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<li class="toctree-l1 has-children"><a class="reference internal" href="../python/export.html">Export Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../python/metal.html">Metal</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../python/nn.html">Neural Networks</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.freeze.html">mlx.nn.Module.freeze</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.leaf_modules.html">mlx.nn.Module.leaf_modules</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.load_weights.html">mlx.nn.Module.load_weights</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.modules.html">mlx.nn.Module.modules</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.named_modules.html">mlx.nn.Module.named_modules</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.parameters.html">mlx.nn.Module.parameters</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.save_weights.html">mlx.nn.Module.save_weights</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.set_dtype.html">mlx.nn.Module.set_dtype</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.train.html">mlx.nn.Module.train</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.trainable_parameters.html">mlx.nn.Module.trainable_parameters</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.unfreeze.html">mlx.nn.Module.unfreeze</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.update.html">mlx.nn.Module.update</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Module.update_modules.html">mlx.nn.Module.update_modules</a></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l2 has-children"><a class="reference internal" href="../python/nn/layers.html">Layers</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ALiBi.html">mlx.nn.ALiBi</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.AvgPool1d.html">mlx.nn.AvgPool1d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.AvgPool2d.html">mlx.nn.AvgPool2d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.AvgPool3d.html">mlx.nn.AvgPool3d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.BatchNorm.html">mlx.nn.BatchNorm</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.CELU.html">mlx.nn.CELU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Conv1d.html">mlx.nn.Conv1d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Conv2d.html">mlx.nn.Conv2d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Conv3d.html">mlx.nn.Conv3d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ConvTranspose1d.html">mlx.nn.ConvTranspose1d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ConvTranspose2d.html">mlx.nn.ConvTranspose2d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ConvTranspose3d.html">mlx.nn.ConvTranspose3d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Dropout.html">mlx.nn.Dropout</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Dropout2d.html">mlx.nn.Dropout2d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Dropout3d.html">mlx.nn.Dropout3d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Embedding.html">mlx.nn.Embedding</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ELU.html">mlx.nn.ELU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.GELU.html">mlx.nn.GELU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.GLU.html">mlx.nn.GLU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.GroupNorm.html">mlx.nn.GroupNorm</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.GRU.html">mlx.nn.GRU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.HardShrink.html">mlx.nn.HardShrink</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.HardTanh.html">mlx.nn.HardTanh</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Hardswish.html">mlx.nn.Hardswish</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.InstanceNorm.html">mlx.nn.InstanceNorm</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.LayerNorm.html">mlx.nn.LayerNorm</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.LeakyReLU.html">mlx.nn.LeakyReLU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Linear.html">mlx.nn.Linear</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.LogSigmoid.html">mlx.nn.LogSigmoid</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.LogSoftmax.html">mlx.nn.LogSoftmax</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.LSTM.html">mlx.nn.LSTM</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.MaxPool1d.html">mlx.nn.MaxPool1d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.MaxPool2d.html">mlx.nn.MaxPool2d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.MaxPool3d.html">mlx.nn.MaxPool3d</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Mish.html">mlx.nn.Mish</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.MultiHeadAttention.html">mlx.nn.MultiHeadAttention</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.PReLU.html">mlx.nn.PReLU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html">mlx.nn.QuantizedEmbedding</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.QuantizedLinear.html">mlx.nn.QuantizedLinear</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.RMSNorm.html">mlx.nn.RMSNorm</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ReLU.html">mlx.nn.ReLU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.ReLU6.html">mlx.nn.ReLU6</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.RNN.html">mlx.nn.RNN</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.RoPE.html">mlx.nn.RoPE</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.SELU.html">mlx.nn.SELU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Sequential.html">mlx.nn.Sequential</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Sigmoid.html">mlx.nn.Sigmoid</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.SiLU.html">mlx.nn.SiLU</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.SinusoidalPositionalEncoding.html">mlx.nn.SinusoidalPositionalEncoding</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Softmin.html">mlx.nn.Softmin</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Softshrink.html">mlx.nn.Softshrink</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Softsign.html">mlx.nn.Softsign</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Softmax.html">mlx.nn.Softmax</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Softplus.html">mlx.nn.Softplus</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Step.html">mlx.nn.Step</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Tanh.html">mlx.nn.Tanh</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Transformer.html">mlx.nn.Transformer</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.Upsample.html">mlx.nn.Upsample</a></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l2 has-children"><a class="reference internal" href="../python/nn/functions.html">Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.elu.html">mlx.nn.elu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.celu.html">mlx.nn.celu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.gelu.html">mlx.nn.gelu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.gelu_approx.html">mlx.nn.gelu_approx</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html">mlx.nn.gelu_fast_approx</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.glu.html">mlx.nn.glu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.hard_shrink.html">mlx.nn.hard_shrink</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.hard_tanh.html">mlx.nn.hard_tanh</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.hardswish.html">mlx.nn.hardswish</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.leaky_relu.html">mlx.nn.leaky_relu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.log_sigmoid.html">mlx.nn.log_sigmoid</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.log_softmax.html">mlx.nn.log_softmax</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.mish.html">mlx.nn.mish</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.prelu.html">mlx.nn.prelu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.relu.html">mlx.nn.relu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.relu6.html">mlx.nn.relu6</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.selu.html">mlx.nn.selu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.sigmoid.html">mlx.nn.sigmoid</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.silu.html">mlx.nn.silu</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.softmax.html">mlx.nn.softmax</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.softmin.html">mlx.nn.softmin</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.softplus.html">mlx.nn.softplus</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.softshrink.html">mlx.nn.softshrink</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.step.html">mlx.nn.step</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.tanh.html">mlx.nn.tanh</a></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l2 has-children"><a class="reference internal" href="../python/nn/losses.html">Loss Functions</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html">mlx.nn.losses.binary_cross_entropy</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.cosine_similarity_loss.html">mlx.nn.losses.cosine_similarity_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.cross_entropy.html">mlx.nn.losses.cross_entropy</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.gaussian_nll_loss.html">mlx.nn.losses.gaussian_nll_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.hinge_loss.html">mlx.nn.losses.hinge_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.huber_loss.html">mlx.nn.losses.huber_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.kl_div_loss.html">mlx.nn.losses.kl_div_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.l1_loss.html">mlx.nn.losses.l1_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.log_cosh_loss.html">mlx.nn.losses.log_cosh_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.margin_ranking_loss.html">mlx.nn.losses.margin_ranking_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.mse_loss.html">mlx.nn.losses.mse_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.nll_loss.html">mlx.nn.losses.nll_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html">mlx.nn.losses.smooth_l1_loss</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary_functions/mlx.nn.losses.triplet_loss.html">mlx.nn.losses.triplet_loss</a></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l2 has-children"><a class="reference internal" href="../python/nn/init.html">Initializers</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.constant.html">mlx.nn.init.constant</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.normal.html">mlx.nn.init.normal</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.uniform.html">mlx.nn.init.uniform</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.identity.html">mlx.nn.init.identity</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.glorot_normal.html">mlx.nn.init.glorot_normal</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.glorot_uniform.html">mlx.nn.init.glorot_uniform</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.he_normal.html">mlx.nn.init.he_normal</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/nn/_autosummary/mlx.nn.init.he_uniform.html">mlx.nn.init.he_uniform</a></li>
|
||
</ul>
|
||
</details></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l1 has-children"><a class="reference internal" href="../python/optimizers.html">Optimizers</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l2 has-children"><a class="reference internal" href="../python/optimizers/optimizer.html">Optimizer</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html">mlx.optimizers.Optimizer.state</a></li>
|
||
<li class="toctree-l3"><a class="reference internal" href="../python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html">mlx.optimizers.Optimizer.apply_gradients</a></li>
|
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<div id="jb-print-docs-body" class="onlyprint">
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<h1>Saving and Loading Arrays</h1>
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<section id="saving-and-loading-arrays">
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<span id="saving-and-loading"></span><h1>Saving and Loading Arrays<a class="headerlink" href="#saving-and-loading-arrays" title="Link to this heading">#</a></h1>
|
||
<p>MLX supports multiple array serialization formats.</p>
|
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<div class="pst-scrollable-table-container"><table class="table" id="id1">
|
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<caption><span class="caption-text">Serialization Formats</span><a class="headerlink" href="#id1" title="Link to this table">#</a></caption>
|
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<colgroup>
|
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<col style="width: 25.6%" />
|
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</colgroup>
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<thead>
|
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<tr class="row-odd"><th class="head"><p>Format</p></th>
|
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<th class="head"><p>Extension</p></th>
|
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<th class="head"><p>Function</p></th>
|
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<th class="head"><p>Notes</p></th>
|
||
</tr>
|
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</thead>
|
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<tbody>
|
||
<tr class="row-even"><td><p>NumPy</p></td>
|
||
<td><p><code class="docutils literal notranslate"><span class="pre">.npy</span></code></p></td>
|
||
<td><p><a class="reference internal" href="../python/_autosummary/mlx.core.save.html#mlx.core.save" title="mlx.core.save"><code class="xref py py-func docutils literal notranslate"><span class="pre">save()</span></code></a></p></td>
|
||
<td><p>Single arrays only</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>NumPy archive</p></td>
|
||
<td><p><code class="docutils literal notranslate"><span class="pre">.npz</span></code></p></td>
|
||
<td><p><a class="reference internal" href="../python/_autosummary/mlx.core.savez.html#mlx.core.savez" title="mlx.core.savez"><code class="xref py py-func docutils literal notranslate"><span class="pre">savez()</span></code></a> and <a class="reference internal" href="../python/_autosummary/mlx.core.savez_compressed.html#mlx.core.savez_compressed" title="mlx.core.savez_compressed"><code class="xref py py-func docutils literal notranslate"><span class="pre">savez_compressed()</span></code></a></p></td>
|
||
<td><p>Multiple arrays</p></td>
|
||
</tr>
|
||
<tr class="row-even"><td><p>Safetensors</p></td>
|
||
<td><p><code class="docutils literal notranslate"><span class="pre">.safetensors</span></code></p></td>
|
||
<td><p><a class="reference internal" href="../python/_autosummary/mlx.core.save_safetensors.html#mlx.core.save_safetensors" title="mlx.core.save_safetensors"><code class="xref py py-func docutils literal notranslate"><span class="pre">save_safetensors()</span></code></a></p></td>
|
||
<td><p>Multiple arrays</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p>GGUF</p></td>
|
||
<td><p><code class="docutils literal notranslate"><span class="pre">.gguf</span></code></p></td>
|
||
<td><p><a class="reference internal" href="../python/_autosummary/mlx.core.save_gguf.html#mlx.core.save_gguf" title="mlx.core.save_gguf"><code class="xref py py-func docutils literal notranslate"><span class="pre">save_gguf()</span></code></a></p></td>
|
||
<td><p>Multiple arrays</p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p>The <a class="reference internal" href="../python/_autosummary/mlx.core.load.html#mlx.core.load" title="mlx.core.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">load()</span></code></a> function will load any of the supported serialization
|
||
formats. It determines the format from the extensions. The output of
|
||
<a class="reference internal" href="../python/_autosummary/mlx.core.load.html#mlx.core.load" title="mlx.core.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">load()</span></code></a> depends on the format.</p>
|
||
<p>Here’s an example of saving a single array to a file:</p>
|
||
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>>>><span class="w"> </span><span class="nv">a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span>mx.array<span class="o">([</span><span class="m">1</span>.0<span class="o">])</span>
|
||
>>><span class="w"> </span>mx.save<span class="o">(</span><span class="s2">"array"</span>,<span class="w"> </span>a<span class="o">)</span>
|
||
</pre></div>
|
||
</div>
|
||
<p>The array <code class="docutils literal notranslate"><span class="pre">a</span></code> will be saved in the file <code class="docutils literal notranslate"><span class="pre">array.npy</span></code> (notice the extension
|
||
is automatically added). Including the extension is optional; if it is missing
|
||
it will be added. You can load the array with:</p>
|
||
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>>>><span class="w"> </span>mx.load<span class="o">(</span><span class="s2">"array.npy"</span><span class="o">)</span>
|
||
array<span class="o">([</span><span class="m">1</span><span class="o">]</span>,<span class="w"> </span><span class="nv">dtype</span><span class="o">=</span>float32<span class="o">)</span>
|
||
</pre></div>
|
||
</div>
|
||
<p>Here’s an example of saving several arrays to a single file:</p>
|
||
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>>>><span class="w"> </span><span class="nv">a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span>mx.array<span class="o">([</span><span class="m">1</span>.0<span class="o">])</span>
|
||
>>><span class="w"> </span><span class="nv">b</span><span class="w"> </span><span class="o">=</span><span class="w"> </span>mx.array<span class="o">([</span><span class="m">2</span>.0<span class="o">])</span>
|
||
>>><span class="w"> </span>mx.savez<span class="o">(</span><span class="s2">"arrays"</span>,<span class="w"> </span>a,<span class="w"> </span><span class="nv">b</span><span class="o">=</span>b<span class="o">)</span>
|
||
</pre></div>
|
||
</div>
|
||
<p>For compatibility with <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.savez.html#numpy.savez" title="(in NumPy v2.2)"><code class="xref py py-func docutils literal notranslate"><span class="pre">numpy.savez()</span></code></a> the MLX <a class="reference internal" href="../python/_autosummary/mlx.core.savez.html#mlx.core.savez" title="mlx.core.savez"><code class="xref py py-func docutils literal notranslate"><span class="pre">savez()</span></code></a> takes arrays
|
||
as arguments. If the keywords are missing, then default names will be
|
||
provided. This can be loaded with:</p>
|
||
<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>>>><span class="w"> </span>mx.load<span class="o">(</span><span class="s2">"arrays.npz"</span><span class="o">)</span>
|
||
<span class="o">{</span><span class="s1">'b'</span>:<span class="w"> </span>array<span class="o">([</span><span class="m">2</span><span class="o">]</span>,<span class="w"> </span><span class="nv">dtype</span><span class="o">=</span>float32<span class="o">)</span>,<span class="w"> </span><span class="s1">'arr_0'</span>:<span class="w"> </span>array<span class="o">([</span><span class="m">1</span><span class="o">]</span>,<span class="w"> </span><span class="nv">dtype</span><span class="o">=</span>float32<span class="o">)}</span>
|
||
</pre></div>
|
||
</div>
|
||
<p>In this case <a class="reference internal" href="../python/_autosummary/mlx.core.load.html#mlx.core.load" title="mlx.core.load"><code class="xref py py-func docutils literal notranslate"><span class="pre">load()</span></code></a> returns a dictionary of names to arrays.</p>
|
||
<p>The functions <a class="reference internal" href="../python/_autosummary/mlx.core.save_safetensors.html#mlx.core.save_safetensors" title="mlx.core.save_safetensors"><code class="xref py py-func docutils literal notranslate"><span class="pre">save_safetensors()</span></code></a> and <a class="reference internal" href="../python/_autosummary/mlx.core.save_gguf.html#mlx.core.save_gguf" title="mlx.core.save_gguf"><code class="xref py py-func docutils literal notranslate"><span class="pre">save_gguf()</span></code></a> are similar to
|
||
<a class="reference internal" href="../python/_autosummary/mlx.core.savez.html#mlx.core.savez" title="mlx.core.savez"><code class="xref py py-func docutils literal notranslate"><span class="pre">savez()</span></code></a>, but they take as input a <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">dict</span></code></a> of string names to arrays:</p>
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<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>>>><span class="w"> </span><span class="nv">a</span><span class="w"> </span><span class="o">=</span><span class="w"> </span>mx.array<span class="o">([</span><span class="m">1</span>.0<span class="o">])</span>
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>>><span class="w"> </span><span class="nv">b</span><span class="w"> </span><span class="o">=</span><span class="w"> </span>mx.array<span class="o">([</span><span class="m">2</span>.0<span class="o">])</span>
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>>><span class="w"> </span>mx.save_safetensors<span class="o">(</span><span class="s2">"arrays"</span>,<span class="w"> </span><span class="o">{</span><span class="s2">"a"</span>:<span class="w"> </span>a,<span class="w"> </span><span class="s2">"b"</span>:<span class="w"> </span>b<span class="o">})</span>
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