrib] = str(c * v.default)
                 elif v.method == VariationMethod.ABSOLUTE:

rllab/dynamics_randomization/randomized_env.py

@@ -1,11 +1,12 @@
+import os.path as osp
+
 from mujoco_py import MjSim
+
 from rllab.core import Serializable
 from rllab.dynamics_randomization import MujocoModelGenerator
 from rllab.envs import Env
 from rllab.envs.mujoco.mujoco_env import MODEL_DIR
 
-import os.path as osp
-
 
 class RandomizedEnv(Env, Serializable):
     """
@@ -33,7 +34,10 @@ def reset(self):
         corresponding parameters in the MuJoCo environment class are
         set.
         """
-        self._wrapped_env.model = self._model_generator.get_model()
+        try:
+            self._wrapped_env.model = self._model_generator.get_model()
+        except AttributeError as e:
+            raise e
         self._wrapped_env.sim = MjSim(self._wrapped_env.model)
         self._wrapped_env.data = self._wrapped_env.sim.data
         self._wrapped_env.init_qpos = self._wrapped_env.sim.data.qpos

rllab/dynamics_randomization/variation.py

@@ -5,15 +5,15 @@ class VariationMethod(Enum):
     """
     The random coefficient is applied according to these methods.
     """
-    """ The randomization is the product of the coeffcient and the dynamic parameter """
+    """ The randomization is the product of the coefficient and the dynamic parameter """
     COEFFICIENT = 1
     """ The randomization is equal to the coefficient """
     ABSOLUTE = 2
 
 
 class VariationDistribution(Enum):
     """
-    The different ways to produce the random cofficient.
+    The different ways to produce the random coefficient.
     """
     """ Guassian distribution """
     GAUSSIAN = 1
@@ -151,9 +151,9 @@ def with_method(self, method):
         Parameters
         ----------
         method : VariationMethod
-            if equal to "absolute", it sets the dyanmic parameter
+            if equal to "absolute", it sets the dynamic parameter
             equal to the random coefficient obtained from the distribution, or
-            if equal to "coefficient", it multiplies the default value provieded
+            if equal to "coefficient", it multiplies the default value provided
             in the XML file by the random coefficient.
         """
         if self._list: