# MindSpore Insight Commands

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## View the Command Help Information

```bash
mindinsight --help
```

## View the Version Information

```bash
mindinsight --version
```

## Start the Service

> MindSpore Insight service only supports local access by default. For remote access, please modify the configuration file `mindinsight\conf\constants.py`.
> Modify the `HOST` in the file to the server IP, and make sure that the startup port has been opened or the firewall has been closed.

```text
mindinsight start [-h] [--workspace <WORKSPACE>] [--port <PORT>]
                  [--url-path-prefix <URL_PATH_PREFIX>]
                  [--reload-interval <RELOAD_INTERVAL>]
                  [--summary-base-dir <SUMMARY_BASE_DIR>]
                  [--enable-debugger <ENABLE_DEBUGGER>]
                  [--debugger-port <DEBUGGER_PORT>]
                  [--offline-debugger-mem-limit <OFFLINE_DEBUGGER_MEMORY_LIMIT>]
                  [--max-offline-debugger-session-num <MAX_OFFLINE_DEBUGGER_SESSION_NUMBER>]
```

Optional parameters are as follows:

|Name|Argument|Description|Type|Default|Scope|Specifications|
|---|---|---|---|---|---|---|
|`-h, --help`|Optional|Displays the help information about the start command.|-|-|-|-|
|`--workspace <WORKSPACE>`|Optional|Specifies the path for storing MindSpore Insight logs.|String|$HOME/mindinsight|-|-|
|`--port <PORT>`|Optional|Specifies the port number of the web visualization service.|Integer|8080|1~65535|-|
|`--url-path-prefix <URL_PATH_PREFIX>`|Optional|Specifies the URL path prefix of the web visualization service.|String|Empty string|-|URL path prefix consists of segments separated by slashes. Each segment supports alphabets / digits / underscores / dashes / dots, but not single dot or double dots.|
|`--reload-interval <RELOAD_INTERVAL>`|Optional|Specifies the interval (unit: second) for loading data.|Integer|3|0~300|The value 0 indicates that data is loaded only once.|
|`--summary-base-dir <SUMMARY_BASE_DIR>`|Optional|Specifies the root directory for loading training log data.|String|./|-|MindSpore Insight traverses the direct subdirectories in this directory and searches for log files. If a direct subdirectory contains log files, it is identified as the log file directory. If a root directory contains log files, it is identified as the log file directory. In the ModelArts development environment, this parameter can be specified as an OBS path. Please refer to [ModelArts documentation](https://support.huaweicloud.com/devtool-modelarts/develop-modelarts-0068.html) for more information.|
|`--enable-debugger <ENABLE_DEBUGGER>`|Optional|Whether to launch the MindSpore Insight Debugger.|Boolean|False|True/False/1/0|The debugger entry can be shown on MindSpore Insight UI only when MindSpore Insight Debugger is launched.|
|`--debugger-port <DEBUGGER_PORT>`|Optional|Specifies the port number of the debugger server.|Integer|50051|1~65535|-|
|`--offline-debugger-mem-limit <OFFLINE_DEBUGGER_MEMORY_LIMIT>`|Optional|Specifies the maximum memory limit of a single offline debugger session. When the offline debugger cannot be executed due to insufficient memory, set it according to the device memory.|Integer|16*1024|6*1024~The upper limit of int32|-|
|`--max-offline-debugger-session-num <MAX_OFFLINE_DEBUGGER_SESSION_NUMBER>`|Optional|Specifies the maximum session number of the offline debugger. The session number refers to the amount of training jobs that can be debugged at the same time.|Integer|2|1~2|-|
|`--max-graph-node-size <MAX_GRAPH_NODE_SIZE >`|Optional|Set the maximum number of graph nodes loaded by the debugger.|Integer|100000|1~2000000|-|

`--workspace` log directory description：

| Module name   | Log directory description                                    | Log format                                |
| ------------- | ------------------------------------------------------------ | ----------------------------------------- |
| datavisual    | Training kanban module, it records all the logs of training Kanban module. | `datavisual.<PORT>.log`                   |
| debugger      | Debugger module, it records all logs of the debugger module. | `debugger.<PORT>.log`                     |
| explainer     | Explain the AI module, it records all logs that explain the data parsed by the AI module. | `explainer.<PORT>.log`                    |
| gunicorn      | Web service module, it records all logs of the Web service module. | `access.<PORT>.log`<br>`error.<PORT>.log` |
| lineage       | Traceability module, it records all logs of the traceability module. | `lineage.<PORT>.log`               |
| notebook      | Record all logs using MindSpore Insight in the ModelArts notebook.  | `notebook.<PORT>.log`                      |
| optimizer     | Optimizer module, it records all optimizer module logs.      | `optimizer.<PORT>.log`                    |
| parse_summary | Summary file parsing module, it records all logs when using the summary file parsing module. | `parse_summary.<PORT>.log`                |
| profiler      | Performance analysis module, it records all logs of the performance analysis module. | `profiler.<PORT>.log`                     |
| restful_api   | RESTFul API module, it records all RESTFul API interaction logs. | `restful_api.<PORT>.log`                  |
| scripts       | Start and stop the MindSpore Insight module, it records all MindSpore Insight starts and stops. | `start.<PORT>.log`<br>`stop.<PORT>.log`   |
| utils         | Public module, it records all logs of the public module.  | `utils.<PORT>.log`                        |

Note: There is one log file for each module, but when a log file exceeds 50M, it will be renamed and archived in the format of `<module name>_<PORT>.log.<id>` ,`module name` indicates the module name, `PORT` indicates the PORT number, and `ID` indicates the number of file renaming and archiving times.

> When the service is started, the parameter values of the command line are saved as the environment variables of the process and start with `MINDINSIGHT_`, for example, `MINDINSIGHT_PORT`, `MINDINSIGHT_WORKSPACE`, etc.

Execute command:

```bash
mindinsight start --port 8000 --workspace /path/to/workspace/dir --summary-base-dir /path/to/summary/base/dir
```

The startup is successful if it prompts as follows:

```text
Web address: http://127.0.0.1:8000
service start state: success
```

## View the Service Process Information

MindSpore Insight provides user with web services. Run the following command to view the running web service process:

```bash
ps -ef | grep mindinsight
```

Run the following command to access the working directory `WORKSPACE` corresponding to the service process based on the service process ID:

```text
lsof -p <PID> | grep access
```

Output the working directory `WORKSPACE` as follows:

```text
gunicorn  <PID>  <USER>  <FD>  <TYPE>  <DEVICE>  <SIZE/OFF>  <NODE>  <WORKSPACE>/log/gunicorn/access.log
```

## Stop the Service

```text
mindinsight stop [-h] [--port PORT]
```

Optional parameters are as follows:

|Name|Argument|Description|Type|Default|Scope|Specifications|
|---|---|---|---|---|---|---|
|`-h, --help`|Optional|Displays the help information about the stop command.|-|-|-|-|
|`--port <PORT>`|Optional|Specifies the port number of the web visualization service.|Integer|8080|1~65535|-|

Execute command:

```bash
mindinsight stop --port 8000
```

The shutdown is successful if it prompts as follows:

```text
Stop mindinsight service successfully
```

## Parse Summary

MindSpore Insight provides tools for parsing summary log files. Users can save the scalars in the summary log file into a csv file and the images into a png file through the commands, which is convenient for viewing and further processing.

```text
mindinsight parse_summary [--summary-dir] [--output]
```

Optional parameters are as follows:

|Name|Argument|Description|Type|Default|Scope|Specifications|
|---|---|---|---|---|---|---|
|`--summary-dir`|Optional|Specifies the root directory of summary files. If the directory contains multiple summary files, only the latest summary file is parsed.|String|./|-|The summary file directory needs to be readable and executable, and the summary file needs to be readable.|
|`--output`|Optional|Specifies the root directory for saving output files.|String|./|-|-|

Execute command:

```bash
mindinsight parse_summary --summary-dir ./ --output ./
```

The output directory structure is as follows:

```text
└─output_{datetime}
    ├─image
    │   └─{tag}_{step}.png
    │
    └─scalar.csv
```

In which,

- output_{datetime} is the output directory. The rule is 'output_yyyyMMdd_HHmmss_SSSSSS' including year, month, day, hour, minute, second and microseconds.

- {tag}\_{step}.png is the image in training process. 'tag' and 'step' are the tag and step in the training (special characters in tag are deleted and '/' is replaced by '_').

- scalar.csv is the file which save scalars (encoding: 'utf-8').

## Use Mindoptimizer to Tune Hyperparameters

MindSpore Insight provides parameters tuning command. The command-line interface (CLI) provides the following commands:

```text
usage: mindoptimizer [-h] [--version] [--config <CONFIG>]
                     [--iter <ITER>]

```

Optional parameters are as follows:

|Name|Argument|Description|Type|Default|Scope|Specifications|
|---|---|---|---|---|---|---|
|`-h, --help`|Optional|Displays the help information about the start command.|-|-|-|-|
|`--config <CONFIG>`|Required|Specifies the configuration file.|String|-|-|Physical file path (file:/path/to/config.yaml), and the file format is yaml.|
|`--iter <ITER>`|Optional|Specifies the run times for tuning parameters|Integer|1|Positive integer|-|