//clika-runtime/io.clika.runtime/Ops/convTranspose

convTranspose

[common]
fun convTranspose(input: Tensor, weight: Tensor, bias: Tensor?, stride: LongArray, padding: LongArray, outputPadding: LongArray, groups: Long, dilation: LongArray, activation: Activation = Activation.IDENTITY): Tensor

convTranspose(input: Tensor, weight: Tensor, bias: Tensor?, stride: LongArray, padding: LongArray, outputPadding: LongArray, groups: Long, dilation: LongArray, activation: Activation = Activation.IDENTITY): the conv_transpose operator. Rank-polymorphic (1-D/2-D/3-D) transposed (fractionally-strided) convolution (learnable upsampling). Layout is channels-last; the WEIGHT is the transpose-flip of conv's: input-channel-first [C_in, K.., O/groups]; C_in == weight[0] and C_out == weight[-1] * groups (the cuDNN-BackwardData / ONNX convention, NOT conv's OHWI). padding is per-side: two entries (lo, hi) per spatial dim. output_padding grows only the output's high side. All geometry spans are explicit here; the conv_transpose1d/2d/3d wrappers below carry the per-rank defaults.