class_docstr: Base class for TPU Embedding Column.
class_docstr_tok: ["Base","class","for","TPU","Embedding","Column","."]
code: def __init__(
      self,
      categorical_column,
      max_sequence_length=0,
      learning_rate_fn=None,
  ):
      self._tpu_categorical_column = categorical_column
      self._max_sequence_length = max_sequence_length
      self._learning_rate_fn = learning_rate_fn
      if self.is_sequence_column() and max_sequence_length < 1:
          raise ValueError(
              "max_sequence_length must be greater than 0 for "
              "sequence columns. Got max_sequence_length={} for "
              "sequence column {}.".format(
                  max_sequence_length, categorical_column.name
              )
          )
      if not self.is_sequence_column() and max_sequence_length != 0:
          raise ValueError(
              "Non zero max_seq_length={} specified for non "
              "sequence column {}.".format(
                  max_sequence_length, categorical_column.name
              )
          )
  
imports: import math
  from tensorflow.python.feature_column import feature_column
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.tpu import tpu
  from tensorflow.python.tpu import tpu_function
  from tensorflow.python.tpu import tpu_replication
label_desc: Use image node_id 1 to create a new _TPUBaseEmbeddingColumn object from inherited base classes: object with example: obj = _TPUBaseEmbeddingColumn(categorical_column, max_sequence_length, learning_rate_fn)