QizhiPei commited on
Commit
f78450b
1 Parent(s): 16195f6

delete file

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  1. .gitignore +2 -1
  2. test_task_all.py +0 -336
.gitignore CHANGED
@@ -1,2 +1,3 @@
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  delete_tasks.sh
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- renumber_tasks.py
 
 
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  delete_tasks.sh
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+ renumber_tasks.py
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+ test_all_tasks.py
test_task_all.py DELETED
@@ -1,336 +0,0 @@
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- #!/usr/bin/env python3
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- from iso639 import languages
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- import json
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- from os import listdir
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- from os.path import isfile, join
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- import argparse
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- import re
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- import numpy as np
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-
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- # get the range of task you want to test, if specified in the command line
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- parser = argparse.ArgumentParser()
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- parser.add_argument("--task",
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- nargs=2,
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- type=int,
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- required=False,
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- help="The range of task you want to parse")
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-
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- args = parser.parse_args()
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- if args.task:
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- begin_task_number, end_task_number = args.task[0], args.task[1]
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- assert begin_task_number > 0, "begin task must be greater than 0"
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- assert end_task_number > begin_task_number, "please specify a range of task you would like to test; i.e. the end task number must be greater than beginning task number"
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-
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- # make sure that there is no json file in the root directory
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- root_files = [f for f in listdir('.') if isfile(join('.', f))]
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- for f in root_files:
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- assert '.json' not in f, 'looks like there is a JSON file in the main directory???'
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-
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- # read all the tasks and make sure that they're following the right pattern
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- tasks_path = 'tasks/'
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- # tasks_path = 'tasks_special_token/'
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-
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- expected_keys = [
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- "Definition",
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- "Input_language",
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- "Output_language",
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- "Positive Examples",
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- "Negative Examples",
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- "Instances",
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- "Contributors",
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- "Categories",
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- "Domains",
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- "Source",
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- "URL",
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- "Reasoning"
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- ]
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-
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- language_names = [
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- x.name.replace('(individual language)', '').replace(" languages", "").strip()
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- for x in list(languages)
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- ]
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-
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-
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- def assert_language_name(name):
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- assert name in language_names, f"Did not find `{name}` among iso639 language names: {language_names}"
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-
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-
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- def extract_categories(string):
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- """
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- Get all the characters between ` and `
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- """
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- return set(re.findall(r'`(.*?)`', string))
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-
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-
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- def dict_raise_on_duplicates(ordered_pairs):
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- """Reject duplicate keys."""
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- d = {}
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- for k, v in ordered_pairs:
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- if k in d:
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- raise ValueError("duplicate key: %r" % (k,))
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- else:
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- d[k] = v
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- return d
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-
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- def atoi(text):
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- return int(text) if text.isdigit() else text
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-
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- def natural_keys(text):
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- '''
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- alist.sort(key=natural_keys) sorts in human order
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- '''
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- return [ atoi(c) for c in re.split(r'(\d+)', text) ]
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-
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-
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- with open("tasks/README.md", 'r') as readmef:
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- task_readme_content = " ".join(readmef.readlines())
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- with open("doc/task-hierarchy.md", 'r') as readmef:
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- hierarchy_content_lines = readmef.readlines()
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- hierarchy_content = " ".join(hierarchy_content_lines)
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- all_categories = extract_categories(hierarchy_content)
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-
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- # make sure there are no repeated lines in the task file
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- task_readme_lines = [x for x in task_readme_content.split("\n") if len(x) > 5]
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- if len(set(task_readme_lines)) != len(task_readme_lines):
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- diff = "\n --> ".join([x for x in task_readme_lines if task_readme_lines.count(x) > 1])
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- assert False, f'looks like there are repeated lines in the task readme file?? \n {diff}'
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-
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- # make sure that the lines are sorted
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- task_numbers = [int(line.replace("`task", "").split("_")[0]) for line in task_readme_lines if "`task" in line]
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- for i in range(0, len(task_numbers) - 1):
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- num1 = task_numbers[i]
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- num2 = task_numbers[i + 1]
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- assert num1 <= num2, f"ERROR: looks like `{num1}` appears before `{num2}`."
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-
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- files = [f for f in listdir(tasks_path) if isfile(join(tasks_path, f))]
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- files.sort(key=natural_keys)
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-
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- # make sure anything that gets mentioned in the readme, correspond to an actual file
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- task_names = [line.split("`")[1] for line in task_readme_lines if '`' in line]
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- for name in task_names:
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- file_name = name + ".json"
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- # pqz
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- # assert file_name in files, f" Did not find `{file_name}` among {files}"
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-
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- # test every file (README is skipped)
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- if not args.task:
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- begin_task_number, end_task_number = 1, len(files)
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-
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- # TODO: over time, we need to fix the skew of the following tasks
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- skew_exclusion = [
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- "150"
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- ]
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-
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- contributor_stats = {}
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- categories_stats = {}
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- reasoning_stats = {}
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- domain_stats = {}
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- tasks_count = 0
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- number_of_instances = 0
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- for file in files[begin_task_number:end_task_number + 1]:
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- if ".json" in file:
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- print(f" --> testing file: {file}")
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- assert '.json' in file, 'the file does not seem to have a .json in it: ' + file
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- file_path = tasks_path + file
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- with open(file_path, 'r') as f:
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- try:
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- data = json.load(f)
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- except:
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- with open(file_path, 'r', encoding='utf-8') as f:
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- data = json.load(f, object_pairs_hook=dict_raise_on_duplicates)
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- for key in expected_keys:
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- assert key in data, f'did not find the key: {key}'
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-
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-
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- assert len(data['Instances']) > 25, f"there must be at least 25 instances; " \
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- f"currently you have {len(data['Instances'])} instances"
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- # pqz
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- # assert len(data['Instances']) <= 6500, f"there must be at most 6.5k instances; " \
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- # f"currently you have {len(data['Instances'])} instances"
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-
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- assert type(data['Definition']) == list, f'Definition must be a list of strings.'
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- assert type(data['Source']) == list, f'Sources must be a list.'
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- assert type(data['URL']) == list, f'URL must be a list.'
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- assert type(data['Contributors']) == list, f'Contributors must be a list.'
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- assert type(data['Categories']) == list, f'Categories must be a list.'
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- assert type(data['Reasoning']) == list, f'Reasoning must be a list.'
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- assert type(data['Domains']) == list, f'Domains must be a list.'
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-
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- number_of_instances = number_of_instances + len(data['Instances'])
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- for c in data['Categories']:
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- assert c in all_categories, f'Did not find category `{c}`'
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- if c not in categories_stats:
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- categories_stats[c] = 0
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- categories_stats[c] += 1
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-
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- for d in data['Domains']:
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- assert d in hierarchy_content, f'Did not find domain `{d}`'
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- if d not in domain_stats:
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- domain_stats[d] = 0
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- domain_stats[d] += 1
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-
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- for r in data['Reasoning']:
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- assert r in hierarchy_content, f'Did not find reasoning `{r}`'
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- if r not in reasoning_stats:
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- reasoning_stats[r] = 0
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- reasoning_stats[r] += 1
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-
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- for d in data['Definition']:
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- assert type(d) == str, f'Each definition must be a string.'
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- assert all((lan in d) for lan in data['Input_language'] if
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- lan != 'English'), f'Definition must contain non-English tasks language.'
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- assert type(data['Input_language']) == list, f'Input_language must be a list of strings.'
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- assert type(data['Output_language']) == list, f'Output_language must be a list of strings.'
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- assert type(data['Instruction_language']) == list, f'Output_language must be a list of strings.'
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-
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- assert 'instruction_language' not in data, f'Found `instruction_language`, but expected `Instruction_language`.'
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- assert 'input_language' not in data, f'Found `input_language`, but expected `Input_language`.'
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- assert 'output_language' not in data, f'Found `output_language`, but expected `Output_language`.'
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-
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- # make sure we use the standard language names
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- # pqz
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- # for lang in data['Input_language'] + data['Output_language'] + data['Instruction_language']:
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- # assert_language_name(lang)
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-
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- instance_ids = set()
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- for x in data['Instances']:
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- for key in ['id', 'input', 'output']:
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- assert key in x, f'expected the key {key} in {x}'
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- assert x['id'] not in instance_ids, f'found duplicate instance id: {x["id"]}'
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- instance_ids.add(x['id'])
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- assert type(x['input']) == str, f'the input of instance {x} is not a string'
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- assert type(x['output']) == list, f'the output of instance {x} is not a list'
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- assert len(x['input']) > 0, f"looks like an input `{x['input']}` is empty?"
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- assert len(x['output']) > 0, f"looks like an output `{x['output']}` is empty?"
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- for i in x['output']:
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- assert type(i) == str, f'the output is not a string'
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- # pqz
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- # assert len(data['Positive Examples']) > 1, "there must be at least 3 positive example"
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- # assert len(data['Negative Examples']) > 0, "there must be at least 2 negative example"
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-
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- for x in data['Positive Examples'] + data['Negative Examples']:
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- for key in ['input', 'output', 'explanation']:
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- assert key in x, f'expected the key {key} in {x}'
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- assert type(x['input']) == str, f'the input of example {x} is not a string'
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- assert type(x['output']) == str, f'the output of example {x} is not a string'
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- assert type(x['explanation']) == str, f'the explanation of example {x} is not a string'
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-
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- # Make sure there are no repeated input examples
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- instances = data['Instances']
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- set_of_instances = {instance['input'] for instance in instances}
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- # Because the set length and total length are different, there must be a duplicate input
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- # pqz
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- # if len(instances) != len(set_of_instances):
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- # for instance in instances:
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- # # If the instance is a duplicate then it has already been removed from the set and a KeyError will be thrown
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- # try:
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- # set_of_instances.remove(instance['input'])
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- # except KeyError:
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- # raise Exception(f" * Looks like we have a repeated example here! "
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- # f"Merge outputs before removing duplicates. :-/ \n {instance}")
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-
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- # Make sure there are no link in instances
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- url_reg = r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'
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- instances = data['Instances']
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- for instance in instances:
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- ck_url = re.findall(url_reg, instance['input'])
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- if ck_url:
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- print(f'⚠️ WARNING: Looks like there is a link in the input: {ck_url}')
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- break
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-
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- # make sure classes are balanced
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- output = [ins['output'] for ins in instances]
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- # flattens the nested arrays
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- outputs = sum(output, [])
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- value, counts = np.unique(outputs, return_counts=True)
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-
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- task_number = file.replace("task", "").split("_")[0]
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- # TODO: drop this condition
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- if int(task_number) not in [902, 903]:
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- assert len(value) > 1, f" Looks like all the instances are mapped to a single output: {value}"
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-
252
- if task_number not in skew_exclusion and len(value) < 15:
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- norm_counts = counts / counts.sum()
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- entropy = -(norm_counts * np.log(norm_counts) / np.log(len(value))).sum()
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- # pqz
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- # assert entropy > 0.8, f"Looks like this task is heavily skewed!\n 📋 classes: {value} \n 📋 Norm_counts: {norm_counts} \n 📋 Distribution of classes: {counts} \n 📊 entropy= {entropy}"
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- # Make sure there are no examples repeated across instances and positive examples
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- examples = [ex['input'] for ex in data['Positive Examples']]
259
- for instance in instances:
260
- if instance['input'] in examples:
261
- raise Exception(f" * Looks like we have a same example across positive examples and instances! "
262
- f"Drop the example from the instances. :-/ \n {instance}")
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-
264
- assert len(instance['output']) > 0, "all the instances must have at least one output"
265
-
266
- true_file = file.replace(".json", "")
267
- for char in true_file:
268
- if char.isupper():
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- raise Exception(f" * Looks like there is an uppercase letter in `{true_file}`. "
270
- f"All letters should be lowercased.")
271
-
272
- if file in task_readme_content:
273
- raise Exception(f" * Looks like the .json file extension ending is "
274
- f"present with the task name in `tasks/README.md` when it should just be `{true_file}`")
275
-
276
- # pqz
277
- # if true_file not in task_readme_content:
278
- # raise Exception(f' * Looks like the task name `{true_file}` is not included '
279
- # f'in the task file `tasks/README.md`')
280
-
281
- if task_readme_content.count(true_file) > 1:
282
- raise Exception(f' * Looks like the task name `{true_file}` is repeated in '
283
- f'the task file `tasks/README.md`')
284
-
285
- for c in data['Contributors']:
286
- if c not in contributor_stats:
287
- contributor_stats[c] = 0
288
- contributor_stats[c] += 1
289
- tasks_count = tasks_count + 1
290
-
291
- # test the the official splits
292
- # pqz
293
- # for split_name in ["mol_text"]:
294
- # train_tasks = [l.strip() for l in open(f"splits/{split_name}/train_tasks.txt")]
295
- # test_tasks = [l.strip() for l in open(f"splits/{split_name}/test_tasks.txt")]
296
- # excluded_tasks = [l.strip() for l in open(f"splits/{split_name}/excluded_tasks.txt")]
297
-
298
- # make east task in the split actually exists
299
- # pqz
300
- # for task in train_tasks + test_tasks + excluded_tasks:
301
- # assert task in task_names, f" Task {task} doesn't exist, but it's included in the {split_name} split."
302
- # make sure each task appears in the split
303
- # pqz
304
- # for task in task_names:
305
- # assert task in train_tasks + test_tasks + excluded_tasks, f" Task {task} is missing in the {split_name} split."
306
- # make sure there is no overlap between test and train task names in the splits files.
307
- # assert len(set(train_tasks) & set(test_tasks)) == 0, f" {split_name} split has overlap tasks in the train & test sets."
308
- # assert len(set(train_tasks) & set(excluded_tasks)) == 0, f" {split_name} split has overlap tasks in the train & excluded sets."
309
- # assert len(set(test_tasks) & set(excluded_tasks)) == 0, f" {split_name} split has overlap tasks in the test & excluded sets."
310
-
311
- print("Did not find any errors! ✅")
312
-
313
- print("\n - - - - - Contributors >= 25 tasks - - - - - ")
314
- keyvalues = sorted(list(contributor_stats.items()), key=lambda x: x[1])
315
- for author, count in keyvalues:
316
- if count >= 25:
317
- print(f" ✍️ {author} -> {count}")
318
-
319
- print("\n - - - - - Category Stats - - - - - ")
320
- keyvalues = sorted(list(categories_stats.items()), key=lambda x: x[1])
321
- for cat, count in categories_stats.items():
322
- print(f" ✍️ {cat} -> {count}")
323
-
324
- print("\n - - - - - Domain Stats - - - - - ")
325
- keyvalues = sorted(list(domain_stats.items()), key=lambda x: x[1])
326
- for dom, count in domain_stats.items():
327
- print(f" ✍️ {dom} -> {count}")
328
-
329
- print("\n - - - - - Reasoning Stats - - - - - ")
330
- keyvalues = sorted(list(reasoning_stats.items()), key=lambda x: x[1])
331
- for res, count in reasoning_stats.items():
332
- print(f" ✍️ {res} -> {count}")
333
-
334
- print("\n - - - - - Instances Stats - - - - - ")
335
- average_number_of_instances = number_of_instances / tasks_count
336
- print(f" ✍️ Average number of Instances -> {average_number_of_instances}")