Minor fixes in the VQA tutorial #196
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
NarineK
commented
Dec 4, 2019
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "vqa_resnet = VQA_Resnet_Model(vqa_net.module.text.embedding.num_embeddings)\n", | ||
| "# `device_ids` contains a list of GPU ids which are used for paralelization supported by `DataParallel`\n", | ||
| "vqa_resnet = torch.nn.DataParallel(vqa_resnet, device_ids=[0,1])\n", |
There was a problem hiding this comment.
Removing fixed number of devices in order to be able to take advantage of all of them.
NarineK
commented
Dec 4, 2019
| @@ -134,7 +128,7 @@ | |||
| "metadata": {}, | |||
| "outputs": [], | |||
| "source": [ | |||
| "vqa_net = torch.nn.DataParallel(Net(num_tokens), device_ids=[0,1])\n", | |||
| "vqa_net = torch.nn.DataParallel(Net(num_tokens))\n", | |||
There was a problem hiding this comment.
Removing fixed number of devices in order to be able to take advantage of all of them.
| "\n", | ||
| " def save_output(module, input, output):\n", | ||
| " self.buffer = output\n", | ||
| " with lock:\n", | ||
| " self.buffer[output.device]= output\n", |
|
LGTM (beside the nit) Thanks, addressed the nit |
orionr
approved these changes
Dec 5, 2019
There was a problem hiding this comment.
@NarineK has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.
miguelmartin75
pushed a commit
to miguelmartin75/captum
that referenced
this pull request
Dec 20, 2019
…ch#196) Summary: allow-large-files + Tested and added proper support for DataParallel that is being executed on all GPUs. Before we used to fix it to 2 devices only. Pull Request resolved: pytorch#196 Differential Revision: D18827192 Pulled By: NarineK fbshipit-source-id: 1c3c0021253e35078f1a72ac879edabc482a4ccb
miguelmartin75
pushed a commit
to miguelmartin75/captum
that referenced
this pull request
Dec 20, 2019
…ch#196) Summary: allow-large-files + Tested and added proper support for DataParallel that is being executed on all GPUs. Before we used to fix it to 2 devices only. Pull Request resolved: pytorch#196 Differential Revision: D18827192 Pulled By: NarineK fbshipit-source-id: 1c3c0021253e35078f1a72ac879edabc482a4ccb
NarineK
added a commit
to NarineK/captum-1
that referenced
this pull request
Nov 19, 2020
…ch#196) Summary: allow-large-files + Tested and added proper support for DataParallel that is being executed on all GPUs. Before we used to fix it to 2 devices only. Pull Request resolved: pytorch#196 Differential Revision: D18827192 Pulled By: NarineK fbshipit-source-id: 1c3c0021253e35078f1a72ac879edabc482a4ccb
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Added Early Forward Termination Exception for the resnet model after accessing the 4th layer and tested that it works properly with DataParallel
Tested and added proper support for DataParallel that is being executed on all GPUs. Before we used to fix it to 2 devices only.