code: def _render_weighted_spans(doc_weighted_spans, preserve_density=None):
      char_weights = get_char_weights(
          doc_weighted_spans, preserve_density
      )
      weight_range = max(abs(x) for x in char_weights)
      return render_weighted_spans(
          PreparedWeightedSpans(
              doc_weighted_spans,
              char_weights=char_weights,
              weight_range=weight_range,
          )
      )
  
imports: import re
  import pytest
  import numpy
  from sklearn.datasets import make_regression
  from sklearn.linear_model import LinearRegression
  from eli5.base import DocWeightedSpans, FeatureWeight
  from eli5 import explain_weights_sklearn, explain_prediction_sklearn
  from eli5.formatters import format_as_text, format_as_html, format_html_styles, FormattedFeatureName
  from eli5.formatters.html import _format_unhashed_feature, render_weighted_spans, _format_single_feature, _format_feature, remaining_weight_color_hsl, weight_color_hsl
  from eli5.formatters.text_helpers import get_char_weights, PreparedWeightedSpans
  from .utils import write_html
label_desc: Use image node_id 1 for calling a global function with example usage: _render_weighted_spans(doc_weighted_spans, preserve_density) and returns: render_weighted_spans