V1 loader default (#4251)

* v1 laoder

* update

* update

fastdeploy/model_executor/utils.py

@@ -14,14 +14,18 @@
 # limitations under the License.
 """
 
+import os
 import re
 from contextlib import contextmanager
 from typing import Any, Optional, Union
 
 import paddle
+from paddleformers.utils.log import logger
 
+from fastdeploy import envs
 from fastdeploy.config import FDConfig
 from fastdeploy.model_executor.layers.utils import get_tensor
+from fastdeploy.platforms import current_platform
 
 
 class BitMaskTracker:
@@ -194,6 +198,53 @@ def default_weight_loader(fd_config: FDConfig) -> None:
     return fn
 
 
+def is_pre_sliced_weight(model_path):
+    rank_dirs = [
+        f for f in os.listdir(model_path) if f.startswith("rank") and os.path.isdir(os.path.join(model_path, f))
+    ]
+    return len(rank_dirs) > 1
+
+
+def v1_loader_support(fd_config):
+    _v1_no_support_archs = ["Qwen2VLForConditionalGeneration", "Qwen2_5_VLForConditionalGeneration"]
+
+    def _err_msg(msg: str) -> str:
+        logger.info(msg + "; fallback to the v0 loader for model loading.")
+
+    if not current_platform.is_cuda():
+        _err_msg("v1loader currently does not support backends other than CUDA")
+        return False
+
+    if is_pre_sliced_weight(fd_config.model_config.model):
+        _err_msg("v1 loader currently does not support pre-sliced weights")
+        return False
+
+    if fd_config.parallel_config.use_ep:
+        _err_msg("v1 loader currently does not support expert parallelism")
+        return False
+
+    if envs.FD_MOE_BACKEND.lower() == "marlin":
+        _err_msg("v1 loader currently does not support marlin backend")
+        return False
+
+    if fd_config.quant_config is not None:
+        if fd_config.quant_config.name() == "mix_quant":
+            moe_quant_type = fd_config.quant_config.moe_quant_type
+            dense_quant_type = fd_config.quant_config.dense_quant_type
+        else:
+            moe_quant_type = fd_config.quant_config.name()
+            dense_quant_type = fd_config.quant_config.name()
+        unsupported_quant = {"w4a8", "w4afp8", "wint2"}
+
+        if unsupported_quant & {moe_quant_type, dense_quant_type}:
+            _err_msg("v1 loader currently does not support w4a8/w4afp8/win2 quantization")
+            return False
+    if fd_config.model_config.architectures[0] in _v1_no_support_archs:
+        _err_msg(f"v1 loader currently does not support {fd_config.model_config.architectures[0]}")
+        return False
+    return True
+
+
 @contextmanager
 def temporary_dtype(dtype: str):
     """Temporarily set Paddle default dtype"""