From 0ec84a54bf7f024e5e50bf77f9f63b4d53106a04 Mon Sep 17 00:00:00 2001
From: yoyoIcy <142126786+yoyoIcy@users.noreply.github.com>
Date: Sun, 10 Sep 2023 22:55:37 -0500
Subject: [PATCH]  Open [xdoctest][task 315] reformat example code with google
 style in python/paddle/sparse/nn/layer/conv.py (#57133)

---
 python/paddle/sparse/nn/layer/conv.py | 96 +++++++++++++--------------
 1 file changed, 48 insertions(+), 48 deletions(-)

diff --git a/python/paddle/sparse/nn/layer/conv.py b/python/paddle/sparse/nn/layer/conv.py
index 4c77947c2ebaa2..d3295148fbc15e 100644
--- a/python/paddle/sparse/nn/layer/conv.py
+++ b/python/paddle/sparse/nn/layer/conv.py
@@ -326,18 +326,18 @@ class Conv3D(_Conv3D):
 
         .. code-block:: python
 
-          import paddle
-
-          indices = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
-          values = [[1], [2], [3], [4]]
-          indices = paddle.to_tensor(indices, dtype='int32')
-          values = paddle.to_tensor(values, dtype='float32')
-          dense_shape = [1, 1, 3, 4, 1]
-          sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
-          conv = paddle.sparse.nn.Conv3D(1, 1, (1, 3, 3))
-          y = conv(sparse_x)
-          print(y.shape)
-          # (1, 1, 1, 2, 1)
+            >>> import paddle
+
+            >>> indices = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
+            >>> values = [[1], [2], [3], [4]]
+            >>> indices = paddle.to_tensor(indices, dtype='int32')
+            >>> values = paddle.to_tensor(values, dtype='float32')
+            >>> dense_shape = [1, 1, 3, 4, 1]
+            >>> sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
+            >>> conv = paddle.sparse.nn.Conv3D(1, 1, (1, 3, 3))
+            >>> y = conv(sparse_x)
+            >>> print(y.shape)
+            [1, 1, 1, 2, 1]
     """
 
     def __init__(
@@ -461,18 +461,18 @@ class Conv2D(_Conv2D):
 
         .. code-block:: python
 
-          import paddle
-
-          indices = [[0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
-          values = [[1], [2], [3], [4]]
-          indices = paddle.to_tensor(indices, dtype='int32')
-          values = paddle.to_tensor(values, dtype='float32')
-          dense_shape = [1, 3, 4, 1]
-          sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
-          conv = paddle.sparse.nn.Conv2D(1, 1, (3, 3))
-          y = conv(sparse_x)
-          print(y.shape)
-          # (1, 1, 2, 1)
+            >>> import paddle
+
+            >>> indices = [[0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
+            >>> values = [[1], [2], [3], [4]]
+            >>> indices = paddle.to_tensor(indices, dtype='int32')
+            >>> values = paddle.to_tensor(values, dtype='float32')
+            >>> dense_shape = [1, 3, 4, 1]
+            >>> sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
+            >>> conv = paddle.sparse.nn.Conv2D(1, 1, (3, 3))
+            >>> y = conv(sparse_x)
+            >>> print(y.shape)
+            [1, 1, 2, 1]
     """
 
     def __init__(
@@ -600,18 +600,18 @@ class SubmConv3D(_Conv3D):
 
         .. code-block:: python
 
-          import paddle
-
-          indices = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
-          values = [[1], [2], [3], [4]]
-          dense_shape = [1, 1, 3, 4, 1]
-          indices = paddle.to_tensor(indices, dtype='int32')
-          values = paddle.to_tensor(values, dtype='float32')
-          sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
-          subm_conv = paddle.sparse.nn.SubmConv3D(1, 1, (1, 3, 3))
-          y = subm_conv(sparse_x)
-          print(y.shape)
-          # (1, 1, 3, 4, 1)
+            >>> import paddle
+
+            >>> indices = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
+            >>> values = [[1], [2], [3], [4]]
+            >>> dense_shape = [1, 1, 3, 4, 1]
+            >>> indices = paddle.to_tensor(indices, dtype='int32')
+            >>> values = paddle.to_tensor(values, dtype='float32')
+            >>> sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
+            >>> subm_conv = paddle.sparse.nn.SubmConv3D(1, 1, (1, 3, 3))
+            >>> y = subm_conv(sparse_x)
+            >>> print(y.shape)
+            [1, 1, 3, 4, 1]
     """
 
     def __init__(
@@ -740,18 +740,18 @@ class SubmConv2D(_Conv2D):
 
         .. code-block:: python
 
-          import paddle
-
-          indices = [[0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
-          values = [[1], [2], [3], [4]]
-          dense_shape = [1, 3, 4, 1]
-          indices = paddle.to_tensor(indices, dtype='int32')
-          values = paddle.to_tensor(values, dtype='float32')
-          sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
-          subm_conv = paddle.sparse.nn.SubmConv2D(1, 1, (3, 3))
-          y = subm_conv(sparse_x)
-          print(y.shape)
-          # (1, 3, 4, 1)
+            >>> import paddle
+
+            >>> indices = [[0, 0, 0, 0], [0, 0, 1, 2], [1, 3, 2, 3]]
+            >>> values = [[1], [2], [3], [4]]
+            >>> dense_shape = [1, 3, 4, 1]
+            >>> indices = paddle.to_tensor(indices, dtype='int32')
+            >>> values = paddle.to_tensor(values, dtype='float32')
+            >>> sparse_x = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape, stop_gradient=True)
+            >>> subm_conv = paddle.sparse.nn.SubmConv2D(1, 1, (3, 3))
+            >>> y = subm_conv(sparse_x)
+            >>> print(y.shape)
+            [1, 3, 4, 1]
     """
 
     def __init__(