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import glob
import json
import math
import os
from dataclasses import dataclass
import dateutil
import numpy as np
from src.display.formatting import make_clickable_model
from src.display.utils import AutoEvalColumn, ModelType, Tasks, Precision, WeightType
from src.submission.check_validity import is_model_on_hub
@dataclass
class EvalResult:
"""Represents one full evaluation. Built from a combination of the result and request file for a given run.
"""
model_name: str
student_id: str
results: dict
@classmethod
def init_from_json_file(self, json_filepath):
"""Inits the result from the specific model result file"""
with open(json_filepath) as fp:
data = json.load(fp)
config = data.get("config")
# Extract results available in this file (some results are split in several files)
results = {}
for task in Tasks:
task = task.value
# We average all scores of a given metric (not all metrics are present in all files)
accs = np.array([v.get(task.metric, None) for k, v in data["results"].items() if task.benchmark == k])
if accs.size == 0 or any([acc is None for acc in accs]):
continue
results[task.col_name] = accs.mean()
return self(
model_name=config.get("model_name", None),
student_id=config.get("student_id", None),
results=results,
)
def update_with_request_file(self, requests_path, model_name, student_id):
"""Finds the relevant request file for the current model and updates info with it"""
request_file = get_request_file_for_model(requests_path, model_name, student_id)
try:
with open(request_file, "r") as f:
request = json.load(f)
self.date = request.get("submitted_time", "")
except Exception:
print(f"Could not find request file for {student_id}_{model_name}")
def to_dict(self):
"""Converts the Eval Result to a dict compatible with our dataframe display"""
data_dict = {
"eval_name": self.eval_name, # not a column, just a save name
"Model Name": self.model_name,
}
# Add task-specific metrics
for task in Tasks:
data_dict[task.value.col_name] = self.results.get(task.value.col_name, None)
# Add student ID and submission date
data_dict["Student ID"] = self.student_id
data_dict["Submission Date"] = self.date
return data_dict
def get_request_file_for_model(requests_path, model_name, student_id):
"""Selects the correct request file for a given model."""
request_files = os.path.join(
requests_path, student_id,
f"request_{student_id}_{model_name}*.json",
)
request_files = glob.glob(request_files)
# Select the latest request file based on the modification date
request_file = ""
request_files = sorted(request_files, key=lambda x: os.path.getmtime(x), reverse=True)
if len(request_files) > 0:
request_file = request_files[0]
return request_file
def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResult]:
"""From the path of the results folder root, extract all needed info for results"""
model_result_filepaths = []
for root, _, files in os.walk(results_path):
# Filter out non-JSON files
files = [f for f in files if f.endswith(".json") and f.startswith("result")]
# Sort the files by date
try:
files.sort(key=lambda x: x.removesuffix(".json").removeprefix("result")[:-7])
except dateutil.parser._parser.ParserError:
files = [files[-1]]
for file in files:
model_result_filepaths.append(os.path.join(root, file))
eval_results = {}
for model_result_filepath in model_result_filepaths:
# Creation of result
eval_result = EvalResult.init_from_json_file(model_result_filepath)
eval_result.update_with_request_file(requests_path, eval_result.model_name, eval_result.student_id)
# Store results of same eval together
eval_name = f"{eval_result.student_id}_{eval_result.model_name}"
eval_result.eval_name = eval_name
if eval_name in eval_results.keys():
eval_results[eval_name].results.update({k: v for k, v in eval_result.results.items() if v is not None})
else:
eval_results[eval_name] = eval_result
results = []
for v in eval_results.values():
try:
v.to_dict() # we test if the dict version is complete
results.append(v)
except KeyError: # not all eval values present
continue
return results
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