model-code

diffsynth/utils/state_dict_converters/ace_step_lm.py

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+"""
+State dict converter for ACE-Step LLM (Qwen3-based).
+
+The safetensors file stores Qwen3 model weights. Different checkpoints
+may have different key formats:
+- Qwen3ForCausalLM format: model.embed_tokens.weight, model.layers.0.*
+- Qwen3Model format: embed_tokens.weight, layers.0.*
+
+Qwen3ForCausalLM wraps a .model attribute (Qwen3Model), so its
+state_dict() has keys:
+    model.model.embed_tokens.weight
+    model.model.layers.0.self_attn.q_proj.weight
+    model.model.norm.weight
+    model.lm_head.weight (tied to model.model.embed_tokens)
+
+This converter normalizes all keys to the Qwen3ForCausalLM format.
+
+Example mapping:
+    model.embed_tokens.weight -> model.model.embed_tokens.weight
+    embed_tokens.weight -> model.model.embed_tokens.weight
+    model.layers.0.self_attn.q_proj.weight -> model.model.layers.0.self_attn.q_proj.weight
+    layers.0.self_attn.q_proj.weight -> model.model.layers.0.self_attn.q_proj.weight
+    model.norm.weight -> model.model.norm.weight
+    norm.weight -> model.model.norm.weight
+"""
+
+
+def ace_step_lm_converter(state_dict):
+    """
+    Convert ACE-Step LLM checkpoint keys to match Qwen3ForCausalLM state dict.
+
+    参数 state_dict 是 DiskMap 类型。
+    遍历时，key 是 key 名，state_dict[key] 获取实际值。
+    """
+    new_state_dict = {}
+    model_prefix = "model."
+    nested_prefix = "model.model."
+
+    for key in state_dict:
+        if key.startswith(nested_prefix):
+            # Already has model.model., keep as is
+            new_key = key
+        elif key.startswith(model_prefix):
+            # Has model., add another model.
+            new_key = "model." + key
+        else:
+            # No prefix, add model.model.
+            new_key = "model.model." + key
+        new_state_dict[new_key] = state_dict[key]
+
+    # Handle tied word embeddings: lm_head.weight shares with embed_tokens
+    if "model.model.embed_tokens.weight" in new_state_dict:
+        new_state_dict["model.lm_head.weight"] = new_state_dict["model.model.embed_tokens.weight"]
+
+    return new_state_dict