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18e5935c
编写于
6月 13, 2017
作者:
T
Travis CI
浏览文件
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差异文件
Deploy to GitHub Pages:
0e2acb8b
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c99a8742
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6
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并排
Showing
6 changed file
with
102 addition
and
50 deletion
+102
-50
develop/doc/_sources/design/cluster_train/pserver_client.md.txt
...p/doc/_sources/design/cluster_train/pserver_client.md.txt
+25
-12
develop/doc/design/cluster_train/pserver_client.html
develop/doc/design/cluster_train/pserver_client.html
+25
-12
develop/doc/searchindex.js
develop/doc/searchindex.js
+1
-1
develop/doc_cn/_sources/design/cluster_train/pserver_client.md.txt
...oc_cn/_sources/design/cluster_train/pserver_client.md.txt
+25
-12
develop/doc_cn/design/cluster_train/pserver_client.html
develop/doc_cn/design/cluster_train/pserver_client.html
+25
-12
develop/doc_cn/searchindex.js
develop/doc_cn/searchindex.js
+1
-1
未找到文件。
develop/doc/_sources/design/cluster_train/pserver_client.md.txt
浏览文件 @
18e5935c
...
...
@@ -74,14 +74,25 @@ typedef enum {
typedef struct {
char* name;
paddle_element_type element_type;
void*
content;
unsigned char*
content;
int content_len;
} paddle_parameter, paddle_gradient;
typedef
struct paddle_pserver_clie
nt paddle_pserver_client;
typedef
i
nt paddle_pserver_client;
paddle_pserver_client* paddle_new_pserver_client();
void paddle_pserver_client_release(paddle_pserver_client* client);
/**
* @brief creates a pserver client that talks to etcd for coordination.
*/
paddle_pserver_client paddle_new_etcd_pserver_client(char* etcd_addr);
/**
* @brief creates a pserver client given pserver addresses.
*
* @param pserver_addrs comma-separated pserver addresses.
* @param selected if current pserver client is selected to initialize all parameter servers.
*/
paddle_pserver_client paddle_new_pserver_client(char* pserver_addrs, int selected);
void paddle_pserver_client_release(paddle_pserver_client c);
/**
* @brief paddle_begin_init_params begins to initialize parameters on
...
...
@@ -95,7 +106,7 @@ void paddle_pserver_client_release(paddle_pserver_client* client);
* @return 1 if the trainer is selected to initialize parameter
* servers, otherwise 0.
*/
int paddle_begin_init_params(paddle_pserver_client
*
client);
int paddle_begin_init_params(paddle_pserver_client client);
/**
* @brief paddle_init_param initializes the parameter on parameter
...
...
@@ -109,7 +120,7 @@ int paddle_begin_init_params(paddle_pserver_client* client);
* @paddle_begin_init_param). Or simply exit the program and wait for
* the cluster management system to restart the trainer.
*/
int paddle_init_param(paddle_pserver_client
*
client, paddle_parameter param, const unsigned char* param_config_proto, int config_len);
int paddle_init_param(paddle_pserver_client client, paddle_parameter param, const unsigned char* param_config_proto, int config_len);
/**
* @brief paddle_finish_init_params tells parameter servers client has
...
...
@@ -120,7 +131,7 @@ int paddle_init_param(paddle_pserver_client* client, paddle_parameter param, con
* @paddle_begin_init_param). Or simply exit the program and wait for
* the cluster management system to restart the trainer.
*/
int paddle_finish_init_params(paddle_pserver_client
*
client);
int paddle_finish_init_params(paddle_pserver_client client);
/**
* @brief paddle_send_grads sends gradients to parameter servers for
...
...
@@ -131,7 +142,7 @@ int paddle_finish_init_params(paddle_pserver_client* client);
* @param learning_rate the learning rate for the gradients.
* @return 0 if successful, otherwise -1.
*/
int paddle_send_grads(paddle_pserver_client
*
client, const paddle_gradient* grads, int len);
int paddle_send_grads(paddle_pserver_client client, const paddle_gradient* grads, int len);
/**
* @brief paddle_get_params gets parameters from parameter servers.
...
...
@@ -139,13 +150,15 @@ int paddle_send_grads(paddle_pserver_client* client, const paddle_gradient* grad
* paddle_get_params will block until parameters are initialized on
* the parameter servers.
*
* @param names the array of names of the parameters to get.
* @param dst the destination array of parameters to save to.
* @param dst the destination array of parameter pointers to save to.
* The parameter pointer must be pre-popullated with required parameter name,
* and the content of parameter must be pre-allocated of the size of required
* parameter on pserver.
* @param len the length of the names array and the paddle_parameter
* array.
* @return 0 if successful, otherwise -1.
*/
int paddle_get_params(paddle_pserver_client
* client, const char** names, paddle_parameter
* dst, int len);
int paddle_get_params(paddle_pserver_client
client, paddle_parameter*
* dst, int len);
/**
* @brief paddle_save_model indicates parameters to save the parameter
...
...
@@ -154,5 +167,5 @@ int paddle_get_params(paddle_pserver_client* client, const char** names, paddle_
* @param path the path to save parameters.
* @return 0 if successful, otherwise -1.
*/
int paddle_save_model(paddle_pserver_client
*
client, const char* path);
int paddle_save_model(paddle_pserver_client client, const char* path);
```
develop/doc/design/cluster_train/pserver_client.html
浏览文件 @
18e5935c
...
...
@@ -244,14 +244,25 @@ name:sparse-n-1
<span
class=
"k"
>
typedef
</span>
<span
class=
"k"
>
struct
</span>
<span
class=
"p"
>
{
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
name
</span><span
class=
"p"
>
;
</span>
<span
class=
"n"
>
paddle_element_type
</span>
<span
class=
"n"
>
element_type
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
void
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
content
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
content
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
content_len
</span><span
class=
"p"
>
;
</span>
<span
class=
"p"
>
}
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"p"
>
;
</span>
<span
class=
"k"
>
typedef
</span>
<span
class=
"k
"
>
struct
</span>
<span
class=
"n"
>
paddle_pserver_clie
nt
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"p"
>
;
</span>
<span
class=
"k"
>
typedef
</span>
<span
class=
"k
t"
>
i
nt
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"p"
>
;
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"o"
>
*
</span>
<span
class=
"nf"
>
paddle_new_pserver_client
</span><span
class=
"p"
>
();
</span>
<span
class=
"kt"
>
void
</span>
<span
class=
"nf"
>
paddle_pserver_client_release
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief creates a pserver client that talks to etcd for coordination.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"nf"
>
paddle_new_etcd_pserver_client
</span><span
class=
"p"
>
(
</span><span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
etcd_addr
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief creates a pserver client given pserver addresses.
</span>
<span
class=
"cm"
>
*
</span>
<span
class=
"cm"
>
* @param pserver_addrs comma-separated pserver addresses.
</span>
<span
class=
"cm"
>
* @param selected if current pserver client is selected to initialize all parameter servers.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"nf"
>
paddle_new_pserver_client
</span><span
class=
"p"
>
(
</span><span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
pserver_addrs
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
selected
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
void
</span>
<span
class=
"nf"
>
paddle_pserver_client_release
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
c
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_begin_init_params begins to initialize parameters on
</span>
...
...
@@ -265,7 +276,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @return 1 if the trainer is selected to initialize parameter
</span>
<span
class=
"cm"
>
* servers, otherwise 0.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_begin_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_begin_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_init_param initializes the parameter on parameter
</span>
...
...
@@ -279,7 +290,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @paddle_begin_init_param). Or simply exit the program and wait for
</span>
<span
class=
"cm"
>
* the cluster management system to restart the trainer.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_init_param
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span>
<span
class=
"n"
>
param
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
param_config_proto
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
config_len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_init_param
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span>
<span
class=
"n"
>
param
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
param_config_proto
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
config_len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_finish_init_params tells parameter servers client has
</span>
...
...
@@ -290,7 +301,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @paddle_begin_init_param). Or simply exit the program and wait for
</span>
<span
class=
"cm"
>
* the cluster management system to restart the trainer.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_finish_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_finish_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_send_grads sends gradients to parameter servers for
</span>
...
...
@@ -301,7 +312,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @param learning_rate the learning rate for the gradients.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_send_grads
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
grads
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_send_grads
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
grads
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_get_params gets parameters from parameter servers.
</span>
...
...
@@ -309,13 +320,15 @@ name:sparse-n-1
<span
class=
"cm"
>
* paddle_get_params will block until parameters are initialized on
</span>
<span
class=
"cm"
>
* the parameter servers.
</span>
<span
class=
"cm"
>
*
</span>
<span
class=
"cm"
>
* @param names the array of names of the parameters to get.
</span>
<span
class=
"cm"
>
* @param dst the destination array of parameters to save to.
</span>
<span
class=
"cm"
>
* @param dst the destination array of parameter pointers to save to.
</span>
<span
class=
"cm"
>
* The parameter pointer must be pre-popullated with required parameter name,
</span>
<span
class=
"cm"
>
* and the content of parameter must be pre-allocated of the size of required
</span>
<span
class=
"cm"
>
* parameter on pserver.
</span>
<span
class=
"cm"
>
* @param len the length of the names array and the paddle_parameter
</span>
<span
class=
"cm"
>
* array.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_get_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
**
</span>
<span
class=
"n"
>
names
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
dst
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_get_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"o"
>
*
*
</span>
<span
class=
"n"
>
dst
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_save_model indicates parameters to save the parameter
</span>
...
...
@@ -324,7 +337,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @param path the path to save parameters.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_save_model
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
path
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_save_model
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
path
</span><span
class=
"p"
>
);
</span>
</pre></div>
</div>
</div>
...
...
develop/doc/searchindex.js
浏览文件 @
18e5935c
因为 它太大了无法显示 source diff 。你可以改为
查看blob
。
develop/doc_cn/_sources/design/cluster_train/pserver_client.md.txt
浏览文件 @
18e5935c
...
...
@@ -74,14 +74,25 @@ typedef enum {
typedef struct {
char* name;
paddle_element_type element_type;
void*
content;
unsigned char*
content;
int content_len;
} paddle_parameter, paddle_gradient;
typedef
struct paddle_pserver_clie
nt paddle_pserver_client;
typedef
i
nt paddle_pserver_client;
paddle_pserver_client* paddle_new_pserver_client();
void paddle_pserver_client_release(paddle_pserver_client* client);
/**
* @brief creates a pserver client that talks to etcd for coordination.
*/
paddle_pserver_client paddle_new_etcd_pserver_client(char* etcd_addr);
/**
* @brief creates a pserver client given pserver addresses.
*
* @param pserver_addrs comma-separated pserver addresses.
* @param selected if current pserver client is selected to initialize all parameter servers.
*/
paddle_pserver_client paddle_new_pserver_client(char* pserver_addrs, int selected);
void paddle_pserver_client_release(paddle_pserver_client c);
/**
* @brief paddle_begin_init_params begins to initialize parameters on
...
...
@@ -95,7 +106,7 @@ void paddle_pserver_client_release(paddle_pserver_client* client);
* @return 1 if the trainer is selected to initialize parameter
* servers, otherwise 0.
*/
int paddle_begin_init_params(paddle_pserver_client
*
client);
int paddle_begin_init_params(paddle_pserver_client client);
/**
* @brief paddle_init_param initializes the parameter on parameter
...
...
@@ -109,7 +120,7 @@ int paddle_begin_init_params(paddle_pserver_client* client);
* @paddle_begin_init_param). Or simply exit the program and wait for
* the cluster management system to restart the trainer.
*/
int paddle_init_param(paddle_pserver_client
*
client, paddle_parameter param, const unsigned char* param_config_proto, int config_len);
int paddle_init_param(paddle_pserver_client client, paddle_parameter param, const unsigned char* param_config_proto, int config_len);
/**
* @brief paddle_finish_init_params tells parameter servers client has
...
...
@@ -120,7 +131,7 @@ int paddle_init_param(paddle_pserver_client* client, paddle_parameter param, con
* @paddle_begin_init_param). Or simply exit the program and wait for
* the cluster management system to restart the trainer.
*/
int paddle_finish_init_params(paddle_pserver_client
*
client);
int paddle_finish_init_params(paddle_pserver_client client);
/**
* @brief paddle_send_grads sends gradients to parameter servers for
...
...
@@ -131,7 +142,7 @@ int paddle_finish_init_params(paddle_pserver_client* client);
* @param learning_rate the learning rate for the gradients.
* @return 0 if successful, otherwise -1.
*/
int paddle_send_grads(paddle_pserver_client
*
client, const paddle_gradient* grads, int len);
int paddle_send_grads(paddle_pserver_client client, const paddle_gradient* grads, int len);
/**
* @brief paddle_get_params gets parameters from parameter servers.
...
...
@@ -139,13 +150,15 @@ int paddle_send_grads(paddle_pserver_client* client, const paddle_gradient* grad
* paddle_get_params will block until parameters are initialized on
* the parameter servers.
*
* @param names the array of names of the parameters to get.
* @param dst the destination array of parameters to save to.
* @param dst the destination array of parameter pointers to save to.
* The parameter pointer must be pre-popullated with required parameter name,
* and the content of parameter must be pre-allocated of the size of required
* parameter on pserver.
* @param len the length of the names array and the paddle_parameter
* array.
* @return 0 if successful, otherwise -1.
*/
int paddle_get_params(paddle_pserver_client
* client, const char** names, paddle_parameter
* dst, int len);
int paddle_get_params(paddle_pserver_client
client, paddle_parameter*
* dst, int len);
/**
* @brief paddle_save_model indicates parameters to save the parameter
...
...
@@ -154,5 +167,5 @@ int paddle_get_params(paddle_pserver_client* client, const char** names, paddle_
* @param path the path to save parameters.
* @return 0 if successful, otherwise -1.
*/
int paddle_save_model(paddle_pserver_client
*
client, const char* path);
int paddle_save_model(paddle_pserver_client client, const char* path);
```
develop/doc_cn/design/cluster_train/pserver_client.html
浏览文件 @
18e5935c
...
...
@@ -251,14 +251,25 @@ name:sparse-n-1
<span
class=
"k"
>
typedef
</span>
<span
class=
"k"
>
struct
</span>
<span
class=
"p"
>
{
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
name
</span><span
class=
"p"
>
;
</span>
<span
class=
"n"
>
paddle_element_type
</span>
<span
class=
"n"
>
element_type
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
void
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
content
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
content
</span><span
class=
"p"
>
;
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
content_len
</span><span
class=
"p"
>
;
</span>
<span
class=
"p"
>
}
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"p"
>
;
</span>
<span
class=
"k"
>
typedef
</span>
<span
class=
"k
"
>
struct
</span>
<span
class=
"n"
>
paddle_pserver_clie
nt
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"p"
>
;
</span>
<span
class=
"k"
>
typedef
</span>
<span
class=
"k
t"
>
i
nt
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"p"
>
;
</span>
<span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"o"
>
*
</span>
<span
class=
"nf"
>
paddle_new_pserver_client
</span><span
class=
"p"
>
();
</span>
<span
class=
"kt"
>
void
</span>
<span
class=
"nf"
>
paddle_pserver_client_release
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief creates a pserver client that talks to etcd for coordination.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"nf"
>
paddle_new_etcd_pserver_client
</span><span
class=
"p"
>
(
</span><span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
etcd_addr
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief creates a pserver client given pserver addresses.
</span>
<span
class=
"cm"
>
*
</span>
<span
class=
"cm"
>
* @param pserver_addrs comma-separated pserver addresses.
</span>
<span
class=
"cm"
>
* @param selected if current pserver client is selected to initialize all parameter servers.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"nf"
>
paddle_new_pserver_client
</span><span
class=
"p"
>
(
</span><span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
pserver_addrs
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
selected
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
void
</span>
<span
class=
"nf"
>
paddle_pserver_client_release
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
c
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_begin_init_params begins to initialize parameters on
</span>
...
...
@@ -272,7 +283,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @return 1 if the trainer is selected to initialize parameter
</span>
<span
class=
"cm"
>
* servers, otherwise 0.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_begin_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_begin_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_init_param initializes the parameter on parameter
</span>
...
...
@@ -286,7 +297,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @paddle_begin_init_param). Or simply exit the program and wait for
</span>
<span
class=
"cm"
>
* the cluster management system to restart the trainer.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_init_param
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span>
<span
class=
"n"
>
param
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
param_config_proto
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
config_len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_init_param
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span>
<span
class=
"n"
>
param
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
unsigned
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
param_config_proto
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
config_len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_finish_init_params tells parameter servers client has
</span>
...
...
@@ -297,7 +308,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @paddle_begin_init_param). Or simply exit the program and wait for
</span>
<span
class=
"cm"
>
* the cluster management system to restart the trainer.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_finish_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_finish_init_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_send_grads sends gradients to parameter servers for
</span>
...
...
@@ -308,7 +319,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @param learning_rate the learning rate for the gradients.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_send_grads
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
grads
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_send_grads
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"n"
>
paddle_gradient
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
grads
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_get_params gets parameters from parameter servers.
</span>
...
...
@@ -316,13 +327,15 @@ name:sparse-n-1
<span
class=
"cm"
>
* paddle_get_params will block until parameters are initialized on
</span>
<span
class=
"cm"
>
* the parameter servers.
</span>
<span
class=
"cm"
>
*
</span>
<span
class=
"cm"
>
* @param names the array of names of the parameters to get.
</span>
<span
class=
"cm"
>
* @param dst the destination array of parameters to save to.
</span>
<span
class=
"cm"
>
* @param dst the destination array of parameter pointers to save to.
</span>
<span
class=
"cm"
>
* The parameter pointer must be pre-popullated with required parameter name,
</span>
<span
class=
"cm"
>
* and the content of parameter must be pre-allocated of the size of required
</span>
<span
class=
"cm"
>
* parameter on pserver.
</span>
<span
class=
"cm"
>
* @param len the length of the names array and the paddle_parameter
</span>
<span
class=
"cm"
>
* array.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_get_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
**
</span>
<span
class=
"n"
>
names
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
dst
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_get_params
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"n"
>
paddle_parameter
</span><span
class=
"o"
>
*
*
</span>
<span
class=
"n"
>
dst
</span><span
class=
"p"
>
,
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"n"
>
len
</span><span
class=
"p"
>
);
</span>
<span
class=
"cm"
>
/**
</span>
<span
class=
"cm"
>
* @brief paddle_save_model indicates parameters to save the parameter
</span>
...
...
@@ -331,7 +344,7 @@ name:sparse-n-1
<span
class=
"cm"
>
* @param path the path to save parameters.
</span>
<span
class=
"cm"
>
* @return 0 if successful, otherwise -1.
</span>
<span
class=
"cm"
>
*/
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_save_model
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"o"
>
*
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
path
</span><span
class=
"p"
>
);
</span>
<span
class=
"kt"
>
int
</span>
<span
class=
"nf"
>
paddle_save_model
</span><span
class=
"p"
>
(
</span><span
class=
"n"
>
paddle_pserver_client
</span>
<span
class=
"n"
>
client
</span><span
class=
"p"
>
,
</span>
<span
class=
"k"
>
const
</span>
<span
class=
"kt"
>
char
</span><span
class=
"o"
>
*
</span>
<span
class=
"n"
>
path
</span><span
class=
"p"
>
);
</span>
</pre></div>
</div>
</div>
...
...
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