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stemann
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Apr 15, 2025
| element_types = MLX.supported_number_types(MLX.DeviceTypeGPU) # TODO Excluding Float64 | ||
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| array_sizes = [ | ||
| # (), # TODO: Excluded broadcasting over 0-dimensional Array: Yields scalar result |
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Broadcasting over a zero-dimensional array returns a scalar and not a zero-dimensional array in current Julia: JuliaLang/julia#28866
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Also:
* Added necessary eval of MLX array data in Base.unsafe_convert(::Type{Ptr{T}}, array::MLXArray{T, N})
* Implemented Base.similar for MLXArray.
* Added supported_number_types(::DeviceType = DeviceTypeCPU)
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* Added handling of broadcast over empty tuple. * Added constructors for UndefInitializer. * Added handling of JuliaLang/julia#28866 - dropping 0-dim arrays to scalars.
* Workaround for sign on CPU for unsigned * Using Julia 1.10 compatible `ceil`, `floor`, and `round`: `ceil(T, x)` -> `T(ceil(x))`
Likely; still broken: log1p, log2
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