translate compiled_program (#780)

* translate compiled_program

* Update doc/fluid/api_guides/low_level/compiled_program_cn.rst
Co-Authored-By: Nacosta123 <42226556+acosta123@users.noreply.github.com>

* Update doc/fluid/api_guides/low_level/compiled_program_cn.rst
Co-Authored-By: Nacosta123 <42226556+acosta123@users.noreply.github.com>

* Update doc/fluid/api_guides/low_level/compiled_program_cn.rst
Co-Authored-By: Nacosta123 <42226556+acosta123@users.noreply.github.com>

doc/fluid/api_guides/low_level/compiled_program_cn.rst

+..  _api_guide_compiled_program:
+
+################
+CompiledProgram
+################
+
+:ref:`cn_api_fluid_CompiledProgram` 用于把程序转化为不同的优化组合。例如，你可以使用with_data_parallel将程序转化为数据并行程序，使其能够运行在多个设备上。 
+
+
+.. code-block:: python
+
+    # 注释：
+    #   - 如果你想在ParallelExecutor中指定用于运行的GPU卡，需要在环境中定义
+    #     CUDA_VISIBLE_DEVICES
+    #   - 如果你想在ParallelExecutor中使用多CPU来运行程序，需要在环境中定义
+    #     CPU_NUM
+    
+    # 首先创建Executor。
+    place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+    exe = fluid.Executor(place)
+    # 运行启动程序仅一次。
+    exe.run(fluid.default_startup_program())
+    
+    # 直接运行主程序，无需编译。
+    loss = exe.run(fluid.default_main_program(),
+                    feed=feed_dict,
+                    fetch_list=[loss.name])
+    
+    # 或者编译程序后用数据并行方式运行模型。
+    exec_strategy = fluid.ExecutionStrategy()
+    exec_strategy.num_threads = dev_count * 4 # the size of thread pool.
+    build_strategy = fluid.BuildStrategy()
+    build_strategy.memory_optimize = True if memory_opt else False  
+    compiled_prog = compiler.CompiledProgram(
+        fluid.default_main_program()).with_data_parallel(
+            loss_name=loss.name,
+            build_strategy=build_strategy,
+            exec_strategy=exec_strategy)
+    loss, = exe.run(compiled_prog,
+                    feed=feed_dict,
+                    fetch_list=[loss.name])
+                    
+- 相关API :
+
+ - :ref:`cn_api_fluid_CompiledProgram`