class_docstr: Represents a TensorFlow dataset for use with MLflow Tracking.
class_docstr_tok: ["Represents","a","TensorFlow","dataset","for","use","with","MLflow","Tracking","."]
docstr: Computes a digest for the dataset. Called if the user doesn't supply
  a digest when constructing the dataset.
docstr_tok: ["Computes","a","digest","for","the","dataset",".","Called","if","the","user","does","n't","supply","a","digest","when","constructing","the","dataset","."]
code: def _compute_digest(self) -> str:
      """
      Computes a digest for the dataset. Called if the user doesn't supply
      a digest when constructing the dataset.
      """
      import tensorflow as tf
  
      return (
          compute_tensorflow_dataset_digest(
              self._features, self._targets
          )
          if isinstance(self._features, tf.data.Dataset)
          else compute_tensor_digest(self._features, 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 2 for calling the TensorFlowDataset obj's underlying member method code with example usage: obj._compute_digest() and returns: unknown