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https://github.com/PaddlePaddle/FastDeploy.git
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[SOT] Extend SOT warmup support to new hardware (#3032)
* add new hardware * add_sot_warmup4new_hardware * fix conflict * rm Optional
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@@ -26,6 +26,10 @@ from paddleformers.utils.log import logger
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from fastdeploy.config import FDConfig
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from fastdeploy.engine.request import Request
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from fastdeploy.model_executor.forward_meta import ForwardMeta
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from fastdeploy.model_executor.graph_optimization.utils import (
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profile_run_guard,
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sot_warmup_guard,
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)
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from fastdeploy.model_executor.guided_decoding import get_guided_backend
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from fastdeploy.model_executor.guided_decoding.base_guided_decoding import (
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LogitsProcessorBase,
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@@ -79,8 +83,10 @@ class GCUModelRunner(ModelRunnerBase):
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self.sampler = SpeculativeSampler(fd_config)
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# Cuda Graph
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self.graph_opt_level = self.graph_opt_config.graph_opt_level
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self.use_cudagraph = self.graph_opt_config.use_cudagraph
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self.cudagraph_capture_sizes = list(reversed(self.graph_opt_config.cudagraph_capture_sizes))
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self.sot_warmup_sizes = self.graph_opt_config.sot_warmup_sizes
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# Initialize share inputs
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self._init_share_inputs(self.parallel_config.max_num_seqs)
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@@ -851,6 +857,17 @@ class GCUModelRunner(ModelRunnerBase):
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time_after_capture = time.perf_counter()
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logger.info(f"Cuda Graph capturing took {time_after_capture - time_before_capture} seconds")
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@sot_warmup_guard(True)
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def sot_warmup(self) -> None:
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start_time = time.perf_counter()
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for batch_size in self.sot_warmup_sizes:
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self._dummy_run(
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num_tokens=self.parallel_config.max_num_batched_tokens,
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batch_size=batch_size,
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)
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logger.info(f"SOT warmup the model with the batch size:{batch_size}")
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logger.info(f"SOT warmup took {time.perf_counter() - start_time} seconds")
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def _get_skip_idx(self, model_forward_batch: Optional[List[Request]] = None):
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"""
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Get the index of the request that needs to be skipped during execution.
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@@ -1041,6 +1058,7 @@ class GCUModelRunner(ModelRunnerBase):
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else:
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raise ValueError(f"{type(self.model)} has no attribute 'empty_input_forward")
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@profile_run_guard(True)
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def profile_run(self) -> None:
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"""Execute a forward pass with dummy inputs to profile the memory usage of the model"""
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