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| title=" The pymalloc allocator holds pools of memory and only allocates |
| when all these pools are used. This means that allocations reported when |
| pymalloc is active will reflect only the allocations that happen when |
| the pools are full. <b>This is what happens at runtime</b> so it is fully |
| representative of a normal application but <b>the number of allocations |
| and the size may not correspond with the number of Python objects |
| created</b> (as pymalloc is reusing memory)." |
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| Python Allocator: pymalloc</span> |
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| Command line: <code>quantize.py --model /storage/yiliu7/deepseek-ai/DeepSeek-V2-Lite-Chat/ -t nvfp4 --use_autoround_format --output_dir ./qmodels</code><br> |
| Start time: <span id="stats-start-time"> 2025-12-10 05:59:20.435000+00:00</span><br> |
| End time: <span id="stats-end-time"> 2025-12-10 05:59:51.749000+00:00</span><br> |
| Duration: 0:00:31.314000<br> |
| Total number of allocations: 40271815<br> |
| Total number of frames seen: 0<br> |
| Peak memory usage: 16.8 GB<br> |
| Python allocator: pymalloc<br> |
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| The table reporter provides a simple tabular representation of memory |
| allocations in the target <b>when the memory usage was at its peak</b>. |
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| You can find more information in the <a target="_blank" href="https://bloomberg.github.io/memray/table.html">documentation</a>. |
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| var data = null; |
| var flamegraphData = null; |
| var invertedNoImportsData = null; |
| const merge_threads = true; |
| const memory_records = 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