tidy: PyTorch now always at 2.x, remove unnecessary code that thinks it can still be 1.x

tests/unit/utilities/test_devices.py

@@ -48,23 +48,12 @@ def test_get_device_cuda_available():
 
 @patch.dict("os.environ", {"TRANSFORMERLENS_ALLOW_MPS": "1"})
 def test_get_device_mps_available():
-    """Test get_device when MPS is available, PyTorch version >= 2.0, and env var set."""
+    """Test get_device when MPS is available and env var set."""
     with patch("torch.cuda.is_available", return_value=False):
         with patch("torch.backends.mps.is_available", return_value=True):
             with patch("torch.backends.mps.is_built", return_value=True):
-                with patch("torch.__version__", "2.0.0"):
-                    device = get_device()
-                    assert device == "mps"
-
-
-def test_get_device_mps_pytorch_1x():
-    """Test get_device when MPS is available but PyTorch version < 2.0."""
-    with patch("torch.cuda.is_available", return_value=False):
-        with patch("torch.backends.mps.is_available", return_value=True):
-            with patch("torch.backends.mps.is_built", return_value=True):
-                with patch("torch.__version__", "1.13.0"):
-                    device = get_device()
-                    assert device == "cpu"
+                device = get_device()
+                assert device == "mps"
 
 
 def test_get_device_cpu_fallback():

transformer_lens/HookedTransformer.py

@@ -35,7 +35,6 @@
 import torch.nn.functional as F
 import tqdm.auto as tqdm
 from jaxtyping import Float, Int
-from packaging import version
 from transformers import AutoTokenizer, PreTrainedModel, PreTrainedTokenizerBase
 from transformers.models.auto.tokenization_auto import AutoTokenizer
 from transformers.tokenization_utils_base import PreTrainedTokenizerBase
@@ -1345,9 +1344,6 @@ def from_pretrained(
             load_in_8bit = qc.get("load_in_8bit", False)
             quant_method = qc.get("quant_method", "")
             assert not load_in_8bit, "8-bit quantization is not supported"
-            assert not (
-                load_in_4bit and (version.parse(torch.__version__) < version.parse("2.1.1"))
-            ), "Quantization is only supported for torch versions >= 2.1.1"
             assert not (
                 load_in_4bit and ("llama" not in model_name.lower())
             ), "Quantization is only supported for Llama models"

transformer_lens/utilities/devices.py

@@ -57,8 +57,7 @@ def get_device() -> str:
     """Get the best available device, with MPS safety checks.
 
     MPS is only auto-selected when the environment variable
-    ``TRANSFORMERLENS_ALLOW_MPS=1`` is set **and** the installed PyTorch
-    version is 2.0 or higher.
+    ``TRANSFORMERLENS_ALLOW_MPS=1`` is set.
 
     Returns:
         str: The best available device name (cuda, mps, or cpu)
@@ -67,17 +66,15 @@ def get_device() -> str:
         return "cuda"
 
     if torch.backends.mps.is_available() and torch.backends.mps.is_built():
-        major_version = int(torch.__version__.split(".")[0])
-        if major_version >= 2:
-            # Only auto-select MPS when explicitly opted-in via env var
-            if os.environ.get("TRANSFORMERLENS_ALLOW_MPS", "") == "1":
-                return "mps"
-            logging.info(
-                "MPS device available but not auto-selected due to known correctness issues "
-                "(PyTorch %s). Set TRANSFORMERLENS_ALLOW_MPS=1 to override. See: "
-                "https://github.com/TransformerLensOrg/TransformerLens/issues/1178",
-                torch.__version__,
-            )
+        # Only auto-select MPS when explicitly opted-in via env var
+        if os.environ.get("TRANSFORMERLENS_ALLOW_MPS", "") == "1":
+            return "mps"
+        logging.info(
+            "MPS device available but not auto-selected due to known correctness issues "
+            "(PyTorch %s). Set TRANSFORMERLENS_ALLOW_MPS=1 to override. See: "
+            "https://github.com/TransformerLensOrg/TransformerLens/issues/1178",
+            torch.__version__,
+        )
 
     return "cpu"