[Bug] DPA-2.4-7M checkpoint cannot be loaded by deepmd-kit v3.1.3 (registered in pretrained registry but incompatible)

## Summary `DPA-2.4-7M` is registered in the v3.1.3 pretrained model registry ([`deepmd/pretrained/registry.py`](https://github.com/deepmodeling/deepmd-kit/blob/v3.1.3/deepmd/pretrained/registry.py), added via PR #5307), but deepmd-kit 3.1.3 cannot actually load this checkpoint. All loading paths (`dp --pt show`, `dp --pt freeze`, and the ASE `DP()` calculator) fail with the same `state_dict` error. ## Error ``` RuntimeError: Error(s) in loading state_dict for ModelWrapper: Missing key(s) in state_dict: "model.Default.atomic_model.descriptor.repinit.type_embd_data", "model.Default.atomic_model.descriptor.repinit_three_body.type_embd_data", "model.Default.atomic_model.descriptor.repinit_three_body.compress_info.0", "model.Default.atomic_model.descriptor.repinit_three_body.compress_data.0" ``` ## Reproduction **Environment**: `registry.dp.tech/dptech/deepmd-kit:3.1.3` **deepmd-kit**: 3.1.3 **PyTorch**: 2.10.0 **GPU**: NVIDIA RTX 4090 (issue is not GPU-related) **Model file**: `dpa-2.4-7M.pt` (80.0 MB) **SHA256**: `7a5ca2b01579d9617502b4203af839107fdcf1ec7e3ae1d66a5b14811bc5b741` (matches the hash in `registry.py` — confirmed same file) **Download source tested**: `https://bohrium.oss-cn-zhangjiakou.aliyuncs.com/13756/27666/store/upload/cd12300a-d3e6-4de9-9783-dd9899376cae/dpa-2.4-7M.pt` ### Steps to reproduce ```bash # Any of these three paths fail: # 1. dp show dp --pt show dpa-2.4-7M.pt model-branch # → RuntimeError: Missing key(s) in state_dict ... # 2. dp freeze dp --pt freeze -c dpa-2.4-7M.pt -o frozen.pth --head Omat24 # → same RuntimeError # 3. ASE calculator python3 -c "from deepmd.calculator import DP; calc = DP('dpa-2.4-7M.pt', head='Omat24')" # → same RuntimeError ``` ### Control: DPA-3.1-3M works fine In the **same environment**, DPA-3.1-3M loads, shows branches, freezes, and runs inference without any issues: ```bash dp --pt show DPA-3.1-3M.pt model-branch # ✅ lists 31 branches dp --pt freeze -c DPA-3.1-3M.pt -o frozen_dpa3.pth --head Omat24 # ✅ 18.0 MB ``` ## Analysis The error occurs at `deepmd/pt/infer/deep_eval.py:173`: ```python self.dp.load_state_dict(state_dict) ``` The current `ModelWrapper` definition expects 4 keys related to `repinit` type embedding and compression data that do not exist in the DPA-2.4-7M checkpoint. This suggests the checkpoint was saved with an older model architecture definition, and deepmd-kit 3.1.3 added these fields to the model class without providing backward-compatible loading (e.g., `strict=False` with default initialization, or a checkpoint migration path). ## Suggested Fix One or more of: 1. Use `strict=False` in `load_state_dict` and initialize the missing keys with sensible defaults (zeros / empty tensors) 2. Add a checkpoint migration utility (`dp --pt migrate`) that patches old checkpoints 3. Re-export DPA-2.4-7M with the new model class so the checkpoint includes the expected keys 4. Add version metadata to checkpoints and auto-migrate on load ## Impact - Users cannot use DPA-2.4-7M with deepmd-kit 3.1.3 in **any** inference mode (ASE, LAMMPS freeze, or direct eval) - The model is listed in the official pretrained registry, creating a false expectation of compatibility - DPA-2.4-7M has domain-specific heads (e.g., `H2O_H2O_PD`, `Electrolyte`) that are not available in DPA-3.x models Investigated and reported by MatMaster (AI agent for computational materials science) Co-authored-by: @SchrodingersCattt