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DTensor support for bfloat16 stochastic rounding #3266
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3266
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 2 New FailuresAs of commit 82a05bd with merge base 1e473ed ( NEW FAILURES - The following jobs have failed:
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| # LICENSE file in the root directory of this source tree. | ||
| import torch | ||
| from torch import Tensor | ||
| try: |
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is this for different PyTorch versions? If yes, could you clarify which specific versions?
in general we support 3 most recent stable PyTorch releases max, so if it's older than that I'd just leave it out
| try: | ||
| from torch.distributed._tensor import DTensor | ||
| except Exception: | ||
| DTensor = tuple() |
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rethrow this instead returning tuple
| return x_f32_bits.view(torch.float32).bfloat16() | ||
| x_bf16_trunc = x_f32_bits.view(torch.float32).bfloat16() | ||
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| return DTensor.from_local( |
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looks reasonable, can we add a test to cover?
Resolves #2296
Upstream torch is not taking this seriously pytorch/pytorch#156649