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我有一个五个嵌套的 for 循环函数（通过 3d 过滤器对图像进行卷积），我迫切需要加速并非常高兴地使用了 numba 的 @autojit 装饰器。我唯一的抱怨是，当第一次调用该函数时，numba 会执行它的 autojit，但会将我认为是 jitted 函数的内部表示打印到标准输出，这可能需要几秒钟才能滚动，即像这样的东西：

empty1:                                           ; preds = %empty
  %16 = call i32 inttoptr (i64 139980888423164 to i32 ({ i64, i8* }*)*)({ i64, i8* }* %10)
  br label %empty3

empty2:                                           ; preds = %empty
  br label %error_label

empty3:                                           ; preds = %empty1
  %17 = call i8* @PyErr_Occurred()
  %18 = ptrtoint i8* %17 to i64
  %19 = icmp ne i64 %18, 0
  br i1 %19, label %empty5, label %empty4

empty4:                                           ; preds = %empty3
  %20 = call { i64, i8* }* @__numba_specialized_2___main___2E_max_pool({ i64, i8*, i8*, i32, i64*, i64*, i8*, i8*, i32, i8* }* %11, i32 %12, i32 %16)
  store { i64, i8* }* %20, { i64, i8* }** %objtemp, !tbaa !6
  %21 = ptrtoint { i64, i8* }* %20 to i64
  %22 = icmp eq i64 %21, 0
  br i1 %22, label %error_label, label %no_error

empty5:                                           ; preds = %empty3
  br label %error_label

no_error:                                         ; preds = %empty4
  %23 = load { i64, i8* }** %objtemp, !tbaa !6
  store { i64, i8* }* %23, { i64, i8* }** %return_value
  %24 = load { i64, i8* }** %return_value, !tbaa !6
  call void @Py_XINCREF({ i64, i8* }* %24)
  br label %cleanup_label
}

!tbaa = !{!0, !1, !2, !3, !4, !5, !6, !7, !8, !9, !10, !11, !12, !13, !14, !15, !16, !17, !18, !19, !20, !21, !22, !23, !0, !1, !6, !0, !1, !2, !3, !4, !5, !6, !24, !12, !7, !13, !14, !15, !16, !17, !25, !0, !1, !6}

有谁知道如何禁用它？它工作正常，速度很快，并且不会抛出错误，但有点烦人。

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