class_docstr: This context manager is used for Pytorch Model Inference.
  
  Provide no grad, thread control and autocast context which is for bf16 model.
class_docstr_tok: ["This","context","manager","is","used","for","Pytorch","Model","Inference",".","Provide","no","grad",",","thread","control","and","autocast","context","which","is","for","bf16","model","."]
code: def __enter__(self):
      # call `torch.set_num_threads` at most once
      self.forecaster.thread_num = set_pytorch_thread(
          self.thread_num, self.forecaster.thread_num
      )
      if hasattr(self.forecaster, "optimized_model_thread_num"):
          self.forecaster.optimized_model_thread_num = (
              set_pytorch_thread(
                  self.thread_num,
                  self.forecaster.optimized_model_thread_num,
              )
          )
      self.forecaster.context_enabled = True
      self.infer_mode.__enter__()
      if self.bf16_enable:
          self.autocast.__enter__()
  
file_path: BigDL/python/chronos/src/bigdl/chronos/pytorch/context_manager.py
imports: import torch
  from bigdl.chronos.forecaster.utils import set_pytorch_thread
label_desc: Use image node_id 2 for calling the ForecasterContextManager obj's underlying member method code with example usage: obj.__enter__() without return types