From 718e424becf678915bbf777a6af1f296b0c6545e Mon Sep 17 00:00:00 2001 From: Travis CI Date: Mon, 23 Oct 2017 05:56:58 +0000 Subject: [PATCH] Deploy to GitHub Pages: 43d69818c0a962973e2035827a0fa1422c363dde --- develop/doc/api/v2/data.html | 48 +++++++++---------- develop/doc/searchindex.js | 2 +- .../_sources/faq/local/index_cn.rst.txt | 2 +- develop/doc_cn/api/v2/data.html | 48 +++++++++---------- develop/doc_cn/faq/local/index_cn.html | 2 +- develop/doc_cn/searchindex.js | 2 +- 6 files changed, 52 insertions(+), 52 deletions(-) diff --git a/develop/doc/api/v2/data.html b/develop/doc/api/v2/data.html index 82b99b7648d..c08c7aacbd2 100644 --- a/develop/doc/api/v2/data.html +++ b/develop/doc/api/v2/data.html @@ -358,9 +358,9 @@ every element in this vector is either zero or one.

-paddle.v2.data_type.sparse_non_value_slot(dim, seq_type=0)
-

Sparse binary vector. It means the input feature is a sparse vector and the -every element in this vector is either zero or one.

+paddle.v2.data_type.sparse_float_vector(dim, seq_type=0) +

Sparse vector. It means the input feature is a sparse vector. Most of the +elements in this vector are zero, others could be any float value.

@@ -383,24 +383,18 @@ every element in this vector is either zero or one.

-paddle.v2.data_type.sparse_value_slot(dim, seq_type=0)
-

Sparse vector. It means the input feature is a sparse vector. Most of the -elements in this vector are zero, others could be any float value.

+paddle.v2.data_type.sparse_float_vector_sequence(dim) +

Data type of a sequence of sparse vector, which most elements are zero, +others could be any float value.

- + - + - +
Parameters:
    -
  • dim (int) – dimension of this vector.
    • -
  • seq_type (int) – sequence type of this input.
    • -
-
Parameters:dim (int) – dimension of sparse vector.
Returns:

An input type object.

-
Returns:An input type object
Return type:

InputType

-
Return type:InputType
@@ -408,9 +402,9 @@ elements in this vector are zero, others could be any float value.

-paddle.v2.data_type.sparse_vector(dim, seq_type=0)
-

Sparse vector. It means the input feature is a sparse vector. Most of the -elements in this vector are zero, others could be any float value.

+paddle.v2.data_type.sparse_non_value_slot(dim, seq_type=0) +

Sparse binary vector. It means the input feature is a sparse vector and the +every element in this vector is either zero or one.

@@ -433,18 +427,24 @@ elements in this vector are zero, others could be any float value.

-paddle.v2.data_type.sparse_vector_sequence(dim)
-

Data type of a sequence of sparse vector, which most elements are zero, -others could be any float value.

+paddle.v2.data_type.sparse_value_slot(dim, seq_type=0) +

Sparse vector. It means the input feature is a sparse vector. Most of the +elements in this vector are zero, others could be any float value.

- + - + - +
Parameters:dim (int) – dimension of sparse vector.
Parameters:
    +
  • dim (int) – dimension of this vector.
    • +
  • seq_type (int) – sequence type of this input.
    • +
+
Returns:An input type object
Returns:

An input type object.

+
Return type:InputType
Return type:

InputType

+
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\ No newline at end of file diff --git a/develop/doc_cn/_sources/faq/local/index_cn.rst.txt b/develop/doc_cn/_sources/faq/local/index_cn.rst.txt index 75c4ba028e4..0e939a2671a 100644 --- a/develop/doc_cn/_sources/faq/local/index_cn.rst.txt +++ b/develop/doc_cn/_sources/faq/local/index_cn.rst.txt @@ -174,7 +174,7 @@ decoder_inputs = paddle.layer.fc( 1. 两者都是对梯度的截断，但截断时机不同，前者在 :code:`optimzier` 更新网络参数时应用；后者在激活函数反向计算时被调用； 2. 截断对象不同：前者截断可学习参数的梯度，后者截断回传给前层的梯度; -除此之外，还可以通过减小学习律或者对数据进行归一化处理来解决这类问题。 +除此之外，还可以通过减小学习率或者对数据进行归一化处理来解决这类问题。 5. 如何调用 infer 接口输出多个layer的预测结果 ----------------------------------------------- diff --git a/develop/doc_cn/api/v2/data.html b/develop/doc_cn/api/v2/data.html index 95a46ded8ed..d46d7872e82 100644 --- a/develop/doc_cn/api/v2/data.html +++ b/develop/doc_cn/api/v2/data.html @@ -372,9 +372,9 @@ every element in this vector is either zero or one.

-paddle.v2.data_type.sparse_non_value_slot(dim, seq_type=0)
-

Sparse binary vector. It means the input feature is a sparse vector and the -every element in this vector is either zero or one.

+paddle.v2.data_type.sparse_float_vector(dim, seq_type=0) +

Sparse vector. It means the input feature is a sparse vector. Most of the +elements in this vector are zero, others could be any float value.

@@ -397,24 +397,18 @@ every element in this vector is either zero or one.

-paddle.v2.data_type.sparse_value_slot(dim, seq_type=0)
-

Sparse vector. It means the input feature is a sparse vector. Most of the -elements in this vector are zero, others could be any float value.

+paddle.v2.data_type.sparse_float_vector_sequence(dim) +

Data type of a sequence of sparse vector, which most elements are zero, +others could be any float value.

- + - + - +
参数:
    -
  • dim (int) – dimension of this vector.
    • -
  • seq_type (int) – sequence type of this input.
    • -
-
参数:dim (int) – dimension of sparse vector.
返回:

An input type object.

-
返回:An input type object
返回类型:

InputType

-
返回类型:InputType
@@ -422,9 +416,9 @@ elements in this vector are zero, others could be any float value.

-paddle.v2.data_type.sparse_vector(dim, seq_type=0)
-

Sparse vector. It means the input feature is a sparse vector. Most of the -elements in this vector are zero, others could be any float value.

+paddle.v2.data_type.sparse_non_value_slot(dim, seq_type=0) +

Sparse binary vector. It means the input feature is a sparse vector and the +every element in this vector is either zero or one.

@@ -447,18 +441,24 @@ elements in this vector are zero, others could be any float value.

-paddle.v2.data_type.sparse_vector_sequence(dim)
-

Data type of a sequence of sparse vector, which most elements are zero, -others could be any float value.

+paddle.v2.data_type.sparse_value_slot(dim, seq_type=0) +

Sparse vector. It means the input feature is a sparse vector. Most of the +elements in this vector are zero, others could be any float value.

- + - + - +
参数:dim (int) – dimension of sparse vector.
参数:
    +
  • dim (int) – dimension of this vector.
    • +
  • seq_type (int) – sequence type of this input.
    • +
+
返回:An input type object
返回:

An input type object.

+
返回类型:InputType
返回类型:

InputType

+
diff --git a/develop/doc_cn/faq/local/index_cn.html b/develop/doc_cn/faq/local/index_cn.html index 5663180919d..e3c71ce959e 100644 --- a/develop/doc_cn/faq/local/index_cn.html +++ b/develop/doc_cn/faq/local/index_cn.html @@ -414,7 +414,7 @@ layer_attr=paddle.attr.ExtraLayerAttribute(

  • 两者都是对梯度的截断，但截断时机不同，前者在 optimzier 更新网络参数时应用；后者在激活函数反向计算时被调用；
  • 截断对象不同：前者截断可学习参数的梯度，后者截断回传给前层的梯度;
    • -

    除此之外，还可以通过减小学习律或者对数据进行归一化处理来解决这类问题。

    +

    除此之外，还可以通过减小学习率或者对数据进行归一化处理来解决这类问题。

    5. 如何调用 infer 接口输出多个layer的预测结果

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