class_docstr: Defines how to apply the EPR algorithm.
class_docstr_tok: ["Defines","how","to","apply","the","EPR","algorithm","."]
code: def project_training_weights(
      self, *training_weights: tf.Tensor
  ) -> tf.Tensor:
      if len(training_weights) == 3:
          # Bias or dense kernel.
          return _transform_dense_weight(
              *training_weights[:-1], quantized=False
          )
      else:
          # Convolution kernel.
          return _transform_conv_weight(
              *training_weights[:-1], quantized=False
          )
  
imports: import functools
  from typing import Callable, List, Tuple
  import tensorflow
  import tensorflow_compression
  from tensorflow_model_optimization.python.core.common.keras.compression import algorithm
label_desc: Use image node_id 2 for calling the EPR obj's underlying member method code with example usage: obj.project_training_weights() and returns: _transform_dense_weight, _transform_conv_weight