code: def datasets() -> Mapping[str, Dataset]:
      sampling_rate = 16_000
      return {
          # Value feature
          "null": value(None, None),
          "bool": value(False, pd.BooleanDtype()),
          "int8": value(-7, pd.Int8Dtype()),
          "int16": value(-7, pd.Int16Dtype()),
          "int32": value(-7, pd.Int32Dtype()),
          "int64": value(-7, pd.Int64Dtype()),
          "uint8": value(7, pd.UInt8Dtype()),
          "uint16": value(7, pd.UInt16Dtype()),
          "uint32": value(7, pd.UInt32Dtype()),
          "uint64": value(7, pd.UInt64Dtype()),
          "float16": value(-3.14, np.float16),
          "float32": value(-3.14, np.float32),
          "float64": value(-3.14, np.float64),
          "time": value(datetime.time(1, 1, 1), None),
          "timestamp_1": value(pd.Timestamp(2020, 1, 1), None),
          "timestamp_2": value(
              pd.Timestamp(1513393355.5, unit="s"), None
          ),
          "timestamp_3": value(
              pd.Timestamp(1513393355500, unit="ms"), None
          ),
          "timestamp_tz": value(
              pd.Timestamp(year=2020, month=1, day=1, tz="US/Pacific"),
              None,
          ),
          "string": value("a string", pd.StringDtype(storage="python")),
          # other types of features
          "class_label": other(
              "positive", ClassLabel(names=["negative", "positive"])
          ),
          "dict": other({"a": 0}, None),
          "list": other([{"a": 0}], None),
          "sequence_simple": other([0], None),
          "sequence": other(
              [{"a": 0}], Sequence(feature={"a": Value(dtype="int64")})
          ),
          "array2d": other(
              np.zeros((2, 2), dtype="float32"),
              Array2D(shape=(2, 2), dtype="float32"),
          ),
          "array3d": other(
              np.zeros((2, 2, 2), dtype="float32"),
              Array3D(shape=(2, 2, 2), dtype="float32"),
          ),
          "array4d": other(
              np.zeros((2, 2, 2, 2), dtype="float32"),
              Array4D(shape=(2, 2, 2, 2), dtype="float32"),
          ),
          "array5d": other(
              np.zeros((2, 2, 2, 2, 2), dtype="float32"),
              Array5D(shape=(2, 2, 2, 2, 2), dtype="float32"),
          ),
          "audio": other(
              {
                  "array": [0.1, 0.2, 0.3],
                  "sampling_rate": sampling_rate,
              },
              Audio(sampling_rate=sampling_rate),
          ),
          "audio_ogg": other(
              str(
                  Path(__file__).resolve().parent
                  / "data"
                  / "test_audio_vorbis.ogg"
              ),
              Audio(sampling_rate=sampling_rate),
          ),
          "image": other(
              str(
                  Path(__file__).resolve().parent
                  / "data"
                  / "test_image_rgb.jpg"
              ),
              Image(),
          ),
          "translation": other(
              {"en": "the cat", "fr": "le chat"},
              Translation(languages=["en", "fr"]),
          ),
          "translation_variable_languages": other(
              {"en": "the cat", "fr": ["le chat", "la chatte"]},
              TranslationVariableLanguages(languages=["en", "fr"]),
          ),
          "images_list": other(
              [
                  str(
                      Path(__file__).resolve().parent
                      / "data"
                      / "test_image_rgb.jpg"
                  ),
                  str(
                      Path(__file__).resolve().parent
                      / "data"
                      / "test_image_rgb.jpg"
                  ),
              ],
              [Image()],
          ),
          "audios_list": other(
              [
                  {"array": [0.1, 0.2, 0.3], "sampling_rate": 16_000},
                  {"array": [0.1, 0.2, 0.3], "sampling_rate": 16_000},
              ],
              [Audio()],
          ),
          "images_sequence": other(
              [
                  str(
                      Path(__file__).resolve().parent
                      / "data"
                      / "test_image_rgb.jpg"
                  ),
                  str(
                      Path(__file__).resolve().parent
                      / "data"
                      / "test_image_rgb.jpg"
                  ),
              ],
              Sequence(feature=Image()),
          ),
          "audios_sequence": other(
              [
                  {"array": [0.1, 0.2, 0.3], "sampling_rate": 16_000},
                  {"array": [0.1, 0.2, 0.3], "sampling_rate": 16_000},
              ],
              Sequence(feature=Audio()),
          ),
          "dict_of_audios_and_images": other(
              {
                  "a": 0,
                  "b": [
                      str(
                          Path(__file__).resolve().parent
                          / "data"
                          / "test_image_rgb.jpg"
                      ),
                      str(
                          Path(__file__).resolve().parent
                          / "data"
                          / "test_image_rgb.jpg"
                      ),
                  ],
                  "c": {
                      "ca": [
                          {
                              "array": [0.1, 0.2, 0.3],
                              "sampling_rate": 16_000,
                          },
                          {
                              "array": [0.1, 0.2, 0.3],
                              "sampling_rate": 16_000,
                          },
                      ]
                  },
              },
              {
                  "a": Value(dtype="int64"),
                  "b": [Image()],
                  "c": {"ca": [Audio()]},
              },
          ),
          "sequence_of_dicts": other(
              [{"a": {"b": 0}}, {"a": {"b": 1}}],
              Sequence(feature={"a": {"b": Value(dtype="int64")}}),
          ),
          "none_value": other({"a": None}, {"a": Value(dtype="int64")}),
          "big": Dataset.from_pandas(
              pd.DataFrame(
                  {"col": ["a" * 1_234 for _ in range(4_567)]},
                  dtype=pd.StringDtype(storage="python"),
              )
          ),
      }
  
file_path: datasets-server/libs/libcommon/tests/fixtures/datasets.py
imports: import datetime
  from collections.abc import Mapping
  from pathlib import Path
  from typing import Any, Optional
  import numpy
  import pandas
  import pytest
  from datasets import Array2D, Array3D, Array4D, Array5D, Audio, ClassLabel, Dataset, Features, Image, Sequence, Translation, TranslationVariableLanguages, Value
  from datasets.features.features import FeatureType
label_desc: Use image node_id 3 for calling a global function with example usage: datasets() and returns: dict