class_docstr: Global environment for extracting tuning tasks from graph
class_docstr_tok: ["Global","environment","for","extracting","tuning","tasks","from","graph"]
docstr: Add AutoTVM task
  
  Parameters
  ----------
  task_name: str
      AutoTVM task name.
  
  args: tuple
      Arguments to the TOPI function.
docstr_tok: ["Add","AutoTVM","task","Parameters","--","--","--","--","--","task_name",":","str","AutoTVM","task","name",".","args",":","tuple","Arguments","to","the","TOPI","function","."]
code: def add_task(self, task_name, args):
      """Add AutoTVM task
  
      Parameters
      ----------
      task_name: str
          AutoTVM task name.
  
      args: tuple
          Arguments to the TOPI function.
      """
      key = (task_name, serialize_args(args))
      if self.allow_duplicate or key not in self.task_collection:
          self.task_collection.append(key)
  
file_path: tvm/python/tvm/autotvm/task/topi_integration.py
imports: import functools
  import tvm.te._ffi_api
  from tvm.target import Target
  from tvm.te import tensor
  from .task import args_to_workload, serialize_args, DispatchContext, _register_task_compute, _register_task_schedule
label_desc: Use image node_id 5 for calling the TaskExtractEnv obj's underlying member method code with example usage: obj.add_task(task_name, args) without return types