Transpose 2D Convolution
Applies a 2D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution".
Calls nn_conv_transpose2d. The parameter in_channels is inferred as the second dimension of the input tensor.
One input channel called "input" and one output channel called "output". For an explanation see PipeOpTorch.
The state is the value calculated by the public method $shapes_out().
out_channels :: integer(1)
Number of output channels produce by the convolution.
kernel_size :: integer()
Size of the convolving kernel.
stride :: integer()
Stride of the convolution. Default: 1.
padding :: integer()`
‘dilation * (kernel_size - 1) - padding’ zero-padding will be added to both sides of the input. Default: 0.
output_padding ::integer()
Additional size added to one side of the output shape. Default: 0.
groups :: integer()
Number of blocked connections from input channels to output channels. Default: 1
bias :: logical(1)
If ‘True’, adds a learnable bias to the output. Default: ‘TRUE’.
dilation :: integer()
Spacing between kernel elements. Default: 1.
padding_mode :: character(1)
The padding mode. One of "zeros", "reflect", "replicate", or "circular". Default is "zeros".
# Construct the PipeOp pipeop = po("nn_conv_transpose2d", kernel_size = 3, out_channels = 2) pipeop # The available parameters pipeop$param_set
Other PipeOps: mlr_pipeops_nn_adaptive_avg_pool1d, mlr_pipeops_nn_adaptive_avg_pool2d, mlr_pipeops_nn_adaptive_avg_pool3d, mlr_pipeops_nn_avg_pool1d, mlr_pipeops_nn_avg_pool2d, mlr_pipeops_nn_avg_pool3d, mlr_pipeops_nn_batch_norm1d, mlr_pipeops_nn_batch_norm2d, mlr_pipeops_nn_batch_norm3d, mlr_pipeops_nn_block, mlr_pipeops_nn_celu, mlr_pipeops_nn_conv1d, mlr_pipeops_nn_conv2d, mlr_pipeops_nn_conv3d, mlr_pipeops_nn_conv_transpose1d, mlr_pipeops_nn_conv_transpose3d, mlr_pipeops_nn_dropout, mlr_pipeops_nn_elu, mlr_pipeops_nn_flatten, mlr_pipeops_nn_gelu, mlr_pipeops_nn_glu, mlr_pipeops_nn_hardshrink, mlr_pipeops_nn_hardsigmoid, mlr_pipeops_nn_hardtanh, mlr_pipeops_nn_head, mlr_pipeops_nn_layer_norm, mlr_pipeops_nn_leaky_relu, mlr_pipeops_nn_linear, mlr_pipeops_nn_log_sigmoid, mlr_pipeops_nn_max_pool1d, mlr_pipeops_nn_max_pool2d, mlr_pipeops_nn_max_pool3d, mlr_pipeops_nn_merge, mlr_pipeops_nn_merge_cat, mlr_pipeops_nn_merge_prod, mlr_pipeops_nn_merge_sum, mlr_pipeops_nn_prelu, mlr_pipeops_nn_relu, mlr_pipeops_nn_relu6, mlr_pipeops_nn_reshape, mlr_pipeops_nn_rrelu, mlr_pipeops_nn_selu, mlr_pipeops_nn_sigmoid, mlr_pipeops_nn_softmax, mlr_pipeops_nn_softplus, mlr_pipeops_nn_softshrink, mlr_pipeops_nn_softsign, mlr_pipeops_nn_squeeze, mlr_pipeops_nn_tanh, mlr_pipeops_nn_tanhshrink, mlr_pipeops_nn_threshold, mlr_pipeops_nn_unsqueeze, mlr_pipeops_torch_ingress, mlr_pipeops_torch_ingress_categ, mlr_pipeops_torch_ingress_ltnsr, mlr_pipeops_torch_ingress_num, mlr_pipeops_torch_loss, mlr_pipeops_torch_model, mlr_pipeops_torch_model_classif, mlr_pipeops_torch_model_regr
mlr3pipelines::PipeOp -> mlr3torch::PipeOpTorch -> mlr3torch::PipeOpTorchConvTranspose -> PipeOpTorchConvTranspose2D
new()Creates a new instance of this R6 class.
PipeOpTorchConvTranspose2D$new(id = "nn_conv_transpose2d", param_vals = list())
id: (character(1))
Identifier of the resulting object.
param_vals: (list())
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction.
clone()The objects of this class are cloneable with this method.
PipeOpTorchConvTranspose2D$clone(deep = FALSE)
deep: Whether to make a deep clone.
Useful links