[Sync] Update to latest code (#2679)

* [Sync] Update to latest code

* Add new code files

* Add new code files

* update code

* Try to fix build.sh

* Try to fix build.sh

* Update code

* Update requirements.txt

* Update code

---------

Co-authored-by: Jiang-Jia-Jun <jiangjiajun@baidu.com>

fastdeploy/worker/gpu_model_runner.py

@@ -20,6 +20,7 @@ from typing import List, Optional
 import numpy as np
 import paddle
 import paddle.nn as nn
+from paddleformers.utils.log import logger
 
 from fastdeploy.config import FDConfig
 from fastdeploy.engine.request import Request
@@ -41,13 +42,10 @@ from fastdeploy.model_executor.pre_and_post_process import (post_process,
                                                             rebuild_padding,
                                                             step_cuda)
 from fastdeploy.spec_decode import MTPProposer, NgramProposer
-from fastdeploy.utils import get_logger
 from fastdeploy.worker.forward_meta import ForwardMeta
 from fastdeploy.worker.model_runner_base import ModelRunnerBase
 from fastdeploy.worker.output import ModelOutputData, ModelRunnerOutput
 
-logger = get_logger("gpu_model_runner", "gpu_model_runner.log")
-
 
 class GPUModelRunner(ModelRunnerBase):
     """ """
@@ -593,6 +591,10 @@ class GPUModelRunner(ModelRunnerBase):
         time_before_load = time.perf_counter()
         # 1. Load original model
         self.model = get_model_from_loader(fd_config=self.fd_config)
+        # 1.1 Load RL dynamic model
+        if self.fd_config.load_config.dynamic_load_weight:
+            from fastdeploy.rl.dynamic_weight_manager import DynamicWeightManager
+            self.dynamic_weight_manager = DynamicWeightManager(self.fd_config, self.model)
 
         # 2. Load lora model
 
@@ -620,6 +622,25 @@ class GPUModelRunner(ModelRunnerBase):
         # Initialzie attention meta data
         for attn_backend in self.attn_backends:
             attn_backend.init_attention_metadata(self.forward_meta)
+    
+    def clear_cache(self):
+        """Clear cached data from shared inputs and forward metadata."""
+        self.share_inputs.pop("caches", None)
+        if self.forward_meta is not None:
+            self.forward_meta.clear_caches()
+
+    def clear_parameters(self, pid):
+        """"dynamic model loader use to clear parameters use for RL"""
+        self.dynamic_weight_manager.clear_parameters(pid)
+        self.clear_cache()
+        paddle.device.cuda.empty_cache()
+        self.dynamic_weight_manager._log_memory("dynamic weight manager clear all memory")
+
+    def update_parameters(self, pid):
+        """"dynamic model loader use to update parameters use for RL"""
+        self.dynamic_weight_manager.update_parameters(pid)
+        self.initialize_kv_cache()
+        self.dynamic_weight_manager._log_memory("dynamic weight manager update all memory")
 
     def initialize_kv_cache(self) -> None:
         """
@@ -691,15 +712,14 @@ class GPUModelRunner(ModelRunnerBase):
         head_dim = self.model_config.head_dim
 
         # Get the attention backend
-        attn_cls = get_attention_backend(
-            self.parallel_config.attention_backend)
+        attn_cls = get_attention_backend()
         attn_backend = attn_cls(self.fd_config,
                                 kv_num_heads=self.model_config.kv_num_heads,
                                 num_heads=num_heads,
                                 head_dim=head_dim)
         if attn_backend is None:
             raise NotImplementedError(
-                f"{ self.parallel_config.attention_backend} attention backend is not support by GPUModelRunner"
+                "Attention backend which you chose is not support by GPUModelRunner"
             )
         self.attn_backends.append(attn_backend)
 
@@ -735,6 +755,7 @@ class GPUModelRunner(ModelRunnerBase):
             is_decode_batch = not ((self.share_inputs["seq_lens_this_time"]
                                     > 1).sum() > 0)
             self.forward_meta.step_use_cudagraph = is_decode_batch and in_capturing
+            self.forward_meta.is_decode_batch = is_decode_batch
             model_output = self.model(
                 ids_remove_padding=self.share_inputs["ids_remove_padding"],
                 forward_meta=self.forward_meta)
@@ -967,6 +988,7 @@ class GPUModelRunner(ModelRunnerBase):
         is_decode_batch = not ((self.share_inputs["seq_lens_this_time"]
                                 > 1).sum() > 0)
         self.forward_meta.step_use_cudagraph = self.use_cudagraph and is_decode_batch
+        self.forward_meta.is_decode_batch = is_decode_batch
         model_output = self.model(
             ids_remove_padding=self.share_inputs["ids_remove_padding"],
             forward_meta=self.forward_meta)
@@ -1124,9 +1146,7 @@ class GPUModelRunner(ModelRunnerBase):
                         batch_size=min(self.parallel_config.max_num_seqs, 3))
 
         # 3. gc
-        del self.share_inputs["caches"]
-        if self.forward_meta is not None:
-            del self.forward_meta.caches
+        self.clear_cache()
 
         if self.speculative_method in ["mtp"]:
             self.proposer.clear_dummy_input()