dsh-training-lens
Training Lens · 训练视窗 — 用于 DeepSeek Harness 的本地只读 TensorBoard 标量仪表板。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:GU143312/dsh-training-lens#30250ee658e713482fd786ebeb8211dc9bc51e99
Training Lens 以 dsh-training-lens 发布，当前版本为 0.1.0。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
A local, read-only training dashboard for DeepSeek Harness (DSH). Turn existing TensorBoard scalar logs into a focused view of progress and trends, without changing your trainer.
简体中文 · DSH plugin documentation
Training Lens with synthetic demonstration scalars
Screenshot uses generated demonstration data, not a training result.
Requires DSH 0.2.1-rc.2 (tested), Node 22+, and Python 3.10+ with TensorBoard. Compatibility outside the declared DSH 0.2 range is not assumed.
Install the versioned release artifact:
dsh plugin --profile desktop add https://github.com/GU143312/dsh-training-lens/releases/download/v0.1.0/dsh-training-lens-0.1.0.tgz
Or install the source bundle (plain JavaScript, no install-time build):
dsh plugin --profile desktop add github:GU143312/dsh-training-lens#v0.1.0
Reload the plugin or restart DSH once when convenient. Use your own profile name in place of desktop if needed. For local testing: dsh plugin --profile lens-test add /absolute/path/to/dsh-training-lens-0.1.0.tgz.
The Python helper uses your existing training environment. If TensorBoard is missing, install the optional Python dependencies with that interpreter, from a source checkout:
python -m pip install -r requirements.txt
The plugin never runs pip automatically. npm registry publication is separate from these GitHub installation methods; do not assume npm install dsh-training-lens is available until an npm release exists.
Ask DSH:
Use training_lens to open my TensorBoard logs at
/absolute/path/to/runs, using Python/absolute/path/to/venv/bin/python.
On Windows, provide the training environment's ...\.venv\Scripts\python.exe. The tool returns a local URL; open it to choose a run and metrics.
Tool parameters:
| Field | Meaning |
|---|---|
action | start, status, or stop |
logdir | Absolute event directory or parent directory of runs |
python | Existing Python executable, not a shell command |
port | 0 chooses a free port; an occupied fixed port fails without stopping its owner |
The process remains tied to the plugin instance. Disabling/reloading the plugin or closing DSH stops its dashboard. Stopping the dashboard leaves the training process and event files untouched. Only one dashboard is owned by a plugin instance; stop it before changing the root/interpreter.
Optional defaults in your profile's cordis.patch.yml:
- id: training-lens
config:
python: /absolute/path/to/venv/bin/python
logdir: /absolute/path/to/runs
port: 0
staleSeconds: 120
startupTimeoutMs: 60000
All runtime paths are provided by the user. No project-specific paths or datasets ship in the package.
Standalone use from a source checkout:
python python/server.py --logdir /absolute/path/to/runs --port 6008
training_epochs in config.yaml; generic Train/loss is not assumed to use epochs.npm ci --ignore-scripts
npm run check
npm test
python -m unittest discover -s tests -p 'test_*.py' -v
npm pack
Set TRAINING_LENS_TEST_PYTHON to a Python executable with TensorBoard to enable the Node end-to-end lifecycle test. Python integration tests explicitly skip if optional dependencies are unavailable; CI installs them. No real training is run in tests. npm pack contains an allowlisted set of source/assets/docs, with no install lifecycle scripts.
MIT license. Python TensorBoard and PyYAML, and npm runtime dependencies, retain their own licenses; they are installed separately rather than vendored.