[Bugfix] Fix broken CI (#2825)

### What this PR does / why we need it?
1. Initial support disable tp for integrating with
[vllm-commit](https://github.com/vllm-project/vllm/pull/23024)
2. [vllm@commit](https://github.com/vllm-project/vllm/pull/23673) now
use `bytes` to save the `BlockHash` to reduce GC overhead, this pr add
the integration

- vLLM version: main
- vLLM main:
e40827280b

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

tests/ut/core/test_scheduler.py

@@ -8,6 +8,7 @@ from vllm.config import (CacheConfig, KVTransferConfig, ModelConfig,
                          SchedulerConfig, SpeculativeConfig, VllmConfig)
 from vllm.multimodal.inputs import PlaceholderRange
 from vllm.sampling_params import SamplingParams
+from vllm.utils import sha256
 from vllm.v1.core.kv_cache_utils import (get_request_block_hasher,
                                          init_none_hash)
 from vllm.v1.core.sched.output import SchedulerOutput
@@ -38,7 +39,7 @@ def create_requests(
     max_tokens: int = 16,
     stop_token_ids: Optional[list[int]] = None,
     block_size: int = 3,
-    hash_fn=hash,
+    hash_fn=sha256,
 ):
     init_none_hash(hash_fn)
     prompt_logprobs = PROMPT_LOGPROBS

tests/ut/kv_connector/utils.py

@@ -10,6 +10,7 @@ import torch
 from vllm import SamplingParams
 from vllm.config import (CacheConfig, DeviceConfig, KVTransferConfig,
                          ModelConfig, SchedulerConfig, VllmConfig)
+from vllm.utils import sha256
 from vllm.v1.core.kv_cache_utils import (get_request_block_hasher,
                                          init_none_hash)
 from vllm.v1.core.sched.scheduler import Scheduler
@@ -129,10 +130,10 @@ def create_request(
     """Make dummy request for testing."""
     global _none_hash_initialized
     if not _none_hash_initialized:
-        init_none_hash(hash)
+        init_none_hash(sha256)
         _none_hash_initialized = True
 
-    block_hasher = get_request_block_hasher(block_size, hash)
+    block_hasher = get_request_block_hasher(block_size, sha256)
 
     kv_transfer_params: Optional[dict[str, Any]] = None
 

vllm_ascend/ops/linear.py

@@ -62,6 +62,7 @@ class AscendColumnParallelLinear(ColumnParallelLinear):
         prefix: str = "",
         *,
         return_bias: bool = True,
+        disable_tp: bool = False,
     ):
         self.comm_group = None
         if prefix.find("gate_up_proj") != -1 and mlp_tp_enable():
@@ -88,7 +89,8 @@ class AscendColumnParallelLinear(ColumnParallelLinear):
                                   params_dtype,
                                   quant_config,
                                   prefix,
-                                  return_bias=return_bias)
+                                  return_bias=return_bias,
+                                  disable_tp=disable_tp)
 
         self.gather_output = gather_output
 
@@ -137,6 +139,7 @@ class AscendRowParallelLinear(RowParallelLinear):
         prefix: str = "",
         *,
         return_bias: bool = True,
+        disable_tp: bool = False,
     ):
         if prefix.find("down_proj") != -1 and mlp_tp_enable():
             comm_group = get_mlp_tp_group()
@@ -156,6 +159,7 @@ class AscendRowParallelLinear(RowParallelLinear):
             self.forward_type = "normal"
         self.comm_group = comm_group
 
+        # TODO: check for disable_tp
         self.tp_size = self.comm_group.world_size
         self.tp_rank = self.comm_group.rank_in_group
 
@@ -171,7 +175,8 @@ class AscendRowParallelLinear(RowParallelLinear):
                                   params_dtype,
                                   quant_config,
                                   prefix,
-                                  return_bias=return_bias)
+                                  return_bias=return_bias,
+                                  disable_tp=disable_tp)
 
         self.input_is_parallel = input_is_parallel
         self.reduce_results = reduce_results
@@ -392,6 +397,7 @@ class AscendMergedColumnParallelLinear(MergedColumnParallelLinear):
         prefix: str = "",
         *,
         return_bias: bool = True,
+        disable_tp: bool = False,
     ):
         if prefix.find("gate_up_proj") != -1 and mlp_tp_enable():
             comm_group = get_mlp_tp_group()
@@ -403,6 +409,7 @@ class AscendMergedColumnParallelLinear(MergedColumnParallelLinear):
             comm_group = get_tp_group()
             self.forward_type = "normal_tp"
         self.comm_group = comm_group
+        # TODO: check for disable_tp
         self.tp_rank = comm_group.rank_in_group
         self.tp_size = comm_group.world_size
 
@@ -418,7 +425,8 @@ class AscendMergedColumnParallelLinear(MergedColumnParallelLinear):
                                             params_dtype=params_dtype,
                                             quant_config=quant_config,
                                             prefix=prefix,
-                                            return_bias=return_bias)
+                                            return_bias=return_bias,
+                                            disable_tp=disable_tp)
 
     def forward(
         self,
@@ -498,6 +506,7 @@ class AscendQKVParallelLinear(QKVParallelLinear):
         prefix: str = "",
         *,
         return_bias: bool = True,
+        disable_tp: bool = False,
     ):
         if dense_optim_enable():
             self.forward_type = "dense_optim"
@@ -511,6 +520,7 @@ class AscendQKVParallelLinear(QKVParallelLinear):
             total_num_kv_heads = total_num_heads
         self.total_num_kv_heads = total_num_kv_heads
         # Divide the weight matrix along the last dimension.
+        # TODO: check for disable_tp
         tp_size = self.comm_group.world_size
         self.num_heads = divide(self.total_num_heads, tp_size)
         if tp_size >= self.total_num_kv_heads:
@@ -537,7 +547,8 @@ class AscendQKVParallelLinear(QKVParallelLinear):
                                             params_dtype=params_dtype,
                                             quant_config=quant_config,
                                             prefix=prefix,
-                                            return_bias=return_bias)
+                                            return_bias=return_bias,
+                                            disable_tp=disable_tp)
 
     def forward(
         self,
@@ -611,4 +622,4 @@ class AscendLinearBase(LinearBase):
             self.quant_method = quant_config.get_quant_method(self,
                                                               prefix=prefix)
         self.return_bias = return_bias
-        self.disable_tp = disable_tp
+        self.disable_tp = disable_tp