[Docs] Fix invalid single-backticks usage in guides docs (Batch 4) (#7872)

Co-authored-by: ooo oo <106524776+ooooo-create@users.noreply.github.com>

Author: Noai-oss

docs/guides/advanced/gradient_clip_cn.rst

@@ -64,7 +64,7 @@
 
 部分参数裁剪需要设置参数的 :ref:`paddle.ParamAttr <cn_api_paddle_ParamAttr>` ，其中的 ``need_clip`` 默认为 True，表示需要裁剪，如果设置为 False，则不会裁剪。
 
-例如：仅裁剪 `linear` 中 `weight` 的梯度，则需要在创建 `linear` 层时设置 `bias_attr` 如下：
+例如：仅裁剪 ``linear`` 中 ``weight`` 的梯度，则需要在创建 ``linear`` 层时设置 ``bias_attr`` 如下：
 
 .. code:: ipython3
 
@@ -113,7 +113,7 @@
 
 部分参数裁剪的设置方式与上面一致，也是通过设置参数的 :ref:`paddle.ParamAttr <cn_api_paddle_ParamAttr>` ，其中的 ``need_clip`` 默认为 True，表示需要裁剪，如果设置为 False，则不会裁剪。
 
-例如：仅裁剪 `linear` 中 `bias` 的梯度，则需要在创建 `linear` 层时设置 `weight_attr` 如下：
+例如：仅裁剪 ``linear`` 中 ``bias`` 的梯度，则需要在创建 ``linear`` 层时设置 ``weight_attr`` 如下：
 
 .. code:: ipython3
 

docs/guides/advanced/gradient_clip_en.rst

@@ -32,10 +32,10 @@ You can also clip gradients of a part of parameters as follow:
 
 **b. Clip a part of gradients**
 
-You can clip a part of gradients by setting `need_clip` of ref:`cn_api_fluid_ParamAttr` . `need_clip` is `True` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped.
+You can clip a part of gradients by setting ``need_clip`` of :ref:`cn_api_fluid_ParamAttr` . ``need_clip`` is ``True`` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped.
 
 For example:
-If only clip the gradient of `weight` in `linear`, you should set `bias_attr` as follow:
+If only clip the gradient of ``weight`` in ``linear``, you should set ``bias_attr`` as follow:
 
 .. code:: ipython3
 
@@ -80,10 +80,10 @@ You can also clip gradients of a part of parameters as follow:
 
 **b. Clip a part of gradients**
 
-You can clip a part of gradients by setting `need_clip` of ref:`cn_api_fluid_ParamAttr` . `need_clip` is `True` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped.
+You can clip a part of gradients by setting ``need_clip`` of :ref:`cn_api_fluid_ParamAttr` . ``need_clip`` is ``True`` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped.
 
 For example:
-If only clip the gradient of `bias` in `linear`, you should set `weight_attr` as follow:
+If only clip the gradient of ``bias`` in ``linear``, you should set ``weight_attr`` as follow:
 
 .. code:: ipython3
 
@@ -131,4 +131,4 @@ You can also clip gradients of a part of parameters as follow:
 
 **b. Clip a part of gradients**
 
-You can clip a part of gradients by setting `need_clip` of ref:`cn_api_fluid_ParamAttr` . `need_clip` is `True` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped. Refer to the sample code above.
+You can clip a part of gradients by setting ``need_clip`` of :ref:`cn_api_fluid_ParamAttr` . ``need_clip`` is ``True`` by default, which represents that its gradient will be clipped. Otherwise, its gradient will not be clipped. Refer to the sample code above.

docs/guides/beginner/index_cn.rst

@@ -8,7 +8,7 @@
 
 当完成了快速上手的任务后，下面这些模块会阐述如何用飞桨框架 2.0，实现深度学习过程中的每一步。具体包括：
 
-- `Tensor 介绍 <./tensor_cn.html>`_ : 介绍飞桨基本数据类型 `Tensor` 的概念与常见用法。
+- `Tensor 介绍 <./tensor_cn.html>`_ : 介绍飞桨基本数据类型 ``Tensor`` 的概念与常见用法。
 - `数据集定义与加载 <./data_load_cn.html>`_ : 飞桨框架数据加载的方式，主要为\ ``paddle.io.Dataset + paddle.io.DataLoader``\ ，以及飞桨内置数据集的介绍。
 - `数据预处理 <./data_preprocessing_cn.html>`_ : 飞桨框架数据预处理的方法，主要是\ ``paddle.vision.transform.*``\ 。
 - `模型组网 <./model_cn.html>`_ : 飞桨框架组网 API 的介绍，主要是\ ``paddle.nn.*``\ ，然后是飞桨框架组网方式的介绍，即 Sequential 的组网与 SubClass 的组网。

docs/guides/flags/debug_cn.rst

@@ -22,7 +22,7 @@ FLAGS_cpu_deterministic
 *******************************************
 (始于 0.15.0)
 
-该 flag 用于调试。它表示是否在 CPU 侧确定计算结果。 在某些情况下，不同求和次序的结果可能不同，例如，`a+b+c+d` 的结果可能与 `c+a+b+d` 的结果不同。
+该 flag 用于调试。它表示是否在 CPU 侧确定计算结果。 在某些情况下，不同求和次序的结果可能不同，例如，``a+b+c+d`` 的结果可能与 ``c+a+b+d`` 的结果不同。
 
 取值范围
 ---------------

docs/guides/flags/debug_en.rst

@@ -21,7 +21,7 @@ FLAGS_cpu_deterministic
 *******************************************
 (since 0.15.0)
 
-This Flag is used for debugging. It indicates whether to make the result of computation deterministic in CPU side. In some case, the result of the different order of summing maybe different，for example, the result of `a+b+c+d` may be different with the result of `c+a+b+d`.
+This Flag is used for debugging. It indicates whether to make the result of computation deterministic in CPU side. In some case, the result of the different order of summing maybe different，for example, the result of ``a+b+c+d`` may be different with the result of ``c+a+b+d``.
 
 Values accepted
 ---------------

docs/guides/flags/npu_cn.rst

@@ -8,7 +8,7 @@ FLAGS_npu_precision_mode
 *******************************************
 (develop)
 
-FLAGS_npu_precision_mode 用于配置昇腾 NPU 芯片算子精度模式。仅在编译选项选择`WITH_ASCEND_CL = ON`时有效。
+FLAGS_npu_precision_mode 用于配置昇腾 NPU 芯片算子精度模式。仅在编译选项选择 ``WITH_ASCEND_CL = ON`` 时有效。
 
 取值范围
 ---------------

docs/guides/flags/npu_en.rst

@@ -8,7 +8,7 @@ FLAGS_npu_precision_mode
 *******************************************
 (develop)
 
-FLAGS_npu_precision_mode is used to set the operator precision mode of Ascend Devices. Only valid when compiled `WITH_ASCEND_CL = ON`.
+FLAGS_npu_precision_mode is used to set the operator precision mode of Ascend Devices. Only valid when compiled ``WITH_ASCEND_CL = ON``.
 
 Values accepted
 ---------------

docs/guides/flags/others_cn.rst

@@ -57,22 +57,22 @@ FLAGS_sync_nccl_allreduce
 *******************************************
 (始于 1.3)
 
-如果 FLAGS_sync_nccl_allreduce 为 True，则会在 allreduce_op_handle 中调用 `cudaStreamSynchronize（nccl_stream）` ，这种模式在某些情况下可以获得更好的性能。
+如果 FLAGS_sync_nccl_allreduce 为 True，则会在 allreduce_op_handle 中调用 ``cudaStreamSynchronize（nccl_stream）`` ，这种模式在某些情况下可以获得更好的性能。
 
 取值范围
 ---------------
 Bool 型，缺省值为 True。
 
 示例
 -------
-FLAGS_sync_nccl_allreduce=True - 在 allreduce_op_handle 中调用 `cudaStreamSynchronize(nccl_stream)` 。
+FLAGS_sync_nccl_allreduce=True - 在 allreduce_op_handle 中调用 ``cudaStreamSynchronize(nccl_stream)`` 。
 
 
 FLAGS_tracer_profile_fname
 *******************************************
 (始于 1.4.0)
 
-FLAGS_tracer_profile_fname 表示由 gperftools 生成的命令式跟踪器的分析器文件名。仅在编译选项选择`WITH_PROFILER = ON`时有效。如果禁用则设为 empty。
+FLAGS_tracer_profile_fname 表示由 gperftools 生成的命令式跟踪器的分析器文件名。仅在编译选项选择 ``WITH_PROFILER = ON`` 时有效。如果禁用则设为 empty。
 
 取值范围
 ---------------

docs/guides/flags/others_en.rst

@@ -57,22 +57,22 @@ FLAGS_sync_nccl_allreduce
 *******************************************
 (since 1.3)
 
-If the FLAGS_sync_nccl_allreduce is true, there will call `cudaStreamSynchronize(nccl_stream)` in allreduce_op_handle, this mode can get better performance in some scenarios.
+If the FLAGS_sync_nccl_allreduce is true, there will call ``cudaStreamSynchronize(nccl_stream)`` in allreduce_op_handle, this mode can get better performance in some scenarios.
 
 Values accepted
 ---------------
 Bool. The default value is True.
 
 Example
 -------
-FLAGS_sync_nccl_allreduce=True will call `cudaStreamSynchronize(nccl_stream)` in allreduce_op_handle.
+FLAGS_sync_nccl_allreduce=True will call ``cudaStreamSynchronize(nccl_stream)`` in allreduce_op_handle.
 
 
 FLAGS_tracer_profile_fname
 *******************************************
 (since 1.4.0)
 
-FLAGS_tracer_profile_fname indicates the profiler filename for imperative tracer, which generated by gperftools. Only valid when compiled `WITH_PROFILER=ON`. Empty if disabled.
+FLAGS_tracer_profile_fname indicates the profiler filename for imperative tracer, which generated by gperftools. Only valid when compiled ``WITH_PROFILER=ON``. Empty if disabled.
 
 Values accepted
 ---------------