Row 86640
Content Data
This page contains data entry 86640 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
You should have a fixed layout for layers to devices. Don't move layers around during forward. Move input tensors instead. This is called CPU offloading. Try to figure which layers are most memory heavy, and move them to CPU during model initialization before first forward pass.
Once you have a good forward run, the autograd engine will know how to move the data in the backward.
| Field | Value |
|---|---|
| text | You should have a fixed layout for layers to devices. Don't move layers around during forward. Move input tensors instead. This is called CPU offloading. Try to figure which layers are most memory heavy, and move them to CPU during model initialization before first forward pass. Once you have a good forward run, the autograd engine will know how to move the data in the backward. |
| label | r/pytorch |
| dataType | comment |
| communityName | r/pytorch |
| datetime | 2024-05-24 |
| username_encoded | Z0FBQUFBQm5Lak1wRHJTRlhZemdHeUFiQ1dpclBRZ0FIWmV2TXBjTUlzM3dwckdKZzh6NktFSXdPSzZqZGFGV0NleTNBTDJYSlkxTUVOa2JFanctREV4SzJ2RkM3ZktxN2c9PQ== |
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Raw Record
{
"text": "You should have a fixed layout for layers to devices. \nDon't move layers around during forward. Move input tensors instead. This is called CPU offloading. Try to figure which layers are most memory heavy, and move them to CPU during model initialization before first forward pass. \n\nOnce you have a good forward run, the autograd engine will know how to move the data in the backward.",
"label": "r/pytorch",
"dataType": "comment",
"communityName": "r/pytorch",
"datetime": "2024-05-24",
"username_encoded": "Z0FBQUFBQm5Lak1wRHJTRlhZemdHeUFiQ1dpclBRZ0FIWmV2TXBjTUlzM3dwckdKZzh6NktFSXdPSzZqZGFGV0NleTNBTDJYSlkxTUVOa2JFanctREV4SzJ2RkM3ZktxN2c9PQ==",
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}
Entry Information
- Entry ID: 86640
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000