class_docstr: Global environment for extracting tuning tasks from graph
class_docstr_tok: ["Global","environment","for","extracting","tuning","tasks","from","graph"]
docstr: Reset task collections
  
  Parameters
  ----------
  wanted_relay_ops: List of tvm.ir.Op
      The relay ops to be extracted
docstr_tok: ["Reset","task","collections","Parameters","--","--","--","--","--","wanted_relay_ops",":","List","of","tvm.ir.Op","The","relay","ops","to","be","extracted"]
code: def reset(self, wanted_relay_ops=None):
      """Reset task collections
  
      Parameters
      ----------
      wanted_relay_ops: List of tvm.ir.Op
          The relay ops to be extracted
      """
      self.task_collection = []
      self.wanted_relay_ops = wanted_relay_ops
  
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 4 for calling the TaskExtractEnv obj's underlying member method code with example usage: obj.reset(wanted_relay_ops) without return types