[CI] Refine comment-preview-urls

.github/workflows/Preview-Url-Comment.yml

@@ -2,7 +2,9 @@ name: Comment Preview URLs
 
 on:
   workflow_run:
-    workflows: ["Doc-Preview"]
+    # A workflow triggered by workflow_run cannot directly be triggered by a workflow that only has the workflow_call trigger.
+    # TODO(ooooo): So now change it to CI-Build, but comment is not timely, at least it's better than nothing.
+    workflows: ["CI-Build"]
     types:
       - completed
 
@@ -14,6 +16,7 @@ jobs:
       github.event.workflow_run.event == 'pull_request' &&
       github.event.workflow_run.conclusion == 'success'
     permissions:
+      actions: read
       pull-requests: write
 
     steps:

.github/workflows/_Doc-Preview.yml

@@ -143,7 +143,7 @@ jobs:
           path: |
             comment_body.txt
             pr_number.txt
-          retention-days: 1
+          retention-days: 7
 
       - name: Terminate and delete the container
         if: always()

python/paddle/nn/layer/pooling.py

@@ -170,12 +170,15 @@ class AvgPool2D(Layer):
             it must contain two integers, (pool_stride_Height, pool_stride_Width).
             Otherwise, the pool stride size will be a square of an int.
             Default None, then stride will be equal to the kernel_size.
-        padding(str|int|list|tuple, optional): The padding size. Padding could be in one of the following forms.
+        padding(str|int|list|tuple, optional): The padding size.
+            Padding could be in one of the following forms:
+
             1. A string in ['valid', 'same'].
             2. An int, which means the feature map is zero padded by size of `padding` on every sides.
             3. A list[int] or tuple(int) whose length is 2, [pad_height, pad_weight] whose value means the padding size of each dimension.
             4. A list[int] or tuple(int) whose length is 4. [pad_height_top, pad_height_bottom, pad_width_left, pad_width_right] whose value means the padding size of each side.
             5. A list or tuple of pairs of integers. It has the form [[pad_before, pad_after], [pad_before, pad_after], ...]. Note that, the batch dimension and channel dimension should be [0,0] or (0,0).
+
             The default value is 0.
         ceil_mode(bool, optional): When True, will use `ceil` instead of `floor` to compute the output shape.
         exclusive(bool, optional): Whether to exclude padding points in average pooling