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~array.T
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~array.dtype
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~array.itemsize
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~array.nbytes
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~array.ndim
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~array.shape
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~array.size
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docs/build/html/_sources/python/_autosummary/mlx.core.linalg.norm.rst
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mlx.core.linalg.norm
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====================
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.. currentmodule:: mlx.core.linalg
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.. autofunction:: norm
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docs/build/html/_sources/python/_autosummary/mlx.core.repeat.rst
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mlx.core.repeat
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===============
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.. currentmodule:: mlx.core
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.. autofunction:: repeat
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docs/build/html/_sources/python/_autosummary/mlx.core.save_safetensors.rst
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docs/build/html/_sources/python/_autosummary/mlx.core.save_safetensors.rst
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mlx.core.save\_safetensors
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==========================
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.. currentmodule:: mlx.core
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.. autofunction:: save_safetensors
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mlx.core.tensordot
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==================
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.. currentmodule:: mlx.core
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.. autofunction:: tensordot
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docs/build/html/_sources/python/linalg.rst
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docs/build/html/_sources/python/linalg.rst
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.. _linalg:
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Linear Algebra
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==============
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.. currentmodule:: mlx.core.linalg
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.. autosummary::
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:toctree: _autosummary
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norm
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docs/build/html/_sources/python/nn.rst
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docs/build/html/_sources/python/nn.rst
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@@ -123,7 +123,7 @@ To get more detailed information on the arrays in a :class:`Module` you can use
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all the parameters in a :class:`Module` do:
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.. code-block:: python
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from mlx.utils import tree_map
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shapes = tree_map(lambda p: p.shape, mlp.parameters())
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@@ -131,7 +131,7 @@ As another example, you can count the number of parameters in a :class:`Module`
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with:
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.. code-block:: python
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from mlx.utils import tree_flatten
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num_params = sum(v.size for _, v in tree_flatten(mlp.parameters()))
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@@ -170,14 +170,13 @@ In detail:
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:meth:`mlx.core.value_and_grad`
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.. autosummary::
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:recursive:
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:toctree: _autosummary
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value_and_grad
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Module
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.. toctree::
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nn/module
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nn/layers
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nn/functions
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nn/losses
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.ALiBi.rst
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mlx.nn.ALiBi
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============
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.. currentmodule:: mlx.nn
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.. autoclass:: ALiBi
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.BatchNorm.rst
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mlx.nn.BatchNorm
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================
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.. currentmodule:: mlx.nn
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.. autoclass:: BatchNorm
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout.rst
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mlx.nn.Dropout
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==============
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.. currentmodule:: mlx.nn
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.. autoclass:: Dropout
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout2d.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout2d.rst
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mlx.nn.Dropout2d
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================
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.. currentmodule:: mlx.nn
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.. autoclass:: Dropout2d
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout3d.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Dropout3d.rst
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mlx.nn.Dropout3d
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================
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.. currentmodule:: mlx.nn
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.. autoclass:: Dropout3d
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.InstanceNorm.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.InstanceNorm.rst
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mlx.nn.InstanceNorm
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===================
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.. currentmodule:: mlx.nn
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.. autoclass:: InstanceNorm
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.apply.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.apply.rst
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mlx.nn.Module.apply
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===================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.apply
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.apply_to_modules.rst
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mlx.nn.Module.apply\_to\_modules
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================================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.apply_to_modules
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.children.rst
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mlx.nn.Module.children
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======================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.children
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.eval.rst
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.eval.rst
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mlx.nn.Module.eval
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==================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.eval
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.filter_and_map.rst
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mlx.nn.Module.filter\_and\_map
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==============================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.filter_and_map
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.freeze.rst
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mlx.nn.Module.freeze
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====================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.freeze
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docs/build/html/_sources/python/nn/_autosummary/mlx.nn.Module.leaf_modules.rst
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mlx.nn.Module.leaf\_modules
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===========================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.leaf_modules
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mlx.nn.Module.load\_weights
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===========================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.load_weights
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mlx.nn.Module.modules
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=====================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.modules
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mlx.nn.Module.named\_modules
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============================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.named_modules
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mlx.nn.Module.parameters
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========================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.parameters
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mlx.nn.Module.save\_weights
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===========================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.save_weights
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mlx.nn.Module.train
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===================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.train
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mlx.nn.Module.trainable\_parameters
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===================================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.trainable_parameters
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mlx.nn.Module.training
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======================
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.. currentmodule:: mlx.nn
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.. autoproperty:: Module.training
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mlx.nn.Module.unfreeze
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======================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.unfreeze
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mlx.nn.Module.update
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====================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.update
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mlx.nn.Module.update\_modules
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=============================
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.. currentmodule:: mlx.nn
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.. automethod:: Module.update_modules
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mlx.nn.SinusoidalPositionalEncoding
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===================================
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.. currentmodule:: mlx.nn
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.. autoclass:: SinusoidalPositionalEncoding
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mlx.nn.Transformer
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==================
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.. currentmodule:: mlx.nn
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.. autoclass:: Transformer
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mlx.nn.losses.hinge\_loss
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=========================
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.. currentmodule:: mlx.nn.losses
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.. autoclass:: hinge_loss
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mlx.nn.losses.huber\_loss
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=========================
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.. currentmodule:: mlx.nn.losses
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.. autoclass:: huber_loss
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mlx.nn.losses.log\_cosh\_loss
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=============================
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.. currentmodule:: mlx.nn.losses
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.. autoclass:: log_cosh_loss
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@@ -9,7 +9,7 @@ Layers
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:toctree: _autosummary
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:template: nn-module-template.rst
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Embedding
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Sequential
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ReLU
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PReLU
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GELU
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@@ -17,13 +17,21 @@ Layers
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Step
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SELU
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Mish
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Embedding
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Linear
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QuantizedLinear
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Conv1d
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Conv2d
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BatchNorm
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LayerNorm
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RMSNorm
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GroupNorm
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RoPE
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InstanceNorm
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Dropout
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Dropout2d
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Dropout3d
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Transformer
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MultiHeadAttention
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Sequential
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QuantizedLinear
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ALiBi
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RoPE
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SinusoidalPositionalEncoding
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@@ -16,4 +16,7 @@ Loss Functions
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mse_loss
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nll_loss
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smooth_l1_loss
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triplet_loss
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triplet_loss
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hinge_loss
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huber_loss
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log_cosh_loss
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Module
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======
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.. currentmodule:: mlx.nn
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.. autoclass:: Module
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.. rubric:: Attributes
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.. autosummary::
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:toctree: _autosummary
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Module.training
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.. rubric:: Methods
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.. autosummary::
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:toctree: _autosummary
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Module.apply
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Module.apply_to_modules
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Module.children
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Module.eval
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Module.filter_and_map
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Module.freeze
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Module.leaf_modules
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Module.load_weights
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Module.modules
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Module.named_modules
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Module.parameters
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Module.save_weights
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Module.train
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Module.trainable_parameters
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Module.unfreeze
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Module.update
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Module.update_modules
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quantize
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quantized_matmul
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reciprocal
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repeat
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reshape
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round
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rsqrt
|
||||
save
|
||||
savez
|
||||
savez_compressed
|
||||
save_safetensors
|
||||
sigmoid
|
||||
sign
|
||||
sin
|
||||
@@ -102,6 +104,7 @@ Operations
|
||||
take_along_axis
|
||||
tan
|
||||
tanh
|
||||
tensordot
|
||||
transpose
|
||||
tri
|
||||
tril
|
||||
|
Reference in New Issue
Block a user