[PR] [AINode]: Integrate MOMENT as a builtin forecasting model [iotdb]

["Eliaaazzz (via GitHub)" <gi...@apache.org>]

Eliaaazzz opened a new pull request, #17383:
URL: https://github.com/apache/iotdb/pull/17383

   ## Summary
   
   Integrate [MOMENT](https://arxiv.org/abs/2402.03885) (A Family of Open Time-series Foundation Models, ICML 2024) into IoTDB AINode as a built-in time series foundation model.
   
   MOMENT is developed by Auton Lab, Carnegie Mellon University. It uses a **T5 encoder-only** backbone with patch-based input embedding and RevIN normalization, supporting zero-shot and fine-tuned forecasting for univariate and multivariate time series.
   
   ### Key Changes
   
   - **New model package** (`iotdb-core/ainode/iotdb/ainode/core/model/moment/`):
     - `configuration_moment.py` — `MomentConfig` extending HuggingFace `PretrainedConfig`
     - `modeling_moment.py` — `MomentForPrediction` wrapping the MOMENT backbone (RevIN + Patching + T5 Encoder + ForecastingHead) as a `PreTrainedModel`
     - `pipeline_moment.py` — `MomentPipeline` extending `ForecastPipeline` with padding/truncation to fixed 512-length input, input mask construction, and iterative long-horizon forecasting
   - **Model registration** in `BUILTIN_HF_TRANSFORMERS_MODEL_MAP` with `repo_id=AutonLab/MOMENT-1-small`
   - **Memory estimate** added to `AINODE_INFERENCE_MODEL_MEM_USAGE_MAP` (~200 MiB for MOMENT-1-small)
   - **Integration test** updated in `AINodeTestUtils.java`
   - **LICENSE** updated with MIT attribution for MOMENT source code
   - **Bug fix**: Quoted `$JAVA` variable in `confignode-env.sh` and `datanode-env.sh` to fix startup failure when `JAVA_HOME` contains spaces
   
   ### Architecture
   
   ```
   Input [batch, n_channels, 512]
     → RevIN normalization (channel-independent)
     → Patching (patch_len=8, stride=8 → 64 patches)
     → Patch embedding (linear projection to d_model)
     → T5 Encoder (self-attention layers)
     → Layer norm
     → ForecastingHead (linear projection to forecast_horizon)
     → RevIN denormalization
     → Output [batch, n_channels, forecast_horizon]
   ```
   
   ### Model Variants
   
   | Variant | HuggingFace Repo | d_model | Layers | Size |
   |---------|-----------------|---------|--------|------|
   | Small (default) | `AutonLab/MOMENT-1-small` | 512 | 8 | ~152 MB |
   | Base | `AutonLab/MOMENT-1-base` | 768 | 12 | ~900 MB |
   | Large | `AutonLab/MOMENT-1-large` | 1024 | 24 | ~1.39 GB |
   
   ## Test plan
   
   - [ ] Verify AINode compiles successfully with `mvn clean package -pl iotdb-core/ainode -P with-ainode -am -DskipTests`
   - [ ] Start IoTDB cluster + AINode, confirm `moment` appears in `SHOW MODELS`
   - [ ] Run forecast query: `SELECT * FROM FORECAST(model_id => 'moment', targets => (...), output_length => 96)`
   - [ ] Verify integration tests pass
   
   🤖 Generated with [Claude Code](https://claude.com/claude-code)


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Re: [PR] [AINode]: Integrate MOMENT as a builtin forecasting model [iotdb]

["Eliaaazzz (via GitHub)" <gi...@apache.org>]

Eliaaazzz closed pull request #17383: [AINode]: Integrate MOMENT as a builtin forecasting model
URL: https://github.com/apache/iotdb/pull/17383


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