Dataset not loading successfully.
Author: hisushanta
Pull request: no

### System Info

* transformers -> 4.36.1
* datasets -> 2.15.0
* huggingface_hub -> 0.19.4
* python -> 3.8.10
* accelerate -> 0.25.0
* pytorch -> 2.0.1+cpu
* Using GPU in Script  -> No

### Who can help?

@patrickvonplaten , @amyeroberts 

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

Hi, please check this line of code, when I run Show attribute error.
```
from datasets import load_dataset
from transformers import WhisperProcessor, WhisperForConditionalGeneration

# Select an audio file and read it:
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
audio_sample = ds[0]["audio"]
waveform = audio_sample["array"]
sampling_rate = audio_sample["sampling_rate"]

# Load the Whisper model in Hugging Face format:
processor = WhisperProcessor.from_pretrained("openai/whisper-tiny.en")
model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")

# Use the model and processor to transcribe the audio:
input_features = processor(
    waveform, sampling_rate=sampling_rate, return_tensors="pt"
).input_features

# Generate token ids
predicted_ids = model.generate(input_features)

# Decode token ids to text
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)

transcription[0]
```
***AttributeError:***
```
AttributeError                            Traceback (most recent call last)
Cell In[9], line 6
      4 # Select an audio file and read it:
      5 ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
----> 6 audio_sample = ds[0]["audio"]
      7 waveform = audio_sample["array"]
      8 sampling_rate = audio_sample["sampling_rate"]

File /opt/pytorch/lib/python3.8/site-packages/datasets/arrow_dataset.py:2795, in Dataset.__getitem__(self, key)
   2793 def __getitem__(self, key):  # noqa: F811
   2794     """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 2795     return self._getitem(key)

File /opt/pytorch/lib/python3.8/site-packages/datasets/arrow_dataset.py:2780, in Dataset._getitem(self, key, **kwargs)
   2778 formatter = get_formatter(format_type, features=self._info.features, **format_kwargs)
   2779 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 2780 formatted_output = format_table(
   2781     pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
   2782 )
   2783 return formatted_output

File /opt/pytorch/lib/python3.8/site-packages/datasets/formatting/formatting.py:629, in format_table(table, key, formatter, format_columns, output_all_columns)
    627 python_formatter = PythonFormatter(features=formatter.features)
    628 if format_columns is None:
--> 629     return formatter(pa_table, query_type=query_type)
    630 elif query_type == "column":
    631     if key in format_columns:

File /opt/pytorch/lib/python3.8/site-packages/datasets/formatting/formatting.py:396, in Formatter.__call__(self, pa_table, query_type)
    394 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
    395     if query_type == "row":
--> 396         return self.format_row(pa_table)
    397     elif query_type == "column":
    398         return self.format_column(pa_table)

File /opt/pytorch/lib/python3.8/site-packages/datasets/formatting/formatting.py:437, in PythonFormatter.format_row(self, pa_table)
    435     return LazyRow(pa_table, self)
    436 row = self.python_arrow_extractor().extract_row(pa_table)
--> 437 row = self.python_features_decoder.decode_row(row)
    438 return row

File /opt/pytorch/lib/python3.8/site-packages/datasets/formatting/formatting.py:215, in PythonFeaturesDecoder.decode_row(self, row)
    214 def decode_row(self, row: dict) -> dict:
--> 215     return self.features.decode_example(row) if self.features else row

File /opt/pytorch/lib/python3.8/site-packages/datasets/features/features.py:1917, in Features.decode_example(self, example, token_per_repo_id)
   1903 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
   1904     """Decode example with custom feature decoding.
   1905 
   1906     Args:
   (...)
   1914         `dict[str, Any]`
   1915     """
-> 1917     return {
   1918         column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
   1919         if self._column_requires_decoding[column_name]
   1920         else value
   1921         for column_name, (feature, value) in zip_dict(
   1922             {key: value for key, value in self.items() if key in example}, example
   1923         )
   1924     }

File /opt/pytorch/lib/python3.8/site-packages/datasets/features/features.py:1918, in <dictcomp>(.0)
   1903 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
   1904     """Decode example with custom feature decoding.
   1905 
   1906     Args:
   (...)
   1914         `dict[str, Any]`
   1915     """
   1917     return {
-> 1918         column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
   1919         if self._column_requires_decoding[column_name]
   1920         else value
   1921         for column_name, (feature, value) in zip_dict(
   1922             {key: value for key, value in self.items() if key in example}, example
   1923         )
   1924     }

File /opt/pytorch/lib/python3.8/site-packages/datasets/features/features.py:1339, in decode_nested_example(schema, obj, token_per_repo_id)
   1336 elif isinstance(schema, (Audio, Image)):
   1337     # we pass the token to read and decode files from private repositories in streaming mode
   1338     if obj is not None and schema.decode:
-> 1339         return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
   1340 return obj

File /opt/pytorch/lib/python3.8/site-packages/datasets/features/audio.py:191, in Audio.decode_example(self, value, token_per_repo_id)
    189 array = array.T
    190 if self.mono:
--> 191     array = librosa.to_mono(array)
    192 if self.sampling_rate and self.sampling_rate != sampling_rate:
    193     array = librosa.resample(array, orig_sr=sampling_rate, target_sr=self.sampling_rate)

File /opt/pytorch/lib/python3.8/site-packages/lazy_loader/__init__.py:78, in attach.<locals>.__getattr__(name)
     76 submod_path = f"{package_name}.{attr_to_modules[name]}"
     77 submod = importlib.import_module(submod_path)
---> 78 attr = getattr(submod, name)
     80 # If the attribute lives in a file (module) with the same
     81 # name as the attribute, ensure that the attribute and *not*
     82 # the module is accessible on the package.
     83 if name == attr_to_modules[name]:

File /opt/pytorch/lib/python3.8/site-packages/lazy_loader/__init__.py:77, in attach.<locals>.__getattr__(name)
     75 elif name in attr_to_modules:
     76     submod_path = f"{package_name}.{attr_to_modules[name]}"
---> 77     submod = importlib.import_module(submod_path)
     78     attr = getattr(submod, name)
     80     # If the attribute lives in a file (module) with the same
     81     # name as the attribute, ensure that the attribute and *not*
     82     # the module is accessible on the package.

File /usr/lib/python3.8/importlib/__init__.py:127, in import_module(name, package)
    125             break
    126         level += 1
--> 127 return _bootstrap._gcd_import(name[level:], package, level)

File <frozen importlib._bootstrap>:1014, in _gcd_import(name, package, level)

File <frozen importlib._bootstrap>:991, in _find_and_load(name, import_)

File <frozen importlib._bootstrap>:975, in _find_and_load_unlocked(name, import_)

File <frozen importlib._bootstrap>:671, in _load_unlocked(spec)

File <frozen importlib._bootstrap_external>:848, in exec_module(self, module)

File <frozen importlib._bootstrap>:219, in _call_with_frames_removed(f, *args, **kwds)

File /opt/pytorch/lib/python3.8/site-packages/librosa/core/audio.py:13
     11 import audioread
     12 import numpy as np
---> 13 import scipy.signal
     14 import soxr
     15 import lazy_loader as lazy

File /opt/pytorch/lib/python3.8/site-packages/scipy/signal/__init__.py:323
    314 from ._spline import (  # noqa: F401
    315     cspline2d,
    316     qspline2d,
   (...)
    319     symiirorder2,
    320 )
    322 from ._bsplines import *
--> 323 from ._filter_design import *
    324 from ._fir_filter_design import *
    325 from ._ltisys import *

File /opt/pytorch/lib/python3.8/site-packages/scipy/signal/_filter_design.py:16
     13 from numpy.polynomial.polynomial import polyval as npp_polyval
     14 from numpy.polynomial.polynomial import polyvalfromroots
---> 16 from scipy import special, optimize, fft as sp_fft
     17 from scipy.special import comb
     18 from scipy._lib._util import float_factorial

File /opt/pytorch/lib/python3.8/site-packages/scipy/optimize/__init__.py:405
      1 """
      2 =====================================================
      3 Optimization and root finding (:mod:`scipy.optimize`)
   (...)
    401 
    402 """
    404 from ._optimize import *
--> 405 from ._minimize import *
    406 from ._root import *
    407 from ._root_scalar import *

File /opt/pytorch/lib/python3.8/site-packages/scipy/optimize/_minimize.py:26
     24 from ._trustregion_krylov import _minimize_trust_krylov
     25 from ._trustregion_exact import _minimize_trustregion_exact
---> 26 from ._trustregion_constr import _minimize_trustregion_constr
     28 # constrained minimization
     29 from ._lbfgsb_py import _minimize_lbfgsb

File /opt/pytorch/lib/python3.8/site-packages/scipy/optimize/_trustregion_constr/__init__.py:4
      1 """This module contains the equality constrained SQP solver."""
----> 4 from .minimize_trustregion_constr import _minimize_trustregion_constr
      6 __all__ = ['_minimize_trustregion_constr']

File /opt/pytorch/lib/python3.8/site-packages/scipy/optimize/_trustregion_constr/minimize_trustregion_constr.py:5
      3 from scipy.sparse.linalg import LinearOperator
      4 from .._differentiable_functions import VectorFunction
----> 5 from .._constraints import (
      6     NonlinearConstraint, LinearConstraint, PreparedConstraint, strict_bounds)
      7 from .._hessian_update_strategy import BFGS
      8 from .._optimize import OptimizeResult

File /opt/pytorch/lib/python3.8/site-packages/scipy/optimize/_constraints.py:8
      6 from ._optimize import OptimizeWarning
      7 from warnings import warn, catch_warnings, simplefilter
----> 8 from numpy.testing import suppress_warnings
      9 from scipy.sparse import issparse
     12 def _arr_to_scalar(x):
     13     # If x is a numpy array, return x.item().  This will
     14     # fail if the array has more than one element.

File /opt/pytorch/lib/python3.8/site-packages/numpy/testing/__init__.py:11
      8 from unittest import TestCase
     10 from . import _private
---> 11 from ._private.utils import *
     12 from ._private.utils import (_assert_valid_refcount, _gen_alignment_data)
     13 from ._private import extbuild, decorators as dec

File /opt/pytorch/lib/python3.8/site-packages/numpy/testing/_private/utils.py:480
    476         pprint.pprint(desired, msg)
    477         raise AssertionError(msg.getvalue())
--> 480 @np._no_nep50_warning()
    481 def assert_almost_equal(actual,desired,decimal=7,err_msg='',verbose=True):
    482     """
    483     Raises an AssertionError if two items are not equal up to desired
    484     precision.
   (...)
    548 
    549     """
    550     __tracebackhide__ = True  # Hide traceback for py.test

File /opt/pytorch/lib/python3.8/site-packages/numpy/__init__.py:313, in __getattr__(attr)
    305     raise AttributeError(__former_attrs__[attr])
    307 # Importing Tester requires importing all of UnitTest which is not a
    308 # cheap import Since it is mainly used in test suits, we lazy import it
    309 # here to save on the order of 10 ms of import time for most users
    310 #
    311 # The previous way Tester was imported also had a side effect of adding
    312 # the full `numpy.testing` namespace
--> 313 if attr == 'testing':
    314     import numpy.testing as testing
    315     return testing

AttributeError: module 'numpy' has no attribute '_no_nep50_warning'

```


### Expected behavior

```
' Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.'
```

Also, make sure this script is provided for your official website so please update:
[script](https://huggingface.co/docs/transformers/model_doc/whisper)

Comments:
Hey @hi-sushanta,

Can you post `datasets`-related issues on the datasets library instead? 
https://github.com/huggingface/datasets

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.