Deploy to GitHub Pages: 0f8dd956

develop/doc/_sources/howto/usage/cluster/cluster_train_en.md.txt

@@ -95,11 +95,11 @@ paddle.init(
 Parameter Description
 
 - use_gpu: **optional, default False**, set to "True" to enable GPU training.
-- trainer_count: **required, default 1**, total count of trainers in the training job.
+- trainer_count: **required, default 1**, number of threads in current trainer.
 - port: **required, default 7164**, port to connect to parameter server.
 - ports_num: **required, default 1**, number of ports for communication.
 - ports_num_for_sparse: **required, default 0**, number of ports for sparse type caculation.
-- num_gradient_servers: **required, default 1**, total number of gradient server.
+- num_gradient_servers: **required, default 1**, number of trainers in current job.
 - trainer_id: **required, default 0**, ID for every trainer, start from 0.
 - pservers: **required, default 127.0.0.1**, list of IPs of parameter servers, separated by ",".
 

develop/doc/howto/usage/cluster/cluster_train_en.html

@@ -301,11 +301,11 @@ python train.py
 <p>Parameter Description</p>
 <ul class="simple">
 <li>use_gpu: <strong>optional, default False</strong>, set to &#8220;True&#8221; to enable GPU training.</li>
-<li>trainer_count: <strong>required, default 1</strong>, total count of trainers in the training job.</li>
+<li>trainer_count: <strong>required, default 1</strong>, number of threads in current trainer.</li>
 <li>port: <strong>required, default 7164</strong>, port to connect to parameter server.</li>
 <li>ports_num: <strong>required, default 1</strong>, number of ports for communication.</li>
 <li>ports_num_for_sparse: <strong>required, default 0</strong>, number of ports for sparse type caculation.</li>
-<li>num_gradient_servers: <strong>required, default 1</strong>, total number of gradient server.</li>
+<li>num_gradient_servers: <strong>required, default 1</strong>, number of trainers in current job.</li>
 <li>trainer_id: <strong>required, default 0</strong>, ID for every trainer, start from 0.</li>
 <li>pservers: <strong>required, default 127.0.0.1</strong>, list of IPs of parameter servers, separated by &#8221;,&#8221;.</li>
 </ul>

develop/doc_cn/_sources/howto/usage/cluster/cluster_train_cn.md.txt

@@ -92,11 +92,11 @@ paddle.init(
 参数说明
 
 - use_gpu： **可选，默认False**，是否启用GPU训练
-- trainer_count：**必选，默认1**，当前训练任务trainer总个数
+- trainer_count：**必选，默认1**，当前trainer的线程数目
 - port：**必选，默认7164**，连接到pserver的端口
 - ports_num：**必选，默认1**，连接到pserver的端口个数
 - ports_num_for_sparse：**必选，默认0**，和pserver之间用于稀疏类型参数通信的端口个数
-- num_gradient_servers：**必选，默认1**，当前训练任务pserver总数
+- num_gradient_servers：**必选，默认1**，当前训练任务trainer总数
 - trainer_id：**必选，默认0**，每个trainer的唯一ID，从0开始的整数
 - pservers：**必选，默认127.0.0.1**，当前训练任务启动的pserver的IP列表，多个IP使用“,”隔开
 

develop/doc_cn/howto/usage/cluster/cluster_train_cn.html

@@ -319,11 +319,11 @@ PaddlePaddle <span class="m">0</span>.10.0, compiled with
 <p>参数说明</p>
 <ul class="simple">
 <li>use_gpu： <strong>可选，默认False</strong>，是否启用GPU训练</li>
-<li>trainer_count：<strong>必选，默认1</strong>，当前训练任务trainer总个数</li>
+<li>trainer_count：<strong>必选，默认1</strong>，当前trainer的线程数目</li>
 <li>port：<strong>必选，默认7164</strong>，连接到pserver的端口</li>
 <li>ports_num：<strong>必选，默认1</strong>，连接到pserver的端口个数</li>
 <li>ports_num_for_sparse：<strong>必选，默认0</strong>，和pserver之间用于稀疏类型参数通信的端口个数</li>
-<li>num_gradient_servers：<strong>必选，默认1</strong>，当前训练任务pserver总数</li>
+<li>num_gradient_servers：<strong>必选，默认1</strong>，当前训练任务trainer总数</li>
 <li>trainer_id：<strong>必选，默认0</strong>，每个trainer的唯一ID，从0开始的整数</li>
 <li>pservers：<strong>必选，默认127.0.0.1</strong>，当前训练任务启动的pserver的IP列表，多个IP使用“,”隔开</li>
 </ul>