jn& ddlZddlmZmZddlmZddlmZmZm Z m Z ddl m Z ddlmZdZdZdZd Zd e jd e fd Z dd e jd e dedefdZdd e jd e defdZdd e jd e defdZGddeZdS)N)partialreduce)product)CallableLiteralTupleUnion)Modulec<t||z}|r-tj|tj|dz |dz z z}n>") $ $ , ,U 3 33r"cjt|||||}tj|d|dz }tj|}tj|}||z }tj|d}|tjd|z f|tj|ffS)Nrra_mina_maxr)r!rclipfloorceil expand_dimsr%r&) rrrrrr indices_l indices_rweights r _linear_indicesr3(sa sEBBGggQa!e444G!!I  I y F ^FB ' 'F   ") $ $a&j1   ") $ $f- r"cNt|||||}tj|}tj|dz}|dz }|dz} ttjdd} | ||dd} | ||dd} | ||dd} | || dd}tj|d|dz }tj|d|dz }tj|d|dz }tj| d|dz } |tj| f|tj| f|tj| f| tj|ffS) NrT) shapelesscd}tj||z }|dkr|dz|z|dzz |z|zdz}n|dz |zdz|zdz |z}|S)Ngrg@g@)rabs)indgriddistaxr2s r _get_weightz#_cubic_indices.._get_weight=sq  F3:   1993w!mq3w/14q81z_interpolate..s*;;62rrBw;;;;;;r") rNrOrPrrYrZr[rrXroperatormulsum)r?rKrdrr\r^rr_rr`rarbsamplesweights idx_weightidxr2s r _interpolaterszs3 6A:D s<    RSSSwHA1Gs1l3344AA 6Aqzz!Q q$??@@@@GGw'55 :& Vq%++#-.///vhlF334444 ;;S'%:%:;;; ; ;;r"c2t||t|SN)r?rKrdr)rsr3r?rKrs r upsample_linearrws%  !"#    r"c2t||t|Sru)rsrJrvs r upsample_cubicrys%  !!#    r"ceZdZdZ d deeefdeddeffd Z d e fd Z d e j d e j fd ZxZS)Upsamplea Upsample the input signal spatially. The spatial dimensions are by convention dimensions ``1`` to ``x.ndim - 2``. The first is the batch dimension and the last is the feature dimension. For example, an audio signal would be 3D with 1 spatial dimension, an image 4D with 2 and so on and so forth. There are three upsampling algorithms implemented nearest neighbor upsampling, linear interpolation, and cubic interpolation. All can be applied to any number of spatial dimensions. The linear interpolation will be bilinear, trilinear etc when applied to more than one spatial dimension. And cubic interpolation will be bicubic when there are 2 spatial dimensions. .. note:: When using one of the linear or cubic interpolation modes the ``align_corners`` argument changes how the corners are treated in the input image. If ``align_corners=True`` then the top and left edge of the input and output will be matching as will the bottom right edge. Parameters: scale_factor (float or tuple): The multiplier for the spatial size. If a ``float`` is provided, it is the multiplier for all spatial dimensions. Otherwise, the number of scale factors provided must match the number of spatial dimensions. mode (str, optional): The upsampling algorithm, either ``"nearest"``, ``"linear"`` or ``"cubic"``. Default: ``"nearest"``. align_corners (bool, optional): Changes the way the corners are treated during ``"linear"`` and ``"cubic"`` upsampling. See the note above and the examples below for more details. Default: ``False``. Examples: >>> import mlx.core as mx >>> import mlx.nn as nn >>> x = mx.arange(1, 5).reshape((1, 2, 2, 1)) >>> x array([[[[1], [2]], [[3], [4]]]], dtype=int32) >>> n = nn.Upsample(scale_factor=2, mode='nearest') >>> n(x).squeeze() array([[1, 1, 2, 2], [1, 1, 2, 2], [3, 3, 4, 4], [3, 3, 4, 4]], dtype=int32) >>> b = nn.Upsample(scale_factor=2, mode='linear') >>> b(x).squeeze() array([[1, 1.25, 1.75, 2], [1.5, 1.75, 2.25, 2.5], [2.5, 2.75, 3.25, 3.5], [3, 3.25, 3.75, 4]], dtype=float32) >>> b = nn.Upsample(scale_factor=2, mode='linear', align_corners=True) >>> b(x).squeeze() array([[1, 1.33333, 1.66667, 2], [1.66667, 2, 2.33333, 2.66667], [2.33333, 2.66667, 3, 3.33333], [3, 3.33333, 3.66667, 4]], dtype=float32) nearestFrKmoder|linearcubicrc@t|dvrtd|t|tt fr(t t t||_nt||_||_ ||_ dS)Nr~z1[Upsample] Got unsupported upsampling algorithm: ) super__init__rP isinstancerSrQrRfloatrKr}r)selfrKr}r __class__s r rzUpsample.__init__s  5 5 5WQUWWXX X lT5M 2 2 4 %c%&>&> ? ?D   %l 3 3D  *r"returnc6d|jd|jd|jS)Nz scale_factor=z, mode=z, align_corners=)rKr}r)rs r _extra_reprzUpsample._extra_reprs9 2D- 2 2di 2 2!/ 2 2 r"r?c|jdz }|dkrtd|jd|j}t|tr)t ||krtd|d|n|f|z}|jdkrt||S|jdkrt|||j S|jd krt|||j Std |j) Nrrzg[Upsample] The input should have at least 1 spatial dimension which means it should be at least 3D but zD was providedzH[Upsample] One scale per spatial dimension is required but scale_factor=z+ and the number of spatial dimensions were r|rrzUnknown interpolation mode: ) rNrPrKrrQrOr}rcrwrry Exception)rr?r\rKs r __call__zUpsample.__call__s.vz 199*6***  ( lE * * 2<  D(( .$0..'+..))?T1L 9 ! !#A|44 4 Y( " ""1lD4FGG G Y' ! !!!\43EFF FF49FFGG Gr")r|F)__name__ __module__ __qualname____doc__r rrrboolrstrrrarrayr __classcell__)rs@r r{r{s;;@7@# ++E5L)+23+ ++++++  S    H"(HrxHHHHHHHHr"r{)F)rl functoolsrr itertoolsrtypingrrrr mlx.corecorermlx.nn.layers.baser r!r'r3rJrrcrrsrwryr{rgr"r rs%%%%%%%%222222222222%%%%%% " " " 4 4 4   ###L>SX<< x<$<2: