[DTensor] fix F.one_hot #162307
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[DTensor] fix F.one_hot #162307
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. [ghstack-poisoned]
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/162307
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. ghstack-source-id: 98860a4 Pull Request resolved: #162307
F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim [ghstack-poisoned]
zou3519
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. ghstack-source-id: 1cc8827 Pull Request resolved: #162307
F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim [ghstack-poisoned]
zou3519
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. ghstack-source-id: 0eac1d6 Pull Request resolved: #162307
ezyang
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Sep 6, 2025
F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. cc H-Huang awgu wanchaol fegin fduwjj wz337 wconstab d4l3k pragupta ezyang msaroufim [ghstack-poisoned]
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. Pull Request resolved: pytorch#162307 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117
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…or operations (#162651) Also updates the error message to point to the guide. Pull Request resolved: #162651 Approved by: https://github.com/ezyang ghstack dependencies: #162117, #162307
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This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: #163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: #162117, #162307, #162651
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This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: #163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: #162117, #162307, #162651
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. Pull Request resolved: pytorch#162307 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117
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Sep 22, 2025
…or operations (pytorch#162651) Also updates the error message to point to the guide. Pull Request resolved: pytorch#162651 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117, pytorch#162307
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This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: pytorch#163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: pytorch#162117, pytorch#162307, pytorch#162651
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. Pull Request resolved: pytorch#162307 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117
cleonard530
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Sep 22, 2025
…or operations (pytorch#162651) Also updates the error message to point to the guide. Pull Request resolved: pytorch#162651 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117, pytorch#162307
cleonard530
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This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: pytorch#163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: pytorch#162117, pytorch#162307, pytorch#162651
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This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: #163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: #162117, #162307, #162651
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F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due to an arange call creating a new Tensor (not DTensor). This PR fixes it by allowing implicit replication of Tensors for the arange call and the one consumer of the arange call (the at::eq call). Test Plan: - new test. Also, F.one_hot(num_classes=-1) is broken so we skip that. Pull Request resolved: pytorch#162307 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117
dsashidh
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Sep 26, 2025
…or operations (pytorch#162651) Also updates the error message to point to the guide. Pull Request resolved: pytorch#162651 Approved by: https://github.com/ezyang ghstack dependencies: pytorch#162117, pytorch#162307
dsashidh
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Sep 26, 2025
This PR adds an experimental way to register a custom rule for if inductor should partition the graph around an operator. Test Plan: - new test Pull Request resolved: pytorch#163310 Approved by: https://github.com/ProExpertProg, https://github.com/BoyuanFeng, https://github.com/eellison ghstack dependencies: pytorch#162117, pytorch#162307, pytorch#162651
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Stack from ghstack (oldest at bottom):
F.one_hot(dtensor) used to run into a mixed DTensor-Tensor operation due
to an arange call creating a new Tensor (not DTensor). This PR fixes it
by allowing implicit replication of Tensors for the arange call and the
one consumer of the arange call (the at::eq call).
Test Plan:
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @ezyang @msaroufim