[testing] replace hardcoded paths to allow running tests from anywhere (#6523)

* [testing] replace hardcoded paths to allow running tests from anywhere

* fix the merge conflict

src/transformers/testing_utils.py

+import inspect
 import os
 import re
 import shutil
@@ -144,6 +145,15 @@ def require_torch_and_cuda(test_case):
         return test_case
 
 
+def get_tests_dir():
+    """
+    returns the full path to the `tests` dir, so that the tests can be invoked from anywhere
+    """
+    # this function caller's __file__
+    caller__file__ = inspect.stack()[1][1]
+    return os.path.abspath(os.path.dirname(caller__file__))
+
+
 #
 # Helper functions for dealing with testing text outputs
 # The original code came from:

tests/test_tokenization_fast.py

@@ -15,7 +15,7 @@ from transformers import (
     TransfoXLTokenizer,
     is_torch_available,
 )
-from transformers.testing_utils import require_torch
+from transformers.testing_utils import get_tests_dir, require_torch
 from transformers.tokenization_distilbert import DistilBertTokenizerFast
 from transformers.tokenization_openai import OpenAIGPTTokenizerFast
 from transformers.tokenization_roberta import RobertaTokenizerFast
@@ -42,7 +42,7 @@ class CommonFastTokenizerTest(unittest.TestCase):
     TOKENIZERS_CLASSES = frozenset([])
 
     def setUp(self) -> None:
-        with open("tests/fixtures/sample_text.txt", encoding="utf-8") as f_data:
+        with open(f"{get_tests_dir()}/fixtures/sample_text.txt", encoding="utf-8") as f_data:
             self._data = f_data.read().replace("\n\n", "\n").strip()
 
     def test_all_tokenizers(self):

tests/test_trainer.py

@@ -4,7 +4,7 @@ import nlp
 import numpy as np
 
 from transformers import AutoTokenizer, TrainingArguments, is_torch_available
-from transformers.testing_utils import require_torch
+from transformers.testing_utils import get_tests_dir, require_torch
 
 
 if is_torch_available():
@@ -20,7 +20,7 @@ if is_torch_available():
     )
 
 
-PATH_SAMPLE_TEXT = "./tests/fixtures/sample_text.txt"
+PATH_SAMPLE_TEXT = f"{get_tests_dir()}/fixtures/sample_text.txt"
 
 
 class RegressionDataset:
@@ -262,7 +262,7 @@ class TrainerIntegrationTest(unittest.TestCase):
         tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
         model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID)
         data_args = GlueDataTrainingArguments(
-            task_name="mrpc", data_dir="./tests/fixtures/tests_samples/MRPC", overwrite_cache=True
+            task_name="mrpc", data_dir=f"{get_tests_dir()}/fixtures/tests_samples/MRPC", overwrite_cache=True
         )
         eval_dataset = GlueDataset(data_args, tokenizer=tokenizer, mode="dev")