From 9c5d610988ad257061a18e3cd0e45d4176ceab8b Mon Sep 17 00:00:00 2001
From: parthmannan <38387286+parthmannan@users.noreply.github.com>
Date: Thu, 19 Jan 2023 23:04:25 -0800
Subject: [PATCH 1/2] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 6708124..e1e1d0b 100644
--- a/README.md
+++ b/README.md
@@ -82,4 +82,4 @@ edge_shapes = [nx_g.edges[x]['shape'] for x in nx.edge_bfs(nx_g, source=source_n
 
 2. Graph drawing of the extracted graph
 Example below
-![Example Graph][examples/fx_graph_extracted_id_count(1).png]
+![Example Graph](examples/fx_graph_extracted_id_count(1).png)

From e0beab51ccf5d7f4e75abbc85dbe91b6b48e8926 Mon Sep 17 00:00:00 2001
From: parthmannan <38387286+parthmannan@users.noreply.github.com>
Date: Thu, 19 Jan 2023 23:05:36 -0800
Subject: [PATCH 2/2] Update README.md

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index e1e1d0b..ed4dd0d 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,7 @@ torch.compile(net, backend='nvprims_nvfuser')
 ```
 I am using `nvprims_nvfuser` backend here to get FX Graph with higher level semantics. You can use TorchInductor (default backend) and you'll get a graph with lower level ops. For example, Softmax would be broken down into primitive ops.
 Though I don't anticipate any issues, this code has not been tested with TorchInductor.
+
 3. Install pydot package
 ```
 pip install pydot