adding scripts for easy local run (#59)

README.md

@@ -67,7 +67,7 @@ bash environments/run_jupyter.sh
 
 # Tooling
 
-One can use [autoenv](https://github.com/hyperupcall/autoenv) to make setting up the environment and environment variables easier. This will run the `.envrc` file upon entering the `/path/to/mattport` folder. It will also remove the environment parameters upon leaving.
+1. One can use [autoenv](https://github.com/hyperupcall/autoenv) to make setting up the environment and environment variables easier. This will run the `.envrc` file upon entering the `/path/to/mattport` folder. It will also remove the environment parameters upon leaving.
 
 ```
 # Install direnv.
@@ -79,4 +79,20 @@ eval "$(direnv hook bash)"
 # Populate your .envrc with commands you want to run. Then, run the following to allow updates.
 cd /path/to/mattport
 direnv allow .
+```
+
+2. To run local **github actions**, you can run:
+```
+python scripts/debugging/run_actions.py 
+```
+
+3. To run local **profiling** to get a flame graph, make sure [pyspy](https://github.com/benfred/py-spy) is installed and you can run:
+```
+pip install py-spy
+
+## for flame graph
+./scripts/debugging/profile.sh -t flame -o flame.svg -p scripts/run_train.py data/dataset=blender_lego
+
+## for live view of functions
+./scripts/debugging/profile.sh -t top -p scripts/run_train.py data/dataset=blender_lego
 ```

scripts/debugging/profile.sh

@@ -0,0 +1,43 @@
+#!/bin/bash
+
+helpFunction_flame()
+{
+   echo "Usage: $0 -o output_file -p program"
+   echo -e "\t-o output .svg filename, where to save flame graph"
+   echo -e "\t-p .py program we want to profile with associated arguments"
+   exit 1 # Exit program after printing help
+}
+
+helpFunction_top()
+{
+   echo "Usage: $0 -p program"
+   echo -e "\t-p .py program we want to profile with associated arguments"
+   exit 1 # Exit program after printing help
+}
+
+
+while getopts "t:o:p:a:" opt; do
+    case "$opt" in
+        t ) type="$OPTARG" ;;
+        o ) output_file="$OPTARG" ;;
+        p ) program="$OPTARG" ;;
+        ? ) helpFunction ;; 
+    esac
+    done
+    if [ -z "$type" ]; then
+        echo "Missing profiling type (flame / top)"
+    fi
+    # Print helpFunction in case parameters are empty
+    if [[ "$type" = "flame" ]]; then
+        if [ -z "$output_file" ] || [ -z "$program" ]; then
+            echo "Some or all of the parameters are empty";
+            helpFunction_flame
+        fi
+        py-spy record -o "$output_file" python "$program" 
+    elif [[ "$type" = "top" ]]; then
+        if [ -z "$program" ]; then
+            echo "Some or all of the parameters are empty";
+            helpFunction_top
+        fi
+        py-spy top python "$program" 
+    fi

scripts/debugging/run_actions.py

@@ -0,0 +1,26 @@
+"""Simple yaml debugger"""
+import subprocess
+
+import yaml
+
+LOCAL_TESTS = ["Run Black", "Python Pylint", "Test with pytest"]
+
+if __name__ == "__main__":
+    with open(".github/workflows/code_checks.yml", "rb") as f:
+        my_dict = yaml.safe_load(f)
+    steps = my_dict["jobs"]["build"]["steps"]
+
+    for step in steps:
+        if "name" in step and step["name"] in LOCAL_TESTS:
+            if step["name"] == "Run Black":
+                curr_command = f"black mattport/ {step['with']['options']};"
+            else:
+                compressed = step["run"].replace("\n", "").replace("\\", "")
+                curr_command = f"{compressed};"
+
+            print("*" * 100)
+            print(f"Running {curr_command}")
+            subprocess.call(curr_command, shell=True)
+        else:
+            print("*" * 100)
+            print(f"Skipping {step}")