Merge branch 'develop' into spilt

Author: fangfangssj

.pre-commit-config.yaml

@@ -3,4 +3,4 @@ repos:
   rev: 23.1.0
   hooks:
   - id: black
-    language_version: python3
+    language_version: python3

README.md

@@ -59,29 +59,19 @@ After executing, `graph_net.torch.test_compiler` will:
 3. Executing the compiled model and collecting its runtime and outputs.
 4. Conduct speedup by comparing the compiled results against the baseline (if no execution failure occurs).
 
-**Step 2: Generate JSON Record**
+**Step 2: Analysis**
 
-Extract runtime, correctness, and failure information from benchmark logs:
-
-```bash
-python -m graph_net.log2json \
-  --log-file $GRAPH_NET_BENCHMARK_PATH/log.log \
-  --output-dir $GRAPH_NET_BENCHMARK_PATH/JSON_results/
-```
-
-**Step 3: Analysis**
-
-Use the three scripts `graph_net.plot_St`, `graph_net.plot_ESt` and `graph_net.plot_violin` to generate St plot, ESt plot, and [violin plot](https://en.m.wikipedia.org/wiki/Violin_plot) based on the JSON results.
+Use the three scripts `graph_net.plot_St`, `graph_net.plot_ESt` and `graph_net.plot_violin` to generate St plot, ESt plot, and [violin plot](https://en.m.wikipedia.org/wiki/Violin_plot) based on speedup, correctness and runtime information from benchmark logs.
 
 ```bash
 python -m graph_net.plot_St \
-  --benchmark-path $GRAPH_NET_BENCHMARK_PATH/JSON_results/ \
+  --benchmark-path $GRAPH_NET_BENCHMARK_PATH/log.log \
   --output-dir $GRAPH_NET_BENCHMARK_PATH \
   --negative-speedup-penalty penalty/power/for/negative/speedup \
   --fpdb base/penalty/for/severe/errors
 
 python -m graph_net.plot_ESt \
-  --benchmark-path $GRAPH_NET_BENCHMARK_PATH/JSON_results/ \
+  --benchmark-path $GRAPH_NET_BENCHMARK_PATH/log.log \
   --output-dir $GRAPH_NET_BENCHMARK_PATH \
   --negative-speedup-penalty penalty/power/for/negative/speedup \
   --fpdb base/penalty/for/severe/errors

docs/README_contribute.md

@@ -49,7 +49,7 @@ import graph_net
 model = ...  
 
 # Extract your own model
-model = graph_net.torch.extract(name="model_name", dynamic="True")(model)
+model = graph_net.torch.extract(name="model_name", dynamic=True)(model)
 ```
 
 After running, the extracted graph will be saved to: `$GRAPH_NET_EXTRACT_WORKSPACE/model_name/`.