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Add discrete distributions to dpnp.random.Generator - #3159
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ndgrigorian
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View rendered docs @ https://intelpython.github.io/dpnp/pull/3159/index.html |
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Array API standard conformance tests for dpnp=0.22.0dev2=np2py314h8d9cdd5_34 ran successfully. |
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Coverage is 84.705% — feature/device-rng-discrete into feature/device-rng-continuous. No base build found for |
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| // sycl::mul_hi is not used: optimized DPC++ 2026.2 builds get it wrong on | ||
| // Intel GPUs when one 64-bit operand is a compile-time constant (all results | ||
| // wrong at -O2, right at -O0). oneMKL's device RNG uses 32-bit halves too. |
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Nit: This works around a DPC++ bug, and AGENTS.md asks for the full issue URL in such a comment, so it can be reverted later. Is there an intel/llvm issue for the sycl::mul_hi miscompile? The new line in dpnp/libtensor/AGENTS.md could link it too.
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Add integers and the poisson, binomial, negative_binomial, geometric, logseries, zipf and hypergeometric samplers, along with noncentral_chisquare and noncentral_f, which need poisson. The discrete samplers return int64 and compute in double precision, or in single precision on devices without fp64, where host parameters are clipped to stay inside their domain once rounded.
Also move test_usm_type_follows_bounds and test_device_integer_param_dtype into their classes: indented into a fixture and a helper, pytest never collected them.
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This PR adds
integersand the discrete distributions todpnp.random.Generator, as part of the series splitting #3147. It is stacked on #3158Adds
integers, using NumPy's bounded integer algorithm (Lemire's method)poisson,binomial(inversion and BTPE),negative_binomial,geometric,logseries,zipfandhypergeometric(HRUA)noncentral_chisquareandnoncentral_f, which needpoissonThe discrete samplers return
int64and compute in double precision, or in single precision on devices without fp64. In single precision, host parameters are clipped so that they stay inside the domain once rounded, and the large log-factorial terms of BTPE and HRUA are gathered into onelog1pso that they don't cancel.zipfusesexpm1/log1p, deliberately departing from NumPy, whose tail foraclose to 1 is too heavy above2**53(documented inrandom.rst)As in #3158, every rejection sampler returns the smallest
int64for device parameters that would make it loop foreverAlso adds
umul_hi, which replacessycl::mul_hi; DPC++ 2026.2 miscompilessycl::mul_hion Intel GPUs when one operand is a compile-time constant