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73144e278b
### What problem does this PR solve? Introduced gpu profile in .env Added Dockerfile_tei fix datrie Removed LIGHTEN flag ### Type of change - [x] Documentation Update - [x] Refactoring
98 lines
2.6 KiB
Python
98 lines
2.6 KiB
Python
#
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# Copyright 2025 The InfiniFlow Authors. 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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#
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import threading
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import subprocess
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import sys
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import os
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import logging
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def string_to_bytes(string):
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return string if isinstance(
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string, bytes) else string.encode(encoding="utf-8")
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def bytes_to_string(byte):
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return byte.decode(encoding="utf-8")
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def convert_bytes(size_in_bytes: int) -> str:
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"""
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Format size in bytes.
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"""
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if size_in_bytes == 0:
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return "0 B"
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units = ['B', 'KB', 'MB', 'GB', 'TB', 'PB']
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i = 0
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size = float(size_in_bytes)
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while size >= 1024 and i < len(units) - 1:
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size /= 1024
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i += 1
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if i == 0 or size >= 100:
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return f"{size:.0f} {units[i]}"
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elif size >= 10:
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return f"{size:.1f} {units[i]}"
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else:
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return f"{size:.2f} {units[i]}"
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def once(func):
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"""
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A thread-safe decorator that ensures the decorated function runs exactly once,
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caching and returning its result for all subsequent calls. This prevents
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race conditions in multi-threaded environments by using a lock to protect
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the execution state.
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Args:
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func (callable): The function to be executed only once.
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Returns:
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callable: A wrapper function that executes `func` on the first call
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and returns the cached result thereafter.
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Example:
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@once
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def compute_expensive_value():
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print("Computing...")
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return 42
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# First call: executes and prints
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# Subsequent calls: return 42 without executing
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"""
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executed = False
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result = None
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lock = threading.Lock()
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def wrapper(*args, **kwargs):
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nonlocal executed, result
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with lock:
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if not executed:
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executed = True
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result = func(*args, **kwargs)
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return result
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return wrapper
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@once
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def pip_install_torch():
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device = os.getenv("DEVICE", "cpu")
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if device=="cpu":
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return
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logging.info("Installing pytorch")
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pkg_names = ["torch>=2.5.0,<3.0.0"]
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subprocess.check_call([sys.executable, "-m", "pip", "install", *pkg_names])
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