[Model] Improve olmo and olmo2 (#23228)

Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>

docs/models/supported_models.md

@@ -384,8 +384,8 @@ th {
 | `MPTForCausalLM` | MPT, MPT-Instruct, MPT-Chat, MPT-StoryWriter | `mosaicml/mpt-7b`, `mosaicml/mpt-7b-storywriter`, `mosaicml/mpt-30b`, etc. | | ✅︎ | ✅︎ |
 | `NemotronForCausalLM` | Nemotron-3, Nemotron-4, Minitron | `nvidia/Minitron-8B-Base`, `mgoin/Nemotron-4-340B-Base-hf-FP8`, etc. | ✅︎ | ✅︎ | ✅︎ |
 | `NemotronHForCausalLM` | Nemotron-H | `nvidia/Nemotron-H-8B-Base-8K`, `nvidia/Nemotron-H-47B-Base-8K`, `nvidia/Nemotron-H-56B-Base-8K`, etc. | ✅︎ | ✅︎ | ✅︎ |
-| `OLMoForCausalLM` | OLMo | `allenai/OLMo-1B-hf`, `allenai/OLMo-7B-hf`, etc. | | ✅︎ | ✅︎ |
-| `OLMo2ForCausalLM` | OLMo2 | `allenai/OLMo-2-0425-1B`, etc. | | ✅︎ | ✅︎ |
+| `OLMoForCausalLM` | OLMo | `allenai/OLMo-1B-hf`, `allenai/OLMo-7B-hf`, etc. | ✅︎ | ✅︎ | ✅︎ |
+| `OLMo2ForCausalLM` | OLMo2 | `allenai/OLMo-2-0425-1B`, etc. | ✅︎ | ✅︎ | ✅︎ |
 | `OLMoEForCausalLM` | OLMoE | `allenai/OLMoE-1B-7B-0924`, `allenai/OLMoE-1B-7B-0924-Instruct`, etc. | | ✅︎ | ✅︎ |
 | `OPTForCausalLM` | OPT, OPT-IML | `facebook/opt-66b`, `facebook/opt-iml-max-30b`, etc. | | ✅︎ | ✅︎ |
 | `OrionForCausalLM` | Orion | `OrionStarAI/Orion-14B-Base`, `OrionStarAI/Orion-14B-Chat`, etc. | | ✅︎ | ✅︎ |

vllm/model_executor/models/olmo.py

@@ -47,7 +47,7 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.sequence import IntermediateTensors
 
-from .interfaces import SupportsPP
+from .interfaces import SupportsLoRA, SupportsPP
 from .utils import (AutoWeightsLoader, is_pp_missing_parameter,
                     make_empty_intermediate_tensors_factory, make_layers,
                     maybe_prefix)
@@ -91,6 +91,7 @@ class OlmoAttention(nn.Module):
             self.total_num_heads,
             bias=config.attention_bias,
             quant_config=quant_config,
+            prefix=f"{prefix}.qkv_proj",
         )
 
         # Rotary embeddings.
@@ -114,6 +115,7 @@ class OlmoAttention(nn.Module):
             self.hidden_size,
             bias=config.attention_bias,
             quant_config=quant_config,
+            prefix=f"{prefix}.o_proj",
         )
 
     def forward(
@@ -142,6 +144,7 @@ class OlmoMLP(nn.Module):
         self,
         config: OlmoConfig,
         quant_config: Optional[QuantizationConfig] = None,
+        prefix: str = "",
     ):
         super().__init__()
         self.config = config
@@ -154,6 +157,7 @@ class OlmoMLP(nn.Module):
             [self.intermediate_size] * 2,
             bias=False,
             quant_config=quant_config,
+            prefix=f"{prefix}.gate_up_proj",
         )
 
         # Activation function.
@@ -165,6 +169,7 @@ class OlmoMLP(nn.Module):
             self.hidden_size,
             bias=False,
             quant_config=quant_config,
+            prefix=f"{prefix}.down_proj",
         )
 
     def forward(
@@ -197,7 +202,7 @@ class OlmoDecoderLayer(nn.Module):
                                        prefix=f"{prefix}.self_attn")
 
         # MLP block.
-        self.mlp = OlmoMLP(config, quant_config)
+        self.mlp = OlmoMLP(config, quant_config, prefix=f"{prefix}.mlp")
 
         # LayerNorm
         self.input_layernorm = nn.LayerNorm(config.hidden_size,
@@ -326,10 +331,21 @@ class OlmoModel(nn.Module):
         return loaded_params
 
 
-class OlmoForCausalLM(nn.Module, SupportsPP):
+class OlmoForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
     """
     Extremely barebones HF model wrapper.
     """
+    packed_modules_mapping = {
+        "qkv_proj": [
+            "q_proj",
+            "k_proj",
+            "v_proj",
+        ],
+        "gate_up_proj": [
+            "gate_proj",
+            "up_proj",
+        ],
+    }
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()

vllm/model_executor/models/olmo2.py

@@ -33,6 +33,7 @@ from torch import nn
 from transformers import Olmo2Config
 
 from vllm.attention import Attention
+from vllm.compilation.decorators import support_torch_compile
 from vllm.config import VllmConfig
 from vllm.distributed import get_pp_group, get_tensor_model_parallel_world_size
 from vllm.distributed.communication_op import tensor_model_parallel_all_gather
@@ -48,7 +49,7 @@ from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead, VocabParallelEmbedding)
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
-from vllm.model_executor.models.interfaces import SupportsPP
+from vllm.model_executor.models.interfaces import SupportsLoRA, SupportsPP
 from vllm.model_executor.models.utils import (
     AutoWeightsLoader, is_pp_missing_parameter,
     make_empty_intermediate_tensors_factory, make_layers, maybe_prefix)
@@ -253,6 +254,7 @@ class Olmo2DecoderLayer(nn.Module):
         return hidden_states
 
 
+@support_torch_compile
 class Olmo2Model(nn.Module):
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
@@ -354,10 +356,21 @@ class Olmo2Model(nn.Module):
         return loaded_params
 
 
-class Olmo2ForCausalLM(nn.Module, SupportsPP):
+class Olmo2ForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
     """
     Extremely barebones HF model wrapper.
     """
+    packed_modules_mapping = {
+        "qkv_proj": [
+            "q_proj",
+            "k_proj",
+            "v_proj",
+        ],
+        "gate_up_proj": [
+            "gate_proj",
+            "up_proj",
+        ],
+    }
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()