Allow soft dependencies in the namespace with ImportErrors at use (#7537)

* PoC on RAG

* Format class name/obj name

* Better name in message

* PoC on one TF model

* Add PyTorch and TF dummy objects + script

* Treat scikit-learn

* Bad copy pastes

* Typo

src/transformers/file_utils.py

@@ -133,6 +133,15 @@ try:
 except ImportError:
     _faiss_available = False
 
+try:
+    import sklearn.metrics  # noqa: F401
+
+    import scipy.stats  # noqa: F401
+
+    _has_sklearn = True
+except (AttributeError, ImportError):
+    _has_sklearn = False
+
 
 default_cache_path = os.path.join(torch_cache_home, "transformers")
 
@@ -194,6 +203,88 @@ def is_faiss_available():
     return _faiss_available
 
 
+def is_sklearn_available():
+    return _has_sklearn
+
+
+DATASETS_IMPORT_ERROR = """
+{0} requires the 🤗 Datasets library but it was not found in your enviromnent. You can install it with:
+```
+pip install datasets
+```
+In a notebook or a colab, you can install it by executing a cell with
+```
+!pip install datasets
+```
+then restarting your kernel.
+
+Note that if you have a local folder named `datasets` or a local python file named `datasets.py` in your current
+working directory, python may try to import this instead of the 🤗 Datasets library. You should rename this folder or
+that python file if that's the case.
+"""
+
+
+FAISS_IMPORT_ERROR = """
+{0} requires the faiss library but it was not found in your enviromnent. Checkout the instructions on the
+installation page of its repo: https://github.com/facebookresearch/faiss/blob/master/INSTALL.md and follow the ones
+that match your enviromnent.
+"""
+
+
+PYTORCH_IMPORT_ERROR = """
+{0} requires the PyTorch library but it was not found in your enviromnent. Checkout the instructions on the
+installation page: https://pytorch.org/get-started/locally/ and follow the ones that match your enviromnent.
+"""
+
+
+SKLEARN_IMPORT_ERROR = """
+{0} requires the scikit-learn library but it was not found in your enviromnent. You can install it with:
+```
+pip install -U scikit-learn
+```
+In a notebook or a colab, you can install it by executing a cell with
+```
+!pip install -U scikit-learn
+```
+"""
+
+
+TENSORFLOW_IMPORT_ERROR = """
+{0} requires the TensorFlow library but it was not found in your enviromnent. Checkout the instructions on the
+installation page: https://www.tensorflow.org/install and follow the ones that match your enviromnent.
+"""
+
+
+def requires_datasets(obj):
+    name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
+    if not is_datasets_available():
+        raise ImportError(DATASETS_IMPORT_ERROR.format(name))
+
+
+def requires_faiss(obj):
+    name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
+    if not is_faiss_available():
+        raise ImportError(FAISS_IMPORT_ERROR.format(name))
+
+
+def requires_pytorch(obj):
+    name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
+    if not is_torch_available():
+        raise ImportError(PYTORCH_IMPORT_ERROR.format(name))
+
+
+def requires_sklearn(obj):
+    name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
+    if not is_sklearn_available():
+        raise ImportError(SKLEARN_IMPORT_ERROR.format(name))
+
+
+def requires_tf(obj):
+    name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
+    if not is_tf_available():
+        raise ImportError(TENSORFLOW_IMPORT_ERROR.format(name))
+
+
 def add_start_docstrings(*docstr):
     def docstring_decorator(fn):
         fn.__doc__ = "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "")