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import yaml
import os
import glob
CONFIG_DIR = "./BeamDiffusionModel/models/diffusionModel/configs" # Directory containing config files
def load_all_configs():
config = {} # Start with an empty config
# Find all YAML files in the directory (sorted for consistency)
config_files = sorted(glob.glob(os.path.join(CONFIG_DIR, "*.yml")))
for file_path in config_files:
with open(file_path, "r") as file:
new_config = yaml.safe_load(file) or {} # Load config (avoid None)
config = deep_merge(config, new_config) # Merge into main config
return config
def deep_merge(dict1, dict2):
"""Recursively merges two dictionaries (deep merge)."""
for key, value in dict2.items():
if isinstance(value, dict) and key in dict1 and isinstance(dict1[key], dict):
dict1[key] = deep_merge(dict1[key], value) # Recursively merge
else:
dict1[key] = value # Overwrite
return dict1
# Load and merge all configs automatically
CONFIG = load_all_configs()
print(os.getcwd())
print("Final Merged Config:")
print(CONFIG) # Display merged config
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