Move tests outside of library.

tests/utils.py

@@ -0,0 +1,88 @@
+import os
+import tempfile
+import unittest
+from distutils.util import strtobool
+
+from transformers.file_utils import _tf_available, _torch_available
+
+
+CACHE_DIR = os.path.join(tempfile.gettempdir(), "transformers_test")
+
+SMALL_MODEL_IDENTIFIER = "julien-c/bert-xsmall-dummy"
+
+
+def parse_flag_from_env(key, default=False):
+    try:
+        value = os.environ[key]
+    except KeyError:
+        # KEY isn't set, default to `default`.
+        _value = default
+    else:
+        # KEY is set, convert it to True or False.
+        try:
+            _value = strtobool(value)
+        except ValueError:
+            # More values are supported, but let's keep the message simple.
+            raise ValueError("If set, {} must be yes or no.".format(key))
+    return _value
+
+
+_run_slow_tests = parse_flag_from_env("RUN_SLOW", default=False)
+_run_custom_tokenizers = parse_flag_from_env("RUN_CUSTOM_TOKENIZERS", default=False)
+
+
+def slow(test_case):
+    """
+    Decorator marking a test as slow.
+
+    Slow tests are skipped by default. Set the RUN_SLOW environment variable
+    to a truthy value to run them.
+
+    """
+    if not _run_slow_tests:
+        test_case = unittest.skip("test is slow")(test_case)
+    return test_case
+
+
+def custom_tokenizers(test_case):
+    """
+    Decorator marking a test for a custom tokenizer.
+
+    Custom tokenizers require additional dependencies, and are skipped
+    by default. Set the RUN_CUSTOM_TOKENIZERS environment variable
+    to a truthy value to run them.
+    """
+    if not _run_custom_tokenizers:
+        test_case = unittest.skip("test of custom tokenizers")(test_case)
+    return test_case
+
+
+def require_torch(test_case):
+    """
+    Decorator marking a test that requires PyTorch.
+
+    These tests are skipped when PyTorch isn't installed.
+
+    """
+    if not _torch_available:
+        test_case = unittest.skip("test requires PyTorch")(test_case)
+    return test_case
+
+
+def require_tf(test_case):
+    """
+    Decorator marking a test that requires TensorFlow.
+
+    These tests are skipped when TensorFlow isn't installed.
+
+    """
+    if not _tf_available:
+        test_case = unittest.skip("test requires TensorFlow")(test_case)
+    return test_case
+
+
+if _torch_available:
+    # Set the USE_CUDA environment variable to select a GPU.
+    torch_device = "cuda" if parse_flag_from_env("USE_CUDA") else "cpu"
+else:
+    torch_device = None