Instantiated the nested PretrainedConfig correctly. Added a test to demo

.gitignore

@@ -3,3 +3,4 @@
 pyrightconfig.json
 *.jpg
 *.pyc
+.env

.vscode/settings.json

@@ -20,4 +20,8 @@
     //     },
     // },
     // "isort.args":["--profile", "black"],
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true,
+    "python.testing.cwd": "${workspaceFolder}/",
+    "python.envFile": "${workspaceFolder}/.env",
 }

src/config.py

@@ -99,6 +99,16 @@ class TinyCLIPConfig(PretrainedConfig):
         self.loss_type = loss_type
         super().__init__(**kwargs)
 
+    @classmethod
+    def from_dict(cls, config_dict, **kwargs):
+        text_config_dict = config_dict.pop("text_config", {})
+        text_config = TinyCLIPTextConfig.from_dict(text_config_dict)
+
+        vision_config_dict = config_dict.pop("vision_config", {})
+        vision_config = TinyCLIPVisionConfig.from_dict(vision_config_dict)
+
+        return cls(text_config=text_config, vision_config=vision_config, **config_dict, **kwargs)
+
 
 class TrainerConfig(pydantic.BaseModel):
     epochs: int = 20
@@ -119,3 +129,8 @@ class TrainerConfig(pydantic.BaseModel):
 
     _model_config: TinyCLIPConfig = TinyCLIPConfig()
     _data_config: DataConfig = DataConfig()
+
+    def __init__(self, **data):
+        super().__init__(**data)
+        if "_model_config" in data:
+            self._model_config = TinyCLIPConfig.from_dict(data["_model_config"])

tests/test_config.py

@@ -0,0 +1,13 @@
+from src import config
+import json
+
+
+def test_trainer_config():
+    trainer_config = config.TrainerConfig.model_validate_json(
+        json.dumps({"epochs": 21, "_model_config": {"text_config": {"text_model": "test"}}})
+    )
+
+    assert trainer_config.epochs == 21
+    assert trainer_config._model_config.text_config.text_model == "test"
+    assert hasattr(trainer_config._model_config.text_config, "max_len")
+    assert trainer_config._model_config.vision_config == config.TinyCLIPVisionConfig()