Allow users to force TF availability (#18650)

* Allow users to force TF availability

* Correctly name the envvar!

src/transformers/utils/import_utils.py

@@ -42,6 +42,8 @@ USE_TF = os.environ.get("USE_TF", "AUTO").upper()
 USE_TORCH = os.environ.get("USE_TORCH", "AUTO").upper()
 USE_JAX = os.environ.get("USE_FLAX", "AUTO").upper()
 
+FORCE_TF_AVAILABLE = os.environ.get("FORCE_TF_AVAILABLE", "AUTO").upper()
+
 _torch_version = "N/A"
 if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
     _torch_available = importlib.util.find_spec("torch") is not None
@@ -57,7 +59,10 @@ else:
 
 
 _tf_version = "N/A"
-if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
+if FORCE_TF_AVAILABLE in ENV_VARS_TRUE_VALUES:
+    _tf_available = True
+else:
+    if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
         _tf_available = importlib.util.find_spec("tensorflow") is not None
         if _tf_available:
             candidates = (
@@ -84,11 +89,13 @@ if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VA
             _tf_available = _tf_version is not None
         if _tf_available:
             if version.parse(_tf_version) < version.parse("2"):
-            logger.info(f"TensorFlow found but with version {_tf_version}. Transformers requires version 2 minimum.")
+                logger.info(
+                    f"TensorFlow found but with version {_tf_version}. Transformers requires version 2 minimum."
+                )
                 _tf_available = False
             else:
                 logger.info(f"TensorFlow version {_tf_version} available.")
-else:
+    else:
         logger.info("Disabling Tensorflow because USE_TORCH is set")
         _tf_available = False