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Revert "Update round size with 1 division behavior (#162203)"

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This reverts commit 12d2ef557f6e127100267c31a31572d8ab5cc788.

Reverted https://github.com/pytorch/pytorch/pull/162203 on behalf of https://github.com/izaitsevfb due to Diff reverted internally ([comment](https://github.com/pytorch/pytorch/pull/162203#issuecomment-3398622898))
This commit is contained in:
PyTorch MergeBot
2025-10-13 18:32:37 +00:00
parent 0ce945790e
commit 955cd7060b
2 changed files with 0 additions and 17 deletions
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2
c10/cuda/CUDACachingAllocator.cpp
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@ -2502,8 +2502,6 @@ class DeviceCachingAllocator {
auto divisions = CUDAAllocatorConfig::roundup_power2_divisions(size);
if (divisions > 1 && size > (kMinBlockSize * divisions)) {
return roundup_power2_next_division(size, divisions);
} else if (divisions == 1) {
return llvm::PowerOf2Ceil(size);
} else {
return kMinBlockSize * ((size + kMinBlockSize - 1) / kMinBlockSize);
}

15
test/test_cuda.py
View File

@ -4564,21 +4564,6 @@ class TestCudaMallocAsync(TestCase):
reg_mem = torch.cuda.memory_stats()[key_allocated]
self.assertEqual(reg_mem - start_mem, nbytes)
# Test division==1 case.
torch.cuda.memory.empty_cache()
div1_start_mem = torch.cuda.memory_stats()[key_allocated]
div1_start_requested = torch.cuda.memory_stats()[key_requested]
torch.cuda.memory._set_allocator_settings("roundup_power2_divisions:1")
torch.rand(nelems, device="cuda")
div1_end_mem = torch.cuda.memory_stats()[key_allocated]
div1_end_requested = torch.cuda.memory_stats()[key_requested]
self.assertEqual(div1_start_mem - start_mem, nbytes)
if not TEST_CUDAMALLOCASYNC:
# not supported with the cudaMallocAsync backend
self.assertEqual(div1_end_mem - div1_start_mem, power2_div(nbytes, 1))
self.assertEqual(div1_end_requested - div1_start_requested, nbytes)
with self.assertRaises(RuntimeError):
torch.cuda.memory._set_allocator_settings("foo:1,bar:2")