Merge branch 'develop' of github.com:roll-away/GraphNet into develop

Author: roll-away

.pre-commit-config.yaml

@@ -3,4 +3,25 @@ repos:
   rev: 23.1.0
   hooks:
   - id: black
-    language_version: python3
+    language_version: python3
+
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  rev: v0.14.4
+  hooks:
+    - id: ruff-check
+      args: [--fix, --exit-non-zero-on-fix, --no-cache]
+
+- repo: https://github.com/PFCCLab/typos-pre-commit-mirror.git
+  rev: v1.39.2
+  hooks:
+    - id: typos
+      args: [--force-exclude]
+
+- repo: https://github.com/Lucas-C/pre-commit-hooks.git
+  rev: v1.5.1
+  hooks:
+    - id: remove-crlf
+    - id: remove-tabs
+      name: Tabs remver (Python)
+      files: (.*\.(py|bzl)|BUILD|.*\.BUILD|WORKSPACE)$
+      args: [--whitespaces-count, '4']

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

graph_net/__init__.py

@@ -1,21 +1,21 @@
-__all__ = ["torch", "paddle"]
-
-from importlib import import_module
-from typing import TYPE_CHECKING, Any, List
-
-
-def __getattr__(name: str) -> Any:
-    if name in __all__:
-        module = import_module(f"{__name__}.{name}")
-        globals()[name] = module
-        return module
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
-
-
-def __dir__() -> List[str]:
-    return sorted(list(globals().keys()) + __all__)
-
-
-if TYPE_CHECKING:
-    from . import torch as torch  # type: ignore
-    from . import paddle as paddle  # type: ignore
+__all__ = ["torch", "paddle"]
+
+from importlib import import_module
+from typing import TYPE_CHECKING, Any, List
+
+
+def __getattr__(name: str) -> Any:
+    if name in __all__:
+        module = import_module(f"{__name__}.{name}")
+        globals()[name] = module
+        return module
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+
+
+def __dir__() -> List[str]:
+    return sorted(list(globals().keys()) + __all__)
+
+
+if TYPE_CHECKING:
+    from . import torch as torch  # type: ignore
+    from . import paddle as paddle  # type: ignore