class_docstr: A custom TensorBoard class that accepts EagerPy tensors and that
  can be disabled by turned into a noop by passing logdir=False.
  
  This makes it possible to add tensorboard logging without any if
  statements and without any computational overhead if it's disabled.
code: def histogram(
      self, tag: str, x: ep.Tensor, step: int, *, first: bool = True
  ) -> None:
      x = x.numpy()
      self.writer.add_histogram(tag, x, step)
      if first:
          self.writer.add_scalar(tag + "/0", x[0].item(), step)
  
file_path: foolbox/foolbox/tensorboard.py
imports: from typing import Union, Callable, TypeVar, Any, cast
  from typing_extensions import Literal
  import eagerpy
  from functools import wraps
label_desc: Use image node_id 8 for calling the TensorBoard obj's underlying member method code with example usage: obj.histogram(tag, x, step) without return types