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MLX 0.0.5 documentation - Home

Install

  • Build and Install

Usage

  • Quick Start Guide
  • Unified Memory
  • Using Streams

Examples

  • Linear Regression
  • Multi-Layer Perceptron
  • LLM inference

Python API Reference

  • Array
    • mlx.core.array
    • mlx.core.array.astype
    • mlx.core.array.item
    • mlx.core.array.tolist
    • mlx.core.array.dtype
    • mlx.core.array.ndim
    • mlx.core.array.shape
    • mlx.core.array.size
    • mlx.core.Dtype
    • mlx.core.array.abs
    • mlx.core.array.all
    • mlx.core.array.any
    • mlx.core.array.argmax
    • mlx.core.array.argmin
    • mlx.core.array.cos
    • mlx.core.array.dtype
    • mlx.core.array.exp
    • mlx.core.array.log
    • mlx.core.array.log1p
    • mlx.core.array.logsumexp
    • mlx.core.array.max
    • mlx.core.array.mean
    • mlx.core.array.min
    • mlx.core.array.prod
    • mlx.core.array.reciprocal
    • mlx.core.array.reshape
    • mlx.core.array.rsqrt
    • mlx.core.array.sin
    • mlx.core.array.split
    • mlx.core.array.sqrt
    • mlx.core.array.square
    • mlx.core.array.sum
    • mlx.core.array.transpose
    • mlx.core.array.T
    • mlx.core.array.var
  • Devices and Streams
    • mlx.core.Device
    • mlx.core.default_device
    • mlx.core.set_default_device
    • mlx.core.Stream
    • mlx.core.default_stream
    • mlx.core.new_stream
    • mlx.core.set_default_stream
  • Operations
    • mlx.core.abs
    • mlx.core.add
    • mlx.core.all
    • mlx.core.allclose
    • mlx.core.any
    • mlx.core.arange
    • mlx.core.arccos
    • mlx.core.arccosh
    • mlx.core.arcsin
    • mlx.core.arcsinh
    • mlx.core.arctan
    • mlx.core.arctanh
    • mlx.core.argmax
    • mlx.core.argmin
    • mlx.core.argpartition
    • mlx.core.argsort
    • mlx.core.array_equal
    • mlx.core.broadcast_to
    • mlx.core.ceil
    • mlx.core.concatenate
    • mlx.core.convolve
    • mlx.core.conv1d
    • mlx.core.conv2d
    • mlx.core.cos
    • mlx.core.cosh
    • mlx.core.divide
    • mlx.core.equal
    • mlx.core.erf
    • mlx.core.erfinv
    • mlx.core.exp
    • mlx.core.expand_dims
    • mlx.core.eye
    • mlx.core.floor
    • mlx.core.flatten
    • mlx.core.full
    • mlx.core.greater
    • mlx.core.greater_equal
    • mlx.core.identity
    • mlx.core.less
    • mlx.core.less_equal
    • mlx.core.load
    • mlx.core.log
    • mlx.core.log2
    • mlx.core.log10
    • mlx.core.log1p
    • mlx.core.logaddexp
    • mlx.core.logical_not
    • mlx.core.logsumexp
    • mlx.core.matmul
    • mlx.core.max
    • mlx.core.maximum
    • mlx.core.mean
    • mlx.core.min
    • mlx.core.minimum
    • mlx.core.moveaxis
    • mlx.core.multiply
    • mlx.core.negative
    • mlx.core.ones
    • mlx.core.ones_like
    • mlx.core.partition
    • mlx.core.pad
    • mlx.core.prod
    • mlx.core.reciprocal
    • mlx.core.reshape
    • mlx.core.rsqrt
    • mlx.core.save
    • mlx.core.savez
    • mlx.core.savez_compressed
    • mlx.core.sigmoid
    • mlx.core.sign
    • mlx.core.sin
    • mlx.core.sinh
    • mlx.core.softmax
    • mlx.core.sort
    • mlx.core.split
    • mlx.core.sqrt
    • mlx.core.square
    • mlx.core.squeeze
    • mlx.core.stack
    • mlx.core.stop_gradient
    • mlx.core.subtract
    • mlx.core.sum
    • mlx.core.swapaxes
    • mlx.core.take
    • mlx.core.take_along_axis
    • mlx.core.tan
    • mlx.core.tanh
    • mlx.core.transpose
    • mlx.core.tri
    • mlx.core.tril
    • mlx.core.triu
    • mlx.core.var
    • mlx.core.where
    • mlx.core.zeros
    • mlx.core.zeros_like
  • Random
    • mlx.core.random.seed
    • mlx.core.random.key
    • mlx.core.random.split
    • mlx.core.random.bernoulli
    • mlx.core.random.categorical
    • mlx.core.random.gumbel
    • mlx.core.random.normal
    • mlx.core.random.randint
    • mlx.core.random.uniform
    • mlx.core.random.truncated_normal
  • Transforms
    • mlx.core.eval
    • mlx.core.grad
    • mlx.core.value_and_grad
    • mlx.core.jvp
    • mlx.core.vjp
    • mlx.core.vmap
    • mlx.core.simplify
  • FFT
    • mlx.core.fft.fft
    • mlx.core.fft.ifft
    • mlx.core.fft.fft2
    • mlx.core.fft.ifft2
    • mlx.core.fft.fftn
    • mlx.core.fft.ifftn
    • mlx.core.fft.rfft
    • mlx.core.fft.irfft
    • mlx.core.fft.rfft2
    • mlx.core.fft.irfft2
    • mlx.core.fft.rfftn
    • mlx.core.fft.irfftn
  • Neural Networks
    • mlx.nn.value_and_grad
    • mlx.nn.Module
    • Layers
      • mlx.nn.Embedding
      • mlx.nn.ReLU
      • mlx.nn.PReLU
      • mlx.nn.GELU
      • mlx.nn.SiLU
      • mlx.nn.Step
      • mlx.nn.SELU
      • mlx.nn.Mish
      • mlx.nn.Linear
      • mlx.nn.Conv1d
      • mlx.nn.Conv2d
      • mlx.nn.LayerNorm
      • mlx.nn.RMSNorm
      • mlx.nn.GroupNorm
      • mlx.nn.RoPE
      • mlx.nn.MultiHeadAttention
      • mlx.nn.Sequential
    • Functions
      • mlx.nn.gelu
      • mlx.nn.gelu_approx
      • mlx.nn.gelu_fast_approx
      • mlx.nn.relu
      • mlx.nn.prelu
      • mlx.nn.silu
      • mlx.nn.step
      • mlx.nn.selu
      • mlx.nn.mish
    • Loss Functions
      • mlx.nn.losses.cross_entropy
      • mlx.nn.losses.binary_cross_entropy
      • mlx.nn.losses.l1_loss
      • mlx.nn.losses.mse_loss
      • mlx.nn.losses.nll_loss
      • mlx.nn.losses.kl_div_loss
  • Optimizers
    • mlx.optimizers.OptimizerState
    • mlx.optimizers.Optimizer
    • mlx.optimizers.SGD
    • mlx.optimizers.RMSprop
    • mlx.optimizers.Adagrad
    • mlx.optimizers.AdaDelta
    • mlx.optimizers.Adam
    • mlx.optimizers.AdamW
    • mlx.optimizers.Adamax
  • Tree Utils
    • mlx.utils.tree_flatten
    • mlx.utils.tree_unflatten
    • mlx.utils.tree_map

C++ API Reference

  • Operations

Further Reading

  • Developer Documentation
  • .rst

Devices and Streams

Devices and Streams#

Device

default_device()

set_default_device(device)

Stream

default_stream(device)

new_stream(device)

set_default_stream(stream)

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By MLX Contributors

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