From 12aca860bf24ddc05a06722c1fc11ff3cfedc893 Mon Sep 17 00:00:00 2001
From: Yang Yu <yuyang18@baidu.com>
Date: Thu, 11 Jan 2018 11:03:54 +0800
Subject: [PATCH] Add comment

---
 .../paddle/v2/fluid/tests/test_parallel_op.py | 58 ++++++++++++++++---
 1 file changed, 51 insertions(+), 7 deletions(-)

diff --git a/python/paddle/v2/fluid/tests/test_parallel_op.py b/python/paddle/v2/fluid/tests/test_parallel_op.py
index 049ae0fe28d..dde7206e4fd 100644
--- a/python/paddle/v2/fluid/tests/test_parallel_op.py
+++ b/python/paddle/v2/fluid/tests/test_parallel_op.py
@@ -4,15 +4,35 @@ import numpy
 
 
 class BaseParallelForTest(unittest.TestCase):
-    def main(self, callback, feed, fetch):
+    def run_test(self, callback, feed, fetch):
+        """
+        Run the unittest for parallel.for
+        Args:
+            callback(callable): A callable function returns a generator. There 
+                are two yields in the generator function. The first yield 
+                returns the data layers, and the second yield returns the loss. 
+                The modified data variables will be sent back during the first 
+                yield.
+            
+            feed(dict): The executor feeding dictionary.
+            fetch(list|basestr): The fetch name lists. 
+
+        Returns:
+            None
+            
+        Raises:
+            AssertionError when the computation of cpu, parallel.for in cpu, 
+                gpu, parallel.for in gpu are different.
+
+        """
         cpu = fluid.CPUPlace()
-        result_cpu = self._main_impl_(
+        result_cpu = self._run_test_impl_(
             callback=callback,
             feed=feed,
             fetch=fetch,
             place=cpu,
             use_parallel=False)
-        result_cpu_parallel = self._main_impl_(
+        result_cpu_parallel = self._run_test_impl_(
             callback=callback,
             feed=feed,
             fetch=fetch,
@@ -20,13 +40,13 @@ class BaseParallelForTest(unittest.TestCase):
             use_parallel=True)
         if fluid.core.is_compile_gpu():
             gpu = fluid.CUDAPlace(0)
-            result_gpu = self._main_impl_(
+            result_gpu = self._run_test_impl_(
                 callback=callback,
                 feed=feed,
                 fetch=fetch,
                 place=gpu,
                 use_parallel=False)
-            result_gpu_parallel = self._main_impl_(
+            result_gpu_parallel = self._run_test_impl_(
                 callback=callback,
                 feed=feed,
                 fetch=fetch,
@@ -37,7 +57,17 @@ class BaseParallelForTest(unittest.TestCase):
         else:
             self._assert_same_(fetch, result_cpu, result_cpu_parallel)
 
-    def _main_impl_(self, callback, feed, fetch, place, use_parallel=False):
+    def _run_test_impl_(self, callback, feed, fetch, place, use_parallel=False):
+        """
+        Run a single test, returns the fetch values
+        Args:
+            place(Place): the computation place. 
+            use_parallel(bool): Whether use parallel.for or not. 
+
+        Returns:
+            Fetched numpy arrays.
+
+        """
         if isinstance(fetch, basestring):
             fetch = [fetch]
         main = fluid.Program()
@@ -77,6 +107,20 @@ class BaseParallelForTest(unittest.TestCase):
         return exe.run(main, feed=feed, fetch_list=fetch)
 
     def _assert_same_(self, fetch, *args):
+        """
+        Assert the return values of `run_test` are same.
+        Args:
+            fetch: Fetch list. Used for print error message
+            *args: The fetch result lists of each situations.
+
+        Returns:
+            None
+            
+        Raises:
+            AssertionError
+
+        """
+
         def _impl_(a, b, fetch_id, item_id):
             item_str = ['CPU', 'ParallelCPU', 'GPU', 'ParallelGPU']
             flag = numpy.allclose(a, b, rtol=0.1)
@@ -100,7 +144,7 @@ class ParallelOpTest(BaseParallelForTest):
             loss = fluid.layers.mean(x=hidden)
             yield loss
 
-        self.main(
+        self.run_test(
             callback=__network__,
             feed={
                 'img': numpy.random.random(size=(128, 784)).astype('float32')
-- 
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