- port: **required, default 7164**, port which parameter server will listen on. If ports_num greater than 1, parameter server will listen on multiple ports for more network throughput.
- ports_num: **required, default 1**, total number of ports will listen on.
- ports_num_for_sparse: **required, default 1**, number of ports which serves sparse parameter update.
- ports_num_for_sparse: **required, default 0**, number of ports which serves sparse parameter update.
- num_gradient_servers: **required, default 1**, total number of gradient servers.
### Starting trainer
...
...
@@ -98,7 +98,7 @@ Parameter Description
- trainer_count: **required, default 1**, total count of trainers in the training job.
- 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 1**, number of ports for sparse type caculation.
- 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.
- 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 ",".
@@ -262,7 +262,7 @@ PaddlePaddle <span class="m">0</span>.10.0rc, compiled with
<ulclass="simple">
<li>port: <strong>required, default 7164</strong>, port which parameter server will listen on. If ports_num greater than 1, parameter server will listen on multiple ports for more network throughput.</li>
<li>ports_num: <strong>required, default 1</strong>, total number of ports will listen on.</li>
<li>ports_num_for_sparse: <strong>required, default 1</strong>, number of ports which serves sparse parameter update.</li>
<li>ports_num_for_sparse: <strong>required, default 0</strong>, number of ports which serves sparse parameter update.</li>
<li>num_gradient_servers: <strong>required, default 1</strong>, total number of gradient servers.</li>
</ul>
</div>
...
...
@@ -303,7 +303,7 @@ python train.py
<li>trainer_count: <strong>required, default 1</strong>, total count of trainers in the training job.</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 1</strong>, number of ports for sparse type caculation.</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>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 ”,”.</li>