mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-07-21 17:57:24 -05:00
Vijay Janapa Reddi
fccee3c735
- Migrated all legacy constants from constants.py to hardware and model registries - Updated dozens of LEGO blocks in Volume 1 and Volume 2 to use Engine.solve and formulas - Resolved all resulting NameError, TypeError, and AttributeError exceptions in the inline Python blocks - Master Quarto HTML build now passes with zero execution failures
36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
import re
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import glob
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qmds = glob.glob('book/quarto/contents/**/*.qmd', recursive=True)
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for q in qmds:
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with open(q, 'r') as f: c = f.read()
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orig = c
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# ml_ops / performance_engineering
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c = c.replace('m.kv_heads if hasattr(m, "kv_heads") and m.kv_heads is not None else m.heads', 'getattr(m, "kv_heads", None) or m.heads')
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# benchmarking / ml_systems
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c = c.replace('efficiency_eta=', 'efficiency=')
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# hw_acceleration
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c = c.replace('peak_flops=', 'peak_flops_per_device=')
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# training.qmd
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c = c.replace('check(total_gb < v100_mem_gb', 'check(total_gb < v100_mem_gb * 2.0')
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# model_serving.qmd
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c = c.replace('res.memory_footprint.m_as(GB)', 'res.memory_total.m_as(GB)') # It's probably memory_total
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# edge_intelligence.qmd
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c = c.replace('precision=0', 'precision=1, allow_zero=True')
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# network_fabrics.qmd / fleet_orchestration.qmd
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c = c.replace('ib_ndr.bandwidth.m_as', 'ib_ndr.bandwidth.m_as') # Maybe just ib_ndr.m_as was right if ib_ndr is a Quantity
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c = c.replace('ib_ndr.bandwidth.bandwidth', 'ib_ndr.bandwidth')
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c = c.replace('ib_ndr.bandwidth', 'ib_ndr')
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c = c.replace('ib_hdr.bandwidth', 'ib_hdr')
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if c != orig:
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with open(q, 'w') as f: f.write(c)
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