update ckpt version

download.py

@@ -4,14 +4,13 @@ import os
 os.environ["HF_HUB_DOWNLOAD_TIMEOUT"] = "1200"
 # os.environ["HF_ENDPOINT"] = "https://hf-mirror.com" 
 
-def download_model(local_dir, repo_id="tencent/SongGeneration", revision="aa9d1b3"):
+def download_model(local_dir, repo_id="tencent/SongGeneration", revision="87bccf1"):
     downloaded_path = snapshot_download(
         repo_id=repo_id,
         local_dir=local_dir,
         revision=revision,
         token=os.environ.get("HF_TOKEN"), 
-        ignore_patterns=['.git*'],
-        endpoint="https://hf-mirror.com"
+        ignore_patterns=['.git*']
     )
     print(f"File downloaded to:{downloaded_path}")
 

z_script.py

@@ -0,0 +1,44 @@
+from hmac import new
+import sys
+import os
+import argparse
+from safetensors.torch import save_file
+
+import time
+import json
+import torch
+import torchaudio
+import numpy as np
+from omegaconf import OmegaConf
+from codeclm.models import builders
+import gc
+from codeclm.trainer.codec_song_pl import CodecLM_PL
+from codeclm.models import CodecLM
+from third_party.demucs.models.pretrained import get_model_from_yaml
+
+cfg_path = "/apdcephfs_cq11/share_300883980/tanwei/SongGeneration-LeVo/ckpt/songgeneration_base/config.yaml"
+cfg = OmegaConf.load(cfg_path)
+cfg.mode = 'inference'
+# audio_tokenizer = builders.get_audio_tokenizer_model(cfg.audio_tokenizer_checkpoint, cfg)
+# model = audio_tokenizer.model.model
+# weights = {k: v.half() for k, v in model.state_dict().items() if isinstance(v, torch.Tensor) and v.numel() > 0}
+# save_file(weights, '/apdcephfs_cq11/share_300883980/tanwei/SongGeneration-LeVo/ckpt/encoder_fp16.safetensors')
+# print(weights)
+
+# seperate_tokenizer = builders.get_audio_tokenizer_model(cfg.audio_tokenizer_checkpoint_sep, cfg)
+# model = seperate_tokenizer.model.model
+# weights = {}
+# for k, v in model.state_dict().items():
+#     if k.startswith("rvq_bestrq_bgm_emb") or k.startswith("rvq_bestrq_emb") or k.startswith("bestrq"):
+#         weights[k] = v.half()
+#     else:
+#         weights[k] = v
+# # weights = {k: v.half() for k, v in model.state_dict().items() if isinstance(v, torch.Tensor) and v.numel() > 0}
+# save_file(weights, '/apdcephfs_cq11/share_300883980/tanwei/SongGeneration-LeVo/ckpt/encoder_fp16.safetensors')
+# print(weights.keys())
+
+ckpt_path = "/apdcephfs_cq11/share_300883980/tanwei/SongGeneration-WX/ckpt/songgeneration_new_small/model_32.pt"
+# audiolm = builders.get_lm_model(cfg)
+checkpoint = torch.load(ckpt_path, map_location='cpu')
+audiolm_state_dict = {k: v.half() for k, v in checkpoint.items()}
+torch.save(audiolm_state_dict, "/apdcephfs_cq11/share_300883980/tanwei/SongGeneration-WX/ckpt/songgeneration_new_small/model.pt")