翻译 This function is used to rebuild the ObjectARX runtime class tree when new classes need to be added. It can be safely called at any time, but is necessary only after the rxInit() functions have been called for any classes to be added to the runtime tree. This is usually done inside the AcRx::kInitAppMsg case of the acrxEntryPoint() switch statement (or a function called from there). This function needs to be called only once after all the rxInit() calls have been made.
时间: 2024-03-31 07:37:27 浏览: 132
这个函数用于在需要添加新类时重新构建ObjectARX运行时类树。它可以在任何时候安全地调用,但仅在rxInit()函数已经被调用以添加到运行时树中的任何类之后才是必需的。通常在acrxEntryPoint() switch语句的AcRx :: kInitAppMsg case内(或从那里调用的函数)中完成这个操作。在所有rxInit()调用完成后,只需要调用此函数一次。
相关问题
2023-06-09 09:46:11.022252: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1900] Ignoring visible gpu device (device: 0, name: GeForce GT 610, pci bus id: 0000:01:00.0, compute capability: 2.1) with Cuda compute capability 2.1. The minimum required Cuda capability is 3.5. 2023-06-09 09:46:11.022646: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX AVX2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. WARNING:tensorflow:5 out of the last 9 calls to <function Model.make_test_function.<locals>.test_function at 0x0000017BB39D0670> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details. WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x0000017BB3AE83A0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.
这是 TensorFlow 在运行时输出的一些警告信息。其中包含了以下几个内容:
1. TensorFlow 检测到了一个 GPU 设备,但由于该设备的 CUDA 计算能力版本太低(2.1),不满足 TensorFlow 最低要求(3.5),因此被忽略。
2. TensorFlow 检测到了一些 CPU 功能,包括 AVX 和 AVX2 指令集。这些指令集可以在一些性能关键的操作中加速计算。为了在其他操作中启用它们,需要使用适当的编译器标志重新构建 TensorFlow。
3. TensorFlow 输出了两个关于 tf.function 的警告信息。这些信息表明,在某些情况下,使用 tf.function 可能会导致 TensorFlow 重新跟踪函数的执行图,并且跟踪是一项昂贵的操作。这可能是由于多次在循环中重复定义 tf.function,或者传递了不同形状的张量,或者传递了 Python 对象而不是张量等原因。为了避免不必要的跟踪,建议将 tf.function 定义在循环外部,或使用实验性的 experimental_relax_shapes=True 选项来松弛参数形状。可以参考 TensorFlow 的文档了解更多细节。
翻译:Enabling the USB UDC stack regardless of Type-C and charger type detection output can be achieved by configuring the USB controller and the USB gadget driver in the kernel. You can do this by modifying the kernel configuration file. Here are the general steps to enable the USB UDC stack in the kernel: Open the kernel configuration file using a text editor, such as nano or vi. Search for the USB gadget driver configuration options. These options are usually located under the "USB Gadget Support" configuration menu. Enable the USB gadget driver by selecting the appropriate option. This option may be named "USB Gadget Drivers" or "Gadget driver support". Configure the USB controller by selecting the appropriate option. This option may be named "USB Peripheral Controller" or "USB Device Controller". Save the changes to the kernel configuration file and exit the text editor. Recompile and rebuild the kernel. Once the kernel is rebuilt and the USB UDC stack is enabled, the USB gadget driver should be able to detect and communicate with USB devices regardless of Type-C and charger type detection output.
在内核中配置USB控制器和USB gadget驱动程序可以实现不考虑Type-C和充电器类型检测输出而启用USB UDC堆栈。您可以通过修改内核配置文件来完成这一点。以下是启用内核中USB UDC堆栈的一般步骤:
1. 使用文本编辑器(如nano或vi)打开内核配置文件。
2. 搜索USB gadget驱动程序配置选项。这些选项通常位于“USB Gadget Support”配置菜单下。
3. 通过选择适当的选项来启用USB gadget驱动程序。此选项可能被命名为“USB Gadget Drivers”或“Gadget driver support”。
4. 通过选择适当的选项来配置USB控制器。此选项可能被命名为“USB Peripheral Controller”或“USB Device Controller”。
5. 保存更改到内核配置文件并退出文本编辑器。
6. 重新编译和重建内核。
一旦内核被重建并启用了USB UDC堆栈,USB gadget驱动程序应该能够检测并与USB设备进行通信,而不考虑Type-C和充电器类型检测输出。
阅读全文