修改COPY-FROM No.15 regularizer (#5961)

PaddlePaddle · Jul 5, 2023 · 299f4f5 · 299f4f5
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diff --git a/docs/api/paddle/regularizer/L1Decay_cn.rst b/docs/api/paddle/regularizer/L1Decay_cn.rst
@@ -28,44 +28,10 @@ L1Decay 实现 L1 权重衰减正则化，用于模型训练，使得权重矩
 代码示例 1
 ::::::::::::
 
-.. code-block:: python
-
-    # Example1: set Regularizer in optimizer
-    import paddle
-    from paddle.regularizer import L1Decay
-    import numpy as np
-    linear = paddle.nn.Linear(10, 10)
-    inp = paddle.rand(shape=[10, 10], dtype="float32")
-    out = linear(inp)
-    loss = paddle.mean(out)
-    beta1 = paddle.to_tensor([0.9], dtype="float32")
-    beta2 = paddle.to_tensor([0.99], dtype="float32")
-    momentum = paddle.optimizer.Momentum(
-        learning_rate=0.1,
-        parameters=linear.parameters(),
-        weight_decay=L1Decay(0.0001))
-    back = out.backward()
-    momentum.step()
-    momentum.clear_grad()
+COPY-FROM: paddle.regularizer.L1Decay:code-example1
 
 
 代码示例 2
 ::::::::::::
 
-.. code-block:: python
-
-    # Example2: set Regularizer in parameters
-    # Set L1 regularization in parameters.
-    # Global regularizer does not take effect on my_conv2d for this case.
-    from paddle.nn import Conv2D
-    from paddle import ParamAttr
-    from paddle.regularizer import L2Decay
-
-    my_conv2d = Conv2D(
-                    in_channels=10,
-                    out_channels=10,
-                    kernel_size=1,
-                    stride=1,
-                    padding=0,
-                    weight_attr=ParamAttr(regularizer=L2Decay(coeff=0.01)),
-                    bias_attr=False)
+COPY-FROM: paddle.regularizer.L1Decay:code-example2
diff --git a/docs/api/paddle/regularizer/L2Decay_cn.rst b/docs/api/paddle/regularizer/L2Decay_cn.rst
@@ -28,44 +28,10 @@ L2Decay 实现 L2 权重衰减正则化，用于模型训练，有助于防止
 代码示例 1
 ::::::::::::
 
-.. code-block:: python
-
-    # Example1: set Regularizer in optimizer
-    import paddle
-    from paddle.regularizer import L2Decay
-    import numpy as np
-    linear = paddle.nn.Linear(10, 10)
-    inp = paddle.rand(shape=[10, 10], dtype="float32")
-    out = linear(inp)
-    loss = paddle.mean(out)
-    beta1 = paddle.to_tensor([0.9], dtype="float32")
-    beta2 = paddle.to_tensor([0.99], dtype="float32")
-    momentum = paddle.optimizer.Momentum(
-        learning_rate=0.1,
-        parameters=linear.parameters(),
-        weight_decay=L2Decay(0.0001))
-    back = out.backward()
-    momentum.step()
-    momentum.clear_grad()
+COPY-FROM: paddle.regularizer.L2Decay:code-example1
 
 
 代码示例 2
 ::::::::::::
 
-.. code-block:: python
-
-    # Example2: set Regularizer in parameters
-    # Set L2 regularization in parameters.
-    # Global regularizer does not take effect on my_conv2d for this case.
-    from paddle.nn import Conv2D
-    from paddle import ParamAttr
-    from paddle.regularizer import L2Decay
-
-    my_conv2d = Conv2D(
-            in_channels=10,
-            out_channels=10,
-            kernel_size=1,
-            stride=1,
-            padding=0,
-            weight_attr=ParamAttr(regularizer=L2Decay(coeff=0.01)),
-            bias_attr=False)
+COPY-FROM: paddle.regularizer.L2Decay:code-example2