chore: update doc for partitioning

Signed-off-by: Bo Wang <[email protected]>

Author: bowang007

core/partitioning/README.md

@@ -1,6 +1,6 @@
 # TRTorch Partitioning
 
-TRTorch partitioning phase is developed to support automatic fallback feature in TRTorch. This phase won't run by
+TRTorch partitioning phase is developed to support `automatic fallback` feature in TRTorch. This phase won't run by
 default until the automatic fallback feature is enabled.
 
 On a high level, TRTorch partitioning phase does the following:
@@ -15,6 +15,8 @@ from the user. Shapes can be calculated by running the graphs with JIT.
   it's still a phase in our partitioning process.
 - `Stitching`. Stitch all TensorRT engines with PyTorch nodes altogether. 
 
+Test cases for each of these components could be found [here](https://github.com/NVIDIA/TRTorch/tree/master/tests/core/partitioning).
+
 Here is the brief description of functionalities of each file:
 - `PartitionInfo.h/cpp`: The automatic fallback APIs that is used for partitioning. 
 - `SegmentedBlock.h/cpp`: The main data structures that is used to maintain information for each segments after segmentation.
@@ -34,8 +36,8 @@ To enable automatic fallback feature, you can set following attributes in Python
     ...
     "torch_fallback" : {
       "enabled" : True,
-      "min_block_size" : 1,
-      "forced_fallback_ops": ["aten::foo"],
+      "min_block_size" : 3,
+      "forced_fallback_ops": ["aten::add"],
     } 
   })
 ```
@@ -58,8 +60,8 @@ auto mod = trtorch::jit::load("trt_ts_module.ts");
 auto input_sizes =  std::vector<trtorch::CompileSpec::InputRange>{{in.sizes()}};
 trtorch::CompileSpec cfg(input_sizes);
 cfg.torch_fallback = trtorch::CompileSpec::TorchFallback(true);
-cfg.torch_fallback.min_block_size = 1;
-cfg.torch_fallback.forced_fallback_ops.push_back("aten::foo");
+cfg.torch_fallback.min_block_size = 2;
+cfg.torch_fallback.forced_fallback_ops.push_back("aten::relu");
 auto trt_mod = trtorch::CompileGraph(mod, cfg);
 auto out = trt_mod.forward({in});
 ```