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Create MLX array from R object

Source: R/class.R
as_mlx.Rd

Create MLX array from R object

Usage

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

Arguments

x

Numeric, logical, or complex vector, matrix, or array to convert

dtype

Data type for the MLX array. One of:

  • Floating point: "float32", "float64"

  • Integer signed: "int8", "int16", "int32", "int64"

  • Integer unsigned: "uint8", "uint16", "uint32", "uint64"

  • Other: "bool", "complex64"

If not specified, defaults to "float32" for numeric, "bool" for logical, and "complex64" for complex inputs.

device

Execution target: supply "gpu", "cpu", or an mlx_stream created via mlx_new_stream(). Defaults to the current mlx_default_device() unless noted otherwise (helpers that act on an existing array typically reuse that array's device or stream).

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 but emits a warning and downcasts to float32

  • 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()].

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"