remove remaining rllab (flow-project#757)

* removed most uses of rllab. Bug pending * added description that separate py files are needed * bug fix * cleanup to tutorials Co-authored-by: Ashkan Y. <[email protected]>
gmartin958 · Jan 8, 2020 · 55e39f1 · 55e39f1
1 parent d61e0c9
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diff --git a/.coveragerc b/.coveragerc
@@ -5,7 +5,6 @@ omit =
     *__init__*
     */scripts/*
     */setup.py
-    *rllab*
     */flow/utils/shflags
     *dummy_server.py
     *aimsun.py

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -32,9 +32,6 @@ def __getattr__(cls, name):
 
 
 MOCK_MODULES = [
-    'rllab',
-    "rllab.core.serializable.Serializable",
-    'rllab.sampler.utils.rollout',
     "AAPI",
     'PyANGKernel',
     'AAPI.GKGUISystem',

diff --git a/tests/fast_tests/test_visualizers.py b/tests/fast_tests/test_visualizers.py
@@ -1,5 +1,3 @@
-# from flow.visualize import visualizer_rllab as vs_rllab
-# from flow.visualize.visualizer_rllab import visualizer_rllab
 from flow.visualize import visualizer_rllib as vs_rllib
 from flow.visualize.visualizer_rllib import visualizer_rllib
 import flow.visualize.capacity_diagram_generator as cdg
@@ -55,19 +53,6 @@ def test_visualizer_multi(self):
         visualizer_rllib(pass_args)
 
 
-# class TestVisualizerRLlab(unittest.TestCase):
-#     """Tests visualizer_rllab"""
-#
-#     def test_visualizer(self):
-#         # current path
-#         current_path = os.path.realpath(__file__).rsplit('/', 1)[0]
-#         arg_str = '{}/../data/rllab_data/itr_0.pkl --num_rollouts 1 ' \
-#                   '--no_render'.format(current_path).split()
-#         parser = vs_rllab.create_parser()
-#         pass_args = parser.parse_args(arg_str)
-#         visualizer_rllab(pass_args)
-
-
 class TestPlotters(unittest.TestCase):
 
     def test_capacity_diagram_generator(self):

diff --git a/tutorials/README.md b/tutorials/README.md
@@ -56,7 +56,7 @@ The content of each tutorial is as follows:
 **Tutorial 3:** Running RLlib experiments for mixed-autonomy traffic.
 
 **Tutorial 4:** Saving and visualizing resuls from non-RL simulations and
-testing simulations in the presence of an RLlib/rllab agent.
+testing simulations in the presence of an RLlib agent.
 
 **Tutorial 5:** Creating custom networks.
 

diff --git a/tutorials/tutorial00_flow.ipynb b/tutorials/tutorial00_flow.ipynb
@@ -110,9 +110,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}
diff --git a/tutorials/tutorial01_sumo.ipynb b/tutorials/tutorial01_sumo.ipynb
@@ -346,22 +346,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# create the network object\n",
-    "network = RingNetwork(name=\"ring_example\",\n",
-    "                      vehicles=vehicles,\n",
-    "                      net_params=net_params,\n",
-    "                      initial_config=initial_config,\n",
-    "                      traffic_lights=traffic_lights)\n",
-    "\n",
-    "# create the environment object\n",
-    "env = AccelEnv(env_params, sim_params, network)\n",
-    "\n",
     "flow_params = dict(\n",
     "    exp_tag='ring_example',\n",
     "    env_name=AccelEnv,\n",
     "    network=RingNetwork,\n",
     "    simulator='traci',\n",
-    "    sim=sumo_params,\n",
+    "    sim=sim_params,\n",
     "    env=env_params,\n",
     "    net=net_params,\n",
     "    veh=vehicles,\n",
@@ -372,7 +362,6 @@
     "# number of time steps\n",
     "flow_params['env'].horizon = 3000\n",
     "exp = Experiment(flow_params)\n",
-    "exp.env - env\n",
     "\n",
     "# run the sumo simulation\n",
     "_ = exp.run(1, convert_to_csv=True)"

diff --git a/tutorials/tutorial02_aimsun.ipynb b/tutorials/tutorial02_aimsun.ipynb
@@ -348,16 +348,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# create the network object\n",
-    "network = RingNetwork(name=\"ring_example\",\n",
-    "                      vehicles=vehicles,\n",
-    "                      net_params=net_params,\n",
-    "                      initial_config=initial_config,\n",
-    "                      traffic_lights=traffic_lights)\n",
-    "\n",
-    "# create the environment object\n",
-    "env = AccelEnv(env_params, sim_params, network, simulator='aimsun')\n",
-    "\n",
     "flow_params = dict(\n",
     "    exp_tag='test_network',\n",
     "    env_name=AccelEnv,\n",
@@ -374,7 +364,6 @@
     "# number of time steps\n",
     "flow_params['env'].horizon = 3000\n",
     "exp = Experiment(flow_params)\n",
-    "exp.env = env\n",
     "\n",
     "# run the Aimsun simulation\n",
     "_ = exp.run(1)"

diff --git a/tutorials/tutorial04_visualize.ipynb b/tutorials/tutorial04_visualize.ipynb
@@ -48,7 +48,7 @@
     "collapsed": true
    },
    "source": [
-    "Visualization is different depending on which reinforcement learning library you are using, if any. Accordingly, the rest of this tutorial explains how to plot rewards, replay policies and collect data when using either no RL library, RLlib or rllab. "
+    "Visualization is different depending on which reinforcement learning library you are using, if any. Accordingly, the rest of this tutorial explains how to plot rewards, replay policies and collect data when using either no RL library, RLlib, or stable-baselines. "
    ]
   },
   {
@@ -63,9 +63,7 @@
     "\n",
     "[How to visualize using SUMO with RLlib](#2.2---Using-SUMO-with-RLlib)\n",
     "\n",
-    "[How to visualize using SUMO with rllab](#2.3---Using-SUMO-with-rllab)\n",
-    "\n",
-    "[**_Example: visualize data on a ring trained using RLlib_**](#2.4---Example:-Visualize-data-on-a-ring-trained-using-RLlib)\n"
+    "[**_Example: visualize data on a ring trained using RLlib_**](#2.3---Example:-Visualize-data-on-a-ring-trained-using-RLlib)\n"
    ]
   },
   {
@@ -213,7 +211,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 2.4 - Example: Visualize data on a ring trained using RLlib"
+    "### 2.3 - Example: Visualize data on a ring trained using RLlib"
    ]
   },
   {

diff --git a/tutorials/tutorial05_networks.ipynb b/tutorials/tutorial05_networks.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -98,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -140,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -217,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -245,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -273,7 +273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -345,7 +345,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -377,7 +377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -405,7 +405,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -423,7 +423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -446,22 +446,12 @@
    "source": [
     "from flow.core.experiment import Experiment\n",
     "\n",
-    "network = myNetwork(  # we use the newly defined network class\n",
-    "    name=\"test_network\",\n",
-    "    vehicles=vehicles,\n",
-    "    net_params=net_params,\n",
-    "    initial_config=initial_config\n",
-    ")\n",
-    "\n",
-    "# AccelEnv allows us to test any newly generated network quickly\n",
-    "env = AccelEnv(env_params, sim_params, network)\n",
-    "\n",
     "flow_params = dict(\n",
     "    exp_tag='test_network',\n",
     "    env_name=AccelEnv,\n",
     "    network=myNetwork,\n",
     "    simulator='traci',\n",
-    "    sim=sumo_params,\n",
+    "    sim=sim_params,\n",
     "    env=env_params,\n",
     "    net=net_params,\n",
     "    veh=vehicles,\n",
@@ -471,7 +461,6 @@
     "# number of time steps\n",
     "flow_params['env'].horizon = 1500\n",
     "exp = Experiment(flow_params)\n",
-    "exp.env = env\n",
     "\n",
     "# run the sumo simulation\n",
     "_ = exp.run(1)"
@@ -501,7 +490,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,

diff --git a/tutorials/tutorial06_osm.ipynb b/tutorials/tutorial06_osm.ipynb
@@ -91,15 +91,7 @@
     "sim_params = SumoParams(render=True)\n",
     "initial_config = InitialConfig()\n",
     "vehicles = VehicleParams()\n",
-    "vehicles.add('human', num_vehicles=100)\n",
-    "\n",
-    "# create the network\n",
-    "network = Network(\n",
-    "    name='bay_bridge',\n",
-    "    net_params=net_params,\n",
-    "    initial_config=initial_config,\n",
-    "    vehicles=vehicles\n",
-    ")"
+    "vehicles.add('human', num_vehicles=100)"
    ]
   },
   {
@@ -115,13 +107,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# create the environment\n",
-    "env = TestEnv(\n",
-    "    env_params=env_params,\n",
-    "    sim_params=sim_params,\n",
-    "    network=network\n",
-    ")\n",
-    "\n",
     "flow_params = dict(\n",
     "    exp_tag='bay_bridge',\n",
     "    env_name=TestEnv,\n",
@@ -137,10 +122,9 @@
     "# number of time steps\n",
     "flow_params['env'].horizon = 1000\n",
     "exp = Experiment(flow_params)\n",
-    "exp.env = env\n",
     "\n",
     "# run the sumo simulation\n",
-    "exp.run(1)"
+    "_ = exp.run(1)"
    ]
   },
   {
@@ -283,21 +267,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# create the network\n",
-    "new_network = BayBridgeOSMNetwork(\n",
-    "    name='bay_bridge',\n",
-    "    net_params=net_params,\n",
-    "    initial_config=new_initial_config,\n",
-    "    vehicles=vehicles,\n",
-    ")\n",
-    "\n",
-    "# create the environment\n",
-    "env = TestEnv(\n",
-    "    env_params=env_params,\n",
-    "    sim_params=sim_params,\n",
-    "    network=new_network\n",
-    ")\n",
-    "\n",
     "flow_params = dict(\n",
     "    exp_tag='bay_bridge',\n",
     "    env_name=TestEnv,\n",
@@ -313,10 +282,9 @@
     "# number of time steps\n",
     "flow_params['env'].horizon = 10000\n",
     "exp = Experiment(flow_params)\n",
-    "exp.env = env\n",
     "\n",
     "# run the sumo simulation\n",
-    "exp.run(1)"
+    "_ = exp.run(1)"
    ]
   },
   {