Exemplos de ResourceManager.adapt_engine_parameters em Python

Exemplo n.º 1

 def adapt_job_parameters(cls,
                          role,
                          job_parameters: RunParameters,
                          create_initiator_baseline=False):
     ResourceManager.adapt_engine_parameters(
         role=role,
         job_parameters=job_parameters,
         create_initiator_baseline=create_initiator_baseline)
     if create_initiator_baseline:
         if job_parameters.task_parallelism is None:
             job_parameters.task_parallelism = JobDefaultConfig.task_parallelism
         if job_parameters.federated_status_collect_type is None:
             job_parameters.federated_status_collect_type = JobDefaultConfig.federated_status_collect_type
     if create_initiator_baseline and not job_parameters.computing_partitions:
         job_parameters.computing_partitions = job_parameters.adaptation_parameters[
             "task_cores_per_node"] * job_parameters.adaptation_parameters[
                 "task_nodes"]

Exemplo n.º 2

 def adapt_job_parameters(cls,
                          role,
                          job_parameters: RunParameters,
                          create_initiator_baseline=False):
     ResourceManager.adapt_engine_parameters(
         role=role,
         job_parameters=job_parameters,
         create_initiator_baseline=create_initiator_baseline)
     if create_initiator_baseline:
         if job_parameters.task_parallelism is None:
             job_parameters.task_parallelism = DEFAULT_TASK_PARALLELISM
         if job_parameters.federated_status_collect_type is None:
             job_parameters.federated_status_collect_type = DEFAULT_FEDERATED_STATUS_COLLECT_TYPE
     if create_initiator_baseline and not job_parameters.computing_partitions:
         job_parameters.computing_partitions = job_parameters.adaptation_parameters[
             "task_cores_per_node"] * job_parameters.adaptation_parameters[
                 "task_nodes"]