Merge pull request #10 from viam-modules/inline-docs

RSDK-9945: edits for inline docs

README.md

@@ -56,7 +56,14 @@ The following attributes are available to configure your module:
 | `model_path` | string | **Required** |         | Path to **standalone** model file |
 | `label_path` | string | Optional     |         | Path to file with class labels.   |
 
+### Example configuration
 
+```json
+{
+    "model_path": "${packages.ml_model.myMLModel}/my_model.pt", 
+    "label_path": "${packages.ml_model.myMLModel}/labels.txt"
+}
+```
 
 
 # Methods

meta.json

@@ -1,12 +1,14 @@
 {
   "module_id": "viam:torch-cpu",
   "visibility": "public",
-  "url": "https://github.com/viam-labs/torch",
+  "url": "https://github.com/viam-modules/torch",
   "description": "Viam ML Module service serving PyTorch models.",
   "models": [
     {
       "api": "rdk:service:mlmodel",
-      "model": "viam:mlmodel:torch-cpu"
+      "model": "viam:mlmodel:torch-cpu",
+      "markdown_link": "README.md#example-configuration",
+      "short_description": "An ML Model Service that can run PyTorch models in a standard format"
     }
   ],
   "build": {
@@ -19,4 +21,4 @@
     ]
   },
   "entrypoint": "dist/main"
-}
+}

src/test_local.py

@@ -180,4 +180,3 @@ def test_infer_method(self):
 
 if __name__ == "__main__":
     unittest.main()
-

src/torch_mlmodel_module.py

@@ -95,7 +95,11 @@ def get_attribute_from_config(attribute_name: str, default, of_type=None):
         self._metadata = self.inspector.find_metadata(label_file)
 
     async def infer(
-        self, input_tensors: Dict[str, NDArray], *, timeout: Optional[float]
+        self,
+        input_tensors: Dict[str, NDArray],
+        *,
+        extra: Optional[Mapping[str, ValueTypes]],
+        timeout: Optional[float],
     ) -> Dict[str, NDArray]:
         """Take an already ordered input tensor as an array,
         make an inference on the model, and return an output tensor map.
@@ -110,7 +114,12 @@ async def infer(
         """
         return self.torch_model.infer(input_tensors)
 
-    async def metadata(self, *, timeout: Optional[float]) -> Metadata:
+    async def metadata(
+            self,
+            *,
+            extra: Optional[Mapping[str, ValueTypes]],
+            timeout: Optional[float],
+    ) -> Metadata:
         """Get the metadata (such as name, type, expected tensor/array shape,
         inputs, and outputs) associated with the ML model.