Alina Lozovskaia commited on
Commit
d041865
1 Parent(s): 1489ff1

added license search

Browse files
Files changed (3) hide show
  1. pyproject.toml +1 -1
  2. requirements.txt +1 -1
  3. src/tools/plots.py +0 -6
pyproject.toml CHANGED
@@ -47,7 +47,7 @@ gradio-space-ci = {git = "https://huggingface.co/spaces/Wauplin/gradio-space-ci"
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  gradio = " 4.20.0"
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  isort = "^5.13.2"
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  ruff = "^0.3.5"
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- gradio-leaderboard = "0.0.7"
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  [build-system]
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  requires = ["poetry-core"]
 
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  gradio = " 4.20.0"
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  isort = "^5.13.2"
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  ruff = "^0.3.5"
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+ gradio-leaderboard = "0.0.8"
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  [build-system]
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  requires = ["poetry-core"]
requirements.txt CHANGED
@@ -15,4 +15,4 @@ transformers==4.40.0
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  tokenizers>=0.15.0
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  gradio-space-ci @ git+https://huggingface.co/spaces/Wauplin/gradio-space-ci@0.2.3 # CI !!!
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  gradio==4.20.0
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- gradio_leaderboard==0.0.7
 
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  tokenizers>=0.15.0
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  gradio-space-ci @ git+https://huggingface.co/spaces/Wauplin/gradio-space-ci@0.2.3 # CI !!!
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  gradio==4.20.0
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+ gradio_leaderboard==0.0.8
src/tools/plots.py CHANGED
@@ -16,11 +16,8 @@ def create_scores_df(raw_data: list[EvalResult]) -> pd.DataFrame:
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  :param results_df: A DataFrame containing result information including metric scores and dates.
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  :return: A new DataFrame containing the maximum scores until each date for every metric.
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  """
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- print(raw_data[0])
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- print(raw_data[0].date)
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  # Step 1: Ensure 'date' is in datetime format and sort the DataFrame by it
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  results_df = pd.DataFrame(raw_data)
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- print(results_df.columns)
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  # results_df["date"] = pd.to_datetime(results_df["date"], format="mixed", utc=True)
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  results_df.sort_values(by="date", inplace=True)
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@@ -79,9 +76,6 @@ def create_plot_df(scores_df: dict[str : pd.DataFrame]) -> pd.DataFrame:
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  # Concatenate all the created DataFrames
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  concat_df = pd.concat(dfs, ignore_index=True)
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- # print("Columns in DataFrame:", concat_df.columns)
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- # if "date" not in concat_df.columns:
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- # raise ValueError("Date column missing from DataFrame. Cannot proceed with sorting.")
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  # Sort values by 'date'
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  concat_df.sort_values(by="date", inplace=True)
 
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  :param results_df: A DataFrame containing result information including metric scores and dates.
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  :return: A new DataFrame containing the maximum scores until each date for every metric.
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  """
 
 
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  # Step 1: Ensure 'date' is in datetime format and sort the DataFrame by it
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  results_df = pd.DataFrame(raw_data)
 
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  # results_df["date"] = pd.to_datetime(results_df["date"], format="mixed", utc=True)
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  results_df.sort_values(by="date", inplace=True)
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  # Concatenate all the created DataFrames
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  concat_df = pd.concat(dfs, ignore_index=True)
 
 
 
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  # Sort values by 'date'
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  concat_df.sort_values(by="date", inplace=True)