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 +1,35 @@
+# 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--> id21{"Does the initialize method inherit from BaseHandler?"}
+    id21{"Does the initialize method inherit from BaseHandler?"} -- Yes --> id2{Model Type?}
+    id21{Does the initialize method inherit from BaseHandler?} -- No --> id20("Create a custom method to
+         load the model in the handler") --> id11(Create a model archive .mar file)
+    id15["Create model archive by passing the
+    weights with --serialized-file option"]
+    id16["Specify path to the weights in model-config.yaml
+    Create model archive by specifying yaml file with --config-file "]
+	id11(Work on creating a model archive .mar file) --> id14{"Is your model large?"} --No--> id22{Do you want a self-contained model artifact}  --Yes--> id15
+	id14{"Is your model large?"} --Yes--> id16
+	id22{Do you want a self-contained model artifact} --No, I want model archieving & loading to be faster--> id16
+	id15 & id16 --> id17["Start TorchServe.
+	Two ways of starting torchserve
+	- Pass the mar file with --models
+	- Start TorchServe and call the register API with mar file"]
+
+
+
+
+```