From 47af5c3c9dbc58d7a8c771bfef2f2d4b177574bd Mon Sep 17 00:00:00 2001
From: Guanghua Yu <742925032@qq.com>
Date: Thu, 26 Nov 2020 10:17:17 +0800
Subject: [PATCH] fix smooth_l1_loss en docs (#29093)

---
 python/paddle/nn/functional/loss.py | 7 +++----
 python/paddle/nn/layer/loss.py      | 9 ++++-----
 2 files changed, 7 insertions(+), 9 deletions(-)

diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py
index cfdeb25c24..cce8f9da13 100755
--- a/python/paddle/nn/functional/loss.py
+++ b/python/paddle/nn/functional/loss.py
@@ -469,14 +469,14 @@ def smooth_l1_loss(input, label, reduction='mean', delta=1.0, name=None):
 
     .. math::
 
-         loss(x,y)=\\frac{1}{n}\\sum_{i}z_i
+         loss(x,y) = \\frac{1}{n}\\sum_{i}z_i
 
 
     where z_i is given by:
 
     .. math::
 
-         \\mathop{z_i}=\\left\\{\\begin{array}{rcl}
+         \\mathop{z_i} = \\left\\{\\begin{array}{rcl}
         0.5(x_i - y_i)^2 & & {if |x_i - y_i| < delta} \\\\
         delta * |x_i - y_i| - 0.5 * delta^2 & & {otherwise}
         \\end{array} \\right.
@@ -511,13 +511,12 @@ def smooth_l1_loss(input, label, reduction='mean', delta=1.0, name=None):
             import paddle
             import numpy as np
 
-            paddle.disable_static()
             input_data = np.random.rand(3,3).astype("float32")
             label_data = np.random.rand(3,3).astype("float32")
             input = paddle.to_tensor(input_data)
             label = paddle.to_tensor(label_data)
             output = paddle.nn.functioanl.smooth_l1_loss(input, label)
-            print(output.numpy())
+            print(output)
     """
     fluid.data_feeder.check_variable_and_dtype(
         input, 'input', ['float32', 'float64'], 'smooth_l1_loss')
diff --git a/python/paddle/nn/layer/loss.py b/python/paddle/nn/layer/loss.py
index 5bc33d0f0f..de5048a278 100644
--- a/python/paddle/nn/layer/loss.py
+++ b/python/paddle/nn/layer/loss.py
@@ -971,13 +971,13 @@ class SmoothL1Loss(fluid.dygraph.Layer):
 
     .. math::
 
-         loss(x,y)=\\frac{1}{n}\\sum_{i}z_i
+         loss(x,y) = \\frac{1}{n}\\sum_{i}z_i
 
     where z_i is given by:
 
     .. math::
 
-         \\mathop{z_i}=\\left\\{\\begin{array}{rcl}
+         \\mathop{z_i} = \\left\\{\\begin{array}{rcl}
         0.5(x_i - y_i)^2 & & {if |x_i - y_i| < delta} \\\\
         delta * |x_i - y_i| - 0.5 * delta^2 & & {otherwise}
         \\end{array} \\right.
@@ -1004,7 +1004,7 @@ class SmoothL1Loss(fluid.dygraph.Layer):
             is the same as the shape of input.
 
     Returns:
-        The tensor variable storing the smooth_l1_loss of input and label.
+        The tensor storing the smooth_l1_loss of input and label.
 
     Return type: Tensor.
 
@@ -1013,14 +1013,13 @@ class SmoothL1Loss(fluid.dygraph.Layer):
 
             import paddle
             import numpy as np
-            paddle.disable_static()
             input_data = np.random.rand(3,3).astype("float32")
             label_data = np.random.rand(3,3).astype("float32")
             input = paddle.to_tensor(input_data)
             label = paddle.to_tensor(label_data)
             loss = paddle.nn.SmoothL1Loss()
             output = loss(input, label)
-            print(output.numpy())
+            print(output)
     """
 
     def __init__(self, reduction='mean', delta=1.0, name=None):
-- 
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