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import json | |
import pickle | |
import numpy as np | |
from collections import OrderedDict | |
def load_pickle(filename): | |
with open(filename, 'rb') as file: | |
data = pickle.load(file) | |
return data | |
def save_pickle_to_json(filename): | |
ordered_dict = load_pickle(filename) | |
json_obj = json.dumps(ordered_dict, cls=NumpyEncoder) | |
with open(filename.replace('.pkl', '.json'), 'w') as f: | |
f.write(json_obj) | |
def load_json(filename): | |
with open(filename, 'r') as read_file: | |
loaded_dict = json.loads(read_file.read()) | |
loaded_dict = OrderedDict(loaded_dict) | |
for k, v in loaded_dict.items(): | |
loaded_dict[k] = np.asarray(v) | |
return loaded_dict | |
class NumpyEncoder(json.JSONEncoder): | |
def default(self, obj): | |
if isinstance(obj, np.ndarray): | |
return obj.tolist() | |
return json.JSONEncoder.default(self, obj) | |
# save_pickle_to_json('data/layer_infos/convnext_layer_infos.pkl') | |
# save_pickle_to_json('data/layer_infos/resnet_layer_infos.pkl') | |
# save_pickle_to_json('data/layer_infos/mobilenet_layer_infos.pkl') | |
file = load_json('data/layer_infos/convnext_layer_infos.json') | |
print(type(file)) | |
print(type(file['embeddings.patch_embeddings'])) | |