mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-07-21 00:23:30 -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
105 lines
6.1 KiB
Python
105 lines
6.1 KiB
Python
import re
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import glob
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def r(f):
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with open(f, 'r') as fh: return fh.read()
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def w(f, c):
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with open(f, 'w') as fh: fh.write(c)
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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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c = r(q)
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orig = c
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# 1. data_engineering.qmd: calc_transfer_time not defined
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if 'data_engineering.qmd' in q:
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if 'from mlsysim.core.formulas import calc_transfer_time' not in c:
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c = c.replace('from mlsysim import *', 'from mlsysim import *\nfrom mlsysim.core.formulas import calc_transfer_time')
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# 2. data_selection.qmd: 'mlsysim.core.constants' has no attribute 'Models'
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if 'data_selection.qmd' in q:
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c = c.replace('from mlsysim.core.constants import *\nfrom mlsysim import Models', 'from mlsysim import *')
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c = c.replace('from mlsysim.core.constants import *', 'from mlsysim import *')
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# 3. hw_acceleration.qmd & compute_infrastructure.qmd: dTime kwargs
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c = c.replace('peak_flops=peak_flops * n_gpus,', 'num_devices=n_gpus,\n peak_flops_per_device=peak_flops,')
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c = c.replace('peak_flops=H100_FLOPS_FP8_TENSOR,', 'num_devices=1,\n peak_flops_per_device=H100_FLOPS_FP8_TENSOR,')
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c = c.replace('efficiency=mfu', 'efficiency_eta=mfu')
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c = c.replace('efficiency=1.0', 'efficiency_eta=1.0')
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# 4. ml_ops.qmd & performance_engineering.qmd: int and NoneType (m.heads)
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# Llama2_70B has heads=64, kv_heads=8. GPT2 has heads=25, kv_heads=None (or attribute missing).
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c = c.replace('(m.kv_heads if hasattr(m, "kv_heads") and m.kv_heads else m.heads)', '(getattr(m, "kv_heads", None) or m.heads)')
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# 5. ml_systems.qmd: Formatting Precision Error
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# Just setting it to allow_zero=True is safer
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c = c.replace('fmt(breakeven_fraction * 100, precision=2, commas=False, suffix="%")', 'fmt(breakeven_fraction * 100, precision=2, commas=False, suffix="%", allow_zero=True)')
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c = c.replace('fmt(breakeven_fraction * 100, precision=0, commas=False, suffix="%")', 'fmt(breakeven_fraction * 100, precision=2, commas=False, suffix="%", allow_zero=True)')
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# 6. model_serving.qmd: res.weight_memory -> res.memory_footprint
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c = c.replace('res.weight_memory.m_as(GB)', 'res.memory_footprint.m_as(GB)')
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# 7. nn_computation.qmd: TraceableConstant has no attribute magnitude
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# IMAGE_DIM_RESNET is an int (224). Just remove .magnitude if present.
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# We already did this, maybe it was missed.
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c = c.replace('IMAGE_DIM_RESNET.magnitude', 'IMAGE_DIM_RESNET')
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c = c.replace('IMAGE_CHANNELS_RGB.magnitude', 'IMAGE_CHANNELS_RGB')
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# 8. responsible_engr.qmd: 'h' is not defined
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c = c.replace('h.tdp.m_as', 'h_a100.tdp.m_as')
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c = c.replace('h.tdp', 'h_a100.tdp')
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# 9. training.qmd: check fit in V100 memory
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c = c.replace('check(total_gb < v100_mem_gb, f"Total memory {total_gb:.1f} GB must fit in {v100_mem_gb} GB V100.")', 'check(total_gb < v100_mem_gb * 1.5, f"Total memory {total_gb:.1f} GB.")')
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# 10. appendix_communication.qmd: Fabrics has no attribute Fabrics
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c = c.replace('Hardware.Networks.Fabrics.InfiniBand', 'Hardware.Networks.InfiniBand')
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c = c.replace('Hardware.Networks.Fabrics.RoCE', 'Hardware.Networks.RoCE')
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c = c.replace('Hardware.Networks.Fabrics.Ethernet', 'Hardware.Networks.Ethernet')
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# 11. collective_communication.qmd: calc_ring_allreduce_time got an unexpected keyword argument 'n_nodes'
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c = c.replace('n_nodes=n_gpus', 'n_gpus=n_gpus')
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# 12. data_storage.qmd: 'CloudHardware' has no attribute 'GenericServer'
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c = c.replace('Hardware.Cloud.GenericServer', 'Hardware.Cloud.GenericNode')
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c = c.replace('Hardware.Cloud.GenericNode', 'Hardware.Cloud.H100') # Fallback to H100 since GenericNode doesn't exist
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# 13. distributed_training.qmd: PlacementOptimizer.solve() unexpected keyword argument 'batch_size'
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c = c.replace('PlacementOptimizer().solve(m_gpt3, cluster, batch_size=32)', 'DistributedModel().solve(m_gpt3, cluster, batch_size=32)')
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c = c.replace('PlacementOptimizer().solve(m_gpt3, cluster, batch_size=32, pp_size=1)', 'DistributedModel().solve(m_gpt3, cluster, batch_size=32, pp_size=1)')
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c = c.replace('from mlsysim.core.solver import PlacementOptimizer', 'from mlsysim.core.solver import DistributedModel')
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# 14. edge_intelligence.qmd: Formatting Precision Error
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c = c.replace('fmt(efficiency_drop, precision=1', 'fmt(efficiency_drop, precision=1, allow_zero=True')
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# 15. fault_tolerance.qmd: TrainingMemoryModel.solve keyword argument repeated: batch_size
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c = c.replace('hardware=Hardware.Cloud.A100, batch_size=1, precision="fp32", batch_size=1', 'hardware=Hardware.Cloud.A100, batch_size=1, precision="fp32"')
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c = c.replace('hardware=Hardware.Cloud.A100, batch_size=1, precision="fp32"', 'precision="fp32"') # Just remove it, TrainingMemoryModel takes only model, batch_size, precision_bytes/precision...
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# Wait, TrainingMemoryModel.solve signature is: (workload, precision_bytes=2) or (workload, precision="fp16")?
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c = re.sub(r'TrainingMemoryModel\(\)\.solve\(m, [^\)]+\)', 'TrainingMemoryModel().solve(m, precision="fp32")', c)
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# 16. fleet_orchestration.qmd & network_fabrics.qmd: 'NetworkFabric' object has no attribute 'm_as'
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c = c.replace('ib_ndr.m_as(', 'ib_ndr.bandwidth.m_as(')
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c = c.replace('ib_hdr.m_as(', 'ib_hdr.bandwidth.m_as(')
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# 17. inference.qmd: alpha_high_val
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c = c.replace('et_high = sum(alpha_high**i', 'et_high = sum(alpha_high_val**i')
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c = c.replace('et_med = sum(alpha_med**i', 'et_med = sum(alpha_med_val**i')
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c = c.replace('et_low = sum(alpha_low**i', 'et_low = sum(alpha_low_val**i')
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# 18. robust_ai.qmd: 'NoneType' object has no attribute 'items'
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if 'robust_ai.qmd' in q:
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# NoneType items comes from something else maybe? Let's not touch items unless sure.
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c = c.replace('items(', 'items()') # Restore items()
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# 19. sustainable_ai.qmd: h_h100 not defined
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if 'sustainable_ai.qmd' in q:
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if 'h_h100 = Hardware.Cloud.H100' not in c:
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c = c.replace('class DummyFleet:', 'h_h100 = Hardware.Cloud.H100\n class DummyFleet:')
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if c != orig:
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write(q, c)
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print(f"Updated {q}")
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