[Misc] Add placeholder module (#11501)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/model_loader/loader.py

@@ -48,6 +48,7 @@ from vllm.model_executor.model_loader.weight_utils import (
     runai_safetensors_weights_iterator, safetensors_weights_iterator)
 from vllm.model_executor.utils import set_weight_attrs
 from vllm.platforms import current_platform
+from vllm.transformers_utils.s3_utils import glob as s3_glob
 from vllm.transformers_utils.utils import is_s3
 from vllm.utils import is_pin_memory_available
 
@@ -1269,16 +1270,6 @@ class RunaiModelStreamerLoader(BaseModelLoader):
 
         If the model is not local, it will be downloaded."""
         is_s3_path = is_s3(model_name_or_path)
-        if is_s3_path:
-            try:
-                from vllm.transformers_utils.s3_utils import glob as s3_glob
-            except ImportError as err:
-                raise ImportError(
-                    "Please install Run:ai optional dependency "
-                    "to use the S3 capabilities. "
-                    "You can install it with: pip install vllm[runai]"
-                ) from err
-
         is_local = os.path.isdir(model_name_or_path)
         safetensors_pattern = "*.safetensors"
         index_file = SAFE_WEIGHTS_INDEX_NAME

vllm/model_executor/model_loader/tensorizer.py

@@ -19,9 +19,7 @@ from vllm.engine.llm_engine import LLMEngine
 from vllm.logger import init_logger
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding)
-from vllm.utils import FlexibleArgumentParser
-
-tensorizer_error_msg = None
+from vllm.utils import FlexibleArgumentParser, PlaceholderModule
 
 try:
     from tensorizer import (DecryptionParams, EncryptionParams,
@@ -34,8 +32,19 @@ try:
         open_stream,
         mode=mode,
     ) for mode in ("rb", "wb+"))
-except ImportError as e:
-    tensorizer_error_msg = str(e)
+except ImportError:
+    tensorizer = PlaceholderModule("tensorizer")
+    DecryptionParams = tensorizer.placeholder_attr("DecryptionParams")
+    EncryptionParams = tensorizer.placeholder_attr("EncryptionParams")
+    TensorDeserializer = tensorizer.placeholder_attr("TensorDeserializer")
+    TensorSerializer = tensorizer.placeholder_attr("TensorSerializer")
+    open_stream = tensorizer.placeholder_attr("stream_io.open_stream")
+    convert_bytes = tensorizer.placeholder_attr("utils.convert_bytes")
+    get_mem_usage = tensorizer.placeholder_attr("utils.get_mem_usage")
+    no_init_or_tensor = tensorizer.placeholder_attr("utils.no_init_or_tensor")
+
+    _read_stream = tensorizer.placeholder_attr("_read_stream")
+    _write_stream = tensorizer.placeholder_attr("_write_stream")
 
 __all__ = [
     'EncryptionParams', 'DecryptionParams', 'TensorDeserializer',
@@ -267,12 +276,6 @@ class TensorizerAgent:
     """
 
     def __init__(self, tensorizer_config: TensorizerConfig, vllm_config):
-        if tensorizer_error_msg is not None:
-            raise ImportError(
-                "Tensorizer is not installed. Please install tensorizer "
-                "to use this feature with `pip install vllm[tensorizer]`. "
-                "Error message: {}".format(tensorizer_error_msg))
-
         self.tensorizer_config = tensorizer_config
         self.tensorizer_args = (
             self.tensorizer_config._construct_tensorizer_args())

vllm/model_executor/model_loader/weight_utils.py

@@ -25,7 +25,15 @@ from vllm.model_executor.layers.quantization import (QuantizationConfig,
                                                      get_quantization_config)
 from vllm.model_executor.layers.quantization.schema import QuantParamSchema
 from vllm.platforms import current_platform
-from vllm.utils import print_warning_once
+from vllm.utils import PlaceholderModule, print_warning_once
+
+try:
+    from runai_model_streamer import SafetensorsStreamer
+except ImportError:
+    runai_model_streamer = PlaceholderModule(
+        "runai_model_streamer")  # type: ignore[assignment]
+    SafetensorsStreamer = runai_model_streamer.placeholder_attr(
+        "SafetensorsStreamer")
 
 logger = init_logger(__name__)
 
@@ -414,13 +422,6 @@ def runai_safetensors_weights_iterator(
     hf_weights_files: List[str]
 ) -> Generator[Tuple[str, torch.Tensor], None, None]:
     """Iterate over the weights in the model safetensor files."""
-    try:
-        from runai_model_streamer import SafetensorsStreamer
-    except ImportError as err:
-        raise ImportError(
-            "Please install Run:ai optional dependency."
-            "You can install it with: pip install vllm[runai]") from err
-
     enable_tqdm = not torch.distributed.is_initialized(
     ) or torch.distributed.get_rank() == 0
     with SafetensorsStreamer() as streamer: