[Feature] GLM-45-AIR Support Mix Quantization(Dense wfp8afp8 and wint8 triton_moe_backend) (#4051)

fastdeploy/model_executor/models/glm4_moe.py

@@ -17,12 +17,9 @@
 from __future__ import annotations
 
 import re
-from functools import partial
 
 import paddle
 from paddle import nn
-from paddleformers.transformers import PretrainedModel
-from paddleformers.utils.log import logger
 
 from fastdeploy.config import FDConfig
 from fastdeploy.distributed.communication import tensor_model_parallel_all_reduce
@@ -494,81 +491,3 @@ class Glm4MoeForCausalLM(ModelForCasualLM):
     def clear_grpah_opt_backend(self):
         """Clear graph optimization backend, the captured cuda graph will be cleaned"""
         self.model.clear_grpah_opt_backend(fd_config=self.fd_config)
-
-
-class Glm4MoePretrainedModel(PretrainedModel):
-    """
-    Glm4MoePretrainedModel
-    """
-
-    config_class = FDConfig
-
-    def _init_weight(self, layer):
-        """
-        _init_weight
-        """
-        return None
-
-    @classmethod
-    def arch_name(self):
-        return "Glm4MoeForCausalLM"
-
-    @classmethod
-    def _get_tensor_parallel_mappings(cls, config, is_split=True):
-
-        logger.info("Glm4Moe inference model _get_tensor_parallel_mappings")
-
-        from paddleformers.transformers.conversion_utils import split_or_merge_func
-
-        fn = split_or_merge_func(
-            is_split=is_split,
-            tensor_parallel_degree=config.tensor_parallel_degree,
-            tensor_parallel_rank=config.tensor_parallel_rank,
-            num_attention_heads=config.num_attention_heads,
-        )
-
-        def get_tensor_parallel_split_mappings(num_layers):
-            final_actions = {}
-
-            base_actions = {
-                "lm_head.weight": partial(fn, is_column=True),
-                "embed_tokens.weight": partial(fn, is_column=False),
-                "layers.0.self_attn.o_proj.weight": partial(fn, is_column=False),
-            }
-
-            # Self Attention Layer which are need TP.
-            base_actions["layers.0.self_attn.q_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.self_attn.k_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.self_attn.v_proj.weight"] = partial(fn, is_column=True)
-
-            # MLP Layer
-            base_actions["layers.0.mlp.gate_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.mlp.up_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.mlp.down_proj.weight"] = partial(fn, is_column=False)
-
-            # Moe Layer
-            for expert_idx in range(config.n_routed_experts):
-                base_actions[f"layers.0.mlp.experts.{expert_idx}.up_proj.weight"] = partial(fn, is_column=True)
-                base_actions[f"layers.0.mlp.experts.{expert_idx}.gate_proj.weight"] = partial(fn, is_column=True)
-                base_actions[f"layers.0.mlp.experts.{expert_idx}.down_proj.weight"] = partial(fn, is_column=False)
-
-            # Shared Expert Layer
-            base_actions["layers.0.mlp.shared_experts.up_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.mlp.shared_experts.gate_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.0.mlp.shared_experts.down_proj.weight"] = partial(fn, is_column=False)
-
-            # MTP parts
-            base_actions["layers.46.embed_tokens.weight"] = partial(fn, is_column=False)
-            base_actions["layers.46.eh_proj.weight"] = partial(fn, is_column=True)
-            base_actions["layers.46.shared_head.head.weight"] = partial(fn, is_column=True)
-
-            for key, action in base_actions.items():
-                if "layers.0." in key:
-                    for i in range(num_layers):
-                        final_actions[key.replace("layers.0.", f"layers.{i}.")] = action
-                final_actions[key] = action
-
-            return final_actions
-
-        mappings = get_tensor_parallel_split_mappings(config.num_hidden_layers)
-        return mappings