[Bug fix] fix block num setting in scheduler v1 for develop (#3303)

* fix block num setting in scheduler v1

* fix block num setting in scheduler v1

* fix max_block_num and max_num_batched_tokens setting

* fix max_block_num and max_num_batched_tokens setting

* fix max_block_num and max_num_batched_tokens setting

* fix max_block_num and max_num_batched_tokens setting

fastdeploy/cache_manager/prefix_cache_manager.py

@@ -64,7 +64,10 @@ class PrefixCacheManager:
         self.speculative_config = config.speculative_config
         self.local_data_parallel_id = local_data_parallel_id
 
-        self.num_gpu_blocks = self.cache_config.prefill_kvcache_block_num
+        if envs.ENABLE_V1_KVCACHE_SCHEDULER:
+            self.num_gpu_blocks = self.cache_config.total_block_num
+        else:
+            self.num_gpu_blocks = self.cache_config.prefill_kvcache_block_num
         self.num_cpu_blocks = self.cache_config.num_cpu_blocks
         self.gpu_free_block_list = list(range(self.num_gpu_blocks - 1, -1, -1))
         if self.num_cpu_blocks > 0:

fastdeploy/config.py

@@ -731,7 +731,10 @@ class CacheConfig:
         self.block_size = 64
         self.gpu_memory_utilization = 0.9
         self.num_gpu_blocks_override = None
-        self.kv_cache_ratio = 0.75
+        if envs.ENABLE_V1_KVCACHE_SCHEDULER:
+            self.kv_cache_ratio = 1.0
+        else:
+            self.kv_cache_ratio = 0.75
         self.enc_dec_block_num = 0 if current_platform.is_iluvatar() else 2
         self.prealloc_dec_block_slot_num_threshold = 5
         self.cache_dtype = "bfloat16"
@@ -816,7 +819,10 @@ class CacheConfig:
         self.dec_token_num = self.enc_dec_block_num * self.block_size
         if self.num_gpu_blocks_override is not None:
             self.total_block_num = self.num_gpu_blocks_override
-            self.prefill_kvcache_block_num = int(self.total_block_num * self.kv_cache_ratio)
+            if envs.ENABLE_V1_KVCACHE_SCHEDULER:
+                self.prefill_kvcache_block_num = self.total_block_num
+            else:
+                self.prefill_kvcache_block_num = int(self.total_block_num * self.kv_cache_ratio)
         else:
             length = num_total_tokens // number_of_tasks
             block_num = (length + self.block_size - 1 + self.dec_token_num) // self.block_size
@@ -829,7 +835,10 @@ class CacheConfig:
         reset gpu block number
         """
         self.total_block_num = num_gpu_blocks
-        self.prefill_kvcache_block_num = int(self.total_block_num * self.kv_cache_ratio)
+        if envs.ENABLE_V1_KVCACHE_SCHEDULER:
+            self.prefill_kvcache_block_num = self.total_block_num
+        else:
+            self.prefill_kvcache_block_num = int(self.total_block_num * self.kv_cache_ratio)
         logger.info(
             f"Reset block num, the total_block_num:{self.total_block_num},"
             f" prefill_kvcache_block_num:{self.prefill_kvcache_block_num}"

fastdeploy/engine/args_utils.py

@@ -18,6 +18,7 @@ import json
 from dataclasses import asdict, dataclass
 from dataclasses import fields as dataclass_fields
 from typing import Any, Dict, List, Optional
+import os
 
 from fastdeploy.config import (
     CacheConfig,
@@ -884,7 +885,10 @@ class EngineArgs:
             if self.enable_chunked_prefill:
                 self.max_num_batched_tokens = 2048
             else:
-                self.max_num_batched_tokens = self.max_model_len
+                if not int(os.getenv('ENABLE_V1_KVCACHE_SCHEDULER', '0')):
+                    self.max_num_batched_tokens = self.max_model_len
+                else:
+                    self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
 
         all_dict = asdict(self)
         all_dict["model_cfg"] = model_cfg

fastdeploy/engine/config.py

@@ -245,7 +245,10 @@ class Config:
             if self.cache_config.enable_chunked_prefill:
                 self.max_num_batched_tokens = 2048
             else:
-                self.max_num_batched_tokens = self.max_model_len
+                if not int(os.getenv('ENABLE_V1_KVCACHE_SCHEDULER', '0')):
+                    self.max_num_batched_tokens = self.max_model_len
+                else:
+                    self.max_num_batched_tokens = 8192 # if set to max_model_len, it's easy to be OOM
 
         if self.long_prefill_token_threshold == 0:
             self.long_prefill_token_threshold = int(self.max_model_len * 0.04)
@@ -293,10 +296,11 @@ class Config:
         )
 
         if not self.cache_config.enable_chunked_prefill:
-            assert self.max_num_batched_tokens >= self.max_model_len, (
+            if not int(os.getenv('ENABLE_V1_KVCACHE_SCHEDULER', '0')):
-                f"max_num_batched_tokens: {self.max_num_batched_tokens} "
+                assert self.max_num_batched_tokens >= self.max_model_len, (
-                f"should be larger than or equal to max_model_len: {self.max_model_len}"
+                    f"max_num_batched_tokens: {self.max_num_batched_tokens} "
-            )
+                    f"should be larger than or equal to max_model_len: {self.max_model_len}"
+                )
         else:
             assert self.max_num_batched_tokens >= self.cache_config.block_size, (
                 f"max_num_batched_tokens: {self.max_num_batched_tokens} "