Update Iris to py312

Author: Didayolo

codabench/iris/README.md

@@ -1,6 +1,6 @@
-# Iris
+# Iris competition bundle
 
-### Codabench competition bundle
+<img src="bundle/logo.png" width="300" alt="logo">
 
 This is a collection of files containing the `competition.yaml` which defines different aspects and attributes of the competition, the logo, the html pages documenting the competition, and the data associated with it. The goal is to provide a ready-to-use template for competition creation on [Codabench](https://github.com/codalab/codabench).
 
@@ -14,5 +14,3 @@ References and credits:
   * Paper: R. A. Fisher. The use of multiple measurements in taxonomic problems. Annual Eugenics, 7, Part II, 179-188 (1936). 
 * The competition protocol was designed by Isabelle Guyon. 
 * The competition bundle was adapted to Codalab V2 by Adrien Pavao.
-
-![logo](bundle/logo.png)

codabench/iris/bundle.zip

@@ -8,7 +8,7 @@ title: Iris
 description: The well known Iris dataset from Fisher's classic paper (Fisher, 1936).
 image: logo.png
 registration_auto_approve: True  # do not require approval from admin to join the comp
-docker_image: 'codalab/codalab-legacy:py37'
+docker_image: codalab/codalab-legacy:py312 # the Docker image in which submissions are run
 
 # Documentation web pages
 terms: pages/terms.html
@@ -42,6 +42,9 @@ tasks:
   reference_data: reference_data/test
   scoring_program: scoring_program
   ingestion_program: ingestion_program
+
+# Solution is an example submission, NOT the ground truth
+# You can leave it empty and give example submissions in the starting kit
 solutions: []
 
 # There are 2 phases: development phase and final phase
@@ -59,7 +62,6 @@ phases:
   execution_time_limit: 500
   tasks:
   - 0
-  solutions: []
   starting_kit: starting_kit
   public_data: input_data
 - index: 1
@@ -73,7 +75,6 @@ phases:
   execution_time_limit: 500
   tasks:
   - 1
-  solutions: []
 
 # Leaderboard
 leaderboards:

codabench/iris/bundle/competition.yaml

@@ -16,6 +16,7 @@
 from scipy.sparse import *
 from sklearn.datasets import load_svmlight_file
 import os
+
 # Note: to check for nan values np.any(map(np.isnan,X_train))
 def file_to_array (filename, verbose=False):
     ''' Converts a file to a list of list of STRING

codabench/iris/bundle/ingestion_program/data_converter.py

@@ -1,5 +1,7 @@
 # This file contains the main settings of the benchmark
 # Learn more here: https://docs.codabench.org/latest/Organizers/Benchmark_Creation/Yaml-Structure/
+
+# Main settings
 title: Mini-AutoML
 version: 2 # this means that it is a Codabench bundle
 description: AutoML Benchmark template with submission to multiple datasets