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process_grid.py
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process_grid.py
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import sys
import os
import json
import glob
import statistics
path_pattern = sys.argv[1]
target_type = sys.argv[2]
best_value, best_result, best_name = None, None, None
mean_result = {}
print(path_pattern)
for dir_path in glob.glob(path_pattern, recursive=True):
entry = os.path.basename(dir_path)
valid_result = None
test_found = os.path.exists(os.path.join(dir_path, "test_results.json"))
valid_path = os.path.join(dir_path, "results.json")
if os.path.exists(valid_path):
print(entry)
with open(valid_path) as file:
valid_result = json.load(file)
else:
print(f"{entry} no validation results")
continue
if not test_found:
print(f"{entry} not tested yet")
if target_type == "max":
metric = sys.argv[3]
metric_value = valid_result[metric]
if best_value is None or metric_value > best_value:
best_value = metric_value
best_result = valid_result
best_name = entry
elif target_type == "mean" or target_type == "median":
if mean_result:
for metric, value in valid_result.items():
if metric not in ["type", "epoch"]:
mean_result[metric].append(value)
else:
mean_result = {metric: [value] for metric, value in valid_result.items() if
metric not in ["type", "epoch"]}
if target_type == "max":
print(f"Best result found at {best_name}: {best_result}")
elif target_type == "mean":
mean_result = {metric: sum(value) / len(value) for metric, value in mean_result.items()}
print(f"Mean result {mean_result}")
elif target_type == "median":
mean_result = {metric: statistics.median(value) for metric, value in mean_result.items()}
print(f"Mean result {mean_result}")