Merge pull request #70 from ModelTC/dev_FIX

Fixed the accuracy fluctuation bug

scripts/run_wan_t2v_enhancer.sh

@@ -25,7 +25,7 @@ fi
 export TOKENIZERS_PARALLELISM=false
 
 export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
-
+export DTYPE=BF16
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
 
@@ -36,5 +36,5 @@ python -m lightx2v.infer \
 --config_json ${lightx2v_path}/configs/wan_t2v_enhancer.json \
 --prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
 --use_prompt_enhancer \
---negative_prompt 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 \
+--negative_prompt "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走" \
 --save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v.mp4

scripts/run_wan_t2v_sparge.sh

@@ -25,7 +25,7 @@ fi
 export TOKENIZERS_PARALLELISM=false
 
 export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
-
+export DTYPE=BF16
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
 
@@ -35,5 +35,5 @@ python -m lightx2v.infer \
 --model_path $model_path \
 --config_json ${lightx2v_path}/configs/wan_t2v_sparge.json \
 --prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
---negative_prompt 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 \
+--negative_prompt "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走" \
 --save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v.mp4

scripts/run_wan_t2v_tea.sh

@@ -24,7 +24,7 @@ fi
 export TOKENIZERS_PARALLELISM=false
 
 export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
-
+export DTYPE=BF16
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
 
@@ -34,5 +34,5 @@ python -m lightx2v.infer \
 --model_path $model_path \
 --config_json ${lightx2v_path}/configs/caching/wan_t2v_Tea.json \
 --prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
---negative_prompt 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 \
+--negative_prompt "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走" \
 --save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v_tea.mp4

scripts/start_api_with_dist_inference.sh

@@ -26,6 +26,7 @@ export TOKENIZERS_PARALLELISM=false
 export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
+export DTYPE=BF16
 
 echo "=========================================="
 echo "启动分布式推理API服务器"

scripts/start_multi_servers.sh

@@ -31,6 +31,7 @@ export TOKENIZERS_PARALLELISM=false
 export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
+export DTYPE=BF16
 
 # Start multiple servers
 python -m lightx2v.api_multi_servers \

scripts/start_server.sh

@@ -27,6 +27,7 @@ export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
 
 export ENABLE_PROFILING_DEBUG=true
 export ENABLE_GRAPH_MODE=false
+export DTYPE=BF16
 
 python -m lightx2v.api_server \
 --model_cls wan2.1 \

tools/convert/converter.py

@@ -339,7 +339,6 @@ def quantize_model(
     weights,
     w_bit=8,
     target_keys=["attn", "ffn"],
-    min_params=1e6,
     key_idx=2,
     ignore_key=None,
     dtype=torch.int8,
@@ -351,7 +350,6 @@ def quantize_model(
         weights: Model state dictionary
         w_bit: Quantization bit width
         target_keys: List of module names to quantize
-        min_params: Minimum parameter count to process tensor
 
     Returns:
         Modified state dictionary with quantized weights and scales
@@ -371,7 +369,7 @@ def quantize_model(
             tensor = weights[key]
 
             # Skip non-tensors, small tensors, and non-2D tensors
-            if not isinstance(tensor, torch.Tensor) or tensor.numel() < min_params or tensor.dim() != 2:
+            if not isinstance(tensor, torch.Tensor) or tensor.dim() != 2:
                 continue
 
             # Check if key matches target modules
@@ -442,7 +440,6 @@ def convert_weights(args):
             converted_weights,
             w_bit=args.bits,
             target_keys=args.target_keys,
-            min_params=args.min_params,
             key_idx=args.key_idx,
             ignore_key=args.ignore_key,
             dtype=args.dtype,
@@ -522,7 +519,7 @@ def convert_weights(args):
 
 
 def copy_non_weight_files(source_dir, target_dir):
-    ignore_extensions = [".pth", ".pt", ".safetensors"]
+    ignore_extensions = [".pth", ".pt", ".safetensors", ".index.json"]
 
     logger.info(f"Start copying non-weighted files and subdirectories...")
 
@@ -575,12 +572,6 @@ def main():
     # Quantization
     parser.add_argument("--quantized", action="store_true")
     parser.add_argument("--bits", type=int, default=8, choices=[8], help="Quantization bit width")
-    parser.add_argument(
-        "--min_params",
-        type=int,
-        default=1000000,
-        help="Minimum parameters to consider for quantization",
-    )
     parser.add_argument(
         "--device",
         type=str,
@@ -595,47 +586,48 @@ def main():
     )
     args = parser.parse_args()
 
-    if args.dtype == "torch.int8":
-        args.dtype = torch.int8
-    elif args.dtype == "torch.float8_e4m3fn":
-        args.dtype = torch.float8_e4m3fn
-    else:
-        raise ValueError(f"Not support dtype :{args.dtype}")
-
-    model_type_keys_map = {
-        "wan_dit": {
-            "key_idx": 2,
-            "target_keys": ["self_attn", "cross_attn", "ffn"],
-            "ignore_key": None,
-        },
-        "hunyuan_dit": {
-            "key_idx": 2,
-            "target_keys": [
-                "img_mod",
-                "img_attn_qkv",
-                "img_attn_proj",
-                "img_mlp",
-                "txt_mod",
-                "txt_attn_qkv",
-                "txt_attn_proj",
-                "txt_mlp",
-                "linear1",
-                "linear2",
-                "modulation",
-            ],
-            "ignore_key": None,
-        },
-        "wan_t5": {"key_idx": 2, "target_keys": ["attn", "ffn"], "ignore_key": None},
-        "wan_clip": {
-            "key_idx": 3,
-            "target_keys": ["attn", "mlp"],
-            "ignore_key": "textual",
-        },
-    }
-
-    args.target_keys = model_type_keys_map[args.model_type]["target_keys"]
-    args.key_idx = model_type_keys_map[args.model_type]["key_idx"]
-    args.ignore_key = model_type_keys_map[args.model_type]["ignore_key"]
+    if args.quantized:
+        if args.dtype == "torch.int8":
+            args.dtype = torch.int8
+        elif args.dtype == "torch.float8_e4m3fn":
+            args.dtype = torch.float8_e4m3fn
+        else:
+            raise ValueError(f"Not support dtype :{args.dtype}")
+
+        model_type_keys_map = {
+            "wan_dit": {
+                "key_idx": 2,
+                "target_keys": ["self_attn", "cross_attn", "ffn"],
+                "ignore_key": None,
+            },
+            "hunyuan_dit": {
+                "key_idx": 2,
+                "target_keys": [
+                    "img_mod",
+                    "img_attn_qkv",
+                    "img_attn_proj",
+                    "img_mlp",
+                    "txt_mod",
+                    "txt_attn_qkv",
+                    "txt_attn_proj",
+                    "txt_mlp",
+                    "linear1",
+                    "linear2",
+                    "modulation",
+                ],
+                "ignore_key": None,
+            },
+            "wan_t5": {"key_idx": 2, "target_keys": ["attn", "ffn"], "ignore_key": None},
+            "wan_clip": {
+                "key_idx": 3,
+                "target_keys": ["attn", "mlp"],
+                "ignore_key": "textual",
+            },
+        }
+
+        args.target_keys = model_type_keys_map[args.model_type]["target_keys"]
+        args.key_idx = model_type_keys_map[args.model_type]["key_idx"]
+        args.ignore_key = model_type_keys_map[args.model_type]["ignore_key"]
 
     if os.path.isfile(args.output):
         raise ValueError("Output path must be a directory, not a file")

tools/convert/readme.md

@@ -33,7 +33,7 @@ python converter.py \
     --quantized \
     --source /Path/To/Wan-AI/Wan2.1-I2V-14B-480P/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name wan_int8 \
     --dtype torch.int8 \
     --model_type wan_dit
@@ -44,7 +44,7 @@ python converter.py \
     --quantized \
     --source /Path/To/Wan-AI/Wan2.1-I2V-14B-480P/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name wan_fp8 \
     --dtype torch.float8_e4m3fn \
     --model_type wan_dit
@@ -57,7 +57,7 @@ python converter.py \
     --quantized \
     --source /Path/To/hunyuan/lightx2v_format/i2v/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name hunyuan_int8 \
     --dtype torch.int8 \
     --model_type hunyuan_dit
@@ -68,7 +68,7 @@ python converter.py \
     --quantized \
     --source /Path/To/hunyuan/lightx2v_format/i2v/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name hunyuan_fp8 \
     --dtype torch.float8_e4m3fn \
     --model_type hunyuan_dit

tools/convert/readme_zh.md

@@ -33,7 +33,7 @@ python converter.py \
     --quantized \
     --source /Path/To/Wan-AI/Wan2.1-I2V-14B-480P/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name wan_int8 \
     --dtype torch.int8 \
     --model_type wan_dit
@@ -44,7 +44,7 @@ python converter.py \
     --quantized \
     --source /Path/To/Wan-AI/Wan2.1-I2V-14B-480P/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name wan_fp8 \
     --dtype torch.float8_e4m3fn \
     --model_type wan_dit
@@ -57,7 +57,7 @@ python converter.py \
     --quantized \
     --source /Path/To/hunyuan/lightx2v_format/i2v/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext ..safetensors \
     --output_name hunyuan_int8 \
     --dtype torch.int8 \
     --model_type hunyuan_dit
@@ -68,7 +68,7 @@ python converter.py \
     --quantized \
     --source /Path/To/hunyuan/lightx2v_format/i2v/ \
     --output /Path/To/output \
-    --output_ext .pth\
+    --output_ext .safetensors \
     --output_name hunyuan_fp8 \
     --dtype torch.float8_e4m3fn \
     --model_type hunyuan_dit