PySDK Command-Line Interface
As a part of PySDK installation, the degirum
executable
console script
is installed into the system path. It implements command-line interface (CLI) to various PySDK management facilities.
This console script extends PySDK functionality through the mechanism of
entry points.
The PySDK CLI supports the following commands:
Command | Description |
---|---|
download-zoo | Command to download AI models from the cloud model zoo |
server | Command to control the operation of AI server |
sys-info | Command to obtain system information dump |
trace | Command to manage AI server tracing facility |
You invoke the console script passing the command from the table above as its first argument followed by command-specific parameters described in the following sections.
Download Model Zoo Command
Command: download-zoo
Using this command you can download ML models from the cloud model zoo of your choice specified by URL. The command has the following parameters:
Parameter | Description | Possible Values | Default |
---|---|---|---|
--path |
Local filesystem path to store models downloaded from a model zoo repo | Valid local directory path | Current directory |
--url |
Cloud model zoo URL | "https://cs.degirum.com[/<zoo URL>]" |
"https://cs.degirum.com" |
--token |
Cloud API access token | Valid token obtained at cs.degirum.com | Empty |
--model_family |
Model family name filter: model name substring or regular expression | Any | Empty |
--device |
Target inference device filter | ORCA, CPU, GPU, EDGETPU, MYRIAD, DLA, DLA_FALLBACK, NPU, RK3588, RK3566, RK3568, NXP_VX, NXP_ETHOSU, ARMNN, VITIS_NPU |
Empty |
--runtime |
Runtime agent type filter | N2X, TFLITE, TENSORRT, OPENVINO, ONNX, RKNN |
Empty |
--precision |
Model calculation precision filter | QUANT, FLOAT |
None |
--pruned |
Model density filter | PRUNED, DENSE |
None |
The URL parameter is specified in the "https://cs.degirum.com/<zoo URL>"
format. Here <zoo URL>
suffix is the
name of the cloud model zoo in the form of <organization>/<zoo>
. You can obtain the model zoo URL suffix on
DeGirum Cloud Portal site https://cs.degirum.com under Management | Models main menu item: just select the model
zoo you want to access to open the model zoo page and click copy button near the model zoo name to copy the model
zoo URL suffix into the clipboard.
Filter parameters work the same way as in degirum.zoo_manager.ZooManager.list_models method: they allow you downloading only models satisfying filter conditions.
Once models are downloaded into the directory specified by --path
parameter, you may use this directory as the
model zoo to be served by AI server (see Server Control Command section).
Example.
Download models for ORCA device type from DeGirum Public cloud model zoo into ./my-zoo
directory.
<your cloud API access token>
is your cloud API access token, which you can generate on DeGirum Cloud Portal
site https://cs.degirum.com under Management | My Tokens main menu item.
Server Control Command
server
Using this command you can start AI server, shut it down, or request AI server to rescan its local model zoo.
You can control only AI server which runs on the same host where you execute this command. The control of remote AI servers is disabled for security reasons.
This command has the following subcommands, which are passed just after the command:
Sub-command | Description |
---|---|
start |
Start AI server |
rescan-zoo |
Request AI server to rescan its model zoo |
shutdown |
Request AI server to shutdown |
The command has the following parameters:
Parameter | Applicable To | Description | Possible Values | Default |
---|---|---|---|---|
--zoo |
start |
Local model zoo directory to serve models from (applicable only to start subcommand) |
Any valid path | Current directory |
--quiet |
start |
Do not display any output (applicable only to start subcommand) |
N/A | Disabled |
--port |
start |
TCP port to bind AI server to | 1...65535 | 8778 |
--protocol |
start |
AI server protocol to use | asio , http , both |
asio |
Starting from PySDK version 0.10.0, AI server supports two protocols: asio
and http
.
The asio
protocol is DeGirum custom socket-based AI server protocol, supported by all previous PySDK versions.
The http
protocol is a new protocol, which is based on REST HTTP requests and WebSockets streaming.
The http
protocol allows to use AI server from any programming language, which supports HTTP requests and WebSockets,
such as browser-based JavaScript, which does not support native sockets, thus precluding the use of asio
protocol.
The asio
protocol is selected by default. You can select the http
protocol by specifying --protocol http
.
You may select both protocols by specifying --protocol both
. In this case, AI server will listen to both protocols on two
consecutive TCP ports: the first port is used for asio
protocol, the second port is used for http
protocol.
Examples.
Start AI server to serve models from ./my-zoo
directory, bind it to default port, and use asio
protocol:
Start AI server to serve models from ./my-zoo
directory, use asio
protocol on port 12345, and use http
protocol on port 12346:
System Info Command
Command: sys-info
Using this command you can query the system information either for the local system or for the remote AI server host. The system info dump is printed to the console.
The command has the following parameters:
Parameter | Description | Possible Values | Default |
---|---|---|---|
--host |
Remote AI server hostname or IP address; omit to query local system | Valid hostname, IP address, or empty | Empty |
Example.
Query system info from remote AI server at IP address 192.168.0.101
:
Trace Management Command
Command: trace
Using this command you can manage AI server tracing facility.
AI server tracing facility is used for AI server debugging and time profiling. It is designed mostly for DeGirum customer support and not intended to be used by the end user directly.
This command has the following subcommands, which are passed just after the command:
Sub-command | Description |
---|---|
list |
List all available trace groups |
configure |
Configure trace levels for trace groups |
read |
Read trace data to file |
The command has the following parameters:
Parameter | Applicable To | Description | Possible Values | Default |
---|---|---|---|---|
--host |
All subcommands | Remote AI server hostname or IP address | Valid hostname or IP address | localhost |
--file |
read |
Filename to save trace data into; omit to print to console | Valid local filename | Empty |
--filesize |
read |
Maximum trace data size to read | Any integer number | 10000000 |
--basic |
configure |
Set Basic trace level for a given list of trace groups |
One or multiple trace group names as returned by list sub-command |
Empty |
--detailed |
configure |
Set Detailed trace level for a given list of trace groups |
One or multiple trace group names as returned by list sub-command |
Empty |
--full |
configure |
Set Full trace level for a given list of trace groups |
One or multiple trace group names as returned by list sub-command |
Empty |
Examples.
Query AI server at 192.168.0.101
address for the list of available trace groups and print it to console:
Configure tracing for AI server on localhost
: by setting various tracing levels for various trace groups:
Read trace data from AI server on localhost
and save it to a file ./my-trace-1.txt