76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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#
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from torch._inductor.pattern_matcher import Match
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from vllm.logger import logger
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def extra_stream_scope_check(match: Match) -> bool:
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"""
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Checks if all nodes in the same stream.
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"""
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non_default_streams = set()
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has_default = False
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for node in match.nodes:
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if node.op == "call_function":
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current_stream = node.meta.get("stream_label")
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if current_stream is None:
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has_default = True
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else:
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non_default_streams.add(current_stream)
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if len(non_default_streams) > 1:
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logger.debug(
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"Cross-stream operation detected in pattern match for AddRMSNormQuant. "
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"Multiple streams found: %s. Fusion is not supported for cross-stream operations.",
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non_default_streams,
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)
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return False
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if has_default and len(non_default_streams) > 0:
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logger.debug(
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"Cross-stream operation detected in pattern match for AddRMSNormQuant. "
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"Multiple streams found: %s. Fusion is not supported for cross-stream operations.",
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non_default_streams,
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)
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return False
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return True
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_register_patterns = set()
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def check_and_register_fusion_pass(pattern_class: type, **kwargs):
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global _register_patterns
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eps = kwargs.get("eps", 1e-6)
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pattern_key = str(pattern_class.__name__) + str(eps)
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if pattern_key in _register_patterns:
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return
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pattern = pattern_class(**kwargs)
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try:
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pattern.register()
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_register_patterns.add(pattern_key)
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except RuntimeError as e:
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if "Duplicate pattern" in str(e):
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logger.warning("Pattern %s eps %s has been registered", pattern_class.__name__, eps)
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_register_patterns.add(pattern_key)
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else:
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raise e
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