Revert "Do not materialize entire randperm in RandomSampler (#103339)"

pytorchmergebot · pytorchmergebot · commit 3a284dae30e1 · 2023-10-26T18:53:14.000Z
This reverts commit d80174e. Reverted #103339 on behalf of https://github.com/kit1980 due to Cause issues on MPS, and also fails without numpy ([comment](#103339 (comment)))
diff --git a/torch/utils/data/sampler.py b/torch/utils/data/sampler.py
@@ -157,13 +157,12 @@ def __iter__(self) -> Iterator[int]:
 
         if self.replacement:
             for _ in range(self.num_samples // 32):
-                yield from map(int, torch.randint(high=n, size=(32,), dtype=torch.int64, generator=generator).numpy())
-            final_samples = torch.randint(high=n, size=(self.num_samples % 32,), dtype=torch.int64, generator=generator)
-            yield from map(int, final_samples.numpy())
+                yield from torch.randint(high=n, size=(32,), dtype=torch.int64, generator=generator).tolist()
+            yield from torch.randint(high=n, size=(self.num_samples % 32,), dtype=torch.int64, generator=generator).tolist()
         else:
             for _ in range(self.num_samples // n):
-                yield from map(int, torch.randperm(n, generator=generator).numpy())
-            yield from map(int, torch.randperm(n, generator=generator)[:self.num_samples % n].numpy())
+                yield from torch.randperm(n, generator=generator).tolist()
+            yield from torch.randperm(n, generator=generator).tolist()[:self.num_samples % n]
 
     def __len__(self) -> int:
         return self.num_samples
