Delete bf16_cast_block_int8.py

bf16_cast_block_int8.py

@@ -1,63 +0,0 @@
-import os
-import json
-from argparse import ArgumentParser
-from glob import glob
-from tqdm import tqdm
-
-import torch
-from safetensors.torch import load_file, save_file
-from huggingface_hub import snapshot_download
-
-from kernel import weight_quant
-
-def main(bf16_path, int8_path, model_name="deepseek-ai/DeepSeek-R1"):
-    torch.set_default_dtype(torch.bfloat16)
-    os.makedirs(int8_path, exist_ok=True)
-    model_index_file = os.path.join(int8_path, "model.safetensors.index.json")
-    
-    if not os.path.exists(model_index_file):
-        snapshot_download(
-            repo_id=model_name,
-            allow_patterns=["model.safetensors.index.json"],
-            local_dir=int8_path,
-            local_dir_use_symlinks=False
-        )
-        print(f"model index file downloaded to {model_index_file}")
-
-    with open(model_index_file, "r") as f:
-        model_index = json.load(f)
-    weight_map = model_index["weight_map"]
-    scale_count = len([key for key in weight_map.keys() if key.endswith("_scale_inv")])
-    
-    safetensor_files = list(glob(os.path.join(bf16_path, "*.safetensors")))
-    safetensor_files.sort()
-    quant_count = 0
-    for safetensor_file in tqdm(safetensor_files):
-        file_name = os.path.basename(safetensor_file)
-        state_dict = load_file(safetensor_file, device="cuda")
-        new_state_dict = {}
-        for weight_name, weight in state_dict.items():
-            scale_inv_name = f"{weight_name}_scale_inv"
-            if scale_inv_name in weight_map:
-                assert weight.element_size() == 2
-                quant_count += 1
-                int8_weight, scale_inv = weight_quant(weight)
-                new_state_dict[weight_name] = int8_weight
-                new_state_dict[scale_inv_name] = scale_inv
-            else:
-                new_state_dict[weight_name] = weight
-        new_safetensor_file = os.path.join(int8_path, file_name)
-        save_file(new_state_dict, new_safetensor_file)
-    assert quant_count == scale_count
-    print(f"{quant_count} weights are quantized.")
-        
-
-if __name__ == "__main__":
-    parser = ArgumentParser()
-    parser.add_argument("--input-bf16-hf-path", type=str, required=True)
-    parser.add_argument("--output-int8-hf-path", type=str, required=True)
-    parser.add_argument("--model-name", type=str, default="deepseek-ai/DeepSeek-R1")
-    args = parser.parse_args()
-    main(args.input_bf16_hf_path, args.output_int8_hf_path, args.model_name)
-    print("done")
-