paddle.v2.layer.l2_distanceThis layer calculates and returns the Euclidean distance between two input +vectors x and y. The equation is as follows:
+The output size of this layer is fixed to be 1. Note that the above +computation is for one sample. Multiple samples are processed in one batch.
+The example usage is:
+l2_sim = l2_distance(x=layer1, y=layer2)
+| Parameters: |
|
+
|---|---|
| Returns: | The returned paddle.v2.config_base.Layer object. + |
+
| Return type: | paddle.v2.config_base.Layer + |
+
IfElse Operator","Design Doc: InferVarType","Design Doc: Model Format","Paddle\u591a\u8bed\u8a00\u63a5\u53e3\u5b9e\u73b0","C-API \u6a21\u578b\u63a8\u65ad\u5b9e\u73b0\u6587\u6863","RNNOp design","Design: Sequence Decoder Generating LoDTensors","Optimizer Design","Averaging Parameter in PaddlePaddle","Design Doc: The C++ Class Parameters","Design Doc: PaddlePaddle Programs","Prune","Design Doc: Python API","Python Data Reader Design Doc","Design Doc: Distributed Training Architecture","Design Doc: Operation Graph Based Parameter Server","Design Doc: Session","Design Doc: Refactorization Overview","Design Doc: Gradient Operators Registration","Regularization in PaddlePaddle","PaddlePaddle\u53d1\u884c\u89c4\u8303","Design of Scope in Paddle","Design Doc: Selected Rows","Interaction between C++ and Python","Design for TensorArray","Background","Simple Linear Regression","Installing from Sources","PaddlePaddle in Docker Containers","Install and Build","GET STARTED","RNN Models","RNN Configuration","Build PaddlePaddle from Source Code and Run Unit Test","Contribute Code","Write New Layers","How to write a new operator","How to use Eigen in Paddle","HOW TO","Tune GPU Performance","PaddlePaddle Distributed Training","Argument Outline","Detail Description","Set Command-line Parameters","Use Case","Distributed PaddlePaddle Training on AWS with Kubernetes","Paddle On Kubernetes","<no title>","<no title>","PaddlePaddle Documentation","Build PaddlePaddle for Android","Build PaddlePaddle for Raspberry Pi","MOBILE","Cluster bootstrapping tool survey","<no title>","Chinese Word Embedding Model Tutorial","Generative Adversarial Networks (GAN)","Model Zoo - ImageNet","Quick 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\ No newline at end of file
diff --git a/develop/doc_cn/_sources/api/v2/config/layer.rst.txt b/develop/doc_cn/_sources/api/v2/config/layer.rst.txt
index b2b55ec419d2f8453e067f202f6c1b7da6c201de..d4d182f6692e09b3e40f3620b77d9a0f20ec5af3 100644
--- a/develop/doc_cn/_sources/api/v2/config/layer.rst.txt
+++ b/develop/doc_cn/_sources/api/v2/config/layer.rst.txt
@@ -382,6 +382,11 @@ cos_sim
.. autoclass:: paddle.v2.layer.cos_sim
:noindex:
+l2_distance
+-----------
+.. autoclass:: paddle.v2.layer.l2_distance
+ :noindex:
+
trans
-----
.. autoclass:: paddle.v2.layer.trans
diff --git a/develop/doc_cn/api/v2/config/layer.html b/develop/doc_cn/api/v2/config/layer.html
index f22ec0719e54e01bb9437687fcaff5f39f063cc9..0aed0a16a6e2a41c9526e47154bda82eebc073b6 100644
--- a/develop/doc_cn/api/v2/config/layer.html
+++ b/develop/doc_cn/api/v2/config/layer.html
@@ -3150,6 +3150,49 @@ processed in one batch.
+paddle.v2.layer.l2_distanceThis layer calculates and returns the Euclidean distance between two input +vectors x and y. The equation is as follows:
+The output size of this layer is fixed to be 1. Note that the above +computation is for one sample. Multiple samples are processed in one batch.
+The example usage is:
+l2_sim = l2_distance(x=layer1, y=layer2)
+| 参数: |
|
+
|---|---|
| 返回: | The returned paddle.v2.config_base.Layer object. + |
+
| 返回类型: | paddle.v2.config_base.Layer + |
+
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