Make predictor top-level key, update documentation and examples (#704)

Author: vishalbollu

cli/cmd/get.go

@@ -272,7 +272,7 @@ func describeAPI(name string, resourcesRes *schema.GetResourcesResponse, flagVer
 
 	out += fmt.Sprintf("\n%s curl %s?debug=true -X POST -H \"Content-Type: application/json\" -d @sample.json", console.Bold("curl:"), apiEndpoint)
 
-	if api.TensorFlow != nil || api.ONNX != nil {
+	if api.Predictor.Type == userconfig.TensorFlowPredictorType || api.Predictor.Type == userconfig.ONNXPredictorType {
 		out += "\n\n" + describeModelInput(groupStatus, apiEndpoint)
 	}
 

docs/deployments/onnx.md

@@ -10,9 +10,10 @@ You can deploy ONNX models as web services by defining a class that implements C
 - kind: api
   name: <string>  # API name (required)
   endpoint: <string>  # the endpoint for the API (default: /<deployment_name>/<api_name>)
-  onnx:
+  predictor:
+    type: onnx
+    path: <string>  # path to a python file with an ONNXPredictor class definition, relative to the Cortex root (required)
     model: <string>  # S3 path to an exported model (e.g. s3://my-bucket/exported_model.onnx) (required)
-    predictor: <string>  # path to a python file with an ONNXPredictor class definition, relative to the Cortex root (required)
     config: <string: value>  # dictionary passed to the constructor of a Predictor (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
     env: <string: string>  # dictionary of environment variables
@@ -36,9 +37,10 @@ See [packaging ONNX models](../packaging-models/onnx.md) for information about e
 ```yaml
 - kind: api
   name: my-api
-  onnx:
+  predictor:
+    type: onnx
+    path: predictor.py
     model: s3://my-bucket/my-model.onnx
-    predictor: predictor.py
   compute:
     gpu: 1
 ```

docs/deployments/prediction-monitoring.md

@@ -21,8 +21,9 @@ For classification models, the tracker should be configured with `model_type: cl
 ```yaml
 - kind: api
   name: iris
-  python:
-    predictor: predictor.py
+  predictor:
+    type: python
+    path: predictor.py
   tracker:
     model_type: classification
 ```

docs/deployments/python.md

@@ -15,8 +15,9 @@ In addition to supporting Python models via the Python Predictor interface, Cort
 - kind: api
   name: <string>  # API name (required)
   endpoint: <string>  # the endpoint for the API (default: /<deployment_name>/<api_name>)
-  python:
-    predictor: <string>  # path to a python file with a PythonPredictor class definition, relative to the Cortex root (required)
+  predictor:
+    type: python
+    path: <string>  # path to a python file with a PythonPredictor class definition, relative to the Cortex root (required)
     config: <string: value>  # dictionary passed to the constructor of a Predictor (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
     env: <string: string>  # dictionary of environment variables

docs/deployments/tensorflow.md

@@ -10,9 +10,10 @@ You can deploy TensorFlow models as web services by defining a class that implem
 - kind: api
   name: <string>  # API name (required)
   endpoint: <string>  # the endpoint for the API (default: /<deployment_name>/<api_name>)
-  tensorflow:
+  predictor:
+    type: tensorflow
+    path: <string>  # path to a python file with a TensorFlowPredictor class definition, relative to the Cortex root (required)
     model: <string>  # S3 path to an exported model (e.g. s3://my-bucket/exported_model) (required)
-    predictor: <string>  # path to a python file with a TensorFlowPredictor class definition, relative to the Cortex root (required)
     signature_key: <string>  # name of the signature def to use for prediction (required if your model has more than one signature def)
     config: <string: value>  # dictionary that can be used to configure custom values (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
@@ -37,9 +38,10 @@ See [packaging TensorFlow models](../packaging-models/tensorflow.md) for how to
 ```yaml
 - kind: api
   name: my-api
-  tensorflow:
+  predictor:
+    type: tensorflow
+    path: predictor.py
     model: s3://my-bucket/my-model
-    predictor: predictor.py
   compute:
     gpu: 1
 ```

docs/packaging-models/onnx.md

@@ -31,7 +31,8 @@ Reference your model in an `api`:
 ```yaml
 - kind: api
   name: my-api
-  onnx:
+  predictor:
+    type: onnx
     model: s3://my-bucket/model.onnx
     predictor: predictor.py
 ```

docs/packaging-models/tensorflow.md

@@ -38,7 +38,8 @@ Reference your model in an `api`:
 ```yaml
 - kind: api
   name: my-api
-  tensorflow:
+  predictor:
+    type: tensorflow
     model: s3://my-bucket/bert
     predictor: predictor.py
 ```
@@ -56,7 +57,8 @@ Reference the zipped model in an `api`:
 ```yaml
 - kind: api
   name: my-api
-  tensorflow:
+  predictor:
+    type: tensorflow
     model: s3://my-bucket/bert.zip
     predictor: predictor.py
 ```

examples/pytorch/answer-generator/cortex.yaml

@@ -5,8 +5,9 @@
 
 - kind: api
   name: generator
-  python:
-    predictor: predictor.py
+  predictor:
+    type: python
+    path: predictor.py
     config:
       device: cuda  # use "cpu" to run on CPUs
   compute:

examples/pytorch/image-classifier/cortex.yaml

@@ -5,8 +5,9 @@
 
 - kind: api
   name: classifier
-  python:
-    predictor: predictor.py
+  predictor:
+    type: python
+    path: predictor.py
   compute:
     cpu: 1
     gpu: 1

examples/pytorch/iris-classifier/cortex.yaml

@@ -5,8 +5,9 @@
 
 - kind: api
   name: classifier
-  python:
-    predictor: predictor.py
+  predictor:
+    type: python
+    path: predictor.py
     config:
       model: s3://cortex-examples/pytorch/iris-classifier/weights.pth
   tracker: