A guide for loading models in TorchServe

docs/README.md

@@ -7,6 +7,7 @@ TorchServe is a performant, flexible and easy to use tool for serving PyTorch ea
 * [Serving Quick Start](https://github.com/pytorch/serve/blob/master/README.md#serve-a-model) - Basic server usage tutorial
 * [Model Archive Quick Start](https://github.com/pytorch/serve/tree/master/model-archiver#creating-a-model-archive) - Tutorial that shows you how to package a model archive file.
 * [Installation](https://github.com/pytorch/serve/blob/master/README.md#install-torchserve) - Installation procedures
+* [Model loading](model_loading.md) - How to load a model in TorchServe?
 * [Serving Models](server.md) - Explains how to use TorchServe
 * [REST API](rest_api.md) - Specification on the API endpoint for TorchServe
 * [gRPC API](grpc_api.md) - TorchServe supports gRPC APIs for both inference and management calls

docs/model_loading.md

@@ -0,0 +1,28 @@
+# How to load a model in TorchServe
+
+There are multiple ways to load to model in TorchServe. The below flowchart tries to simplify the process and shows the various options
+
+```mermaid
+flowchart TD
+    id1[[How to load a model in TorchServe?]] --> id13{Handler has an initialize method?}
+    id13{Handler has an initialize method?} -- No, using BaseHandler initialize method --> id2{Model Type?} --> id3(PyTorch Eager)  & id4(TorchScripted) & id5(ONNX) & id6(TensorRT)
+    id3(PyTorch Eager) --Required--> id7(Model File & weights file)
+    id4(TorchScripted) --Required--> id8(TorchScripted weights ending in '.pt')
+    id5(ONNX) --Required--> id9(Weights ending in '.onnx')
+    id6(TensorRT) --Required--> id10(TensorRT weights ending in '.pt')
+    id7(Model File & weights file) & id8(TorchScripted weights ending in '.pt') &  id9(Weights ending in '.onnx') & id10(TensorRT weights ending in '.pt') --> id11(Created a model archive .mar file)
+    id13{Handler has an initialize method?} -- yes --> id11(Create a model archive .mar file)
+    id15["Pass the weights with --serialized-file option
+    - Completely packaged for production/reproducibility
+    - Model archiving and model loading can be slow for large models"]
+    id16["Pass the path to the weights in model-config.yaml
+    - Extremely fast to create model archive
+    - You can use deferred initialization for large models
+    - Model loading can be faster for large model
+    - Model management can be harder"]
+	id11(Create a model archive .mar file) --> id14{Self-contained package} --Yes--> id15
+	id14{Self-contained package} --No--> id16
+	id15 & id16 --> id17[Start TorchServe with mar file]
+	id15 & id16 --> id18[Start TorchServe] --> id19[Register Model with mar file]
+
+```