class_docstr: Construct and access Dense + BatchNorm + activation models.
docstr: Return input shape with batch size.
docstr_tok: ["Return","input","shape","with","batch","size","."]
code: def get_batched_input_shape(cls):
      """Return input shape with batch size."""
      shape = [cls.params["batch_size"]]
      shape.extend(cls.params["input_shape"])
      return shape
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/layers/dense_batchnorm_test_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 1 for calling the DenseModel obj's underlying member method code with example usage: obj.get_batched_input_shape(cls) and returns: shape