1D Convolution
Applies a 1D convolution over an input signal composed of several input planes.
Calls torch::nn_conv1d() when trained. The paramter in_channels is inferred from the second dimension of the input tensor.
out_channels :: integer(1)
Number of channels produced by the convolution.
kernel_size :: integer()
Size of the convolving kernel.
stride :: integer()
Stride of the convolution. The default is 1.
padding :: integer()
‘dilation * (kernel_size - 1) - padding’ zero-padding will be added to both sides of the input. 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".
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 $shapes_out().
# Construct the PipeOp pipeop = po("nn_conv1d", kernel_size = 10, out_channels = 1) pipeop # The available parameters pipeop$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_conv2d, mlr_pipeops_nn_conv3d, mlr_pipeops_nn_conv_transpose1d, mlr_pipeops_nn_conv_transpose2d, 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::PipeOpTorchConv -> PipeOpTorchConv1D
new()Creates a new instance of this R6 class.
PipeOpTorchConv1D$new(id = "nn_conv1d", param_vals = list())
id: (character(1))
Identifier of the resulting object.
param_vals: (list())
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction.
clone()The objects of this class are cloneable with this method.
PipeOpTorchConv1D$clone(deep = FALSE)
deep: Whether to make a deep clone.
Useful links