merge multiple safetensors

examples/opensora_pku/README.md

@@ -151,6 +151,11 @@ python tools/model_conversion/convert_wfvae.py --src LanguageBind/Open-Sora-Plan
 python tools/model_conversion/convert_pytorch_ckpt_to_safetensors.py --src google/mt5-xxl/pytorch_model.bin --target google/mt5-xxl/model.safetensors  --config google/mt5-xxl/config.json
 ```
 
+In addition, please merge the multiple .saftensors files under `any93x640x640/` into a merged checkpoint:
+```shell
+python tools/ckpt/merge_safetensors.py -i LanguageBind/Open-Sora-Plan-v1.3.0/any93x640x640/ -o LanguageBind/Open-Sora-Plan-v1.3.0/diffusion_pytorch_model.safetensors  -f LanguageBind/Open-Sora-Plan-v1.3.0/any93x640x640/diffusion_pytorch_model.safetensors.index.json
+```
+
 Once the checkpoint files have all been prepared, you can refer to the inference guidance below.
 
 ## Inference

examples/opensora_pku/tools/ckpt/merge_safetensors.py

@@ -0,0 +1,68 @@
+import argparse
+import json
+import os
+
+from safetensors import safe_open
+from safetensors.torch import save_file
+
+
+def load_index_file(index_file):
+    with open(index_file, "r") as f:
+        return json.load(f)
+
+
+def _load_huggingface_safetensor(ckpt_file):
+    db_state_dict = {}
+    with safe_open(ckpt_file, framework="pt", device="cpu") as f:
+        for key in f.keys():
+            db_state_dict[key] = f.get_tensor(key)
+    return db_state_dict
+
+
+def merge_safetensors(input_folder, index_file, output_file):
+    # Load the index file
+    index_data = load_index_file(index_file)
+    # Iterate through the files specified in the index
+    weight_map = index_data.get("weight_map", {})
+    weight_names = []
+    file_paths = []
+    for weight_name in weight_map.keys():
+        file_paths.append(weight_map[weight_name])
+        weight_names.append(weight_name)
+    file_paths = set(file_paths)
+    weight_names = set(weight_names)
+
+    sd = []
+    for file_path in file_paths:
+        if file_path:
+            file_path = os.path.join(input_folder, file_path)
+            partial_sd = _load_huggingface_safetensor(file_path)
+            sd.append(partial_sd)
+
+    # Merge all tensors together
+    merged_tensor = sd[0]
+    for tensor in sd[1:]:
+        merged_tensor.update(tensor)
+
+    # Save the merged tensor to a new Safetensor file
+    save_file(merged_tensor, output_file)
+    print(f"Merged Safetensors saved as: {output_file}")
+
+
+def main():
+    # Set up argument parsing
+    parser = argparse.ArgumentParser(description="Merge multiple Safetensors files into one using an index.")
+    parser.add_argument("--input_folder", "-i", type=str, help="Path to the folder containing Safetensors files.")
+    parser.add_argument("--index_file", "-f", type=str, help="Path to the index JSON file.")
+    parser.add_argument("--output_file", "-o", type=str, help="Path to the output merged Safetensors file.")
+
+    # Parse the arguments
+    args = parser.parse_args()
+
+    # Call the merge function
+    assert args.output_file.endswith(".safetensors")
+    merge_safetensors(args.input_folder, args.index_file, args.output_file)
+
+
+if __name__ == "__main__":
+    main()