class_docstr: Defines metrics/loss among all moment retrieval models.
  
  A model is class with three members: get_metrics_fn, loss_fn, & a flax_model.
  
  get_metrics_fn returns a callable function, metric_fn, that calculates the
  metrics and returns a dictionary. The metric function computes f(logits_i,
  batch_i) on a minibatch, it has API:
    ```metric_fn(logits, batch).```
  
  The trainer will then aggregate and compute the mean across all samples
  evaluated.
  
  loss_fn is a function of API
    loss = loss_fn(logits, batch, model_params=None).
  
  This model class defines two losses, sigmoid cross entropy for classification
  and IoU for boundary regression.
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docstr: Default config for the flax model that is built in `build_flax_model`.
  
  This function in particular serves the testing functions and supposed to
  provide config tha are passed to the flax_model when it's build in
  `build_flax_model` function, e.g., `model_dtype_str`.
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code: def default_flax_model_config(self):
      """Default config for the flax model that is built in `build_flax_model`.
  
      This function in particular serves the testing functions and supposed to
      provide config tha are passed to the flax_model when it's build in
      `build_flax_model` function, e.g., `model_dtype_str`.
      """
      raise NotImplementedError(
          "Subclasses must implement default_flax_model_config()."
      )
  
imports: import functools
  from typing import Any, Dict, Mapping, Optional, Tuple, Union
  import immutabledict
  import jax.numpy
  import ml_collections
  from scenic.model_lib.base_models import base_model
  from scenic.model_lib.base_models import model_utils
  from scenic.projects.unloc import temporal_localization_base_model
label_desc: Use image node_id 6 for calling the MomentRetrievalModel obj's underlying member method code with example usage: obj.default_flax_model_config() without return types