class_docstr: This class implements a DGM with the TensorFlow framework.
class_docstr_tok: ["This","class","implements","a","DGM","with","the","TensorFlow","framework","."]
docstr: Perform projections over a batch of encodings.
  
  :param x: Encodings.
  :param batch_size: Batch size.
  :return: Array of prediction projections of shape `(num_inputs, nb_classes)`.
docstr_tok: ["Perform","projections","over","a","batch","of","encodings",".",":","param","x",":","Encodings",".",":","param","batch_size",":","Batch","size",".",":","return",":","Array","of","prediction","projections","of","shape","`","(","num_inputs",",","nb_classes",")","`","."]
code: def predict(
      self, x: np.ndarray, batch_size: int = 128, **kwargs
  ) -> np.ndarray:
      """
      Perform projections over a batch of encodings.
  
      :param x: Encodings.
      :param batch_size: Batch size.
      :return: Array of prediction projections of shape `(num_inputs, nb_classes)`.
      """
      logging.info("Projecting new sample from z value")
      feed_dict = {self.input_ph: x}
      if self.feed_dict is not None:
          feed_dict.update(self.feed_dict)
      y = self._sess.run(self._model, feed_dict=feed_dict)
      return y
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import Any, Dict, List, Optional, Union, Tuple, TYPE_CHECKING
  import numpy
  from art.estimators.generation.generator import GeneratorMixin
  from art.estimators.tensorflow import TensorFlowEstimator, TensorFlowV2Estimator
label_desc: Use image node_id 6 for calling the TensorFlowGenerator obj's underlying member method code with example usage: obj.predict(x, batch_size) and returns: y