Fix types

lightly/models/modules/memory_bank.py

@@ -4,7 +4,7 @@
 # All Rights Reserved
 
 import warnings
-from typing import Sequence, Union
+from typing import Sequence, Tuple, Union
 
 import torch
 from torch import Tensor
@@ -72,11 +72,13 @@ def __init__(
         self.size = size_tuple
         self.gather_distributed = gather_distributed
         self.feature_dim_first = feature_dim_first
+        self.bank: Tensor
         self.register_buffer(
             "bank",
             tensor=torch.empty(size=self.size, dtype=torch.float),
             persistent=False,
         )
+        self.bank_ptr: Tensor
         self.register_buffer(
             "bank_ptr",
             tensor=torch.empty(1, dtype=torch.long),
@@ -97,7 +99,7 @@ def __init__(
             self._init_memory_bank(dim=None)
 
     @torch.no_grad()
-    def _init_memory_bank(self, dim: Union[Sequence[int], None]):
+    def _init_memory_bank(self, dim: Union[Sequence[int], None]) -> None:
         """Initialize the memory bank if it's empty.
 
         Args:
@@ -116,7 +118,7 @@ def _init_memory_bank(self, dim: Union[Sequence[int], None]):
         self.bank_ptr = torch.zeros(1).type_as(self.bank_ptr)
 
     @torch.no_grad()
-    def _dequeue_and_enqueue(self, batch: Tensor):
+    def _dequeue_and_enqueue(self, batch: Tensor) -> None:
         """Dequeue the oldest batch and add the latest one
 
         Args:
@@ -141,7 +143,7 @@ def forward(
         output: Tensor,
         labels: Union[Tensor, None] = None,
         update: bool = False,
-    ):
+    ) -> Tuple[Tensor, Union[Tensor, None]]:
         """Query memory bank for additional negative samples
 
         Args:

lightly/utils/benchmarking/metric_callback.py

@@ -60,7 +60,7 @@ def _append_metrics(
         self, metrics_dict: Dict[str, List[float]], trainer: Trainer
     ) -> None:
         for name, value in trainer.callback_metrics.items():
-            if isinstance(value, float) or (
-                isinstance(value, Tensor) and value.numel() == 1
-            ):
-                metrics_dict.setdefault(name, []).append(float(value))
+            if isinstance(value, Tensor) and value.numel() > 1:
+                # Ignore non-scalar tensors.
+                continue
+            metrics_dict.setdefault(name, []).append(float(value))

tests/models/modules/test_memory_bank.py

@@ -8,11 +8,11 @@
 
 
 class TestNTXentLoss(unittest.TestCase):
-    def test_init__negative_size(self):
+    def test_init__negative_size(self) -> None:
         with self.assertRaises(ValueError):
             MemoryBankModule(size=-1)
 
-    def test_forward_easy(self):
+    def test_forward_easy(self) -> None:
         bsz = 3
         dim, size = 2, 9
         n = 33 * bsz
@@ -37,7 +37,7 @@ def test_forward_easy(self):
 
             ptr = (ptr + bsz) % size
 
-    def test_forward(self):
+    def test_forward(self) -> None:
         bsz = 3
         dim, size = 2, 10
         n = 33 * bsz
@@ -50,7 +50,7 @@ def test_forward(self):
             _, _ = memory_bank(output)
 
     @unittest.skipUnless(torch.cuda.is_available(), "cuda not available")
-    def test_forward__cuda(self):
+    def test_forward__cuda(self) -> None:
         bsz = 3
         dim, size = 2, 10
         n = 33 * bsz