Yeyito commited on
Commit
d649c17
1 Parent(s): 0217809

Modulized subprocess

Browse files
Files changed (3) hide show
  1. .gitignore +4 -0
  2. app.py +20 -11
  3. requirements.txt +1 -0
.gitignore ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
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+ Environment/
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+ out/
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+ flagged/
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+
app.py CHANGED
@@ -1,16 +1,25 @@
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  import gradio as gr
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  import subprocess
 
 
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- dataset = "truthful_qa"
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- def greet(model):
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- global dataset
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- command = f"python detect-pretrain-code-contamination/src/run.py --target_model {model} --ref_model roneneldan/TinyStories-Instruct-1M --data {dataset} --output_dir detect-pretrain-code-contamination/out/{dataset} --ratio_gen 0.4"
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- result = subprocess.run(command, shell=True,capture_output=True, text=True)
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-
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- if result.returncode == 0:
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- return result.stdout
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- else:
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- return f"Error: {result.stderr}"
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- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 
 
 
 
 
 
 
 
 
 
 
 
 
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  iface.launch()
 
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  import gradio as gr
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  import subprocess
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+ import os
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+ import sys
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+ # Add the path to the "src" directory of detect-pretrain-code-contamination to the sys.path
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+ project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "detect-pretrain-code-contamination"))
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+ src_dir = os.path.join(project_root, "src")
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+ sys.path.insert(0, src_dir)
 
 
 
 
 
 
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+ import run as evaluator # Import the run module
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+
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+ def evaluate(model):
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+ return evaluator.main(
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+ target_model="roneneldan/TinyStories-1M",
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+ ref_model="roneneldan/TinyStories-Instruct-1M",
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+ output_dir="out",
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+ data="truthful_qa",
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+ length=64,
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+ key_name="input",
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+ ratio_gen=0.4
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+ ) # Call the run_main function directly
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+
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+ iface = gr.Interface(fn=evaluate, inputs="text", outputs="text")
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  iface.launch()
requirements.txt CHANGED
@@ -7,3 +7,4 @@ ipdb
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  matplotlib
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  scikit-learn
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  accelerate
 
 
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  matplotlib
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  scikit-learn
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  accelerate
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+ gradio