first pass at kubernetes

docker/Makefile

@@ -1,3 +1,4 @@
+REGISTRY=nervana-dockrepo01.fm.intel.com:5001/
 IMAGE=zdwiel/coach
 # IMAGE=gcr.io/deep-greens/inference:v5
 
@@ -43,5 +44,9 @@ run_training_worker: build
 run_rollout_worker: build
 	${DOCKER} run ${RUN_ARGUMENTS} -it ${IMAGE} python3 rl_coach/rollout_worker.py --preset CartPole_DQN_distributed
 
-push:
-	docker push ${IMAGE}
+kubernetes: build push
+	kubectl run -i --tty --attach --image=${IMAGE} --restart=Never date -- python3 rl_coach/orchestrators/start_training.py --preset CartPole_DQN_distributed --image ${IMAGE}
+
+push: build
+	${DOCKER} tag ${IMAGE} ${REGISTRY}${IMAGE}
+	${DOCKER} push ${REGISTRY}${IMAGE}

rl_coach/orchestrators/start_training.py

@@ -0,0 +1,48 @@
+import argparse
+
+from rl_coach.orchestrators.kubernetes_orchestrator import KubernetesParameters, Kubernetes
+
+
+def main(preset, image='ajaysudh/testing:coach', redis_ip='redis-service.ajay.svc'):
+    rollout_command = ['python3', 'rl_coach/rollout_worker.py', '-p', preset]
+    training_command = ['python3', 'rl_coach/training_worker.py', '-p', preset]
+
+    rollout_params = KubernetesParameters(image, rollout_command, redis_ip=redis_ip, redis_port=6379, num_workers=1)
+    training_params = KubernetesParameters(image, training_command, redis_ip=redis_ip, redis_port=6379, num_workers=1)
+
+    training_obj = Kubernetes(training_params)
+    if not training_obj.setup():
+        print("Could not setup")
+
+    rollout_obj = Kubernetes(training_params)
+    if not rollout_obj.setup():
+        print("Could not setup")
+
+    if training_obj.deploy():
+        print("Successfully deployed")
+    else:
+        print("Could not deploy")
+
+    if rollout_obj.deploy():
+        print("Successfully deployed")
+    else:
+        print("Could not deploy")
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--image',
+                        help="(string) Name of a docker image.",
+                        type=str,
+                        required=True)
+    parser.add_argument('-p', '--preset',
+                        help="(string) Name of a preset to run (class name from the 'presets' directory.)",
+                        type=str,
+                        required=True)
+    # parser.add_argument('--checkpoint_dir',
+    #                     help='(string) Path to a folder containing a checkpoint to write the model to.',
+    #                     type=str,
+    #                     default='/checkpoint')
+    args = parser.parse_args()
+
+    main(preset=args.preset, image=args.image)

rl_coach/rollout_worker.py

@@ -41,8 +41,8 @@ def wait_for_checkpoint(checkpoint_dir, timeout=10):
         return
 
     raise ValueError((
-        'Waited {timeout} seconds, but checkpoint never found in'
-        ' {checkpoint_dir}'
+        'Waited {timeout} seconds, but checkpoint never found in '
+        '{checkpoint_dir}'
     ).format(
         timeout=timeout,
         checkpoint_dir=checkpoint_dir,