code: def _generate_dropout_mask(
      ones: tf.Tensor,
      rate: float,
      training: Optional[bool] = None,
      count: int = 1,
  ) -> tf.Tensor:
      """Returns a mask for implementing dropout."""
  
      def dropped_inputs():
          return tf.keras.backend.dropout(ones, rate)
  
      if count > 1:
          return [
              tf.keras.backend.in_train_phase(
                  dropped_inputs, ones, training=training
              )
              for _ in range(count)
          ]
      return tf.keras.backend.in_train_phase(
          dropped_inputs, ones, training=training
      )
  
file_path: model_search/model_search/ops/svdf_conv.py
imports: from typing import Any, Callable, Dict, List, Optional, Text, Union
  from absl import logging
  from six.moves import range
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: _generate_dropout_mask(ones, rate, training, count) and returns: tf, tf, unknown