text: Title: Failed Index Uniqueness Validation for Dask Series 
  Body: **Describe the bug**
  A clear and concise description of what the bug is.
  
  - [X ] I have checked that this issue has not already been reported.
  - [X ] I have confirmed this bug exists on the latest version of pandera.
  - [X ] (optional) I have confirmed this bug exists on the main branch of pandera.
  
  
  #### Code Sample
  
  ```python
  import pandera as pa
  import dask.dataframe as dd
  import pandas as pd
  
  example_schema = pa.SeriesSchema(
      float,
      index=pa.Index(pa.dtypes.Timestamp, unique=True),
      nullable=False,
      unique=False,
  )
  
  example_series = dd.from_pandas(
      pd.Series([1.333, 2.22, 3.333, 4.311, 5.222], index=[1, 2, 3, 5, 5]),
      npartitions=1,
  )
  
  # Skips validation despite having a duplicate 
  example_schema.validate(example_series).compute()
  
  # Validates correctly and throws an exception.
  # Note that when we execute .compute(), we are dealing with a Pandas Series
  example_schema.validate(example_series.compute())
  ```
  
  #### Expected behavior
  pandera should be able to validate a Dask Series directly and throw an exception if it fails the validation.
  
  #### Desktop (please complete the following information):
   - OS: Windows 10
   - Browser: Chrome
   - Version: pandera 0.20.3
  
  ### Additional Information
  I have validated that this issue is only occurring with Dask Series. If we convert Dask Series into a DataFrame, pandera throws an exception:
  > SchemaError: series 'None' contains duplicate values:
  > 3    5
  > 4    5
  > dtype: int64