mlr_pipeops_nn_conv_transpose2d {mlr3torch}

Transpose 2D Convolution

Description

Applies a 2D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution".

Input and Output Channels

One input channel called "input" and one output channel called "output". For an explanation see PipeOpTorch.

State

The state is the value calculated by the public method ⁠$shapes_out()⁠.

Credit

Part of this documentation have been copied or adapted from the documentation of torch.

Internals

Calls nn_conv_transpose2d. The parameter in_channels is inferred as the second dimension of the input tensor.

Parameters

• 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".

Super classes

mlr3pipelines::PipeOp -> mlr3torch::PipeOpTorch -> mlr3torch::PipeOpTorchConvTranspose -> PipeOpTorchConvTranspose2D

Methods

Public methods

• PipeOpTorchConvTranspose2D$new()

• PipeOpTorchConvTranspose2D$clone()

Inherited methods

• mlr3pipelines::PipeOp$help()
• mlr3pipelines::PipeOp$predict()
• mlr3pipelines::PipeOp$print()
• mlr3pipelines::PipeOp$train()
• mlr3torch::PipeOpTorch$shapes_out()

Method new()

Creates a new instance of this R6 class.

Usage

PipeOpTorchConvTranspose2D$new(id = "nn_conv_transpose2d", param_vals = list())

Arguments

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.

Method clone()

The objects of this class are cloneable with this method.

Usage

PipeOpTorchConvTranspose2D$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other PipeOps: 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_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

Examples

# Construct the PipeOp
pipeop = po("nn_conv_transpose2d", kernel_size = 3, out_channels = 2)
pipeop
# The available parameters
pipeop$param_set