mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-05-10 15:49:25 -05:00
ef7ad0a0b4
Gap fill (68 new questions): - Cloud: 17 questions (L1/L2 architecture, data, reliability, optimization) - Mobile: 24 questions (L1-L6+ across data, networking, reliability) - Edge: 8 questions (L4-L6+ networking, parallelism) - TinyML: 19 questions (L1-L6+ data, optimization, networking) - All with verified napkin math, MCQ for L1-L3 Math review Round 2 (Opus, per-track deep review): - Cloud: 817 reviewed, 3 errors (H100/A100 TFLOPS swaps, INT4→INT8) - Edge: 798 reviewed, 0 errors - Mobile: 768 reviewed, 2 errors (per-minute→per-hour, 48→45 TOPS) - TinyML: 712 reviewed, 2 errors (unit conversion cascade, throughput) - Combined R2 error rate: 0.22% (7/3095) Corpus: 3,248 total (3,161 published + 87 archived)
44 lines
1.1 KiB
INI
44 lines
1.1 KiB
INI
[DEFAULT]
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# All sections below are required unless otherwise specified.
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# See https://github.com/fastai/nbdev/blob/master/settings.ini for examples.
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### Python library ###
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repo = TinyTorch
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lib_name = tinytorch
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version = 0.1.9
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min_python = 3.10
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license = MIT
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black_formatting = False
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### nbdev ###
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doc_path = _docs
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lib_path = tinytorch
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nbs_path = modules
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nbs_path_release = modules/release
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recursive = True
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tst_flags = notest
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put_version_in_init = False
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### Docs ###
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branch = main
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custom_sidebar = False
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doc_host = https://tinytorch.github.io
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doc_baseurl = /TinyTorch/
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git_url = https://github.com/harvard-edge/cs249r_book/
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title = TinyTorch
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### PyPI ###
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audience = Developers
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author = TinyTorch Team
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author_email = team@tinytorch.org
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copyright = 2024 onwards, TinyTorch Team
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description = Build ML Systems from Scratch - A hands-on systems course
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keywords = machine learning, deep learning, systems, education
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language = English
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status = 3
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user = tinytorch
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### Optional ###
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requirements = numpy>=1.20.0 matplotlib>=3.3.0 rich>=10.0.0 jupyter>=1.0.0 pytest>=6.0.0
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dev_requirements = nbdev>=2.3.0 black>=22.0.0
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