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[xnnpack][lite-int] Handle Constant Data #89445
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Handling constant data for xnnpack delegation. This allows us to handle new modules like such: ``` class Module(torch.nn.Module): def __init__(self): super().__init__() self._constant = torch.ones(4, 4, 4) def forward(self, x): return x + self._constant ``` this is the precursor work to handling convolution, as we need to serialize constant data(weights) Differential Revision: [D41050349](https://our.internmc.facebook.com/intern/diff/D41050349/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/89445
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 60f0edf: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
Handling constant data for xnnpack delegation. This allows us to handle new modules like such: ``` class Module(torch.nn.Module): def __init__(self): super().__init__() self._constant = torch.ones(4, 4, 4) def forward(self, x): return x + self._constant ``` this is the precursor work to handling convolution, as we need to serialize constant data(weights) Differential Revision: [D41050349](https://our.internmc.facebook.com/intern/diff/D41050349/) ghstack-source-id: 174129439 Pull Request resolved: #89445
Handling constant data for xnnpack delegation. This allows us to handle new modules like such: ``` class Module(torch.nn.Module): def __init__(self): super().__init__() self._constant = torch.ones(4, 4, 4) def forward(self, x): return x + self._constant ``` this is the precursor work to handling convolution, as we need to serialize constant data(weights) Differential Revision: [D41050349](https://our.internmc.facebook.com/intern/diff/D41050349/) [ghstack-poisoned]
Pull Request resolved: #89445 Handling constant data for xnnpack delegation. This allows us to handle new modules like such: ``` class Module(torch.nn.Module): def __init__(self): super().__init__() self._constant = torch.ones(4, 4, 4) def forward(self, x): return x + self._constant ``` this is the precursor work to handling convolution, as we need to serialize constant data(weights) ghstack-source-id: 174132826 Differential Revision: [D41050349](https://our.internmc.facebook.com/intern/diff/D41050349/)
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LGTM
@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Handling constant data for xnnpack delegation. This allows us to handle new modules like such: ``` class Module(torch.nn.Module): def __init__(self): super().__init__() self._constant = torch.ones(4, 4, 4) def forward(self, x): return x + self._constant ``` this is the precursor work to handling convolution, as we need to serialize constant data(weights) Differential Revision: [D41050349](https://our.internmc.facebook.com/intern/diff/D41050349/) Pull Request resolved: pytorch#89445 Approved by: https://github.com/digantdesai
Stack from ghstack (oldest at bottom):
Handling constant data for xnnpack delegation. This allows us to handle new modules like such:
this is the precursor work to handling convolution, as we need to serialize constant data(weights)
Differential Revision: D41050349