class_docstr: TECompiler to get lowered code.
class_docstr_tok: ["TECompiler","to","get","lowered","code","."]
docstr: JIT a source_func to a tvm.runtime.PackedFunc.
  
  Parameters
  ----------
  source_func : Union[tvm.relay.Function, CCacheKey]
      The source relay function.
  
  target : tvm.Target
      The target platform.
  
  Returns
  -------
  jited_func: tvm.runtime.PackedFunc
      The result of jited function.
docstr_tok: ["JIT","a","source_func","to","a","tvm.runtime.PackedFunc",".","Parameters","--","--","--","--","--","source_func",":","Union","[","tvm.relay.Function",",","CCacheKey","]","The","source","relay","function",".","target",":","tvm.Target","The","target","platform",".","Returns","--","--","--","-","jited_func",":","tvm.runtime.PackedFunc","The","result","of","jited","function","."]
code: def jit(self, source_func, target=None):
      """JIT a source_func to a tvm.runtime.PackedFunc.
  
      Parameters
      ----------
      source_func : Union[tvm.relay.Function, CCacheKey]
          The source relay function.
  
      target : tvm.Target
          The target platform.
  
      Returns
      -------
      jited_func: tvm.runtime.PackedFunc
          The result of jited function.
      """
      key = _get_cache_key(source_func, target)
      return _backend._TECompilerJIT(self, key)
  
imports: from __future__ import absolute_import
  import logging
  import numpy
  import tvm
  from tvm import autotvm, te
  from tvm.auto_scheduler import is_auto_scheduler_enabled
  from tvm.meta_schedule import is_meta_schedule_enabled
  from tvm.runtime import Object
  from tvm.support import libinfo
  from tvm.target import Target
  from ..None import function
  from ..None import ty
  from ..backend.utils import mangle_module_name
  from .None import _backend
label_desc: Use image node_id 3 for calling the TECompiler obj's underlying member method code with example usage: obj.jit(source_func, target) and returns: _backend