class_docstr: Matcher based on highest value.
  
  This class computes matches from a similarity matrix. Each column is matched
  to a single row.
  
  To support object detection target assignment this class enables setting both
  matched_threshold (upper threshold) and unmatched_threshold (lower thresholds)
  defining three categories of similarity which define whether examples are
  positive, negative, or ignored:
  (1) similarity >= matched_threshold: Highest similarity. Matched/Positive!
  (2) matched_threshold > similarity >= unmatched_threshold: Medium similarity.
          Depending on negatives_lower_than_unmatched, this is either
          Unmatched/Negative OR Ignore.
  (3) unmatched_threshold > similarity: Lowest similarity. Depending on flag
          negatives_lower_than_unmatched, either Unmatched/Negative OR Ignore.
  For ignored matches this class sets the values in the Match object to -2.
docstr: Set the indicated fields of x to val.
  
  Args:
    x: tensor.
    indicator: boolean with same shape as x.
    val: scalar with value to set.
  
  Returns:
    modified tensor.
docstr_tok: ["Set","the","indicated","fields","of","x","to","val",".","Args",":","x",":","tensor",".","indicator",":","boolean","with","same","shape","as","x.","val",":","scalar","with","value","to","set",".","Returns",":","modified","tensor","."]
code: def _set_values_using_indicator(self, x, indicator, val):
      """Set the indicated fields of x to val.
  
      Args:
        x: tensor.
        indicator: boolean with same shape as x.
        val: scalar with value to set.
  
      Returns:
        modified tensor.
      """
      indicator = tf.cast(indicator, x.dtype)
      return x * (1 - indicator) + val * indicator
  
imports: import tensorflow.compat.v1
  from .None import matcher
  from .None import shape_utils
label_desc: Use image node_id 3 for calling the ArgMaxMatcher obj's underlying member method code with example usage: obj._set_values_using_indicator(x, indicator, val) and returns: unknown