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z$*kl1FhLmKMi^WSlr1*MjPyK6|3rd2DXIKUMG)3XD1ymKdLZGTsXLH>;)FNEJInGP zq4`O^@cfOd1q)~$h%;{ea5N}8UZi|bA=ur|t0=i<2`;*B1=PlL^)h5qMv2`zBA1sggNjB7Bi$$qf=&*LQtyJP zdI04Qz)g dfA|T*g8SwdO#E#5?lgT_Ee*ZR$!dE~{RgSNaK-=t diff --git a/examples/networks/compare.py b/examples/networks/compare.py index 498af3f..9958ec0 100644 --- a/examples/networks/compare.py +++ b/examples/networks/compare.py @@ -59,8 +59,9 @@ def get_optimizers(args): { "learning_rate": get_cosine_schedule(3e-3, 1e-6, n_warmup, decay_steps), "weight_decay": weight_decay, - "learning_rate_1d": get_cosine_schedule(3e-3, 1e-6, n_warmup, decay_steps), - "weight_decay_1d": weight_decay, + "optimize_1d": True, + # "learning_rate_1d": get_cosine_schedule(3e-3, 1e-6, n_warmup, decay_steps), + # "weight_decay_1d": weight_decay, }, ), ] From e1b49cd325ec055a8786dcb01b81866ce3fa2363 Mon Sep 17 00:00:00 2001 From: Jason Stock Date: Thu, 21 Nov 2024 08:42:56 -0700 Subject: [PATCH 2/5] examples: comparison w/ mars optimizing 1d --- examples/networks/compare.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/examples/networks/compare.py b/examples/networks/compare.py index 9958ec0..43d1eb5 100644 --- a/examples/networks/compare.py +++ b/examples/networks/compare.py @@ -60,8 +60,6 @@ def get_optimizers(args): "learning_rate": get_cosine_schedule(3e-3, 1e-6, n_warmup, decay_steps), "weight_decay": weight_decay, "optimize_1d": True, - # "learning_rate_1d": get_cosine_schedule(3e-3, 1e-6, n_warmup, decay_steps), - # "weight_decay_1d": weight_decay, }, ), ] From fa68f8fbc027ce6a3784d990c7404321db89c5d4 Mon Sep 17 00:00:00 2001 From: Jason Stock Date: Fri, 22 Nov 2024 12:13:10 -0700 Subject: [PATCH 3/5] optim: adopt to use clipping (#46) --- CHANGELOG.md | 3 +++ mlx_optimizers/adopt.py | 45 ++++++++++++++++++++++++++--------------- tests/test_basic.py | 2 +- tests/test_neuralnet.py | 1 + 4 files changed, 34 insertions(+), 17 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 28e6c02..abb1a96 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## Unreleased +### Fixed +- optim: ADOPT update to use clipping (arXiv v2) + ## [v0.4.0](https://github.com/stockeh/mlx-optimizers/releases/tag/v0.4.0) - 2024-11-20 ### Added diff --git a/mlx_optimizers/adopt.py b/mlx_optimizers/adopt.py index 1117be6..f1d6fbe 100644 --- a/mlx_optimizers/adopt.py +++ b/mlx_optimizers/adopt.py @@ -1,4 +1,4 @@ -from typing import Callable, List, Union +from typing import Callable, List, Optional, Union import mlx.core as mx from mlx.optimizers import Optimizer @@ -9,10 +9,10 @@ class ADOPT(Optimizer): .. math:: - v_0 &= g_0^2, m_1 = g_1 / \max{\sqrt{v_0}, \epsilon} \\ - \theta_{t} &= \theta_{t-1} - \eta m_{t-1} \\ + m_0 &= \mathbf{0}, \quad v_0 = g_0^2 \\ + m_t &= \beta_1 m_{t-1} + (1 - \beta_1) \text{clip} \left( \frac{g_t}{\text{max}(\sqrt{v_{t-1}, \epsilon})}, c_t\right) \\ + \theta_{t} &= \theta_{t-1} - \eta m_t \\ v_{t} &= \beta_2 v_{t-1} + (1 - \beta_2) g_t^2 - m_{t+1} &= \beta_1 m_{t} + (1 - \beta_1) (g_{t+1} / \max{\sqrt{v_t}, \epsilon}) [1] Taniguchi, Shohei, et al., 2024. ADOPT: Modified Adam Can Converge with Any :math:`\beta_2` with the Optimal Rate. NeurIPS 2024. @@ -25,6 +25,9 @@ class ADOPT(Optimizer): :math:`(\beta_1, \beta_2)` used for computing running averages of the gradient and its square. Default: ``(0.9, 0.9999)`` weight_decay (float, optional): The weight decay. Default: ``0.0`` + decouple (bool, optional): AdamW if ``True``. Default: ``False`` + clip_lambda (callable, optional): The clipping function :math:`c_t` for the + gradient. Set to ``None`` for previous behavior. Default: ``step**0.25`` eps (float, optional): The term :math:`\epsilon` added to the denominator to improve numerical stability. Default: ``1e-6`` @@ -36,6 +39,8 @@ def __init__( learning_rate: Union[float, Callable[[mx.array], mx.array]], betas: List[float] = [0.9, 0.9999], weight_decay: float = 0.0, + decouple: bool = False, + clip_lambda: Optional[Callable[[mx.array], mx.array]] = lambda step: mx.power(step, 0.25), eps: float = 1e-6, ): super().__init__() @@ -43,37 +48,45 @@ def __init__( self._maybe_schedule("learning_rate", learning_rate) self.betas = betas self.weight_decay = weight_decay + self.decouple = decouple + self.clip_lambda = clip_lambda self.eps = eps def init_single(self, parameter: mx.array, state: dict): """Initialize optimizer state""" - state["m"] = [] + state["m"] = mx.zeros_like(parameter) state["c"] = 0 def apply_single(self, gradient: mx.array, parameter: mx.array, state: dict): """Performs a single optimization step, updating :math:`m` and :math:`v`""" - state["c"] += 1 - if self.weight_decay != 0: - gradient = gradient + self.weight_decay * parameter + weight_decay = self.weight_decay + decouple = self.decouple - if state["c"] == 1: + if weight_decay != 0 and not decouple: + gradient = gradient + weight_decay * parameter + + if state["c"] == 0: state["v"] = mx.square(gradient) + state["c"] += 1 return parameter lr = self.learning_rate.astype(gradient.dtype) + + if weight_decay != 0 and decouple: + parameter = parameter - lr * weight_decay * parameter + b1, b2 = self.betas - eps = self.eps m = state["m"] v = state["v"] - denom = mx.maximum(mx.sqrt(v), eps) - - if state["c"] == 2: - m = gradient / denom - else: - m = b1 * m + (1 - b1) * gradient / denom + denom = mx.maximum(mx.sqrt(v), self.eps) + normed_grad = gradient / denom + if self.clip_lambda is not None: + clip = self.clip_lambda(self.step - 1) + normed_grad = mx.clip(normed_grad, -clip, clip) + m = b1 * m + (1 - b1) * normed_grad parameter = parameter - lr * m state["v"] = b2 * v + (1 - b2) * mx.square(gradient) diff --git a/tests/test_basic.py b/tests/test_basic.py index 0d2049b..01b1fe0 100644 --- a/tests/test_basic.py +++ b/tests/test_basic.py @@ -36,7 +36,7 @@ def beale(xy): (optim.QHAdam, {"learning_rate": 0.25}, 150), (optim.DiffGrad, {"learning_rate": 0.3}, 150), (optim.MADGRAD, {"learning_rate": 0.03}, 150), - (optim.ADOPT, {"learning_rate": 0.17}, 150), + (optim.ADOPT, {"learning_rate": 0.5}, 250), ( optim.Muon, # using alternate for ndim < 2 { diff --git a/tests/test_neuralnet.py b/tests/test_neuralnet.py index e3ab01d..a2e6e34 100644 --- a/tests/test_neuralnet.py +++ b/tests/test_neuralnet.py @@ -49,6 +49,7 @@ def generate_moons(n_samples: int = 100, noise: float = 0.2): ), (optim.MADGRAD, {"learning_rate": 0.01}, 50), (optim.ADOPT, {"learning_rate": 0.03}, 50), + (optim.ADOPT, {"learning_rate": 0.03, "clip_lambda": None}, 50), (optim.Lamb, {"learning_rate": 0.03}, 50), (optim.Shampoo, {"learning_rate": 0.03}, 50), (optim.Kron, {"learning_rate": 0.03}, 50), From 532473a984e8072f72210cc8f2d561b4c215cb91 Mon Sep 17 00:00:00 2001 From: Jason Stock Date: Fri, 22 Nov 2024 12:19:20 -0700 Subject: [PATCH 4/5] examples: rosenbrock run with adopt --- docs/src/_static/media/rosenbrock_ADOPT.png | Bin 841011 -> 844749 bytes examples/rosenbrock.py | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/_static/media/rosenbrock_ADOPT.png b/docs/src/_static/media/rosenbrock_ADOPT.png index c1380c0cf2b9f2fab265d76020ff6d7c14717adf..e84bd5974b477f9fe8842b031b1b4a54ffd97422 100644 GIT binary patch literal 844749 zcmeEug;$jO_BZM=umLFnIdlpF(q+&oA+1O^NauhGB8`;f&?zmQqok734bt5)Fx0!} zoL{c@FL>8_?^@S;C1&RNK6`)mC-$TN3kAtr*Y97)!NIvDEhVOmgLAna2j|l9wJY$I z$k#DQ_#b`;aSaC*8)FA&Jv$>Dc|C`>mNpKSX8M0S8QIyJ*;sS2@w0KV{%z{u@YY^{ zo!#ocet^x!&V-#x;nE1a2<}@cO?w<1HX7`IFSulgI^kTv!I2hws_K%kHsPqDs!jZT zdg?co-}Q2RXJ=*p9ozug`j7wXbs7Kvi~K)%CQB|`e=Zms8)vIBt1=VP$wVH`^LKT1O}BnJ zwRdvjIe7!O+0X0f_&7oYf!RW*q)SK4Y-~IjYQ%qb4ezSlj2jNNbfhX@*SR$}e!Anj zze1>s@}&FwZyZ@!*>GCvXDvabzv6k>4-O7&h2>HtHz(_GuV2585_UgW<0J1(Vq#?U z%T+Jj*_wVX;&mqX;>F$a@^ZtjgxFN^z?naP?hZWLP@WX(>gqzm!rQyMjV&!#1O)}Z8UA|q{^I4LZ{IjI z&g<*zb*k(>wuVy9PEWtr%BQ!TX)^4Li_&in2;;NW_uhXfrc+W>^rpcF*I{iK59iLE zJHB@)yS~26opCXQi`0*o$ydvrb;Fi@lb1idfJ&xZWo4yl85t?*HfGtnhPl33K)?msqtQscD#Gmd-JW`BKV278KW9Bg)o^MFk-S0*_Hg=3<#Z;??ukyfcGo@Wi*nzfOV#pp$TK|z&b zeewKql`I9NlxLSeO2!lkd!EF^a+!QX96Qz4)$Kn>Q_f*j$-H@r*-ukSlPDHyh*8QN zP|ec_>&sGH9apdSIGTD*ahIID!}k`MMzQ|op@LU5w6tQIwh|H&k!-KxChOe$(xnNS z&k{vF4!@6g+m_*2kdDW7#PSzGCs{xK$=e0@_+gAB_L>eWgxdBjyv%57(KhW zS%@YfARzdvmfx2A)H_?J>KpZGz+u+2kJsJK2P5wepoZXlN<2^9#4&lV>jXaCp$ysC zPDx3bYmW{+MsHq<8|r9}W>+aSRT6Ij)SD4~_7Gst&y?S3E$063W1F41Ujh5GOG_kr zqCKaJOH0`g_}(UCT7t;}f;UY}x)WbUvubj-7(C|WROYo9l!If(pXI3aI8qL4WqIy< zb7iE&B-i`HhrNTe{!Kc1l;rap*RH)V`T6;2?o_sjjRI02gKGg!melDxu9TFNpWDgd zwz-N*pQ$iAvubv-Cwk+R&YknFyWUgA72d^fNhT%EhLh^1e(J!`+86_R8J- z{Q2(whs!tm{qgAnwpTmDXe2!?Zl0Z;tvnER%YMoHvJ_+8o9;i_-o9FaA=*|s+L^y~ z@LDzH*+<6Ulvg!Q0sESDZu_R9SK@hXLV7Bpe`(2;XR(0pmkEU_=`t0^ZSkVDv01h7 zb)Ejkc-1{-Rlnh={1>ss(4rMoS!@nj9ajM>4+*P)rhO z&bHY$VFpalxkDur_t@;&LPu<)4IqL2-ck=Ac^H(#Fg-VRborSc?#$n)ao!BsIwNL( zz4Q>B9C>oIyK037^k{Ftp{S^M@#015U|Ya^XBh6lp_7+T-@Ar z>IFJI0TBX@E2b2buRJ|HrF4Uo`_4}x7W9@2n-Co zAsPB$fJqNfMH|kzWq)-DKB2VbEkT)Q&z~>k;zE)INHIU ztHW|{igJz%oI9Z9;@qzYtwO;E4<10lAOWk*>3*fA0?417qNm)B3w5eE=i8zhdwTF# zSXcn6u>%Eqa{+2ZU~zA`?<)KUDvoIWY`~nmGoE*`BbG}5ogp3JtCp`7#%-Yn2i^sYtg28YkRw=Dmha*XQ@9&C1|F3 z4#6(xaL)5oMcH)g&kwlCG__XnCtSos2?IdtZOVJCTwU1veI9xF2GJ5L>eSWDHCHYF z-m zZKnaEjZk|Ii424+YC$_kqR|5WfoNeH8yn=}@vjI50|Yq?z8T+th@YS7&m>XQV02cV zX31AFZu9g3WB6nTdwVDA_4;v#XCr_;{WOvxK}BblT?zbYQKm3OR(}6};W$z4xZeV! z(jNm@-4lR5+%|Ch@!|4*3tX&1B zw?`97dkp2MNHQoS3c299ID2IAKIjm71v_cj1@|4)*thdyk;$RL4d} zmYXzSltgx&?=44+4i2gJl6iR2BRROB_-~PdYm+7yvfyq$J>04>H_2(&EIlkvuM@P_LzIN-h-`Pzv zUhDp^Ik!JEC_czkOgd|~=Q8g22?y&i%Ak;t-M{52Yih~}<<;8V&0gF2>z6;Ez`4`f zScOfA*STjtkBW-Q+1as8IK4ckeb>s;a=6x&YjAK-YrQX1zHw^mJbDo-4ExT=1EcmY zdS+%v?YkH3=6?QI>Pd4Pg}Nil*d=Dw_zuWdHVW`0ktBlfbhYkD6(<#R%2U$@A_%V( zs60hIEr`IBc0C{l@JaznV*5BX=D6x{yXg4|K_OZUdOU?(+T#Yu6Q#Y~%rDGQ0X$Zt zFG`H%kzxvlWN%ucfcw}V?HILvd6;WIRgX9xu6DGDobfn044ZEJv|6hERn^~dbx_an zUP&mibOinUaIrzURM@jzVPK{J-OY@~a(sMzj~td>AP?*pyGYX|Y(0vNJMZU@y@X$N zE=wgyg*miRDj)NRs;%sccA2?2oObCb5Q1hH2ZW?kn=!)f#yT}T0| zU@~5Mo5@60U0f~It#`^_3H2IAXs~+W>*oF6Gu-U#>`rULDSZ$6#52oAg~ho1VWb|UtX@E<; zMS9Pn(PWwf2$x68SO6AGV8&r@FSbEPHKH8me&Qj^G5f0q`uh0!d>A%masda%mRZaz zDk`c{i=mKr@7`^d1AmR+vC?YB{8m59HvARd6QYv+f(oW@8Man4UM7lDBDi+a1Z2-m zMA4K{q-8M02h9S1HGe%k82A4Q6w$Qq^~p)%^xB#nd`hWUPC96u46pOE=|bYpIBpss z$#Y%Ec=>o9=^d3&)cKkAqD}JK>4u)yJ$I8}UQ4c)11lkB)A38|!P3!(|9S?ge->%W zqoShJ8j_#9zbLR@!fQ2}9(CxixH42&$g6ak8yh0%ywNl^rk&e4JRAeFmRX=4xbRXb zQphzN0EA^!(GZ_OA+K*?d70GWv^CS~>_~FesX(XdUQXjl&4&*kmL_U=p-GJaceW2U znKHW)g>(DVfO(s?O2cIU!uFWgfU-!4T8QPhr-wqgg?d$GXH@O5oT}mB<>iHZ$-u+I z!@=BX0N}6EH#IetBpb~p?v|LAmezGSj@M>Vtj0@JRCIh|qHHwP4o@j(QDM5_qoaBF zYT&6Z-rc)TU>;;^6jK9_q!zCu6DW8aGK!dsQ zJ`r@=%kJu!qCBmQC4U0}8RoxiOrg3Dw`Ut|pfy+X z#ZLu+{-*XBTUe0Ix?s)<_D`)nBVq9FEOr+TIL)^a))@qL^rT5T%E-Me(Bbd3-#fLI zmzM{kBUOsIEm&yUld1*1X$`blTu@DC7mdy`?u>I&rxRa*QE{^AbsngkQz-faO5HK> zTun`_)U<~>L?Zp>jT<+RLqq2cD^~#fQIhymSY6HzghYa2JF~D<8c3dlxlZel9YeBc z)y(W{T7}OO5)%^>WI3==W`5QuTsKNU`wOgtAXTnqM}SPuaK4i4?fpD&k22nRvNne+ zP?R3`aYitO;1|U4!N)0uxW`QST4fC|4WYQ>L8ox(HT(sdHic{V0EInCP!gtPv2k%T zpfb~3Fvhs82Unth{P+PqsIWRS0zL36h9fQY^hD@6>7kKX_|K(y(sLN!x`{(2CW`rE zPoF*wBI9LiJH7JPUrXdR`ueHP&F!HeeYVi(A#
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zz=Yj%73ixd)Nd5pteDucK01$8=V^&ZSEg5XK0E8#7btuIYy^r}QT>snwaiXTAMj~ML zEAf(b8{Y+WqDgja{9*}|qN9{GXE z<*}S7uvR;ila)0+-kwrA{Cj!h?f>7~l@mxo2Y|RFVh*#H9|nJ^orHimRXeGzNl!FO zhnPgv?TY#a(kasamC!)g1_NrL63;USAhLEZu4rg!hk%m@hj{WSH%Cg z?f%C_`+qz1w~_y=Zl3=aU4sAruK4mM|DWuYGoQZG>(jbl-A5?kM@mfYU4e+f=l=(T C?KiLh diff --git a/examples/rosenbrock.py b/examples/rosenbrock.py index 1023de9..ef14fb9 100644 --- a/examples/rosenbrock.py +++ b/examples/rosenbrock.py @@ -117,7 +117,7 @@ def execute_experiments(optimizers, objective, func, plot_func, initial_state): (optim.QHAdam, 0, 0.5, {}), (optim.DiffGrad, 0, 0.5, {}), (optim.MADGRAD, 0, 0.5, {}), - (optim.ADOPT, 0, 0.25, {}), + (optim.ADOPT, 0, 0.5, {}), (optim.Lamb, 0, 0.25, {}), (optim.Muon, 0, 0.2, {"alternate_optimizer": AdamW(learning_rate=0.0842)}), # fixed lr (optim.Shampoo, 0, 2, {}), From c92923fa6c7f9943ab0ae65cae25249ef7f37ef8 Mon Sep 17 00:00:00 2001 From: Jason Stock Date: Fri, 22 Nov 2024 12:21:52 -0700 Subject: [PATCH 5/5] Bump version to v0.4.1 for release --- CHANGELOG.md | 2 ++ mlx_optimizers/version.py | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index abb1a96..0d27a2f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,6 +7,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## Unreleased +## [v0.4.1](https://github.com/stockeh/mlx-optimizers/releases/tag/v0.4.1) - 2024-11-22 + ### Fixed - optim: ADOPT update to use clipping (arXiv v2) diff --git a/mlx_optimizers/version.py b/mlx_optimizers/version.py index eca97dc..008b370 100644 --- a/mlx_optimizers/version.py +++ b/mlx_optimizers/version.py @@ -2,7 +2,7 @@ _MINOR = "4" # On main and in a nightly release the patch should be one ahead of the last # released build. -_PATCH = "0" +_PATCH = "1" # This is mainly for nightly builds which have the suffix ".dev$DATE". See # https://semver.org/#is-v123-a-semantic-version for the semantics. _SUFFIX = ""

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