class_docstr: A container class for metrics passed to `Model.compile`.
class_docstr_tok: ["A","container","class","for","metrics","passed","to","`","Model.compile","`","."]
docstr: Resets the state of all `Metric`s in this container.
code: def reset_state(self):
      """Resets the state of all `Metric`s in this container."""
      if self._built:
          metrics = self._metrics_in_order
      else:
          # If the user supplied `Metric` objects directly, we should
          # reset those. This could also contain `str`s or `function`s
          # though.
          metrics = nest.flatten(self._user_metrics) + nest.flatten(
              self._user_weighted_metrics
          )
  
      for metric_obj in metrics:
          if isinstance(metric_obj, metrics_mod.Metric):
              metric_obj.reset_state()
  
imports: import copy
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.keras import losses
  from tensorflow.python.keras import metrics
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import losses_utils
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 10 for calling the MetricsContainer obj's underlying member method code with example usage: obj.reset_state() without return types