mirror of
https://github.com/nod-ai/AMD-SHARK-Studio.git
synced 2026-02-19 11:56:43 -05:00
cec6eda6b4
* Optimize device enumeration overhead and log details on long operations. * Various fixes to add `@functools.cache` to what should be one time, expensive, device enumeration and setup activities. Cuts several seconds off of initialization on my machine. * Add detailed tracing to actual invocations if they exceed a certain timeout or have an exception. * Add detailed tracing to loading status. * By default detail logging is only printed if an operation takes an excessive amount of time. All logging/timing can be printed by setting the variable `$env:SHARK_DETAIL_TRACE = "1"` * Remove cache from unhashable functions
77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
# Copyright 2023 The Nod Team. All rights reserved.
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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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from typing import List, Tuple
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import os
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import threading
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import time
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def _enable_detail_trace() -> bool:
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return os.getenv("SHARK_DETAIL_TRACE", "0") == "1"
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class DetailLogger:
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"""Context manager which can accumulate detailed log messages.
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Detailed log is only emitted if the operation takes a long time
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or errors.
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"""
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def __init__(self, timeout: float):
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self._timeout = timeout
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self._messages: List[Tuple[float, str]] = []
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self._start_time = time.time()
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self._active = not _enable_detail_trace()
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self._lock = threading.RLock()
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self._cond = threading.Condition(self._lock)
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self._thread = None
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def __enter__(self):
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self._thread = threading.Thread(target=self._run)
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self._thread.start()
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return self
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def __exit__(self, type, value, traceback):
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with self._lock:
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self._active = False
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self._cond.notify()
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if traceback:
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self.dump_on_error(f"exception")
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def _run(self):
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with self._lock:
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timed_out = not self._cond.wait(self._timeout)
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if timed_out:
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self.dump_on_error(f"took longer than {self._timeout}s")
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def log(self, msg):
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with self._lock:
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timestamp = time.time()
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if self._active:
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self._messages.append((timestamp, msg))
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else:
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print(f" +{(timestamp - self._start_time) * 1000}ms: {msg}")
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def dump_on_error(self, summary: str):
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with self._lock:
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if self._active:
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print(f"::: Detailed report ({summary}):")
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for timestamp, msg in self._messages:
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print(
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f" +{(timestamp - self._start_time) * 1000}ms: {msg}"
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)
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self._active = False
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