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82 lines
2.0 KiB
ReStructuredText
82 lines
2.0 KiB
ReStructuredText
.. _saving_and_loading:
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Saving and Loading Arrays
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=========================
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.. currentmodule:: mlx.core
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MLX supports multiple array serialization formats.
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.. list-table:: Serialization Formats
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:widths: 20 8 25 25
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:header-rows: 1
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* - Format
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- Extension
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- Function
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- Notes
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* - NumPy
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- ``.npy``
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- :func:`save`
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- Single arrays only
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* - NumPy archive
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- ``.npz``
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- :func:`savez` and :func:`savez_compressed`
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- Multiple arrays
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* - Safetensors
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- ``.safetensors``
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- :func:`save_safetensors`
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- Multiple arrays
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* - GGUF
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- ``.gguf``
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- :func:`save_gguf`
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- Multiple arrays
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The :func:`load` function will load any of the supported serialization
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formats. It determines the format from the extensions. The output of
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:func:`load` depends on the format.
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Here's an example of saving a single array to a file:
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.. code-block:: shell
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>>> a = mx.array([1.0])
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>>> mx.save("array", a)
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The array ``a`` will be saved in the file ``array.npy`` (notice the extension
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is automatically added). Including the extension is optional; if it is missing
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it will be added. You can load the array with:
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.. code-block:: shell
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>>> mx.load("array.npy")
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array([1], dtype=float32)
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Here's an example of saving several arrays to a single file:
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.. code-block:: shell
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>>> a = mx.array([1.0])
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>>> b = mx.array([2.0])
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>>> mx.savez("arrays", a, b=b)
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For compatibility with :func:`numpy.savez` the MLX :func:`savez` takes arrays
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as arguments. If the keywords are missing, then default names will be
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provided. This can be loaded with:
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.. code-block:: shell
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>>> mx.load("arrays.npz")
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{'b': array([2], dtype=float32), 'arr_0': array([1], dtype=float32)}
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In this case :func:`load` returns a dictionary of names to arrays.
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The functions :func:`save_safetensors` and :func:`save_gguf` are similar to
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:func:`savez`, but they take as input a :obj:`dict` of string names to arrays:
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.. code-block:: shell
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>>> a = mx.array([1.0])
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>>> b = mx.array([2.0])
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>>> mx.save_safetensors("arrays", {"a": a, "b": b})
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