class_docstr: The analysis transform.
class_docstr_tok: ["The","analysis","transform","."]
code: def __init__(self, latent_depth):
      super().__init__()
      conv = functools.partial(
          tfc.SignalConv2D,
          corr=True,
          strides_down=2,
          padding="same_zeros",
          use_bias=True,
      )
      layers = [
          tf.keras.layers.Lambda(lambda x: x / 255.0),
          conv(
              192,
              (5, 5),
              name="layer_0",
              activation=tfc.GDN(name="gdn_0"),
          ),
          conv(
              192,
              (5, 5),
              name="layer_1",
              activation=tfc.GDN(name="gdn_1"),
          ),
          conv(
              192,
              (5, 5),
              name="layer_2",
              activation=tfc.GDN(name="gdn_2"),
          ),
          conv(latent_depth, (5, 5), name="layer_3", activation=None),
      ]
      for layer in layers:
          self.add(layer)
  
imports: import argparse
  import functools
  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(latent_depth)