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[DTensor] Add sharding strategy to aten.view.dtype #144286
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module: dtensor
distributed tensor tag
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awgu
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Jan 6, 2025
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…se op" Fixes #144286 Viewing a tensor to a different dtype is pointwise and does not require any redistribution. cc H-Huang kwen2501 wanchaol fegin fduwjj wz337 wconstab d4l3k c-p-i-o [ghstack-poisoned]
awgu
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Jan 8, 2025
Fixes #144286 Viewing a tensor to a different dtype is pointwise and does not require any redistribution. cc H-Huang kwen2501 wanchaol fegin fduwjj wz337 wconstab d4l3k c-p-i-o [ghstack-poisoned]
awgu
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Jan 8, 2025
…se op" Fixes #144286 Viewing a tensor to a different dtype is pointwise and does not require any redistribution. cc H-Huang kwen2501 wanchaol fegin fduwjj wz337 wconstab d4l3k c-p-i-o [ghstack-poisoned]
awgu
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Jan 8, 2025
Fixes #144286 Viewing a tensor to a different dtype is pointwise and does not require any redistribution. cc H-Huang kwen2501 wanchaol fegin fduwjj wz337 wconstab d4l3k c-p-i-o [ghstack-poisoned]
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Labels
module: dtensor
distributed tensor tag
oncall: distributed
Add this issue/PR to distributed oncall triage queue
🚀 The feature, motivation and pitch
Would be great to have a sharding strategy for aten.view.dtype. Currently, when doing .view(dtype) on a DTensor, you get the following error:
This has caused issues for FSDP2 + stochastic rounding for me. See: pytorch/ao#1505
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cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @tianyu-l @XilunWu
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