docs/build/doctrees/python/_autosummary/mlx.optimizers.Adamax.doctree

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descclassname<6D>eh%]<5D>h']<5D>h)]<5D>hjhkuh+hmhhEhhhhlhNubh<00>	desc_name<6D><65><EFBFBD>)<29><>}<7D>(h<05>Adamax<61>h]<5D>h<16>Adamax<61><78><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>(<28>sig-name<6D><65>descname<6D>eh%]<5D>h']<5D>h)]<5D>hjhkuh+hhhEhhhhlhNubh<00>desc_parameterlist<73><74><EFBFBD>)<29><>}<7D>(h<05>Slearning_rate: float, betas: ~typing.List[float] = [0.9, 0.999], eps: float = 1e-08<30>h]<5D>(h<00>desc_parameter<65><72><EFBFBD>)<29><>}<7D>(h<05>learning_rate: floatfloat<61>h]<5D>(h<00>
desc_sig_name<6D><65><EFBFBD>)<29><>}<7D>(h<05>
learning_rate<74>h]<5D>h<16>
learning_rate<74><65><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D><>n<>ah%]<5D>h']<5D>h)]<5D>uh+h<>hh<>ubh<00>desc_sig_punctuation<6F><6E><EFBFBD>)<29><>}<7D>(h<05>:<3A>h]<5D>h<16>:<3A><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D><>p<>ah%]<5D>h']<5D>h)]<5D>uh+h<>hh<>ubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShh<>ubh<62>)<29><>}<7D>(h<05>
floatfloat<EFBFBD>h]<5D>h<00>pending_xref<65><66><EFBFBD>)<29><>}<7D>(hhh]<5D>(h<00>pending_xref_condition<6F><6E><EFBFBD>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F><6E>resolved<65>uh+h<>hh<>ubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hh<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F><6E>*<2A>uh+h<>hh<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69><6E>py<70><79>reftype<70><65>class<73><73>	reftarget<65><74>float<61><74>refspecific<69><63><EFBFBD>	py:module<6C><65>mlx.optimizers<72><73>py:class<73>Nuh+h<>hh<>ubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hh<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>hjhkuh+h<>hh<>ubh<62>)<29><>}<7D>(h<05>*betas: ListList[floatfloat] = [0.9, 0.999]<5D>h]<5D>(h<>)<29><>}<7D>(h<05>betas<61>h]<5D>h<16>betas<61><73><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hjubh<62>)<29><>}<7D>(h<05>:<3A>h]<5D>h<16>:<3A><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj&hhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hjubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj4hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShjubh<62>)<29><>}<7D>(h<05>ListList[floatfloat]<5D>h]<5D>(h<>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>List<73>h]<5D>h<16>List<73><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjIhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjFubh<62>)<29><>}<7D>(h<05>List<73>h]<5D>h<16>List<73><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjXhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjFubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>h<EFBFBD><68>reftype<70><65>obj<62><6A>	reftarget<65><74>typing.List<73><74>refspecific<69><63><EFBFBD>	py:module<6C>j<00>py:class<73>Nuh+h<>hjBubh<62>)<29><>}<7D>(h<05>[<5B>h]<5D>h<16>[<5B><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjuhhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hjBubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>h<EFBFBD><68>reftype<70>j<00>	reftarget<65><74>float<61><74>refspecific<69><63><EFBFBD>	py:module<6C>j<00>py:class<73>Nuh+h<>hjBubh<62>)<29><>}<7D>(h<05>]<5D>h]<5D>h<16>]<5D><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hjBubeh}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hjubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShjubh<00>desc_sig_operator<6F><72><EFBFBD>)<29><>}<7D>(h<05>=<3D>h]<5D>h<16>=<3D><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D><>o<>ah%]<5D>h']<5D>h)]<5D>uh+j<>hjubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShjubh	<09>inline<6E><65><EFBFBD>)<29><>}<7D>(h<05>[0.9, 0.999]<5D>h]<5D>h<16>[0.9, 0.999]<5D><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D><>
default_value<75>ah%]<5D>h']<5D>h)]<5D><>support_smartquotes<65><73>uh+j<>hjubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>hjhkuh+h<>hh<>ubh<62>)<29><>}<7D>(h<05>eps: floatfloat = 1e-08<30>h]<5D>(h<>)<29><>}<7D>(h<05>eps<70>h]<5D>h<16>eps<70><73><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hj
ubh<62>)<29><>}<7D>(h<05>:<3A>h]<5D>h<16>:<3A><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hj
ubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj*hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShj
ubh<62>)<29><>}<7D>(h<05>
floatfloat<EFBFBD>h]<5D>h<EFBFBD>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj?hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<ubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjNhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>h<EFBFBD><68>reftype<70>j<00>	reftarget<65><74>float<61><74>refspecific<69><63><EFBFBD>	py:module<6C>j<00>py:class<73>Nuh+h<>hj8ubah}<7D>(h!]<5D>h#]<5D>h<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+h<>hj
ubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjphhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShj
ubj<62>)<29><>}<7D>(h<05>=<3D>h]<5D>h<16>=<3D><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj~hhhNhNubah}<7D>(h!]<5D>h#]<5D>j<EFBFBD>ah%]<5D>h']<5D>h)]<5D>uh+j<>hj
ubhT)<29><>}<7D>(h<05> <20>h]<5D>h<16> <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h`ah%]<5D>h']<5D>h)]<5D>uh+hShj
ubj<62>)<29><>}<7D>(h<05>1e-08<30>h]<5D>h<16>1e-08<30><38><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>j<EFBFBD>ah%]<5D>h']<5D>h)]<5D><>support_smartquotes<65><73>uh+j<>hj
ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>hjhkuh+h<>hh<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>hjhkuh+h<>hhEhhhhlhNubeh}<7D>(h!]<5D>h<ah#]<5D>(<28>sig<69><67>
sig-object<63>eh%]<5D>h']<5D>h)]<5D><>module<6C><65>mlx.optimizers<72>jh<06>fullname<6D>h<EFBFBD>uh+hChhlhKhh@hhubh<00>desc_content<6E><74><EFBFBD>)<29><>}<7D>(hhh]<5D>(h	<09>	paragraph<70><68><EFBFBD>)<29><>}<7D>(h<05>_Implementation of the Adamax optimizer. It is a variant of Adam based
on the infinity norm [1].<2E>h]<5D>h<16>_Implementation of the Adamax optimizer. It is a variant of Adam based
on the infinity norm [1].<2E><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>h<1D>W/Users/awnihannun/repos/mlx/python/mlx/optimizers.py:docstring of mlx.optimizers.Adamax<61>hKhj<>hhubj<62>)<29><>}<7D>(h<05><>Our Adam implementation follows the original paper and omits the bias
correction in the first and second moment estimates. In detail,<2C>h]<5D>h<16><>Our Adam implementation follows the original paper and omits the bias
correction in the first and second moment estimates. In detail,<2C><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj<>hKhj<>hhubj<62>)<29><>}<7D>(h<05>Z[1]: Kingma, D.P. and Ba, J., 2015. Adam: A method for stochastic
optimization. ICLR 2015.<2E>h]<5D>h<16>Z[1]: Kingma, D.P. and Ba, J., 2015. Adam: A method for stochastic
optimization. ICLR 2015.<2E><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj<>hKhj<>hhubh	<09>
math_block<EFBFBD><EFBFBD><EFBFBD>)<29><>}<7D>(h<05><>m_{t+1} &= \beta_1 m_t + (1 - \beta_1) g_t \\
v_{t+1} &= \max(\beta_2 v_t, |g_t|) \\
w_{t+1} &= w_t - \lambda \frac{m_{t+1}}{v_{t+1} + \epsilon}<7D>h]<5D>h<16><>m_{t+1} &= \beta_1 m_t + (1 - \beta_1) g_t \\
v_{t+1} &= \max(\beta_2 v_t, |g_t|) \\
w_{t+1} &= w_t - \lambda \frac{m_{t+1}}{v_{t+1} + \epsilon}<7D><><EFBFBD><EFBFBD><EFBFBD>}<7D>hj<>sbah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>docname<6D><65>)python/_autosummary/mlx.optimizers.Adamax<61><78>number<65>N<EFBFBD>label<65>N<EFBFBD>nowrap<61><70>hjhkuh+j<>hj<>hK
hj<>hhubh	<09>
field_list<EFBFBD><EFBFBD><EFBFBD>)<29><>}<7D>(hhh]<5D>h	<09>field<6C><64><EFBFBD>)<29><>}<7D>(hhh]<5D>(h	<09>
field_name<EFBFBD><EFBFBD><EFBFBD>)<29><>}<7D>(h<05>
Parameters<EFBFBD>h]<5D>h<16>
Parameters<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jhjhhlhKubh	<09>
field_body<EFBFBD><EFBFBD><EFBFBD>)<29><>}<7D>(hhh]<5D>h	<09>bullet_list<73><74><EFBFBD>)<29><>}<7D>(hhh]<5D>(h	<09>	list_item<65><6D><EFBFBD>)<29><>}<7D>(hhh]<5D>j<EFBFBD>)<29><>}<7D>(h<05>8learning_rate (floatfloat) -- The learning rate \lambda.<2E>h]<5D>(h<00>literal_strong<6E><67><EFBFBD>)<29><>}<7D>(h<05>
learning_rate<74>h]<5D>h<16>
learning_rate<74><65><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj6hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j4hj0ubh<16> (<28><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj0hhhNhNubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>h<00>literal_emphasis<69><73><EFBFBD>)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjQhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhjKubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjHubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhjfubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjHubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69><6E>py<70><79>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>jl<00>refspecific<69><63><EFBFBD>	py:module<6C>j<EFBFBD><00>py:class<73>h<EFBFBD>uh+h<>hj0ubh<16>)<29><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj0hhhNhNubh<16> – <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj0hhhNhNubh<16>The learning rate <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj0hhhNhNubh	<09>math<74><68><EFBFBD>)<29><>}<7D>(h<05>:math:`\lambda`<60>h]<5D>h<16>\lambda<64><61><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj0hhhNhNubh<16>.<2E><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj0hhhNhNubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj-ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j+hj(ubj,)<29><>}<7D>(hhh]<5D>j<EFBFBD>)<29><>}<7D>(h<05><>betas (TupleTuple[floatfloat, floatfloat], optionaloptional) -- The coefficients
(\beta_1, \beta_2) used for computing running averages of the
gradient and its square. Default: (0.9, 0.999)<29>h]<5D>(j5)<29><>}<7D>(h<05>betas<61>h]<5D>h<16>betas<61><73><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j4hj<>ubh<16> (<28><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>Tuple<6C>h]<5D>jP)<29><>}<7D>(h<05>Tuple<6C>h]<5D>h<16>Tuple<6C><65><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubh<62>)<29><>}<7D>(h<05>Tuple<6C>h]<5D>jP)<29><>}<7D>(h<05>Tuple<6C>h]<5D>h<16>Tuple<6C><65><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>j<EFBFBD>j<><00>j<EFBFBD>j<>j<>h<>uh+h<>hj<>ubjP)<29><>}<7D>(h<05>[<5B>h]<5D>h<16>[<5B><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj&hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj"ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj?hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj;ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>jAj<><00>j<EFBFBD>j<>j<>h<>uh+h<>hj<>ubjP)<29><>}<7D>(h<05>, <20>h]<5D>h<16>, <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj^hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjshhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhjoubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjlubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjlubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>j<EFBFBD>j<><00>j<EFBFBD>j<>j<>h<>uh+h<>hj<>ubjP)<29><>}<7D>(h<05>]<5D>h]<5D>h<16>]<5D><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubjP)<29><>}<7D>(h<05>, <20>h]<5D>h<16>, <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>optional<61>h]<5D>jP)<29><>}<7D>(h<05>optional<61>h]<5D>h<16>optional<61><6C><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubh<62>)<29><>}<7D>(h<05>optional<61>h]<5D>jP)<29><>}<7D>(h<05>optional<61>h]<5D>h<16>optional<61><6C><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>j<EFBFBD>j<><00>j<EFBFBD>j<>j<>h<>uh+h<>hj<>ubh<16>)<29><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubh<16> – <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubh<16>The coefficients
<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubj<62>)<29><>}<7D>(h<05>:math:`(\beta_1, \beta_2)`<60>h]<5D>h<16>(\beta_1, \beta_2)<29><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj<>hhhNhNubh<16>N used for computing running averages of the
gradient and its square. Default: <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubh	<09>literal<61><6C><EFBFBD>)<29><>}<7D>(h<05>``(0.9, 0.999)``<60>h]<5D>h<16>(0.9, 0.999)<29><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj&hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j$hj<>hhhNhNubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j+hj(ubj,)<29><>}<7D>(hhh]<5D>j<EFBFBD>)<29><>}<7D>(h<05>~eps (floatfloat, optionaloptional) -- The term \epsilon added to the
denominator to improve numerical stability. Default: 1e-8<>h]<5D>(j5)<29><>}<7D>(h<05>eps<70>h]<5D>h<16>eps<70><73><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjGhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j4hjCubh<16> (<28><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjChhhNhNubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj`hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj\ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjYubh<62>)<29><>}<7D>(h<05>float<61>h]<5D>jP)<29><>}<7D>(h<05>float<61>h]<5D>h<16>float<61><74><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjyhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhjuubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hjYubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>j{j<><00>j<EFBFBD>j<>j<>h<>uh+h<>hjCubjP)<29><>}<7D>(h<05>, <20>h]<5D>h<16>, <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhjCubh<62>)<29><>}<7D>(hhh]<5D>(h<>)<29><>}<7D>(h<05>optional<61>h]<5D>jP)<29><>}<7D>(h<05>optional<61>h]<5D>h<16>optional<61><6C><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubh<62>)<29><>}<7D>(h<05>optional<61>h]<5D>jP)<29><>}<7D>(h<05>optional<61>h]<5D>h<16>optional<61><6C><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jOhj<>ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	condition<6F>h<EFBFBD>uh+h<>hj<>ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>	refdomain<69>j<EFBFBD><00>refexplicit<69><74><EFBFBD>reftype<70>j<00>	reftarget<65>j<EFBFBD>j<><00>j<EFBFBD>j<>j<>h<>uh+h<>hjCubh<16>)<29><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjChhhNhNubh<16> – <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjChhhNhNubh<16>	The term <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjChhhNhNubj<62>)<29><>}<7D>(h<05>:math:`\epsilon`<60>h]<5D>h<16>\epsilon<6F><6E><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj<>hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hjChhhNhNubh<16>C added to the
denominator to improve numerical stability. Default: <20><><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjChhhNhNubj%)<29><>}<7D>(h<05>``1e-8``<60>h]<5D>h<16>1e-8<><38><EFBFBD><EFBFBD><EFBFBD>}<7D>(hjhhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j$hjChhhNhNubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j<>hj@ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j+hj(ubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j&hj#ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j!hjubeh}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jhj	ubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+jhj<>hhhNhNubh	<09>rubric<69><63><EFBFBD>)<29><>}<7D>(h<05>Methods<64>h]<5D>h<16>Methods<64><73><EFBFBD><EFBFBD><EFBFBD>}<7D>(hj7hhhNhNubah}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D>uh+j5hj<>hhhh,hKubh<00>tabular_col_spec<65><63><EFBFBD>)<29><>}<7D>(hhh]<5D>h}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>spec<65><63>\X{1}{2}\X{1}{2}<7D>uh+jEhj<>hhh<1D>c/Users/awnihannun/repos/mlx/docs/src/python/_autosummary/mlx.optimizers.Adamax.rst:16:<autosummary><3E>hNub<75>sphinx.ext.autosummary<72><79>autosummary_table<6C><65><EFBFBD>)<29><>}<7D>(h<05><>


__init__(learning_rate[, betas, eps])


apply_single(gradient, parameter, state)

Performs the Adamax parameter update and stores v and m in the optimizer state.<2E>h]<5D>h	<09>table<6C><65><EFBFBD>)<29><>}<7D>(hhh]<5D>h	<09>tgroup<75><70><EFBFBD>)<29><>}<7D>(hhh]<5D>(h	<09>colspec<65><63><EFBFBD>)<29><>}<7D>(hhh]<5D>h}<7D>(h!]<5D>h#]<5D>h%]<5D>h']<5D>h)]<5D><>colwidth<74>K
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