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iterator]iterator]iterator]iterator]keys keys KLDivLoss L1Loss L1LossOptions LayerNorm LayerNormOptions LazyBatchNorm1d LazyBatchNorm2d LazyBatchNorm3d LazyConv1d LazyConv2d LazyConv3d LazyConvOptions LazyConvTranspose1d LazyConvTranspose2d LazyConvTranspose3d LazyConvTransposeOptions LazyInstanceNorm1d LazyInstanceNorm2d LazyInstanceNorm3d LazyLinear LeakyReLU LeakyReLUOptions Linear LinearOptions load_state_dict load_state_dict LocalResponseNorm LocalResponseNormOptions log_prob LogSigmoid LogSoftmax LogSoftmaxOptions LPPool1d LPPool1dOptions LPPool2d LPPool2dOptions LPPool3d LPPool3dOptions LSTM LSTMCell LSTMCellOptions MarginRankingLoss MarginRankingLossOptions materialize materialize materialize_uninitialized materialize_uninitialized MaxPool1d MaxPool1dOptions MaxPool2d MaxPool2dOptions MaxPool3d MaxPool3dOptions MaxUnpool1d MaxUnpool1dOptions MaxUnpool2d MaxUnpool2dOptions MaxUnpool3d MaxUnpool3dOptions Mish Module ModuleBuffers ModuleChildren ModuleDict ModuleDictOptions 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abs acos acosh AdaptivePool1dShape AdaptivePool2dShape add addbmm AddbmmOptions addcdiv AddcdivOptions addcmul AddcmulOptions addmm AddmmOptions addmv AddmvOptions addr AddrOptions adjoint all allclose AllcloseOptions AlphaBetaOptions amax amin aminmax AminmaxOptions angle any applyOut arange are_deterministic_algorithms_enabled argmax argmin argsort argwhere as_strided as_tensor asin asinh AssertNoShapeError AssertNotError AsStridedOptions At at_error_index_out_of_bounds atan atan2 atanh atleast_1d atleast_2d atleast_3d AtShape autocast_decrement_nesting autocast_increment_nesting autograd_gradient_mismatch_error autograd_not_registered_error AutogradConfig AutogradDevice AutogradDType AutogradEntry AutogradHandle AutogradHandleImpl AxesRecord BackwardFn baddbmm BaddbmmOptions bartlett_window BaseKernelConfig batch_dimensions_do_not_match_error bernoulli BernoulliOptions BinaryBackwardFn BinaryBroadcastResult BinaryDType BinaryKernelConfigCPU BinaryKernelCPU BinaryOpConfig 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istft ISTFTOptions IsUnaryOp IsUnaryOpName item_error_not_scalar ItemResult kaiser_window KaiserWindowOptions kernel_not_registered_error kernel_signature_mismatch_error KernelConfig KernelConfigWebGPU KernelEntry KernelHandle KernelInfo KernelPredicate KernelRegistry KernelWebGPU kron kthvalue KthvalueOptions lcm ldexp le leaky_relu leaky_relu_LeakyReluFunctionalOptions lerp levenshteinDistance lgamma linalg_error_not_square_matrix linalg_error_requires_2d linalg_error_requires_at_least_2d linear linspace list_custom_devices list_custom_dtypes list_devices list_dtypes list_functions list_kernels list_methods list_ops listCustomDTypes listDTypes listFunctions listKernels ListKernelsOptions listMethods listOps ListOpsOptions log log_softmax log10 log1p log2 logaddexp logaddexp2 logcumsumexp logical_and logical_not logical_or logical_xor LogitOptions LogNormalOptions LogOptions logsigmoid logspace logsumexp LogsumexpOptions lt LUShape LuSolveOptions masked_fill masked_select 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conv_transpose1d

torch.nn.functional.conv_transpose1d

function conv_transpose1d<S extends Shape, D extends DType = DType, Dev extends DeviceType = DeviceType>(input: Tensor<S, D, Dev>, weight: Tensor): Tensor<Shape, D, Dev>

function conv_transpose1d<S extends Shape, D extends DType = DType, Dev extends DeviceType = DeviceType>(input: Tensor<S, D, Dev>, weight: Tensor, bias: Tensor | null, stride: number, padding: number, output_padding: number, groups: number, dilation: number, options: ConvTranspose1dFunctionalOptions): Tensor<Shape, D, Dev>

1D transposed convolution: applies a 1D transposed convolution operator over an input signal.

Essential for upsampling in sequence generation, GANs, and encoder-decoder architectures.

Parameters

inputTensor<S, D, Dev>: Input tensor of shape (batch, in_channels, iW)
weightTensor: Filters of shape (in_channels, out_channels/groups, kW)

Returns

Tensor<Shape, D, Dev>– Output tensor of shape (batch, out_channels, oW)

See Also

PyTorch torch.nn.functional.conv_transpose1d

channel_shuffle

conv_transpose2d