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import numpy as np
import pickle
import torch
import json
# np_data = np.load('/home/hui007/rna/rna_repr/zhiyuan/train_data_final.npz')
# data_list = pickle.loads(np_data['data_list'])
# training_json = []
# for item in data_list:
# full_id = item['full_id']
# sequence = ''.join([i[1] for i in item['data']])
# # entry = {
# # "sequences": [
# # {
# # "rnaSequence": {
# # "sequence": sequence,
# # "count": 1
# # }
# # }
# # ],
# # "name": full_id
# # }
# # training_json.append(entry)
# data = item['data']
# extracted = [[j[1], j[2]] for j in data]
# torch.save(extracted, f"/home/hui007/Protenix/coord/{full_id}.pt")
# # coords = [coord for i in item['data'] for coord in i[2]['coord_list']]
# # tensor = torch.tensor(coords, dtype=torch.float32)
# # centroid = tensor.mean(dim=0, keepdim=True)
# # normalized_pos = (tensor - centroid) / 20.3689
# # torch.save(normalized_pos, f"/home/hui007/Protenix/coord/{full_id}.pt")
# # with open("/home/hui007/Protenix/training.json", "w") as f:
# # json.dump(training_json, f, indent=2)
# import os
# import json
# from pathlib import Path
# # === 路径设置 ===
# embedding_dir = Path("/home/hui007/Protenix/protenix_1d_embeddings")
# input_json_path = "/home/hui007/Protenix/training_json/training.json"
# output_prefix = "training"
# # === 加载 JSON 数据 ===
# with open(input_json_path, "r") as f:
# data = json.load(f)
# # === 只保留那些其 name.pt 不存在的条目 ===
# filtered_data = []
# for item in data:
# name = item["name"]
# pt_path = embedding_dir / f"{name}.pt"
# if not pt_path.exists():
# filtered_data.append(item)
# print(f"共有 {len(filtered_data)} 条数据将被保留并拆分")
# # === 平均分成 4 份 ===
# chunk_size = (len(filtered_data) + 5) // 6 # 向上取整
# chunks = [filtered_data[i:i+chunk_size] for i in range(0, len(filtered_data), chunk_size)]
# # === 保存为 training1.json ~ training4.json ===
# for i, chunk in enumerate(chunks):
# out_path = f"/home/hui007/Protenix/training_json/{output_prefix}{i+1}.json"
# with open(out_path, "w") as f:
# json.dump(chunk, f, indent=2)
# print(f"保存 {out_path}，包含 {len(chunk)} 条")
from huggingface_hub import upload_folder
upload_folder(
repo_id="Yimingbear/protenix",
repo_type="dataset",
folder_path=".",
ignore_patterns=["coord/*", "ModelGenerator/*", "protenix_1d_embeddings/*", "protenix_3d_embeddings/*", "second_stage/*", "training_json/*", "examples/*"] # 忽略 scale 文件夹
) |