code: def _create_dense_dataset(
      self, strategy, include_weights=False, weight=0.5
  ):
      features = (
          constant_op.constant(
              self.feature_watched_values[: self.data_batch_size],
              dtype=dtypes.int32,
          ),
          constant_op.constant(
              self.feature_favorited_values[: self.data_batch_size],
              dtype=dtypes.int32,
          ),
          constant_op.constant(
              self.feature_friends_values[: self.data_batch_size],
              dtype=dtypes.int32,
          ),
      )
      if include_weights:
          weights = [
              array_ops.ones_like(t, dtype=dtypes.float32) * weight
              for t in features
          ]
          features = (features, tuple(weights))
  
      dataset = dataset_ops.DatasetV2.from_tensors(features)
      return (
          dataset.unbatch()
          .repeat()
          .batch(
              self.batch_size * strategy.num_replicas_in_sync,
              drop_remainder=True,
          )
      )
  
imports: import os
  from typing import Tuple
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import tpu_strategy
  from tensorflow.python.distribute.cluster_resolver import tpu_cluster_resolver
  from tensorflow.python.eager import remote
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu_embedding_v2
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.util import nest
label_desc: Use image node_id 12 for calling the TPUEmbeddingBaseTest obj's underlying member method code with example usage: obj._create_dense_dataset(strategy, include_weights, weight) and returns: dataset