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Revert "Chunked prefill support" (#799)

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This commit is contained in:
Ying Sheng
2024-07-29 02:38:31 -07:00
committed by GitHub
parent 2ec39ab712
commit 98111fbe3e
5 changed files with 54 additions and 160 deletions
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118
python/sglang/srt/managers/controller/tp_worker.py
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@@ -77,10 +77,6 @@ class ModelTpServer:
self.schedule_heuristic = server_args.schedule_heuristic
self.disable_regex_jump_forward = server_args.disable_regex_jump_forward
# Chunked prefill
self.chunked_prefill_size = server_args.chunked_prefill_size
self.current_inflight_req = None
# Init model and tokenizer
self.model_config = ModelConfig(
server_args.model_path,
@@ -161,7 +157,7 @@ class ModelTpServer:
self.token_to_kv_pool = self.model_runner.token_to_kv_pool
# Init running status
self.waiting_queue: List[Req] = []
self.forward_queue: List[Req] = []
self.running_batch: Batch = None
self.out_pyobjs = []
self.decode_forward_ct = 0
@@ -224,7 +220,6 @@ class ModelTpServer:
# Run a new prefill batch
self.forward_prefill_batch(new_batch)
self.cache_filled_batch(new_batch)
self.filter_out_inflight(new_batch)
if not new_batch.is_empty():
if self.running_batch is None:
@@ -266,7 +261,7 @@ class ModelTpServer:
f"#token: {num_used}, "
f"token usage: {num_used / self.max_total_num_tokens:.2f}, "
f"gen throughput (token/s): {throughput:.2f}, "
f"#queue-req: {len(self.waiting_queue)}"
f"#queue-req: {len(self.forward_queue)}"
)
def check_memory(self):
@@ -333,10 +328,9 @@ class ModelTpServer:
),
self.max_req_input_len - 1 - len(req.origin_input_ids),
)
self.waiting_queue.append(req)
self.forward_queue.append(req)
def get_new_prefill_batch(self) -> Optional[Batch]:
# TODO(lsyin): organize this function
running_bs = (
len(self.running_batch.reqs) if self.running_batch is not None else 0
)
@@ -344,7 +338,7 @@ class ModelTpServer:
return
# Compute matched prefix length
for req in self.waiting_queue:
for req in self.forward_queue:
req.input_ids = req.origin_input_ids + req.output_ids
prefix_indices, last_node = self.tree_cache.match_prefix(req.input_ids)
if req.return_logprob:
@@ -354,7 +348,7 @@ class ModelTpServer:
req.last_node = last_node
# Get priority queue
self.waiting_queue = self.scheduler.get_priority_queue(self.waiting_queue)
self.forward_queue = self.scheduler.get_priority_queue(self.forward_queue)
# Add requests if there is available space
can_run_list = []
@@ -373,33 +367,7 @@ class ModelTpServer:
]
)
# Handle the current inflight request
take_inflight = 0
if self.current_inflight_req:
take_inflight = 1
r = self.current_inflight_req
r.input_ids = r.origin_input_ids + r.output_ids
truncated = (
len(r.input_ids) - len(r.prefix_indices) > self.chunked_prefill_size
)
r.extend_input_len = min(
len(r.input_ids) - len(r.prefix_indices), self.chunked_prefill_size
)
r.input_ids = r.input_ids[: len(r.prefix_indices) + r.extend_input_len]
can_run_list.append(r)
if not truncated:
# Finish inflight
self.current_inflight_req = None
new_batch_total_tokens += (
r.extend_input_len + r.sampling_params.max_new_tokens
)
new_batch_input_tokens += r.extend_input_len
else:
new_batch_total_tokens += r.extend_input_len
new_batch_input_tokens += r.extend_input_len
for req in self.waiting_queue:
for req in self.forward_queue:
if req.return_logprob and req.normalized_prompt_logprob is None:
# Need at least two tokens to compute normalized logprob
if req.extend_input_len < 2:
@@ -441,36 +409,11 @@ class ModelTpServer:
break
else:
# Add this request to the running batch
if (
new_batch_input_tokens + req.extend_input_len
<= self.chunked_prefill_size
or (
req.return_logprob and req.normalized_prompt_logprob is None
)
):
can_run_list.append(req)
new_batch_total_tokens += (
req.extend_input_len + req.sampling_params.max_new_tokens
)
new_batch_input_tokens += req.extend_input_len
else:
trunc_len = self.chunked_prefill_size - new_batch_input_tokens
if trunc_len <= 0:
# Undo locking
delta = self.tree_cache.dec_lock_ref(req.last_node)
available_size += delta
break
req.extend_input_len = trunc_len
req.input_ids = req.input_ids[
: len(req.prefix_indices) + req.extend_input_len
]
can_run_list.append(req)
self.current_inflight_req = req
new_batch_input_tokens += req.extend_input_len
new_batch_total_tokens += req.extend_input_len
break
can_run_list.append(req)
new_batch_total_tokens += (
req.extend_input_len + req.sampling_params.max_new_tokens
)
new_batch_input_tokens += req.extend_input_len
else:
break
@@ -497,7 +440,7 @@ class ModelTpServer:
f"#cached-token: {hit_tokens}, "
f"cache hit rate: {100.0 * tree_cache_hit_rate:.2f}%, "
f"#running-req: {running_bs}, "
f"#queue-req: {len(self.waiting_queue) - len(can_run_list) + take_inflight}"
f"#queue-req: {len(self.forward_queue) - len(can_run_list)}"
)
# Return the new batch
@@ -507,7 +450,7 @@ class ModelTpServer:
self.token_to_kv_pool,
self.tree_cache,
)
self.waiting_queue = [x for x in self.waiting_queue if x not in can_run_list]
self.forward_queue = [x for x in self.forward_queue if x not in can_run_list]
return new_batch
def forward_prefill_batch(self, batch: Batch):
@@ -539,10 +482,9 @@ class ModelTpServer:
# Check finish conditions
pt = 0
for i, req in enumerate(batch.reqs):
if req is not self.current_inflight_req:
req.completion_tokens_wo_jump_forward += 1
req.output_ids.append(next_token_ids[i])
req.check_finished()
req.completion_tokens_wo_jump_forward += 1
req.output_ids.append(next_token_ids[i])
req.check_finished()
if req.return_logprob:
self.add_logprob_return_values(i, req, pt, next_token_ids, output)
@@ -603,7 +545,7 @@ class ModelTpServer:
req_pool_indices_cpu = batch.req_pool_indices.cpu().numpy()
for i, req in enumerate(batch.reqs):
new_prefix_indices, new_last_node = self.tree_cache.cache_req(
token_ids=tuple(req.input_ids),
token_ids=tuple(req.origin_input_ids + req.output_ids)[:-1],
last_uncached_pos=len(req.prefix_indices),
req_pool_idx=req_pool_indices_cpu[i],
del_in_memory_pool=False,
@@ -611,10 +553,6 @@ class ModelTpServer:
)
req.prefix_indices, req.last_node = new_prefix_indices, new_last_node
if req is self.current_inflight_req:
# inflight request would get a new req idx
self.req_to_token_pool.free(int(req_pool_indices_cpu[i]))
def forward_decode_batch(self, batch: Batch):
# Check if decode out of memory
if not batch.check_decode_mem():
@@ -628,7 +566,7 @@ class ModelTpServer:
f"#retracted_reqs: {len(retracted_reqs)}, "
f"#new_token_ratio: {old_ratio:.4f} -> {self.new_token_ratio:.4f}"
)
self.waiting_queue.extend(retracted_reqs)
self.forward_queue.extend(retracted_reqs)
else:
self.new_token_ratio = max(
self.new_token_ratio - self.new_token_ratio_decay,
@@ -638,7 +576,7 @@ class ModelTpServer:
if not self.disable_regex_jump_forward:
# Check for jump-forward
jump_forward_reqs = batch.check_for_jump_forward(self.model_runner)
self.waiting_queue.extend(jump_forward_reqs)
self.forward_queue.extend(jump_forward_reqs)
if batch.is_empty():
return
@@ -773,18 +711,8 @@ class ModelTpServer:
else:
batch.reqs = []
def filter_out_inflight(self, batch: Batch):
# TODO(lsyin): reduce the overhead, make a special version for this
if self.current_inflight_req is None:
return
unfinished_indices = list(range(len(batch.reqs)))
unfinished_indices.remove(batch.reqs.index(self.current_inflight_req))
batch.filter_batch(unfinished_indices)
def flush_cache(self):
if len(self.waiting_queue) == 0 and (
if len(self.forward_queue) == 0 and (
self.running_batch is None or len(self.running_batch.reqs) == 0
):
self.tree_cache.reset()
@@ -797,20 +725,20 @@ class ModelTpServer:
else:
warnings.warn(
f"Cache not flushed because there are pending requests. "
f"#queue-req: {len(self.waiting_queue)}, "
f"#queue-req: {len(self.forward_queue)}, "
f"#running-req: {0 if self.running_batch is None else len(self.running_batch.reqs)}"
)
def abort_request(self, recv_req):
# Delete requests in the waiting queue
to_del = None
for i, req in enumerate(self.waiting_queue):
for i, req in enumerate(self.forward_queue):
if req.rid == recv_req.rid:
to_del = i
break
if to_del is not None:
del self.waiting_queue[to_del]
del self.forward_queue[to_del]
# Delete requests in the running batch
if self.running_batch: