test 2.0.2 (#161)

* Dev (#125) * update workflow and install method. * build(deps): update pyproject.toml * build(deps): update pyproject.toml * chore: delete release-check.md * ci: update publish-to-pypi.yml * Update pyproject.toml * Update pyproject.toml * update mix.ep50.pth, mix.iter500.pth and train_config.json (#126) * update h-BN example, ckpt and the related doc. (#127) * update mix.ep50.pth, mix.iter500.pth and train_config.json * update hBN example * docs: update hands_on.md * update run.py: (#128) * update run.py: support change device and dtype when postprocess the model * update argcheck.py * update argcheck.py * add E3 features (node/edge) to hamiltonian/density blocks (#129) * stack changes * fix test ham to feature * update write block function in command line (#132) * update write block * update task naming for each mdoel * feat(dftb): add support sk params from dftb skf files . (#133) * add xitorch interp1d * feat: create dptb/utils/_xitorch/__init__.py * update C_chain example * add sk * read skfile and load sk para * update sk_param.py * update onsite.py: add support load onsite E from the dftb skf files. * update sk_param.py * update sk_param.py * add hopping dptb * add core for dftb support. * update sk_param.py: make the outof skparams in the same format as nnsk model parameters. * update dftbsk.py： make the skparas from skf files in the same style of nnsk. * update hopping_dptb.py * update onsite.py * update dftbsk.py and nnsk.py * add new mix type: dftb + nnenv * update build.py * update build.py and dftbsk.py * update deeptb.py * add build_model for dftbsk and dftbsk+nnenv two new mode. * add hBN dftb example * fix(SKParam): Update SKParam class to handle missing keys in skdict and raise appropriate errors. Add unit tests for SKParam class. * feat(train): Add skints loss function for training with nnsk model * test(hopping_dptb): Update dftb/hopping_dptb.py and add test_dftbsk.py * test(build_model): Update deeptb.py and test_build_model.py with dftbsk changes * test: Refactor test_build_model.py to remove unnecessary blank lines and add validation for model_options in test_build_model_failure() * update deeptb.py * test(test_sktb): to add new tests for dftbsk and nnsk models * 📃 docs(dftb): Update hBN_dftb example with new data and input files * Update deeptb.py * Update SE2Aggregation class in se2.py to use the last 4 columns of x instead of the last 3 columns. Update _SE2Descriptor class in se2.py to set the flow parameter to "target_to_source". and add radial info into env matrix (#135) * feat(command): add cskf command to collect the skfiles into a pth database (#134) * add xitorch interp1d * feat: create dptb/utils/_xitorch/__init__.py * update C_chain example * add sk * read skfile and load sk para * update sk_param.py * update onsite.py: add support load onsite E from the dftb skf files. * update sk_param.py * update sk_param.py * add hopping dptb * add core for dftb support. * update sk_param.py: make the outof skparams in the same format as nnsk model parameters. * update dftbsk.py： make the skparas from skf files in the same style of nnsk. * update hopping_dptb.py * update onsite.py * update dftbsk.py and nnsk.py * add new mix type: dftb + nnenv * update build.py * update build.py and dftbsk.py * update deeptb.py * add build_model for dftbsk and dftbsk+nnenv two new mode. * add hBN dftb example * fix(SKParam): Update SKParam class to handle missing keys in skdict and raise appropriate errors. Add unit tests for SKParam class. * feat(train): Add skints loss function for training with nnsk model * test(hopping_dptb): Update dftb/hopping_dptb.py and add test_dftbsk.py * test(build_model): Update deeptb.py and test_build_model.py with dftbsk changes * test: Refactor test_build_model.py to remove unnecessary blank lines and add validation for model_options in test_build_model_failure() * update deeptb.py * test(test_sktb): to add new tests for dftbsk and nnsk models * 📃 docs(dftb): Update hBN_dftb example with new data and input files * 🦄 refactor(SKParam): Update SKParam class to include HubdU and Occu in skdict * Update deeptb.py * ✨ feat(cskf): Add collectskf.py to collect sktb params from sk files * 🧪 test(csfk): update test_skparam to add unit test for cskf command * 📃 docs(dftb): add docs about dftb example into index.rst * Fix bugs in SE2Aggregation and _SE2Descriptor classes * add example mos2 * update hBN example * fix(se2): update the smooth function in getting env descriptor (#136) * 🐞 fix(se2): update the smooth function in getting env descriptor * test: update test_emb_se2.py * test: update test_emb_se2.py * Update version 2.0.1 in pyproject.toml * Fix(nnsk): NNSK class in nnsk.py to use the get() method when accessing the full orbital (#139) * Update NNSK class in nnsk.py to use the get() method when accessing values in the full_basis_to_basis dictionary. * fix digital error in test_emb_se2 * temp * Update(nnsk): automatic orthogonalization (#141) * fix(data): fix the bug in dm parse (#142) * Update(nnsk): automatic orthogonalization * update DM parse * feat:add support to pass kpoints np.array to get band eigenvalues. (#145) * feat: create toskint.ipynb * feat:add support to pass kpoints nparray to get band eigenvalues. * feat(curve_fitting.py): develop a curve fitting function that converts the dftb model to nnsk (#146) * update fitting dftb * add(dftb2nnsk): develop fitting class for converting dftb to nnsk model * remove(curve-fitting.ipynb): remove the notebook for development * fix test split * add(test_dftb2nnsk): add simple test for dftb2nnsk class * temp * fix test * fix(nnsk): fix device type errpr in to json function * rename hopping_dptb to hopping_dftb * temp * align inferences * update decaying function * remove rc from dftb2nnsk * fix test nrl * fix test nrl * update argcheck * update dftb2nnsk.py * update argcheck * update read_NRL_tojson.py --------- Co-authored-by: qqgu <[email protected]> * feat(data): add parse md trajectory of abacus (#144) * update abacus parse md * fix(default_dataset): The natom and nframe default setting * shift the 'pos‘ position in test default dataset * fix lattice constant transform * update parse_abacus_md * update abacus.py * update abacus.py * update parse abacus scf lattice constant --------- Co-authored-by: qqgu <[email protected]> * style: optmize the import of each submodule (#154) * data import * optimize imports * fix: idp(data) in nnsk and deeptb, and refactor soc switch in hr2hk (#152) * refactor: plotting code in dftb2nnsk.py fix push_decay method and update push options (#156) * Refactor plotting code in dftb2nnsk.py * refactor(nnsk): Refactor NNSK class in nnsk.py to fix push_decay method and update push options * update saver.py to save ckpt with name of ovlp * fix: update nnsk from reference and change the sign of ovp_thr * update saver.py * update mos2 example * Update test_sktb.py with new model weights and fix init_model path in test_md * docs: Update dftb.md with hBN model training steps and fix formatting (#157) * docs: Update dftb.md with hBN model training steps and fix formatting * Bump actions/setup-python from 4 to 5 (#131) Bumps [actions/setup-python](https://github.com/actions/setup-python) from 4 to 5. - [Release notes](https://github.com/actions/setup-python/releases) - [Commits](actions/setup-python@v4...v5) --- updated-dependencies: - dependency-name: actions/setup-python dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Bump actions/checkout from 3 to 4 (#130) Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4. - [Release notes](https://github.com/actions/checkout/releases) - [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md) - [Commits](actions/checkout@v3...v4) --- updated-dependencies: - dependency-name: actions/checkout dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * feat: add -v to get dptb version, and update the version.py to load version number and git version (#158) * Refactor plotting code in dftb2nnsk.py * refactor(nnsk): Refactor NNSK class in nnsk.py to fix push_decay method and update push options * update saver.py to save ckpt with name of ovlp * fix: update nnsk from reference and change the sign of ovp_thr * update saver.py * update mos2 example * Update test_sktb.py with new model weights and fix init_model path in test_md * docs: Update dftb.md with hBN model training steps and fix formatting * Refactor main.py to add version flag and handle unknown version * Update pyproject.toml to add toml dependency * feat: update pyproject.toml and __init__.py to automatically get the version number. (#160) * Refactor plotting code in dftb2nnsk.py * refactor(nnsk): Refactor NNSK class in nnsk.py to fix push_decay method and update push options * update saver.py to save ckpt with name of ovlp * fix: update nnsk from reference and change the sign of ovp_thr * update saver.py * update mos2 example * Update test_sktb.py with new model weights and fix init_model path in test_md * docs: Update dftb.md with hBN model training steps and fix formatting * Refactor main.py to add version flag and handle unknown version * Update pyproject.toml to add toml dependency * update pyproject.toml and add -v command * update ut.sh * update unit_test.yml and ut.sh * ci: update unit_test.yml * ci: update unit_test.yml * ci: update unit_test.yml * ci: update unit_test.yml * ci: update unit_test.yml * ci: update unit_test.yml * build(deps): update 2 files and delete 1 file * ci: update devcontainer.yml * ci: update devcontainer.yml * ci: update devcontainer.yml * ci: update devcontainer.yml * ci: update devcontainer.yml * back to main * Update devcontainer.yml and unit_test.yml workflows --------- Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: Yinzhanghao Zhou <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
deepmodeling · May 6, 2024 · 6e97dd9 · 6e97dd9
1 parent df2917b
commit 6e97dd9
Show file tree

Hide file tree

Showing 58 changed files with 7,363 additions and 316 deletions.
diff --git a/.github/workflows/devcontainer.yml b/.github/workflows/devcontainer.yml
@@ -6,12 +6,6 @@ on:
       - 'docs/**'
     branches:
       - main
-  pull_request:
-    branches:
-      - main
-    paths:
-      - '.github/workflows/devcontainer.yml'
-      - '.github/workflows/unit_test.yml'
 
 jobs:
   build_container_and_push:
@@ -28,14 +22,14 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@v2
+        uses: docker/login-action@v3
         with:
           registry: ghcr.io
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Login to Aliyun Registry
-        uses: docker/login-action@v2
+        uses: docker/login-action@v3
         with:
           registry: registry.dp.tech
           username: ${{ secrets.DP_HARBOR_USERNAME }}
@@ -50,4 +44,4 @@ jobs:
           file: Dockerfile.${{ matrix.dockerfile }}
           cache-from: type=registry,ref=ghcr.io/deepmodeling/deeptb-${{ matrix.dockerfile }}:latest
           cache-to: type=inline
-          push: true
+          push: true
diff --git a/.github/workflows/publish-to-pypi.yml b/.github/workflows/publish-to-pypi.yml
@@ -8,9 +8,9 @@ jobs:
   publish:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.x'
     - name: Install dependencies

diff --git a/.github/workflows/publish-to-testpypi.yml b/.github/workflows/publish-to-testpypi.yml
@@ -10,10 +10,10 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.x'
 

diff --git a/.github/workflows/unit_test.yml b/.github/workflows/unit_test.yml
@@ -4,7 +4,6 @@ on:
   pull_request:
     paths-ignore:
       - 'docs/**'
-      - '.github/workflows/devcontainer.yml'
 
 jobs: 
   build:
@@ -21,6 +20,9 @@ jobs:
         with:
           fetch-depth: 0
           ref: "refs/pull/${{ github.event.number }}/merge"
+      - name: Add safe directory
+        run: |
+          git config --global --add safe.directory ${GITHUB_WORKSPACE}
       - name: Install DeePTB & Run Test
         id: s2
         run: |

diff --git a/docs/advanced/dftb.md b/docs/advanced/dftb.md
@@ -3,7 +3,9 @@
 This example demonstrates how to build a DeePTB model from DFTB SK files. The DFTB SK files are generated by the DFTB+ code. 
 
 
-## Step 1: Download DFTB SK Files
+## Example: train hBN model with DFTB SK files
+
+### Step 1: Download DFTB SK Files
 
 you can download the skfiles from the [dftb.org](https://dftb.org/parameters/download) website. Here we provide the some sk files in the folder `examples/hBN_dftb/slakos`. 
 
@@ -20,7 +22,9 @@ examples/hBN_dftb/slakos
 └── Si-Si.skf
 ```
 
-## Step 2: Load DFTB skfiles to in DeePTB to plot band structure:
+
+### Step 2: Load DFTB skfiles to in DeePTB to plot band structure:
+
 
 ```bash
 cd examples/hBN_dftb
@@ -77,7 +81,9 @@ bcal.band_plot(ref_band = kpath_kwargs["ref_band"],
 <img src="../img/hbn_dftb.png" alt="示例图片" width="500"/>
 
 
-## Step 3: Use SK params from DFTB skfiles to train DeePTB nnsk model
+
+### Step 3: Use SK params from DFTB skfiles to train DeePTB nnsk model
+
 
 
 use the input.json in the following:
@@ -239,7 +245,9 @@ bcal.band_plot(ref_band = kpath_kwargs["ref_band"],
 <img src="../img/hbn_nnsk_dftb.png" alt="示例图片" width="500"/>
 
 
-## Step4: load the previous trained model to further train the model use eigenvalues
+
+### Step4: load the previous trained model to further train the model use eigenvalues
+
 
 The input json looks like:
 

diff --git a/dptb/__init__.py b/dptb/__init__.py
@@ -1,2 +1,3 @@
-from dptb.version import get_version as _get_version
-__version__ = _get_version()
+import importlib.metadata
+
+__version__ = importlib.metadata.version("dptb")
diff --git a/dptb/data/__init__.py b/dptb/data/__init__.py
@@ -14,14 +14,13 @@
     AtomicInMemoryDataset,
     NpzDataset,
     ASEDataset,
-    HDF5Dataset,
     ABACUSDataset,
     ABACUSInMemoryDataset,
     DefaultDataset
 )
 from .dataloader import DataLoader, Collater, PartialSampler
-from .build import dataset_from_config
-from .test_data import EMTTestDataset
+from .build import build_dataset
+from .transforms import OrbitalMapper
 
 __all__ = [
     AtomicData,
@@ -33,17 +32,16 @@
     AtomicInMemoryDataset,
     NpzDataset,
     ASEDataset,
-    HDF5Dataset,
     ABACUSDataset,
     ABACUSInMemoryDataset,
     DefaultDataset,
     DataLoader,
     Collater,
     PartialSampler,
-    dataset_from_config,
+    OrbitalMapper,
+    build_dataset,
     _NODE_FIELDS,
     _EDGE_FIELDS,
     _GRAPH_FIELDS,
     _LONG_FIELDS,
-    EMTTestDataset,
 ]
diff --git a/dptb/data/dataset/_default_dataset.py b/dptb/data/dataset/_default_dataset.py
@@ -65,22 +65,11 @@ def __init__(self,
         else:
             raise ValueError("Wrong cell dimensions.")
 
-        # load atomic numbers
-        atomic_numbers = np.loadtxt(os.path.join(root, "atomic_numbers.dat"))
-        natoms = self.info["natoms"]
-        if natoms < 0:
-            natoms = atomic_numbers.shape[-1]
-        if atomic_numbers.shape[0] == self.info["natoms"]:
-            # same atomic_numbers, copy it to all frames.
-            atomic_numbers = np.expand_dims(atomic_numbers, axis=0)
-            self.data["atomic_numbers"] = np.broadcast_to(atomic_numbers, (self.info["nframes"], natoms))
-        elif atomic_numbers.shape[0] == natoms * self.info["nframes"]:
-            self.data["atomic_numbers"] = atomic_numbers.reshape(self.info["nframes"],natoms)
-        else:
-            raise ValueError("Wrong atomic_number dimensions.")
-
         # load positions, stored as cartesion no matter what provided.
         pos = np.loadtxt(os.path.join(root, "positions.dat"))
+        natoms = self.info["natoms"]
+        if natoms < 0:
+            natoms = int(pos.shape[0] / self.info["nframes"])
         assert pos.shape[0] == self.info["nframes"] * natoms
         pos = pos.reshape(self.info["nframes"], natoms, 3)
         # ase use cartesian by default.
@@ -91,6 +80,17 @@ def __init__(self,
         else:
             raise NameError("Position type must be cart / frac.")
 
+        # load atomic numbers
+        atomic_numbers = np.loadtxt(os.path.join(root, "atomic_numbers.dat"))
+        if atomic_numbers.shape[0] == natoms:
+            # same atomic_numbers, copy it to all frames.
+            atomic_numbers = np.expand_dims(atomic_numbers, axis=0)
+            self.data["atomic_numbers"] = np.broadcast_to(atomic_numbers, (self.info["nframes"], natoms))
+        elif atomic_numbers.shape[0] == natoms * self.info["nframes"]:
+            self.data["atomic_numbers"] = atomic_numbers.reshape(self.info["nframes"],natoms)
+        else:
+            raise ValueError("Wrong atomic_number dimensions.")
+
         # load optional data files
         if get_eigenvalues == True:
             if os.path.exists(os.path.join(self.root, "eigenvalues.npy")):