class_docstr: A linear probe.
class_docstr_tok: ["A","linear","probe","."]
code: def __call__(self, x, train: bool = False, debug: bool = False):
      del train, debug
      x = jax.lax.stop_gradient(x)
      x = nn.Dense(features=self.num_classes)(x)
      return x
  
imports: import functools
  import logging
  from typing import Any, Callable, Dict, List, Mapping, Optional, Text, Tuple, Type, Union
  from absl import logging
  from clu import metric_writers
  import flax
  from flax import jax_utils
  import flax.linen
  import jax
  from jax.example_libraries.optimizers import clip_grads
  import jax.numpy
  import ml_collections
  import numpy
  import optax
  from scenic.dataset_lib import dataset_utils
  from scenic.model_lib.base_models import classification_model
  from scenic.model_lib.base_models import model_utils
  from scenic.train_lib import classification_trainer
  from scenic.train_lib import lr_schedules
  from scenic.train_lib import optimizers
  from scenic.train_lib import train_utils
label_desc: Use image node_id 1 for calling the LinearProbe obj's underlying member method code with example usage: obj.__call__(x, train, debug) and returns: x