add doc: create a model (deepmodeling#1143)

* add doc: create a model

* use another reference style

doc/development/create-a-model.md

@@ -0,0 +1,71 @@
+# Create a model
+
+If you'd like to create a new model that isn't covered by the existing DeePMD-kit library, but reuse DeePMD-kit's other efficient module such as data processing, trainner, etc, you may want to read this section.
+
+To incorporate your custom model you'll need to:
+1. Register and implement new components (e.g. descriptor) in a Python file. You may also want to regiester new TensorFlow OPs if necessary.
+2. Register new arguments for user inputs.
+3. Package new codes into a Python package.
+4. Test new models.
+
+## Design a new component
+
+When creating a new component, take descriptor as the example, you should inherit {py:class}`deepmd.descriptor.descriptor.Descriptor` class and override several methods. Abstract methods such as {py:class}`deepmd.descriptor.descriptor.Descriptor.build` must be implemented and others are not. You should keep arguments of these methods unchanged.
+
+After implementation, you need to register the component with a key:
+```py
+from deepmd.descriptor import Descriptor
+
+@Descriptor.register("some_descrpt")
+class SomeDescript(Descriptor):
+    def __init__(self, arg1: bool, arg2: float) -> None:
+        pass
+```
+
+## Register new arguments
+
+To let some one uses your new component in their input file, you need to create a new methods that returns some `Argument` of your new component, and then register new arguments. For example, the code below
+
+```py
+from typing import List
+
+from dargs import Argument
+from deepmd.utils.argcheck import descrpt_args_plugin
+
+@descrpt_args_plugin.register("some_descrpt")
+def descrpt_some_args() -> List[Argument]:
+    return [
+        Argument("arg1", bool, optional=False, doc="balabala"),
+        Argument("arg2", float, optional=True, default=6.0, doc="haha"),
+    ]
+```
+
+allows one to use your new descriptor as below:
+
+```json
+"descriptor" :{
+    "type": "some_descrpt",
+    "arg1": true,
+    "arg2": 6.0
+}
+```
+
+The arguments here should be consistent with the class arguments of your new componenet.
+
+## Package new codes
+
+You may use `setuptools` to package new codes into a new Python package. It's crirical to add your new component to `entry_points['deepmd']` in `setup.py`:
+
+```py
+    entry_points={
+        'deepmd': [
+            'some_descrpt=deepmd_some_descrtpt:SomeDescript',
+        ],
+    },
+```
+
+where `deepmd_some_descrtpt` is the module of your codes. It is equivalent to `from deepmd_some_descrtpt import SomeDescript`.
+
+If you place `SomeDescript` and `descrpt_some_args` into different modules, you are also expected to add `descrpt_some_args` to `entry_points`.
+
+After you install your new package, you can now use `dp train` to run your new model.