class_docstr: Partial Dependence Plot interpreter.
docstr: Returns all values to try for a given feature.
docstr_tok: ["Returns","all","values","to","try","for","a","given","feature","."]
code: def get_vals_to_test(self, feat, dataset: lit_dataset.IndexedDataset):
      """Returns all values to try for a given feature."""
      numeric = isinstance(dataset.spec()[feat], types.Scalar)
      # Get categorical values to test from the spec vocab.
      if not numeric:
          return (
              cast(types.MulticlassPreds, dataset.spec()[feat]).vocab
              or []
          )
  
      # Create 10 values from min to max of a numeric feature to test and store
      # it for later use as well.
      nums = [ex[feat] for ex in dataset.examples]
      min_val = np.min(nums)
      max_val = np.max(nums)
      return np.linspace(min_val, max_val, 10)
  
file_path: lit/lit_nlp/components/pdp.py
imports: import functools
  from typing import cast, Optional
  from absl import logging
  from lit_nlp.api import components
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import utils
  import numpy
label_desc: Use image node_id 2 for calling the PdpInterpreter obj's underlying member method code with example usage: obj.get_vals_to_test(feat, dataset) and returns: np, unknown