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Create MLX array from R object

Source: R/class.R
as_mlx.Rd

If dtype is not specified, numeric inputs use "float32", logical inputs use "bool", and complex inputs use "complex64".

Usage

as_mlx(
  x,
  dtype = c("float32", "float64", "bool", "complex64", "int8", "int16", "int32", "int64",
    "uint8", "uint16", "uint32", "uint64")
)

Arguments

x

An mlx array, or an R array/matrix/vector that will be converted via as_mlx().

dtype

Data type string. Supported types include:

  • Floating point: "float32", "float64"

  • Integer: "int8", "int16", "int32", "int64", "uint8", "uint16", "uint32", "uint64"

  • Other: "bool", "complex64"

Not all functions support all types. See individual function documentation.

Value

An object of class mlx

Integer types require explicit dtype

R integer vectors (like 1:10) convert to float32 by default. To create integer MLX arrays, you must explicitly specify dtype:

x <- as_mlx(1:10, dtype = "int32")  # Creates int32 array
x <- as_mlx(1:10)                    # Creates float32 array

Type precision

  • float64 is supported on CPU only. Use with_device() or local_device() to run float64 work on CPU.

  • Integer arithmetic may promote types (e.g., int32 + int32 might → int64)

  • Mixed integer/float operations promote to float

Missing values

MLX does not have an NA sentinel. When you pass numeric NA values from R, they are stored as NaN inside MLX and returned to R as NaN. Use is.nan() on MLX arrays if you need to detect them. is.na() on mlx objects calls is.nan().

Scalars

MLX allows scalar values, with a zero-length dimension (integer(0)). These are not usually what R users want. as_mlx() never returns a scalar; call [mlx_reshape(x, integer(0))][mlx_reshape()] to create one explicitly, or use [mlx_array(..., allow_scalar = TRUE)][mlx_array()].

Details

MLX does not support float64 operations on GPU. When this function creates a float64 array or converts one back to R, Rmlx temporarily switches only that internal creation or layout work to CPU. Later operations on the returned array still use the current mlx_device().

See also

mlx.core.array

mlx-methods

Examples

# Default float32 for numeric
x <- as_mlx(c(1.5, 2.5, 3.5))
mlx_dtype(x)  # "float32"
#> [1] "float32"

# R integers also default to float32
x <- as_mlx(1:10)
mlx_dtype(x)  # "float32"
#> [1] "float32"

# Explicit integer types
x_int <- as_mlx(1:10, dtype = "int32")
mlx_dtype(x_int)  # "int32"
#> [1] "int32"

# Unsigned integers
x_uint <- as_mlx(c(0, 128, 255), dtype = "uint8")

# Logical → bool
mask <- as_mlx(c(TRUE, FALSE, TRUE))
mlx_dtype(mask)  # "bool"
#> [1] "bool"