GJjrddlZddlmZddlmZddlmZGddeZGddeZ Gdd eZ y) N)Union)Modulec\eZdZdZ d dededededededed effd Zd Zd ZxZ S)ConvTranspose1daApplies a 1-dimensional transposed convolution over the multi-channel input sequence. The channels are expected to be last i.e. the input shape should be ``NLC`` where: * ``N`` is the batch dimension * ``L`` is the sequence length * ``C`` is the number of input channels Args: in_channels (int): The number of input channels out_channels (int): The number of output channels kernel_size (int): The size of the convolution filters stride (int, optional): The stride when applying the filter. Default: ``1``. padding (int, optional): How many positions to 0-pad the input with. Default: ``0``. dilation (int, optional): The dilation of the convolution. output_padding(int, optional): Additional size added to one side of the output shape. Default: ``0``. bias (bool, optional): If ``True`` add a learnable bias to the output. Default: ``True`` in_channels out_channels kernel_sizestridepaddingdilationoutput_paddingbiasc  t |tjd||zz } tj j | | |||f|_|rt j|f|_ ||_ ||_ ||_ ||_ y)Nlowhighshape)super__init__mathsqrtmxrandomuniformweightzerosrr r r r selfrrr r r r r rscale __class__s m/Users/ahmed/devFolder/claude-voice/.venv/lib/python3.12/site-packages/mlx/nn/layers/convolution_transpose.pyrzConvTranspose1d.__init__"s  !{[89:ii''k:(  ,1DI    ,c|jjdd|jjdd|jjdd|jd|jd|jd |j d d |vS) N, r, kernel_size=r , stride= , padding= , dilation=, output_padding=, bias=rrrr r r r rs r" _extra_reprzConvTranspose1d._extra_repr=s{{  $%R (9(9!(<'=>;;,,Q/0 $++G||nK ?"1123dN#  % r#ctj||j|j|j|j |j }d|vr||jz}|SNr)rconv_transpose1drr r r r rrxys r"__call__zConvTranspose1d.__call__FU    KK KK LL MM      T>DII Ar#rrrrT) __name__ __module__ __qualname____doc__intboolrr/r6 __classcell__r!s@r"rr sv8--- -  -  ----6  r#rceZdZdZ d dededeeefdeeefdeeefdeeefdeeefd effd Zd Z d Z xZ S)ConvTranspose2da7Applies a 2-dimensional transposed convolution over the multi-channel input image. The channels are expected to be last i.e. the input shape should be ``NHWC`` where: * ``N`` is the batch dimension * ``H`` is the input image height * ``W`` is the input image width * ``C`` is the number of input channels Args: in_channels (int): The number of input channels. out_channels (int): The number of output channels. kernel_size (int or tuple): The size of the convolution filters. stride (int or tuple, optional): The size of the stride when applying the filter. Default: ``1``. padding (int or tuple, optional): How many positions to 0-pad the input with. Default: ``0``. dilation (int or tuple, optional): The dilation of the convolution. output_padding(int or tuple, optional): Additional size added to one side of the output shape. Default: ``0``. bias (bool, optional): If ``True`` add a learnable bias to the output. Default: ``True`` rrr r r r r rc dt |td||||f\}}}}tjd||dz|dzz } t j j| | |g|||_|rt j|f|_ ||_ ||_ ||_ ||_y)Nc.t|tr||fS|SN isinstancer=r4s r"z*ConvTranspose2d.__init__..{s 1c 2q!f99r#rrrrrmaprrrrrrrrr r r r rs r"rzConvTranspose2d.__init__ms 7: 9 &'> :8 4 VWn !{[^;k!nLMNii'';+;{;(  ,1DI    ,r#c|jjdd|jjdd|jjddd|jd|jd |jd |j d d |vS) Nr%r&rr'rr(r)r*r+r,rr-r.s r"r/zConvTranspose2d._extra_repr{{  $%R (9(9!(<'=>;;,,Qq12)DKK=I||nK ?"1123dN#  % r#ctj||j|j|j|j |j }d|vr||jz}|Sr1)rconv_transpose2drr r r r rr3s r"r6zConvTranspose2d.__call__r7r#r8 r9r:r;r<r=rtupler>rr/r6r?r@s@r"rBrBTs:%&%&&',----3:& - c5j! - sEz" -U #-c5j)-->  r#rBceZdZdZ d dededeeefdeeefdeeefdeeefdeeefd effd Zd Z d Z xZ S)ConvTranspose3da]Applies a 3-dimensional transposed convolution over the multi-channel input image. The channels are expected to be last i.e. the input shape should be ``NDHWC`` where: * ``N`` is the batch dimension * ``D`` is the input image depth * ``H`` is the input image height * ``W`` is the input image width * ``C`` is the number of input channels Args: in_channels (int): The number of input channels. out_channels (int): The number of output channels. kernel_size (int or tuple): The size of the convolution filters. stride (int or tuple, optional): The size of the stride when applying the filter. Default: ``1``. padding (int or tuple, optional): How many positions to 0-pad the input with. Default: ``0``. dilation (int or tuple, optional): The dilation of the convolution. output_padding(int or tuple, optional): Additional size added to one side of the output shape. Default: ``0``. bias (bool, optional): If ``True`` add a learnable bias to the output. Default: ``True`` rrr r r r r rc pt |td||||f\}}}}tjd||dz|dz|dzz } t j j| | |g|||_|rt j|f|_ ||_ ||_ ||_ ||_y)Nc0t|tr|||fS|SrErFrHs r"rIz*ConvTranspose3d.__init__..s:a#5q!Qi<1 :8 4 VWn {1~- A>QO P ii'';+;{;(  ,1DI    ,r#c|jjdd|jjdd|jjddd|jd|jd |jd |j d d |vS) Nr%r&rr'rr(r)r*r+r,rr-r.s r"r/zConvTranspose3d._extra_reprrNr#ctj||j|j|j|j |j }d|vr||jz}|Sr1)rconv_transpose3drr r r r rr3s r"r6zConvTranspose3d.__call__r7r#r8rQr@s@r"rTrTs<%&%&&',----3:& - c5j! - sEz" -U #-c5j)--B  r#rT) rtypingrmlx.corecorermlx.nn.layers.baserrrBrTr#r"r`s? %GfGTLfL^OfOr#