class_docstr: Represents a TensorFlow dataset for use with MLflow Tracking.
class_docstr_tok: ["Represents","a","TensorFlow","dataset","for","use","with","MLflow","Tracking","."]
docstr: The targets of the dataset.
docstr_tok: ["The","targets","of","the","dataset","."]
code: def targets(self):
      """
      The targets of the dataset.
      """
      return self._targets
  
imports: import json
  import logging
  from functools import cached_property
  from typing import Any, Dict, Optional, Tuple, Union
  import numpy
  from mlflow.data.dataset import Dataset
  from mlflow.data.dataset_source import DatasetSource
  from mlflow.data.digest_utils import compute_tensor_digest, compute_tensorflow_dataset_digest
  from mlflow.data.pyfunc_dataset_mixin import PyFuncConvertibleDatasetMixin, PyFuncInputsOutputs
  from mlflow.data.schema import TensorDatasetSchema
  from mlflow.exceptions import MlflowException
  from mlflow.models.evaluation.base import EvaluationDataset
  from mlflow.protos.databricks_pb2 import INTERNAL_ERROR, INVALID_PARAMETER_VALUE
  from mlflow.types.schema import Schema
  from mlflow.types.utils import _infer_schema
  from mlflow.utils.annotations import experimental
label_desc: Use image node_id 6 for calling the TensorFlowDataset obj's underlying member method code with example usage: obj.targets() and returns: self