code: def __init__(
      self, n_filters, kernel_size, dilation_rate, rate, scope
  ):
      self.scope = scope
      self.rate = rate
      self.n_filters = n_filters
      self.conv1 = tf.keras.layers.Conv1D(
          filters=n_filters,
          kernel_size=kernel_size,
          padding="same",
          activation=tf.nn.relu,
          dilation_rate=dilation_rate,
          kernel_initializer=tf.compat.v1.initializers.glorot_normal,
          name="conv1",
      )
      self.conv2 = tf.keras.layers.Conv1D(
          filters=n_filters,
          kernel_size=kernel_size,
          padding="same",
          dilation_rate=dilation_rate,
          activation=tf.nn.relu,
          kernel_initializer=tf.compat.v1.initializers.glorot_normal,
          name="conv2",
      )
      self.downsample = tf.keras.layers.Conv1D(
          filters=n_filters, kernel_size=1, padding="same"
      )
  
imports: import tensorflow
  from finetune.util.shapes import lengths_from_eos_idx
  from finetune.base_models.gpt.featurizer import dropout, embed
label_desc: Use image node_id 1 to create a new TemporalBlock object  with example: obj = TemporalBlock(n_filters, kernel_size, dilation_rate, rate, scope)