Revert "Add simple CPU offloading support" (#2252)

We'll re-add the commit to correctly ack Kaichao's authorship

python/sglang/srt/models/gemma2.py

@@ -38,7 +38,6 @@ from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.layers.vocab_parallel_embedding import VocabParallelEmbedding
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.utils import make_layers
 
 
 # Aligned with HF's implementation, using sliding window inclusive with the last token
@@ -268,15 +267,11 @@ class Gemma2Model(nn.Module):
             config.vocab_size,
             config.hidden_size,
         )
-        self.layers = make_layers(
-            config.num_hidden_layers,
-            lambda idx, prefix: Gemma2DecoderLayer(
-                layer_id=idx,
-                config=config,
-                cache_config=cache_config,
-                quant_config=quant_config,
-            ),
-            prefix="",
+        self.layers = nn.ModuleList(
+            [
+                Gemma2DecoderLayer(layer_id, config, cache_config, quant_config)
+                for layer_id in range(config.num_hidden_layers)
+            ]
         )
         self.norm = GemmaRMSNorm(config.hidden_size, eps=config.rms_norm_eps)
 

python/sglang/srt/models/llama.py

@@ -43,7 +43,6 @@ from sglang.srt.layers.vocab_parallel_embedding import (
 )
 from sglang.srt.managers.schedule_batch import global_server_args_dict
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.utils import make_layers
 
 
 class LlamaMLP(nn.Module):
@@ -256,12 +255,13 @@ class LlamaModel(nn.Module):
             config.vocab_size,
             config.hidden_size,
         )
-        self.layers = make_layers(
-            config.num_hidden_layers,
-            lambda idx, prefix: LlamaDecoderLayer(
-                config=config, quant_config=quant_config, layer_id=idx, prefix=prefix
-            ),
-            prefix="model.layers",
+        self.layers = nn.ModuleList(
+            [
+                LlamaDecoderLayer(
+                    config, i, quant_config=quant_config, prefix=f"model.layers.{i}"
+                )
+                for i in range(config.num_hidden_layers)
+            ]
         )
 
         self.norm = RMSNorm(config.hidden_size, eps=config.rms_norm_eps)

python/sglang/srt/models/olmo.py

@@ -38,7 +38,6 @@ from sglang.srt.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding,
 )
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.utils import make_layers
 
 
 class OlmoAttention(nn.Module):
@@ -221,13 +220,11 @@ class OlmoModel(nn.Module):
         self.embed_tokens = VocabParallelEmbedding(
             config.vocab_size, config.hidden_size
         )
-        self.layers = make_layers(
-            config.num_hidden_layers,
-            lambda idx, prefix: OlmoDecoderLayer(
-                layer_id=idx,
-                config=config,
-                quant_config=quant_config,
-            ),
+        self.layers = nn.ModuleList(
+            [
+                OlmoDecoderLayer(config, layer_id, quant_config)
+                for layer_id in range(config.num_hidden_layers)
+            ]
         )
         self.norm = nn.LayerNorm(
             config.hidden_size, elementwise_affine=False, bias=False

python/sglang/srt/models/olmoe.py

@@ -48,7 +48,6 @@ from sglang.srt.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding,
 )
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.utils import make_layers
 
 
 class OlmoeMoE(nn.Module):
@@ -262,13 +261,11 @@ class OlmoeModel(nn.Module):
             config.vocab_size,
             config.hidden_size,
         )
-        self.layers = make_layers(
-            config.num_hidden_layers,
-            lambda idx, prefix: OlmoeDecoderLayer(
-                config=config,
-                quant_config=quant_config,
-                layer_id=idx,
-            ),
+        self.layers = nn.ModuleList(
+            [
+                OlmoeDecoderLayer(config, layer_id, quant_config=quant_config)
+                for layer_id in range(config.num_hidden_layers)
+            ]
         )
         self.norm = RMSNorm(config.hidden_size, eps=1e-5)
 

python/sglang/srt/models/qwen2.py

@@ -40,7 +40,6 @@ from sglang.srt.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding,
 )
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.utils import make_layers
 
 Qwen2Config = None
 
@@ -231,13 +230,11 @@ class Qwen2Model(nn.Module):
             config.vocab_size,
             config.hidden_size,
         )
-        self.layers = make_layers(
-            config.num_hidden_layers,
-            lambda idx, prefix: Qwen2DecoderLayer(
-                layer_id=idx,
-                config=config,
-                quant_config=quant_config,
-            ),
+        self.layers = nn.ModuleList(
+            [
+                Qwen2DecoderLayer(config, i, quant_config=quant_config)
+                for i in range(config.num_hidden_layers)
+            ]
         )
         self.norm = RMSNorm(config.hidden_size, eps=config.rms_norm_eps)