From ada70b8c26c373e8ebf1b2a3c19f687036ac131c Mon Sep 17 00:00:00 2001 From: Travis CI Date: Tue, 2 Jan 2018 23:17:10 +0000 Subject: [PATCH] Deploy to GitHub Pages: 87f46ebb368929feae76b7d909944b317d7dad92 --- develop/doc/api/v2/fluid/layers.html | 39 +++++++++++++++++++++++-- develop/doc/searchindex.js | 2 +- develop/doc_cn/api/v2/fluid/layers.html | 39 +++++++++++++++++++++++-- develop/doc_cn/searchindex.js | 2 +- 4 files changed, 76 insertions(+), 6 deletions(-) diff --git a/develop/doc/api/v2/fluid/layers.html b/develop/doc/api/v2/fluid/layers.html index 14cdc61d69d..06e44d9d725 100644 --- a/develop/doc/api/v2/fluid/layers.html +++ b/develop/doc/api/v2/fluid/layers.html @@ -1025,8 +1025,43 @@ the given labels as soft labels, default False.
paddle.v2.fluid.layers.square_error_cost(input, label, **kwargs)
-

This functions returns the squared error cost using the input and label. -The output is appending the op to do the above.

+

Square error cost layer

+

This layer accepts input predictions and target label and returns the squared error cost. +For predictions, \(X\), and target labels, \(Y\), the equation is:

+
+\[Out = (X - Y)^2\]
+

In the above equation:

+
+
    +
  • \(X\): Input predictions, a tensor.
    • +
  • \(Y\): Input labels, a tensor.
    • +
  • \(Out\): Output value, same shape with \(X\).
    • +
+
+ +++ + + + + + + + +
Parameters:
    +
  • input (Variable) – Input tensor, has predictions.
    • +
  • label (Variable) – Label tensor, has target labels.
    • +
+
Returns:

The tensor variable storing the element-wise squared error difference of input and label.

+
Return type:

Variable

+
+

Examples

+
y = layers.data(name='y', shape=[1], dtype='float32')
+y_predict = layers.data(name='y_predict', shape=[1], dtype='float32')
+cost = layers.square_error_cost(input=y_predict, label=y)
+
+
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\ No newline at end of file diff --git a/develop/doc_cn/api/v2/fluid/layers.html b/develop/doc_cn/api/v2/fluid/layers.html index 7c2bb91d204..3b0cbc424ec 100644 --- a/develop/doc_cn/api/v2/fluid/layers.html +++ b/develop/doc_cn/api/v2/fluid/layers.html @@ -1038,8 +1038,43 @@ the given labels as soft labels, default False.
paddle.v2.fluid.layers.square_error_cost(input, label, **kwargs)
-

This functions returns the squared error cost using the input and label. -The output is appending the op to do the above.

+

Square error cost layer

+

This layer accepts input predictions and target label and returns the squared error cost. +For predictions, \(X\), and target labels, \(Y\), the equation is:

+
+\[Out = (X - Y)^2\]
+

In the above equation:

+
+
    +
  • \(X\): Input predictions, a tensor.
    • +
  • \(Y\): Input labels, a tensor.
    • +
  • \(Out\): Output value, same shape with \(X\).
    • +
+
+ +++ + + + + + + + +
参数:
    +
  • input (Variable) – Input tensor, has predictions.
    • +
  • label (Variable) – Label tensor, has target labels.
    • +
+
返回:

The tensor variable storing the element-wise squared error difference of input and label.

+
返回类型:

Variable

+
+

Examples

+
y = layers.data(name='y', shape=[1], dtype='float32')
+y_predict = layers.data(name='y_predict', shape=[1], dtype='float32')
+cost = layers.square_error_cost(input=y_predict, label=y)
+
+
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