Feat/adaptive avg pool

DESCRIPTION

@@ -99,6 +99,7 @@ Collate:
     'PipeOpTorch.R'
     'PipeOpTaskPreprocTorch.R'
     'PipeOpTorchActivation.R'
+    'PipeOpTorchAdaptiveAvgPool.R'
     'PipeOpTorchAvgPool.R'
     'PipeOpTorchBatchNorm.R'
     'PipeOpTorchBlock.R'

NAMESPACE

@@ -77,6 +77,9 @@ export(ModelDescriptor)
 export(PipeOpModule)
 export(PipeOpTaskPreprocTorch)
 export(PipeOpTorch)
+export(PipeOpTorchAdaptiveAvgPool1D)
+export(PipeOpTorchAdaptiveAvgPool2D)
+export(PipeOpTorchAdaptiveAvgPool3D)
 export(PipeOpTorchAvgPool1D)
 export(PipeOpTorchAvgPool2D)
 export(PipeOpTorchAvgPool3D)

R/PipeOpTorchAdaptiveAvgPool.R

@@ -0,0 +1,126 @@
+PipeOpTorchAdaptiveAvgPool = R6Class("PipeOpTorchAdaptiveAvgPool",
+  inherit = PipeOpTorch,
+  public = list(
+    initialize = function(id, d, param_vals = list()) {
+      private$.d = assert_int(d, lower = 1, upper = 3)
+      module_generator = switch(d, nn_adaptive_avg_pool1d, nn_adaptive_avg_pool2d, nn_adaptive_avg_pool3d)
+      check_vector = make_check_vector(private$.d)
+      param_set = ps(
+        output_size = p_uty(custom_check = check_vector, tags = c("required", "train"))
+      )
+
+      super$initialize(
+        id = id,
+        param_set = param_set,
+        param_vals = param_vals,
+        module_generator = module_generator
+      )
+    }
+  ),
+  private = list(
+    .shapes_out = function(shapes_in, param_vals, task) {
+      list(adaptive_avg_output_shape(
+        shape_in = shapes_in[[1]],
+        conv_dim = private$.d,
+        output_size = param_vals$output_size
+      ))
+    },
+    .d = NULL
+  )
+)
+
+adaptive_avg_output_shape = function(shape_in, conv_dim, output_size) {
+  shape_in = assert_integerish(shape_in, min.len = conv_dim, coerce = TRUE)
+
+  if (length(output_size) == 1) output_size = rep(output_size, conv_dim)
+
+  shape_head = utils::head(shape_in, -conv_dim)
+  if (length(shape_head) <= 1) warningf("Input tensor does not have batch dimension.")
+
+  shape_tail = output_size
+
+  c(shape_head, shape_tail)
+}
+
+#' @title 1D Adaptive Average Pooling
+#' 
+#' @templateVar id nn_adaptive_avg_pool1d
+#' @template pipeop_torch_channels_default
+#' @template pipeop_torch
+#' @template pipeop_torch_example
+#' 
+#' @inherit torch::nnf_adaptive_avg_pool1d description
+#' 
+#' @section Parameters:
+#' * `output_size` :: `integer(1)`\cr
+#'   The target output size. A single number.
+#' 
+#' @section Internals:
+#' Calls [`nn_adaptive_avg_pool1d()`][torch::nn_adaptive_avg_pool1d] during training.
+#' @export
+PipeOpTorchAdaptiveAvgPool1D = R6Class("PipeOpTorchAdaptiveAvgPool1D", inherit = PipeOpTorchAdaptiveAvgPool,
+  public = list(
+    #' @description Creates a new instance of this [R6][R6::R6Class] class.
+    #' @template params_pipelines
+    initialize = function(id = "nn_adaptive_avg_pool1d", param_vals = list()) {
+      super$initialize(id = id, d = 1, param_vals = param_vals)
+    }
+  )
+)
+
+#' @title 2D Adaptive Average Pooling
+#' 
+#' @templateVar id nn_adaptive_avg_pool2d
+#' @template pipeop_torch_channels_default
+#' @template pipeop_torch
+#' @template pipeop_torch_example
+#' 
+#' @inherit torch::nnf_adaptive_avg_pool2d description
+#' 
+#' @section Parameters:
+#' * `output_size` :: `integer()`\cr
+#'   The target output size. Can be a single number or a vector.
+#' 
+#' @section Internals:
+#' Calls [`nn_adaptive_avg_pool2d()`][torch::nn_adaptive_avg_pool2d] during training.
+#' @export
+PipeOpTorchAdaptiveAvgPool2D = R6Class("PipeOpTorchAdaptiveAvgPool2D", inherit = PipeOpTorchAdaptiveAvgPool,
+  public = list(
+    #' @description Creates a new instance of this [R6][R6::R6Class] class.
+    #' @template params_pipelines
+    initialize = function(id = "nn_adaptive_avg_pool2d", param_vals = list()) {
+      super$initialize(id = id, d = 2, param_vals = param_vals)
+    }
+  )
+)
+
+#' @title 3D Adaptive Average Pooling
+#' 
+#' @templateVar id nn_adaptive_avg_pool3d
+#' @template pipeop_torch_channels_default
+#' @template pipeop_torch
+#' @template pipeop_torch_example
+#' 
+#' @inherit torch::nnf_adaptive_avg_pool3d description
+#' 
+#' @section Parameters:
+#' * `output_size` :: `integer()`\cr
+#'   The target output size. Can be a single number or a vector.
+#' 
+#' @section Internals:
+#' Calls [`nn_adaptive_avg_pool3d()`][torch::nn_adaptive_avg_pool3d] during training.
+#' @export
+PipeOpTorchAdaptiveAvgPool3D = R6Class("PipeOpTorchAdaptiveAvgPool3D", inherit = PipeOpTorchAdaptiveAvgPool,
+  public = list(
+    #' @description Creates a new instance of this [R6][R6::R6Class] class.
+    #' @template params_pipelines
+    initialize = function(id = "nn_adaptive_avg_pool3d", param_vals = list()) {
+      super$initialize(id = id, d = 3, param_vals = param_vals)
+    }
+  )
+)
+
+#' @include zzz.R
+register_po("nn_adaptive_avg_pool1d", PipeOpTorchAdaptiveAvgPool1D)
+register_po("nn_adaptive_avg_pool2d", PipeOpTorchAdaptiveAvgPool2D)
+register_po("nn_adaptive_avg_pool3d", PipeOpTorchAdaptiveAvgPool3D)

R/PipeOpTorchAvgPool.R

@@ -66,7 +66,7 @@ avg_output_shape = function(shape_in, conv_dim, padding, stride, kernel_size, ce
 #' @template pipeop_torch
 #' @template pipeop_torch_example
 #'
-#' @inherit torch::nnf_adaptive_avg_pool1d description
+#' @inherit torch::nnf_avg_pool1d description
 #'
 #' @section Parameters:
 #' * `kernel_size` :: (`integer()`)\cr
@@ -104,7 +104,7 @@ PipeOpTorchAvgPool1D = R6Class("PipeOpTorchAvgPool1D", inherit = PipeOpTorchAvgP
 #' @template pipeop_torch
 #' @template pipeop_torch_example
 #'
-#' @inherit torch::nnf_adaptive_avg_pool2d description
+#' @inherit torch::nnf_avg_pool2d description
 #'
 #' @inheritSection mlr_pipeops_nn_avg_pool1d Parameters
 #'
@@ -128,7 +128,7 @@ PipeOpTorchAvgPool2D = R6Class("PipeOpTorchAvgPool2D", inherit = PipeOpTorchAvgP
 #' @template pipeop_torch
 #' @template pipeop_torch_example
 #'
-#' @inherit torch::nnf_adaptive_avg_pool3d description
+#' @inherit torch::nnf_avg_pool3d description
 #'
 #' @inheritSection mlr_pipeops_nn_avg_pool1d Parameters
 #'