undo sync engine change

serve/mlc_serve/engine/sync_engine.py

@@ -5,28 +5,25 @@
 import logging
 from typing import Deque, Set, Dict
 from collections import deque
+from sre_parse import Tokenizer
 from threading import Condition, Lock
+from uuid import uuid4
 
 from .base import (
+    DebugOptions,
     FinishReason,
     InferenceEngine,
     InferenceStepResult,
     Request,
     RequestId,
     RequestOutput,
     RequestState,
+    SamplingParams,
     SequenceOutput,
+    StoppingCriteria,
     check_stopping_sequences,
-    ValidationError,
-)
-from .model_module import (
-    DecodeRequest,
-    ModelModule,
-    PrefillRequest,
-    SequenceId,
-    TextGenerator,
-    Tokenizer as TokenizerP,
 )
+from .model_module import DecodeRequest, ModelModule, PrefillRequest, SequenceId, TextGenerator, Tokenizer as TokenizerP
 from ..model.base import ModelArtifactConfig
 
 logger = logging.getLogger(__name__)
@@ -37,7 +34,6 @@ class SynchronousInferenceEngine(InferenceEngine):
     A implementation of InferenceEngine that does inference synchronously in the current thread
     when `step` is called.
     """
-
     text_generator: TextGenerator
     tokenizer: TokenizerP
     model_artifact_config: ModelArtifactConfig
@@ -61,9 +57,7 @@ def __init__(
         self.conversation_template = model_module.conversation_template
         self.cache_manager = model_module.cache_manager
         self.model_artifact_config = model_module.model_artifact_config
-        assert (
-            self.model_artifact_config.max_context_length
-        ), "max_context_length must not be zero"
+        assert self.model_artifact_config.max_context_length, "max_context_length must not be zero"
         self.max_context_length = self.model_artifact_config.max_context_length
         self.max_num_batched_tokens = model_module.engine_config.max_num_batched_tokens
         self.max_decode_steps = min(
@@ -159,23 +153,13 @@ def step(self) -> InferenceStepResult:
 
         previous_requests_to_be_cancelled = set(self.requests_to_be_cancelled)
         self._adjust_batch()
-
+        
         if not self.current_batch:
             if len(self.queue) > 0:
                 logger.warning(
                     f"The engine has {len(self.queue)} requests to be processed in the queue, but none of them were added to the current batch during the execution of SyncEngine._adjust_batch"
                 )
 
-                hung_request_ids = []
-
-                for state in self.queue:
-                    hung_request_ids.append(state.request_id)
-                    # TODO(masahi): Proper error enum?
-                    state.validation_err = ValidationError("Canceled due to a hang")
-
-                for request_id in hung_request_ids:
-                    self.cancel(request_id)
-
         for request_id in previous_requests_to_be_cancelled:
             if request_id not in self.requests_to_be_cancelled:
                 outputs.append(