[Core] Refactor model loading code

.buildkite/test-pipeline.yaml

@@ -92,7 +92,7 @@ steps:
   parallelism: 4
 
 - label: Tensorizer Test
-  command: apt-get install curl libsodium23 && pytest -v -s tensorizer
+  command: apt-get install curl libsodium23 && pytest -v -s tensorizer_loader
 
 - label: Metrics Test
   command: pytest -v -s metrics

examples/fp8/extract_scales.py

@@ -11,7 +11,7 @@
 from vllm.model_executor.layers.quantization.schema import QuantParamSchema
 
 
-# Adapted from vllm/model_executor/weight_utils.py
+# Adapted from vllm/model_executor/model_loader/weight_utils.py
 # The main differences are that we add the NPZ format and simplify
 # its functionality drastically for our purposes (e.g. we assume that
 # the quantized model exists locally and there is no need to download it)
@@ -71,7 +71,7 @@ def _prepare_hf_weights(
     return hf_weights_files, use_safetensors
 
 
-# Adapted from vllm/model_executor/weight_utils.py
+# Adapted from vllm/model_executor/model_loader/weight_utils.py
 def _hf_tensorfile_iterator(filename: str, load_format: str,
                             use_safetensors: bool):
     if load_format == "npz":

examples/tensorize_vllm_model.py

@@ -16,8 +16,8 @@
 from vllm.distributed import initialize_model_parallel
 from vllm.engine.arg_utils import EngineArgs
 from vllm.engine.llm_engine import LLMEngine
+from vllm.model_executor.model_loader.tensorizer import TensorizerArgs
 from vllm.model_executor.models import ModelRegistry
-from vllm.model_executor.tensorizer_loader import TensorizerArgs
 
 # yapf conflicts with isort for this docstring
 # yapf: disable

tests/lora/conftest.py

@@ -153,11 +153,11 @@ def llama_2_7b_engine_extra_embeddings() -> nn.Module:
     cleanup()
     get_model_old = get_model
 
-    def get_model_patched(model_config, device_config, **kwargs):
-        return get_model_old(model_config,
-                             device_config,
-                             lora_config=LoRAConfig(max_loras=4,
-                                                    max_lora_rank=8))
+    def get_model_patched(*, model_config, device_config, **kwargs):
+        kwargs["lora_config"] = LoRAConfig(max_loras=4, max_lora_rank=8)
+        return get_model_old(model_config=model_config,
+                             device_config=device_config,
+                             **kwargs)
 
     with patch("vllm.worker.model_runner.get_model", get_model_patched):
         engine = vllm.LLM("meta-llama/Llama-2-7b-hf", enable_lora=False)

tests/lora/test_worker.py

@@ -3,8 +3,8 @@
 import tempfile
 from unittest.mock import patch
 
-from vllm.config import (CacheConfig, DeviceConfig, LoRAConfig, ModelConfig,
-                         ParallelConfig, SchedulerConfig)
+from vllm.config import (CacheConfig, DeviceConfig, LoadConfig, LoRAConfig,
+                         ModelConfig, ParallelConfig, SchedulerConfig)
 from vllm.lora.models import LoRAMapping
 from vllm.lora.request import LoRARequest
 from vllm.worker.worker import Worker
@@ -18,12 +18,14 @@ def test_worker_apply_lora(sql_lora_files):
             "meta-llama/Llama-2-7b-hf",
             tokenizer_mode="auto",
             trust_remote_code=False,
-            download_dir=None,
-            load_format="dummy",
             seed=0,
             dtype="float16",
             revision=None,
         ),
+        load_config=LoadConfig(
+            download_dir=None,
+            load_format="dummy",
+        ),
         parallel_config=ParallelConfig(1, 1, False),
         scheduler_config=SchedulerConfig(32, 32, 32),
         device_config=DeviceConfig("cuda"),

tests/model_executor/weight_utils.py

@@ -3,7 +3,7 @@
 import huggingface_hub.constants
 import pytest
 
-from vllm.model_executor.weight_utils import enable_hf_transfer
+from vllm.model_executor.model_loader.weight_utils import enable_hf_transfer
 
 
 def test_hf_transfer_auto_activation():

tests/quantization/test_autogptq_marlin_configs.py

@@ -36,8 +36,6 @@ def test_auto_gptq(model_quant_type: str, ) -> None:
         model_path,
         tokenizer_mode="auto",
         trust_remote_code=False,
-        download_dir=None,
-        load_format="dummy",
         seed=0,
         dtype="float16",
         revision=None,
@@ -49,8 +47,6 @@ def test_auto_gptq(model_quant_type: str, ) -> None:
         model_path,
         tokenizer_mode="auto",
         trust_remote_code=False,
-        download_dir=None,
-        load_format="dummy",
         seed=0,
         dtype="float16",
         revision=None,

tests/samplers/test_sampler.py

@@ -32,7 +32,12 @@ def _prepare_test(
                              1e-2,
                              dtype=input_tensor.dtype)
     sampler = MockLogitsSampler(fake_logits)
-    model_runner = ModelRunner(None, None, None, None, None)
+    model_runner = ModelRunner(model_config=None,
+                               parallel_config=None,
+                               scheduler_config=None,
+                               device_config=None,
+                               load_config=None,
+                               lora_config=None)
     return input_tensor, fake_logits, sampler, model_runner
 
 
@@ -591,7 +596,12 @@ def test_sampler_top_k_top_p(seed: int, device: str):
                                device=input_tensor.device,
                                dtype=input_tensor.dtype)
     sampler = MockLogitsSampler(fake_logits)
-    model_runner = ModelRunner(None, None, None, None, None)
+    model_runner = ModelRunner(model_config=None,
+                               parallel_config=None,
+                               scheduler_config=None,
+                               device_config=None,
+                               load_config=None,
+                               lora_config=None)
 
     generation_model = GenerationMixin()
     generation_config = GenerationConfig(top_k=top_k,

tests/spec_decode/utils.py

@@ -118,6 +118,7 @@ def create_worker(cls: type,
         scheduler_config=engine_config.scheduler_config,
         device_config=engine_config.device_config,
         cache_config=engine_config.cache_config,
+        load_config=engine_config.load_config,
         local_rank=0,
         rank=0,
         distributed_init_method=distributed_init_method,

tests/tensorizer/tensorize_vllm_model_for_testing.py → tests/tensorizer_loader/tensorize_vllm_model_for_testing.py

@@ -16,8 +16,8 @@
 from vllm.distributed import initialize_model_parallel
 from vllm.engine.arg_utils import EngineArgs
 from vllm.engine.llm_engine import LLMEngine
+from vllm.model_executor.model_loader.tensorizer import TensorizerArgs
 from vllm.model_executor.models import ModelRegistry
-from vllm.model_executor.tensorizer_loader import TensorizerArgs
 
 # yapf conflicts with isort for this docstring
 # yapf: disable
@@ -74,7 +74,7 @@ def parse_args():
                     "extremely quickly. Tensor encryption and decryption is "
                     "also supported, although libsodium must be installed to "
                     "use it.")
-    parser = EngineArgs.add_cli_args(parser)
+    parser = TensorizerArgs.add_cli_args(EngineArgs.add_cli_args(parser))
     subparsers = parser.add_subparsers(dest='command')
 
     serialize_parser = subparsers.add_parser(