chore: import upstream snapshot with attribution

2026-07-13 13:23:58 +08:00
commit 770d92cb1f
694 changed files with 114634 additions and 0 deletions
@@ -0,0 +1,79 @@
+"""
+This file specifies how MLC's Phi parameter maps from other formats, for example HuggingFace
+PyTorch, HuggingFace safetensors.
+"""
+
+import functools
+
+from mlc_llm.loader import ExternMapping
+from mlc_llm.quantization import Quantization
+
+from .phi3_model import Phi3Config, Phi3ForCausalLM
+
+
+def phi3_huggingface(model_config: Phi3Config, quantization: Quantization) -> ExternMapping:
+    """Returns a parameter mapping that maps from the names of MLC LLM parameters to
+    the names of Phi-1/Phi-1.5 HuggingFace PyTorch parameters.
+
+    Parameters
+    ----------
+    model_config : PhiConfig
+        The configuration of the Phi model.
+
+    quantization : Quantization
+        The quantization configuration.
+
+    Returns
+    -------
+    param_map : ExternMapping
+        The parameter mapping from MLC to HuggingFace PyTorch.
+    """
+    model = Phi3ForCausalLM(model_config)
+    if quantization is not None:
+        model.to(quantization.model_dtype)
+    _, _named_params = model.export_tvm(spec=model.get_default_spec())
+    named_parameters = dict(_named_params)
+
+    mapping = ExternMapping()
+
+    def _add(mlc_name, hf_name):
+        mapping.add_mapping(
+            mlc_name,
+            [hf_name],
+            functools.partial(
+                lambda x, dtype: x.astype(dtype),
+                dtype=named_parameters[mlc_name].dtype,
+            ),
+        )
+
+    # Skip lm_head.weight if tie_word_embeddings is enabled
+    if not getattr(model_config, "tie_word_embeddings", False):
+        _add("lm_head.weight", "lm_head.weight")
+    _add("transformer.norm.weight", "model.norm.weight")
+    _add("transformer.embd.weight", "model.embed_tokens.weight")
+
+    prefix = "transformer.h"
+    hf_prefix = "model.layers"
+    for i in range(model_config.num_hidden_layers):
+        _add(f"{prefix}.{i}.ln.weight", f"{hf_prefix}.{i}.input_layernorm.weight")
+        _add(
+            f"{prefix}.{i}.mlp.down_proj.weight",
+            f"{hf_prefix}.{i}.mlp.down_proj.weight",
+        )
+        _add(
+            f"{prefix}.{i}.mlp.gate_up_proj.weight",
+            f"{hf_prefix}.{i}.mlp.gate_up_proj.weight",
+        )
+        _add(
+            f"{prefix}.{i}.post_attention_layernorm.weight",
+            f"{hf_prefix}.{i}.post_attention_layernorm.weight",
+        )
+        _add(
+            f"{prefix}.{i}.mixer.out_proj.weight",
+            f"{hf_prefix}.{i}.self_attn.o_proj.weight",
+        )
+        _add(
+            f"{prefix}.{i}.mixer.qkv_proj.weight",
+            f"{hf_prefix}.{i}.self_attn.qkv_proj.weight",
+        )
+    return mapping