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
@@ -57,40 +59,45 @@ else:
 
 
 _tf_version = "N/A"
-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 = (
-            "tensorflow",
-            "tensorflow-cpu",
-            "tensorflow-gpu",
-            "tf-nightly",
-            "tf-nightly-cpu",
-            "tf-nightly-gpu",
-            "intel-tensorflow",
-            "intel-tensorflow-avx512",
-            "tensorflow-rocm",
-            "tensorflow-macos",
-            "tensorflow-aarch64",
-        )
-        _tf_version = None
-        # For the metadata, we have to look for both tensorflow and tensorflow-cpu
-        for pkg in candidates:
-            try:
-                _tf_version = importlib_metadata.version(pkg)
-                break
-            except importlib_metadata.PackageNotFoundError:
-                pass
-        _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.")
-            _tf_available = False
-        else:
-            logger.info(f"TensorFlow version {_tf_version} available.")
+if FORCE_TF_AVAILABLE in ENV_VARS_TRUE_VALUES:
+    _tf_available = True
 else:
-    logger.info("Disabling Tensorflow because USE_TORCH is set")
-    _tf_available = False
+    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 = (
+                "tensorflow",
+                "tensorflow-cpu",
+                "tensorflow-gpu",
+                "tf-nightly",
+                "tf-nightly-cpu",
+                "tf-nightly-gpu",
+                "intel-tensorflow",
+                "intel-tensorflow-avx512",
+                "tensorflow-rocm",
+                "tensorflow-macos",
+                "tensorflow-aarch64",
+            )
+            _tf_version = None
+            # For the metadata, we have to look for both tensorflow and tensorflow-cpu
+            for pkg in candidates:
+                try:
+                    _tf_version = importlib_metadata.version(pkg)
+                    break
+                except importlib_metadata.PackageNotFoundError:
+                    pass
+            _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."
+                )
+                _tf_available = False
+            else:
+                logger.info(f"TensorFlow version {_tf_version} available.")
+    else:
+        logger.info("Disabling Tensorflow because USE_TORCH is set")
+        _tf_available = False
 
 
 if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES: