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https://git.datalinker.icu/vllm-project/vllm.git
synced 2026-04-07 13:17:06 +08:00
comments cleanup etc
Signed-off-by: Sage Moore <sage@neuralmagic.com>
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10ca263058
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@ -593,6 +593,7 @@ class GPUModelRunner(LoRAModelRunnerMixin):
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total_num_scheduled_tokens >= \
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self.parallel_config.microbatching_token_threshold \
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and max_num_scheduled_tokens == 1
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# Don't microbatch unless every other DP worker is also microbatching
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should_ubatch = self.should_ubatch(should_attempt_ubatching)
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if not should_ubatch:
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@ -611,20 +612,20 @@ class GPUModelRunner(LoRAModelRunnerMixin):
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]
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num_pad_tokens = 0
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num_tokens_after_padding = None
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ubatch_bailout = False
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ubatch_abort = False
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num_pad_tokens, num_tokens_after_padding = self.get_dp_padding_ubatch(ubatch_slices)
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if num_pad_tokens > 0:
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# Check if the padding would result in an empty second ubatch.
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# If so abort ubatching
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if num_pad_tokens < scheduler_output.total_num_scheduled_tokens:
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self.pad_out_ubatch_first_stage(ubatch_slices, num_pad_tokens)
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else:
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# We bail out of ubatching here. This accounts for the case where
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# the padding would result in an "empty" second ubatch.
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# TODO: just make the second ubatch a dummy ubatch
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ubatch_bailout = True
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ubatch_abort = True
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# Note that if we are attempting to ubatch by this point then we know that no
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# DP ranks are doing dummy runs
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should_ubatch = self.should_ubatch(False if ubatch_bailout else True)
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# DP ranks are doing dummy runs. Meaning, we don't need a second call to
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# should_ubatch in _dummy_run
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should_ubatch = self.should_ubatch(False if ubatch_abort else True)
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if not should_ubatch:
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return (None, 0, None)
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return (ubatch_slices, num_pad_tokens, num_tokens_after_padding)
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@ -65,26 +65,16 @@ class UBatchContext:
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self.current_stream = stream
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torch.cuda.set_stream(self.current_stream)
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def ctx_valid_state(self):
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assert forward_context._forward_context == self.forward_context
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assert current_stream() == self.current_stream
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assert not self.cpu_wait_event.is_set()
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pass
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def _signal_comm_done(self):
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self.ctx_valid_state()
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self.gpu_comm_done_event.record(self.comm_stream)
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def _signal_compute_done(self):
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self.ctx_valid_state()
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self.gpu_compute_done_event.record(self.compute_stream)
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def _wait_compute_done(self):
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self.ctx_valid_state()
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self.comm_stream.wait_event(self.gpu_compute_done_event)
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def _wait_comm_done(self):
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self.ctx_valid_state()
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self.compute_stream.wait_event(self.gpu_comm_done_event)
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def stream_string(self):
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@ -96,29 +86,30 @@ class UBatchContext:
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return "COMM"
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def _cpu_yield(self):
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self.ctx_valid_state()
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# It is critical for correctness that only one thread is running
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# at a time. These asserts just make sure that this is the only
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# thread running before waking the other one up and going to sleep
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assert forward_context._forward_context == self.forward_context
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assert current_stream() == self.current_stream
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assert not self.cpu_wait_event.is_set()
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self.cpu_signal_event.set()
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self.cpu_wait_event.wait()
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self.cpu_wait_event.clear()
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self._restore_context()
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self.ctx_valid_state()
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def yield_and_switch_from_compute_to_comm(self):
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assert current_stream() == self.compute_stream
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self.ctx_valid_state()
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self._signal_compute_done()
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self._cpu_yield()
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self.ctx_valid_state()
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assert self.current_stream == self.compute_stream
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self.update_stream(self.comm_stream)
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self._wait_compute_done()
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def yield_and_switch_from_comm_to_compute(self):
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assert current_stream() == self.comm_stream
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self.ctx_valid_state()
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self._signal_comm_done()
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self._cpu_yield()
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self.ctx_valid_state()
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assert self.current_stream == self.comm_stream
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self.update_stream(self.compute_stream)
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self._wait_comm_done()
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