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fix(readme): the depth timing band was above every run; measure it an…
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docs: fix self-contradicting spiral claim and five other unmeasured n…
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docs(readme): plainer prose, verified numbers, working install line
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feat: batched matmul adjoints, retain_graph semantics, iterative topo…
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chore(release): bump to 0.1.0 + py.typed marker
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chore: CHANGELOG for v0.1.0
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docs(readme): badges, TL;DR snippet, examples, roadmap
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docs(theory): reverse-mode autodiff in 5 minutes
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example: two-spiral classifier with 3-layer MLP
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example: XOR with a 2-layer net (classification)
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example: 2-hidden-layer MLP fits sin(x) (regression)
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feat: flat public API at the tinydiff package root
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test(gradcheck): quadratic + linear-layer match autograd
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feat(gradcheck): central-difference numerical gradient verifier
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test(optim): SGD/Adam descend on quadratic; momentum helps
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feat(optim): SGD with momentum + Adam
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fix(ci): populate flat API incrementally so intermediate imports resolve
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test(loss): MSE grad value + softmax-xent simplex grad
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feat(loss): MSE + numerically-stable softmax cross-entropy
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test(nn): Linear / Sequential forward + param collection
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feat(nn): Module base + Linear + Sequential
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test(ops): matmul, relu, exp/log, pow, broadcast, mean
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test(autograd): scalar chain rule + add/mul gradients
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feat(ops): binary ops with broadcast-aware gradients
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feat(tensor): Tensor class + reverse-topo backward()
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