[Feature] Add MLA draft model support for Eagle3 training

configs/draft_models/kimi_k25_eagle3_mla.json

@@ -0,0 +1,41 @@
+{
+  "architectures": [
+    "Eagle3DeepseekV2ForCausalLM"
+  ],
+  "model_type": "kimi_k2",
+  "hidden_size": 7168,
+  "intermediate_size": 18432,
+  "num_hidden_layers": 1,
+  "num_attention_heads": 64,
+  "num_key_value_heads": 64,
+  "q_lora_rank": 1536,
+  "kv_lora_rank": 512,
+  "qk_nope_head_dim": 128,
+  "qk_rope_head_dim": 64,
+  "v_head_dim": 128,
+  "hidden_act": "silu",
+  "rms_norm_eps": 1e-05,
+  "vocab_size": 163840,
+  "draft_vocab_size": 163840,
+  "torch_dtype": "bfloat16",
+  "rope_theta": 50000.0,
+  "rope_scaling": {
+    "beta_fast": 1.0,
+    "beta_slow": 1.0,
+    "factor": 64.0,
+    "mscale": 1.0,
+    "mscale_all_dim": 1.0,
+    "original_max_position_embeddings": 4096,
+    "type": "yarn"
+  },
+  "eagle_config": {
+    "eagle_aux_hidden_state_layer_ids": [1, 29, 57],
+    "use_aux_hidden_state": true,
+    "use_input_layernorm_in_first_layer": true,
+    "use_last_layernorm": true,
+    "use_mtp_layernorm": false
+  },
+  "bos_token_id": 163584,
+  "eos_token_id": 163585,
+  "pad_token_id": 0
+}

configs/draft_models/qwen3_8b_eagle3_mla.json

@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "DeepSeekForCausalLMEagle3"
+  ],
+  "model_type": "deepseek_v3",
+  "hidden_size": 4096,
+  "num_attention_heads": 32,
+  "num_key_value_heads": 32,
+  "num_hidden_layers": 1,
+  "intermediate_size": 12288,
+  "hidden_act": "silu",
+  "rms_norm_eps": 1e-06,
+  "q_lora_rank": 1536,
+  "kv_lora_rank": 512,
+  "qk_nope_head_dim": 128,
+  "qk_rope_head_dim": 64,
+  "v_head_dim": 128,
+  "max_position_embeddings": 262144,
+  "rope_theta": 1000000,
+  "rope_scaling": {
+    "type": "yarn",
+    "factor": 64.0,
+    "original_max_position_embeddings": 4096,
+    "beta_fast": 1.0,
+    "beta_slow": 1.0,
+    "mscale": 1.0,
+    "mscale_all_dim": 1.0
+  },
+  "vocab_size": 151936,
+  "tie_word_embeddings": false,
+  "pretraining_tp": 1,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "pad_token_id": 0
+}

configs/sglang_qwen3_8b.yaml

@@ -15,8 +15,8 @@ model:
 
 dataset:
   train_data_path: ../examples/data/sample_conversations.jsonl
-  eval_data_path: ../examples/data/eval_conversations.jsonl
-  eval_interval: 100
+  # eval_data_path: ../examples/data/eval_conversations.jsonl
+  # eval_interval: 100
   chat_template: qwen
   prompt_key: conversations
 

configs/sglang_qwen3_8b_mla_draft.yaml

@@ -0,0 +1,61 @@
+# Configuration for Qwen3-8B target model with MLA draft model
+#
+# Same as sglang_qwen3_8b.yaml but uses DeepSeek MLA attention in the draft model.
+#
+# Usage:
+#   python -m torchspec.train_entry --config configs/sglang_qwen3_8b_mla_draft.yaml
+#   ./examples/qwen3-8b-single-node/run.sh configs/sglang_qwen3_8b_mla_draft.yaml
+
+model:
+  target_model_path: Qwen/Qwen3-8B
+  draft_model_config: configs/draft_models/qwen3_8b_eagle3_mla.json
+  trust_remote_code: true
+
+dataset:
+  train_data_path: ../examples/data/sample_conversations.jsonl
+  chat_template: qwen
+  prompt_key: conversations
+
+training:
+  attention_backend: flex_attention
+  micro_batch_size: 1
+  draft_accumulation_steps: 1
+  learning_rate: 1e-4
+  max_concurrent_batches: 1
+  max_grad_norm: 0.5
+  max_seq_length: 16384
+  num_epochs: 1
+  seed: 42
+  training_num_gpus_per_node: 2
+  training_num_nodes: 1
+  ttt_length: 7
+  save_per_epoch: true
+  warmup_ratio: 0.015
+
+inference:
+  inference_engine_type: sgl
+  inference_num_gpus: 1
+  inference_num_gpus_per_engine: 1
+  inference_num_gpus_per_node: 1
+  max_sample_pool_size: 64
+  inference_buffer_threshold: 32
+  inference_batch_size: 8
+  sglang:
+    tp_size: 1
+    mem_fraction_static: 0.7
+
+mooncake:
+  master_server_address: null
+  metadata_server: null
+  protocol: tcp
+  global_segment_size: 16GB
+  local_buffer_size: 4GB
+
+output_dir: ./outputs/qwen3-8b-mla-draft
+cache_dir: ./cache/qwen3-8b-mla-draft
+model_download_dir: null
+
+debug:
+  save_debug_train_data: null
+  debug_train_only: false
+  debug_inference_only: false

examples/qwen3-8b-single-node/run.sh

@@ -56,12 +56,14 @@ echo "Local IP: $LOCAL_IP"
 echo "Extra args: $*"
 echo "=============================================="
 
+# TODO: unify tp_size config across sglang/vllm backends
 python3 -m torchspec.train_entry \
     --config "$CONFIG_FILE" \
     training.training_num_gpus_per_node="$TRAIN_GPUS" \
     inference.inference_num_gpus="$INFERENCE_GPUS" \
     inference.inference_num_gpus_per_engine=2 \
     inference.inference_num_gpus_per_node="$TOTAL_GPUS" \
+    inference.sglang.tp_size=2 \
     "$@"
 
 echo "=============================================="