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# Context:
USER: in `show_stats` plot a horizontal bar graph. sort on "model" and "edit_format". group the bars by model. plot the pass_rate_1 for each model/edit_format.
ASSISTANT: To implement this change, we need to modify the `show_stats` function in the `benchmark/benchmark.py` file. We will use the pandas and matplotlib libraries to create the bar plot.
Here are the steps:
1. Import the matplotlib library at the top of the file.
2. In the `show_stats` function, after creating the DataFrame `df`, sort it based on "model" and "edit_format".
3. Group the DataFrame by "model" and plot a bar graph for "pass_rate_1".
Here are the changes:
```python
benchmark/benchmark.py
<<<<<<< ORIGINAL
import pandas as pd
=======
import pandas as pd
import matplotlib.pyplot as plt
>>>>>>> UPDATED
```
```python
benchmark/benchmark.py
<<<<<<< ORIGINAL
def show_stats(dirnames):
rows = []
for dirname in dirnames:
row = summarize_results(dirname)
rows.append(vars(row))
df = pd.DataFrame.from_records(rows)
print(df)
df.to_csv("tmp.benchmark.csv")
=======
def show_stats(dirnames):
rows = []
for dirname in dirnames:
row = summarize_results(dirname)
rows.append(vars(row))
df = pd.DataFrame.from_records(rows)
df.sort_values(by=["model", "edit_format"], inplace=True)
df_grouped = df.groupby("model")["pass_rate_1"].mean()
df_grouped.plot(kind='barh', figsize=(10, 6))
plt.xlabel('Pass Rate 1')
plt.ylabel('Model')
plt.title('Pass Rate 1 for each Model/Edit Format')
plt.show()
df.to_csv("tmp.benchmark.csv")
>>>>>>> UPDATED
```
Please note that this will create a bar graph with the average of "pass_rate_1" for each model. If you want to plot "pass_rate_1" for each "edit_format" within each model, we would need to modify the grouping and plotting code.
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|---|---|---|
| .. | ||
| __init__.py | ||
| benchmark.py | ||
| docker.sh | ||
| docker_build.sh | ||
| Dockerfile | ||
| prompts.py | ||
| test_benchmark.py | ||