Redirect datasets output

docs/source/notebooks/walkthrough.ipynb

@@ -158,11 +158,16 @@
     }
    ],
    "source": [
-    "import datasets\n",
+    "from datasets import load_dataset\n",
+    "from contextlib import redirect_stdout\n",
     "from pprint import pprint\n",
-    "# Loading a huggingface dataset returns an instance of DatasetDict\n",
-    "# which contains the dataset splits (usually: train, valid, test) \n",
-    "imdb = datasets.load_dataset('imdb')\n",
+    "\n",
+    "# Silence download logs\n",
+    "with redirect_stdout(None):\n",
+    "    # Loading a huggingface dataset returns an instance of DatasetDict\n",
+    "    # which contains the dataset splits (usually: train, valid, test) \n",
+    "    imdb = load_dataset('imdb')\n",
+    "\n",
     "print(imdb.keys())\n",
     "\n",
     "# Each dataset has a set of features which need to be mapped\n",

docs/source/walkthrough.rst

@@ -73,11 +73,16 @@ Converting a dataset from 🤗 datasets into Podium requires some work from your
 
 .. code-block:: python
 
-  >>> import datasets
+  >>> from datasets import load_dataset
+  >>> from contextlib import redirect_stdout
   >>> from pprint import pprint
-  >>> # Loading a huggingface dataset returns an instance of DatasetDict
-  >>> # which contains the dataset splits (usually: train, valid, test) 
-  >>> imdb = datasets.load_dataset('imdb')
+  >>>
+  >>> # Silence download logs
+  >>> with redirect_stdout(None):
+  >>>     # Loading a huggingface dataset returns an instance of DatasetDict
+  >>>     # which contains the dataset splits (usually: train, valid, test) 
+  >>>     imdb = load_dataset('imdb')
+  >>>
   >>> print(imdb.keys())
   dict_keys(['train', 'test', 'unsupervised'])
   >>>