remove RTTI check for TensorImpl shadow copy #22773
Closed
Conversation
This file contains hidden or 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
pytorchbot
added
module: autograd
ljk53
requested review from
dzhulgakov,
gchanan and
yf225
and removed request for
dzhulgakov and
yf225
pytorchbot
added
the
module: mkldnn
gchanan
requested changes
Jul 12, 2019
ljk53
force-pushed
the
export-D16212472
branch
2 times, most recently
from
53f7415 to
ac9baac
Compare
gchanan
reviewed
Jul 12, 2019
gchanan
approved these changes
Jul 12, 2019
Contributor
gchanan
left a comment
gchanan
left a comment
There was a problem hiding this comment.
approved assuming we figure out the correct thing to do for HIP.
ljk53
force-pushed
the
export-D16212472
branch
2 times, most recently
from
b0a7a9e to
bf13962
Compare
Contributor
Author
|
@pytorchbot retest this please |
Summary: We introduced RTTI in recent change: pytorch#21613 For internal mobile build we don't enable '-frtti' yet. This diff is trying to replace RTTI with alternative approach. According to dzhulgakov we could compare two tensors' type_id directly in most cases - which is more strict than comparing TensorImpl subclass type as TensorImpl -> type_id mapping is 1-to-n but it's more proper for this use case. The only two cases where we can relax direct type comparison (for legacy reason) are: 1. CPUTensor <-> CUDATensor; 2. SparseCPUTensor <-> SparseCUDATensor; Differential Revision: D16212472 fbshipit-source-id: 5946ca605e86820329762f84761db9142fd06a29
Contributor
facebook-github-bot
left a comment
facebook-github-bot
left a comment
There was a problem hiding this comment.
@ljk53 is landing this pull request. If you are a Facebook employee, you can view this diff on Phabricator.
zdevito
pushed a commit
to zdevito/ATen
that referenced
this pull request
Jul 16, 2019
Summary: We introduced RTTI in recent change: pytorch/pytorch#21613 For internal mobile build we don't enable '-frtti' yet. This diff is trying to replace RTTI with alternative approach. According to dzhulgakov we could compare two tensors' type_id directly in most cases - which is more strict than comparing TensorImpl subclass type as TensorImpl -> type_id mapping is 1-to-n but it's more proper for this use case. The only two cases where we can relax direct type comparison (for legacy reason) are: 1. CPUTensor <-> CUDATensor; 2. SparseCPUTensor <-> SparseCUDATensor; Pull Request resolved: pytorch/pytorch#22773 Differential Revision: D16277696 Pulled By: ljk53 fbshipit-source-id: 043e264fbacc37b7a11af2046983c70ddb62a599
Contributor
Contributor
|
@ljk53 are you not using gh tools? |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
6 participants
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.
Summary:
We introduced RTTI in recent change: #21613
For internal mobile build we don't enable '-frtti' yet. This diff is trying to replace
RTTI with alternative approach.
According to dzhulgakov we could compare two tensors' type_id directly in most cases -
which is more strict than comparing TensorImpl subclass type as TensorImpl -> type_id
mapping is 1-to-n but it's more proper for this use case.
The only two cases where we can relax direct type comparison (for legacy reason) are:
Differential Revision: D16212472