Add modules.py

Additional: 1. PointNetLit is renamed to PointLit to avoid confusion that it can be used only with PointNet. 2. Necessary changes in unit tests and docs due to 1.
adosar · Jul 3, 2024 · f5dfacc · f5dfacc
1 parent 24891da
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diff --git a/.github/workflows/pylint.yaml b/.github/workflows/pylint.yaml
@@ -15,5 +15,6 @@ jobs:
         run: |
           python -m pip install --upgrade pip
           pip install pylint
+          pip install .
       - name: Run pylint
         run: pylint src/aidsorb/
diff --git a/.github/workflows/unittest.yaml b/.github/workflows/unittest.yaml
@@ -11,5 +11,10 @@ jobs:
         uses: actions/setup-python@v5
         with:
           python-version: "3.11"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install pylint
+          pip install .
       - name: Run unit tests
         run: python -m unittest
diff --git a/README.md b/README.md
@@ -1,5 +1,5 @@
 <h1 align="center">
-  <img alt="Logo" src="https://raw.githubusercontent.com/adosar/trial/master/docs/source/images/aidsorb_logo_light.svg"/>
+  <img alt="AIdsorb logo" src="https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/aidsorb_logo_light.svg" width=50%/>
 </h1>
 
 <h4 align="center">
@@ -13,17 +13,13 @@
 
 **AIdsorb** is a Python package for **deep learning on molecular point clouds**.
 
-**AIdsorb** aims to provide a **fast, easy-to-use and reproduce** interface for:
+This package aims to provide a **fast, easy-to-use and reproduce** interface for:
 
 -   📥 **Creating molecular point clouds**
 
 -   🤖 **Training DL algorithms on molecular point clouds**
 
 
-<p align="center">
-  <img alt="Point cloud" src="https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/pcd.gif" width="25%"/>
-</p>
-
 ## ⚙️  Installation
 > [!IMPORTANT] 
 > It is strongly recommended to **perform the installation inside a virtual environment**.
@@ -44,6 +40,11 @@ Here is a summary of what you can do from the command line:
 	aidsorb visualize path/to/structure
 	```
 
+<p align="center">
+  <img alt="Point cloud" src="https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/pcd.gif" width="25%"/>
+</p>
+
+
 2.  Create and prepare point clouds:
 	```bash
 	aidsorb create path/to/inp path/to/out  # Create point clouds

diff --git a/docs/source/_autosummary/aidsorb.data.rst b/docs/source/_autosummary/aidsorb.data.rst
@@ -2,6 +2,6 @@
 ============
 
 .. automodule:: aidsorb.data
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.datamodules.rst b/docs/source/_autosummary/aidsorb.datamodules.rst
@@ -2,6 +2,6 @@
 ===================
 
 .. automodule:: aidsorb.datamodules
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.litmodels.rst b/docs/source/_autosummary/aidsorb.litmodels.rst
@@ -2,6 +2,6 @@
 =================
 
 .. automodule:: aidsorb.litmodels
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.models.rst b/docs/source/_autosummary/aidsorb.models.rst
@@ -2,6 +2,6 @@
 ==============
 
 .. automodule:: aidsorb.models
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.modules.rst b/docs/source/_autosummary/aidsorb.modules.rst
@@ -0,0 +1,7 @@
+aidsorb.modules
+===============
+
+.. automodule:: aidsorb.modules
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.transforms.rst b/docs/source/_autosummary/aidsorb.transforms.rst
@@ -2,6 +2,6 @@
 ==================
 
 .. automodule:: aidsorb.transforms
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.utils.rst b/docs/source/_autosummary/aidsorb.utils.rst
@@ -2,6 +2,6 @@
 =============
 
 .. automodule:: aidsorb.utils
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_autosummary/aidsorb.visualize.rst b/docs/source/_autosummary/aidsorb.visualize.rst
@@ -2,6 +2,6 @@
 =================
 
 .. automodule:: aidsorb.visualize
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/_templates/module.rst b/docs/source/_templates/module.rst
@@ -2,6 +2,6 @@
 {{ underline }}
 
 .. automodule:: {{ fullname }}
-	:members:
-	:undoc-members:
-	:show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/source/api.rst b/docs/source/api.rst
@@ -3,25 +3,23 @@
 :octicon:`book` API Documentation
 =================================
 
-..
 .. automodule:: aidsorb
     :members:
     :undoc-members:
     :show-inheritance:
 
-..
 .. rubric:: Submodules
 
-..
 .. autosummary::
-	:nosignatures:
-	:template: module.rst
-	:toctree: _autosummary
+    :nosignatures:
+    :template: module.rst
+    :toctree: _autosummary
 
-	aidsorb.utils
-	aidsorb.visualize
-	aidsorb.data
-	aidsorb.datamodules
-	aidsorb.transforms
-	aidsorb.models
-	aidsorb.litmodels
+    aidsorb.utils
+    aidsorb.visualize
+    aidsorb.data
+    aidsorb.datamodules
+    aidsorb.transforms
+    aidsorb.modules
+    aidsorb.models
+    aidsorb.litmodels
diff --git a/docs/source/auto_examples/auto_examples_jupyter.zip b/docs/source/auto_examples/auto_examples_jupyter.zip
diff --git a/docs/source/auto_examples/auto_examples_python.zip b/docs/source/auto_examples/auto_examples_python.zip
diff --git a/docs/source/auto_examples/resume.ipynb b/docs/source/auto_examples/resume.ipynb
@@ -11,7 +11,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "After training a model, you might want to test its performance, make\npredictions or do whatever you want with it, such as continue training.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>This example assummes:\n        * [PyTorch Lightning checkpoints](https://lightning.ai/docs/pytorch/stable/common/checkpointing_basic.html#lightningmodule-from-checkpoint)\n          are enabled during training.\n        * Training was performed with AIdsorb :doc:`../cli` or `AIdsorb +\n          PyTorch Lightning <aidsorb_with_pytorch_and_lightning>`.</p></div>\n\n"
+        "After training a model, you might want to test its performance, make\npredictions or do whatever you want with it.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>This example assummes:\n        * [PyTorch Lightning checkpoints](https://lightning.ai/docs/pytorch/stable/common/checkpointing_basic.html#lightningmodule-from-checkpoint)\n          are enabled during training.\n        * Training was performed with AIdsorb :doc:`../cli` or `AIdsorb +\n          PyTorch Lightning <aidsorb_with_pytorch_and_lightning>`.</p></div>\n\n"
       ]
     },
     {
@@ -22,7 +22,7 @@
       },
       "outputs": [],
       "source": [
-        "import yaml\nimport torch\nimport lightning as L\nfrom lightning.pytorch.cli import LightningCLI, LightningArgumentParser\nfrom aidsorb.datamodules import PCDDataModule\nfrom aidsorb.litmodels import PointNetLit\nfrom aidsorb.visualize import draw_pcd"
+        "import yaml\nimport torch\nimport lightning as L\nfrom lightning.pytorch.cli import LightningCLI, LightningArgumentParser\nfrom aidsorb.datamodules import PCDDataModule\nfrom aidsorb.litmodels import PointLit\nfrom aidsorb.visualize import draw_pcd"
       ]
     },
     {
@@ -40,7 +40,7 @@
       },
       "outputs": [],
       "source": [
-        "def load_from_config(filename):\n    r\"\"\"\n    Load configuration, trainer, model and datamodule from a ``.yaml`` file.\n\n    .. note::\n        You are responsible for restoring the model's state (the weights of the model).\n\n    Parameters\n    ----------\n    filename: str\n        Absolute or relative path to the ``.yaml`` configuration file.\n    \"\"\"\n    with open(filename, 'r') as f:\n        config_dict = yaml.safe_load(f)\n\n    config_dict['trainer']['logger'] = False\n    del config_dict['seed_everything'], config_dict['ckpt_path']\n\n    parser = LightningArgumentParser()\n    parser.add_class_arguments(PointNetLit, 'model', fail_untyped=False)\n    parser.add_class_arguments(PCDDataModule, 'data', fail_untyped=False)\n    parser.add_class_arguments(L.Trainer, 'trainer', fail_untyped=False)\n    config = parser.parse_object(config_dict)\n    objects = parser.instantiate_classes(config)\n\n    return config, objects.trainer, objects.model, objects.data"
+        "def load_from_config(filename):\n    r\"\"\"\n    Load configuration, trainer, model and datamodule from a ``.yaml`` file.\n\n    .. note::\n        You are responsible for restoring the model's state (the weights of the model).\n\n    Parameters\n    ----------\n    filename: str\n        Absolute or relative path to the ``.yaml`` configuration file.\n    \"\"\"\n    with open(filename, 'r') as f:\n        config_dict = yaml.safe_load(f)\n\n    config_dict['trainer']['logger'] = False\n    del config_dict['seed_everything'], config_dict['ckpt_path']\n\n    parser = LightningArgumentParser()\n    parser.add_class_arguments(PointLit, 'model', fail_untyped=False)\n    parser.add_class_arguments(PCDDataModule, 'data', fail_untyped=False)\n    parser.add_class_arguments(L.Trainer, 'trainer', fail_untyped=False)\n\n    config = parser.parse_object(config_dict)\n    objects = parser.instantiate_classes(config)\n\n    return config, objects.trainer, objects.model, objects.data"
       ]
     },
     {

diff --git a/docs/source/auto_examples/resume.py b/docs/source/auto_examples/resume.py
@@ -5,7 +5,7 @@
 
 # %%
 # After training a model, you might want to test its performance, make
-# predictions or do whatever you want with it, such as continue training.
+# predictions or do whatever you want with it.
 #
 # .. note::
 #     This example assummes:
@@ -20,7 +20,7 @@
 import lightning as L
 from lightning.pytorch.cli import LightningCLI, LightningArgumentParser
 from aidsorb.datamodules import PCDDataModule
-from aidsorb.litmodels import PointNetLit
+from aidsorb.litmodels import PointLit
 from aidsorb.visualize import draw_pcd
 
 # %%
@@ -53,9 +53,10 @@ def load_from_config(filename):
     del config_dict['seed_everything'], config_dict['ckpt_path']
 
     parser = LightningArgumentParser()
-    parser.add_class_arguments(PointNetLit, 'model', fail_untyped=False)
+    parser.add_class_arguments(PointLit, 'model', fail_untyped=False)
     parser.add_class_arguments(PCDDataModule, 'data', fail_untyped=False)
     parser.add_class_arguments(L.Trainer, 'trainer', fail_untyped=False)
+
     config = parser.parse_object(config_dict)
     objects = parser.instantiate_classes(config)
 

diff --git a/docs/source/auto_examples/resume.rst b/docs/source/auto_examples/resume.rst
@@ -24,7 +24,7 @@ Coming back after model training
 .. GENERATED FROM PYTHON SOURCE LINES 7-17
 
 After training a model, you might want to test its performance, make
-predictions or do whatever you want with it, such as continue training.
+predictions or do whatever you want with it.
 
 .. note::
     This example assummes:
@@ -44,7 +44,7 @@ predictions or do whatever you want with it, such as continue training.
     import lightning as L
     from lightning.pytorch.cli import LightningCLI, LightningArgumentParser
     from aidsorb.datamodules import PCDDataModule
-    from aidsorb.litmodels import PointNetLit
+    from aidsorb.litmodels import PointLit
     from aidsorb.visualize import draw_pcd
 
 
@@ -60,7 +60,7 @@ with the same settings as in the ``.yaml`` configuration file. For more
 information 👉 `here
 <https://github.com/Lightning-AI/pytorch-lightning/discussions/10363#discussioncomment-2326235>`_.
 
-.. GENERATED FROM PYTHON SOURCE LINES 36-64
+.. GENERATED FROM PYTHON SOURCE LINES 36-65
 
 .. code-block:: Python
 
@@ -84,29 +84,30 @@ information 👉 `here
         del config_dict['seed_everything'], config_dict['ckpt_path']
 
         parser = LightningArgumentParser()
-        parser.add_class_arguments(PointNetLit, 'model', fail_untyped=False)
+        parser.add_class_arguments(PointLit, 'model', fail_untyped=False)
         parser.add_class_arguments(PCDDataModule, 'data', fail_untyped=False)
         parser.add_class_arguments(L.Trainer, 'trainer', fail_untyped=False)
+
         config = parser.parse_object(config_dict)
         objects = parser.instantiate_classes(config)
 
         return config, objects.trainer, objects.model, objects.data
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 65-68
+.. GENERATED FROM PYTHON SOURCE LINES 66-69
 
 .. code-block:: Python
 
 
     config, trainer, litmodel, dm = load_from_config('path/to/logs/config.yaml')
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 71-73
+.. GENERATED FROM PYTHON SOURCE LINES 72-74
 
 Restoring model's state 
 -----------------------
 
-.. GENERATED FROM PYTHON SOURCE LINES 73-77
+.. GENERATED FROM PYTHON SOURCE LINES 74-78
 
 .. code-block:: Python
 
@@ -115,7 +116,7 @@ Restoring model's state
     model_weights = {k: v for k, v in ckpt['state_dict'].items() if k.startswith('model.')}
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 78-84
+.. GENERATED FROM PYTHON SOURCE LINES 79-85
 
 .. code-block:: Python
 
@@ -126,7 +127,7 @@ Restoring model's state
     litmodel(x);
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 85-89
+.. GENERATED FROM PYTHON SOURCE LINES 86-90
 
 .. code-block:: Python
 
@@ -135,7 +136,7 @@ Restoring model's state
     litmodel.load_state_dict(model_weights)
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 90-96
+.. GENERATED FROM PYTHON SOURCE LINES 91-97
 
 .. code-block:: Python
 
@@ -146,12 +147,12 @@ Restoring model's state
 
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 97-99
+.. GENERATED FROM PYTHON SOURCE LINES 98-100
 
 Measure performance and make predictions
 ----------------------------------------
 
-.. GENERATED FROM PYTHON SOURCE LINES 99-103
+.. GENERATED FROM PYTHON SOURCE LINES 100-104
 
 .. code-block:: Python
 
@@ -160,7 +161,7 @@ Measure performance and make predictions
     trainer.test(litmodel, dm)
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 104-110
+.. GENERATED FROM PYTHON SOURCE LINES 105-111
 
 .. code-block:: Python
 

diff --git a/docs/source/auto_examples/resume_codeobj.pickle b/docs/source/auto_examples/resume_codeobj.pickle
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -45,7 +45,6 @@
      'examples_dirs': 'examples',   # path to your example scripts
      'gallery_dirs': 'auto_examples',  # path to where to save gallery generated output
      'ignore_pattern': r'{/.*\.xyz, /.*\.cif}',
-     'image_scrapers': (plotly_sg_scraper,),
 }
 
 intersphinx_mapping = {

diff --git a/docs/source/download/config.yaml b/docs/source/download/config.yaml
@@ -1,6 +1,7 @@
 seed_everything: 1  # Workers are seeded as well.
 
 # Here you setup the Trainer.
+# https://lightning.ai/docs/pytorch/stable/common/trainer.html#trainer-class-api
 trainer:
   max_epochs: 2
   accelerator: 'gpu'