inform_errors: Inform About Compilation Errors

In kerasnip: A Bridge Between 'keras' and 'tidymodels'

Inform About Compilation Errors

Description

This helper function inspects the results from compile_keras_grid() and prints a formatted, easy-to-read summary of any compilation errors that occurred.

Usage

inform_errors(compiled_grid, n = 10)

Arguments

compiled_grid	A tibble, the result of a call to compile_keras_grid().
n	A single integer for the maximum number of distinct errors to display in detail.

Details

Display a Summary of Compilation Errors

This is most useful for interactive debugging of complex tuning grids where some hyperparameter combinations may lead to invalid Keras models.

Value

Invisibly returns the input compiled_grid. Called for its side effect of printing a summary to the console.

Examples

if (requireNamespace("keras3", quietly = TRUE)) {
  library(keras3)
  library(parsnip)
  library(dials)

  # 1. Define layer blocks
  input_block <- function(model, input_shape) {
    keras_model_sequential(input_shape = input_shape)
  }
  hidden_block <- function(model, units = 32) {
    model |> layer_dense(units = units, activation = "relu")
  }
  output_block <- function(model, num_classes) {
    model |> layer_dense(units = num_classes, activation = "softmax")
  }

  # 2. Define a kerasnip model specification
  create_keras_sequential_spec(
    model_name = "my_mlp_grid_3",
    layer_blocks = list(
      input = input_block,
      hidden = hidden_block,
      output = output_block
    ),
    mode = "classification"
  )

  mlp_spec <- my_mlp_grid_3(
    hidden_units = tune(),
    compile_loss = "categorical_crossentropy",
    compile_optimizer = "adam"
  )

  # 3. Create a hyperparameter grid
  param_grid <- tibble::tibble(
    hidden_units = c(32, 64, -10)
  )

  # 4. Prepare dummy data
  x_train <- matrix(rnorm(100 * 10), ncol = 10)
  y_train <- factor(sample(0:1, 100, replace = TRUE))

  # 5. Compile models over the grid
  compiled_grid <- compile_keras_grid(
    spec = mlp_spec,
    grid = param_grid,
    x = x_train,
    y = y_train
  )

  # 6. Inform about errors
  inform_errors(compiled_grid)
  remove_keras_spec("my_mlp_grid_3")
}

kerasnip documentation built on Nov. 5, 2025, 7:32 p.m.