From 35d0963820b2c8a9503bf2901ff5ab8b90f1bc6e Mon Sep 17 00:00:00 2001
From: Vamshidhar Dantu <36211508+vdantu@users.noreply.github.com>
Date: Wed, 19 May 2021 15:52:14 -0700
Subject: [PATCH] Expose all CPUs to TorchServe

Handle the error described [in sagemaker docs here](https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model-troubleshoot.html)
---
 src/sagemaker_pytorch_serving_container/torchserve.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/sagemaker_pytorch_serving_container/torchserve.py b/src/sagemaker_pytorch_serving_container/torchserve.py
index d90e0000..76a89bcc 100644
--- a/src/sagemaker_pytorch_serving_container/torchserve.py
+++ b/src/sagemaker_pytorch_serving_container/torchserve.py
@@ -151,7 +151,7 @@ def _generate_ts_config_properties():
     env = environment.Environment()
 
     user_defined_configuration = {
-        "default_response_timeout": env.model_server_timeout,
+        "vmargs":"-XX:-UseContainerSupport -XX:InitialRAMPercentage=8.0 -XX:MaxRAMPercentage=10.0 -XX:-UseLargePages -XX:+UseG1GC -XX:+ExitOnOutOfMemoryError",        "default_response_timeout": env.model_server_timeout,
         "default_workers_per_model": env.model_server_workers,
         "inference_address": "http://0.0.0.0:{}".format(env.inference_http_port),
         "management_address": "http://0.0.0.0:{}".format(env.management_http_port),