class_docstr: The analysis transform.
code: def __init__(self, num_filters):
      super().__init__(name="analysis")
      self.add(tf.keras.layers.Lambda(lambda x: x / 255.0))
      self.add(
          tfc.SignalConv2D(
              num_filters,
              (5, 5),
              name="layer_0",
              corr=True,
              strides_down=2,
              padding="same_zeros",
              use_bias=True,
              activation=tfc.GDN(name="gdn_0"),
          )
      )
      self.add(
          tfc.SignalConv2D(
              num_filters,
              (5, 5),
              name="layer_1",
              corr=True,
              strides_down=2,
              padding="same_zeros",
              use_bias=True,
              activation=tfc.GDN(name="gdn_1"),
          )
      )
      self.add(
          tfc.SignalConv2D(
              num_filters,
              (5, 5),
              name="layer_2",
              corr=True,
              strides_down=2,
              padding="same_zeros",
              use_bias=True,
              activation=tfc.GDN(name="gdn_2"),
          )
      )
      self.add(
          tfc.SignalConv2D(
              num_filters,
              (5, 5),
              name="layer_3",
              corr=True,
              strides_down=2,
              padding="same_zeros",
              use_bias=True,
              activation=None,
          )
      )
  
imports: import argparse
  import glob
  import sys
  from absl import app
  from absl.flags import argparse_flags
  import tensorflow
  import tensorflow_compression
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new AnalysisTransform object from inherited base classes: tf.keras with example: obj = AnalysisTransform(num_filters)