_

ml-agents/mlagents/trainers/stats.py

 from mlagents.tf_utils import tf, generate_session_config
 from mlagents.tf_utils.globals import get_rank
 
+from mlagents.torch_utils import cpu_utils
+
 
 logger = get_logger(__name__)
 
         else:
             log_info.append("No episode was completed since last summary")
             log_info.append(is_training)
+        log_info.append("NUM CPU " + str(cpu_utils.get_num_threads_to_use()))
         logger.info(". ".join(log_info))
 
     def add_property(

ml-agents/mlagents/torch_utils/cpu_utils.py

 
 import os
 
+from mlagents_envs.logging_util import get_logger
+logger = get_logger(__name__)
 
 def get_num_threads_to_use() -> Optional[int]:
     """
     """
     num_cpus = _get_num_available_cpus()
+    print("NUM_CPU ", num_cpus)
+    logger.info("\n\n\n\n\n NUMCPU " + str(num_cpus) + "\n\n\n\n\n")
     return max(min(num_cpus // 2, 4), 1) if num_cpus is not None else None
 
 
     for Docker containers that are limited in cores.
     """
     period = _read_in_integer_file("/sys/fs/cgroup/cpu/cpu.cfs_period_us")
+    logger.info("period "+str(period))
+    logger.info("quota " + str(quota))
+
+    shares = _read_in_integer_file("/sys/fs/cgroup/cpu/cpu.shares")
+    logger.info("shares "+str(shares))
     if period > 0 and quota > 0:
         return int(quota // period)
     else: