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name = " NNlibCUDA"
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uuid = " a00861dc-f156-4864-bf3c-e6376f28a68d"
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- version = " 0.2.5 "
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+ version = " 0.2.6 "
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[deps ]
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Adapt = " 79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -13,7 +13,7 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
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[compat ]
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Adapt = " 3.3"
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CUDA = " 3.11"
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- NNlib = " 0.8.14 "
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+ NNlib = " 0.8.15 "
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julia = " 1.6"
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[extras ]
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NNlib. _rng_from_array (:: CuArray ) = CUDA. default_rng ()
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+ NNlib. _rng_compat_array (rng:: CUDA.RNG , A:: CuArray ) = nothing
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+ NNlib. _rng_compat_array (rng:: AbstractRNG , A:: CuArray ) = throw (ArgumentError (
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+ " cannot use rng::$(typeof (rng)) with array::CuArray, only CUDA's own RNG type works" ))
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+
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function divide_kernel! (xs, ys, max_idx)
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index = threadIdx (). x + (blockIdx (). x - 1 ) * blockDim (). x
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