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* Add MNIST data to gitignore * Add simple tensor round-trip benchmark * Use deepseq + cleaner imports * Use safe version of fromIntegral in FFI code * Don't copy data when fetching tensors BEFORE benchmarking feedFetch/4 byte time 55.79 μs (54.88 μs .. 56.62 μs) 0.998 R² (0.997 R² .. 0.999 R²) mean 55.61 μs (55.09 μs .. 56.11 μs) std dev 1.828 μs (1.424 μs .. 2.518 μs) variance introduced by outliers: 34% (moderately inflated) benchmarking feedFetch/4 KiB time 231.4 μs (221.9 μs .. 247.3 μs) 0.988 R² (0.974 R² .. 1.000 R²) mean 226.6 μs (224.1 μs .. 236.2 μs) std dev 13.45 μs (7.115 μs .. 27.14 μs) variance introduced by outliers: 57% (severely inflated) benchmarking feedFetch/4 MiB time 485.8 ms (424.6 ms .. 526.7 ms) 0.998 R² (0.994 R² .. 1.000 R²) mean 515.7 ms (512.5 ms .. 517.9 ms) std dev 3.320 ms (0.0 s .. 3.822 ms) variance introduced by outliers: 19% (moderately inflated) AFTER benchmarking feedFetch/4 byte time 53.11 μs (52.12 μs .. 54.22 μs) 0.996 R² (0.995 R² .. 0.998 R²) mean 54.64 μs (53.59 μs .. 56.18 μs) std dev 4.249 μs (2.910 μs .. 6.076 μs) variance introduced by outliers: 75% (severely inflated) benchmarking feedFetch/4 KiB time 83.83 μs (82.72 μs .. 84.92 μs) 0.999 R² (0.998 R² .. 0.999 R²) mean 83.82 μs (83.20 μs .. 84.35 μs) std dev 1.943 μs (1.557 μs .. 2.614 μs) variance introduced by outliers: 20% (moderately inflated) benchmarking feedFetch/4 MiB time 95.54 ms (93.62 ms .. 97.82 ms) 0.999 R² (0.998 R² .. 1.000 R²) mean 96.61 ms (95.76 ms .. 97.51 ms) std dev 1.408 ms (1.005 ms .. 1.889 ms)
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**/.stack-work
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.stack/
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tensorflow-mnist-input-data/data/*.gz
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