[BE] Remove dependency on six and future
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XuehaiPan
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/94709
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 44ea65d: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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We should revisit all changes from @XuehaiPan would you have some time to look into that by any chance? |
pytorchmergebot
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Mar 28, 2023
…es (#97737) Slack thread: https://pytorch.slack.com/archives/GEEQ2K4MD/p1679962409906099 I was seeing some massive (~2x) slowdowns on a job after running it on PyTorch 2.0. From some profiling in `py-spy` it looked like the pin_memory thread was doing a lot more work than before. Looking at a trace in `nsys` I saw the thread doing the forward pass having a bunch of `pthread_cond_timedwait` with GIL reacquire calls in it’s call stack, and it seemed like the thread doing the forward pass was getting blocked (waiting for the GIL) by the pin memory thread (which was holding the GIL). After some debugging I found out the issue. If a `bytes` was passed into `pin_memory`, previously in 1.13 (before #94709) it would short-circuit and return here https://github.com/pytorch/pytorch/blob/d922c29a22e4bf0fba49526f7536395eb8cd66f4/torch/utils/data/_utils/pin_memory.py#L54-L55 since `bytes` was in `torch._six.string_classes`: ``` >>> from torch._six import string_classes >>> string_classes (<class 'str'>, <class 'bytes'>) >>> ``` However after #94709, if a `bytes` was passed into `pin_memory` it would fall into here instead https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L68-L73 because the previous check is now doing `isinstance(data, str)` instead of `isinstance(data, (str, bytes))`! https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L56-L57 As a result, `pin_memory` gets called recursively for each element in the `bytes` leading to a ton of wasted recursion. This also explains the slowdown / GIL contention I was seeing. This PR simply changes `isinstance(data, str)` to `isinstance(data, (str, bytes))` to match the behavior before #94709 Pull Request resolved: #97737 Approved by: https://github.com/albanD, https://github.com/NivekT
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@albanD I opened a PR to re-add relevant |
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Revisit `torch._six.string_classes` (which is `(str, bytes)`) removal: `isinstance(obj, string_classes) -> isinstance(obj, str)`.
Both `str` and `bytes` are `Sequence` classes.
```python
In [1]: from typing import Sequence
In [2]: issubclass(bytes, Sequence)
Out[2]: True
In [3]: issubclass(str, Sequence)
Out[3]: True
```
Re-add `bytes` to type guards like:
```python
def is_seq(obj):
return isinstance(obj, Sequence) and not isinstance(obj, (str, bytes))
```
Ref:
- #94709 (comment)
- #97737
- #97789
Pull Request resolved: #97863
Approved by: https://github.com/Skylion007, https://github.com/albanD
XuehaiPan
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Mar 31, 2023
…es (pytorch#97737) Slack thread: https://pytorch.slack.com/archives/GEEQ2K4MD/p1679962409906099 I was seeing some massive (~2x) slowdowns on a job after running it on PyTorch 2.0. From some profiling in `py-spy` it looked like the pin_memory thread was doing a lot more work than before. Looking at a trace in `nsys` I saw the thread doing the forward pass having a bunch of `pthread_cond_timedwait` with GIL reacquire calls in it’s call stack, and it seemed like the thread doing the forward pass was getting blocked (waiting for the GIL) by the pin memory thread (which was holding the GIL). After some debugging I found out the issue. If a `bytes` was passed into `pin_memory`, previously in 1.13 (before pytorch#94709) it would short-circuit and return here https://github.com/pytorch/pytorch/blob/d922c29a22e4bf0fba49526f7536395eb8cd66f4/torch/utils/data/_utils/pin_memory.py#L54-L55 since `bytes` was in `torch._six.string_classes`: ``` >>> from torch._six import string_classes >>> string_classes (<class 'str'>, <class 'bytes'>) >>> ``` However after pytorch#94709, if a `bytes` was passed into `pin_memory` it would fall into here instead https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L68-L73 because the previous check is now doing `isinstance(data, str)` instead of `isinstance(data, (str, bytes))`! https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L56-L57 As a result, `pin_memory` gets called recursively for each element in the `bytes` leading to a ton of wasted recursion. This also explains the slowdown / GIL contention I was seeing. This PR simply changes `isinstance(data, str)` to `isinstance(data, (str, bytes))` to match the behavior before pytorch#94709 Pull Request resolved: pytorch#97737 Approved by: https://github.com/albanD, https://github.com/NivekT
XuehaiPan
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…97863) Revisit `torch._six.string_classes` (which is `(str, bytes)`) removal: `isinstance(obj, string_classes) -> isinstance(obj, str)`. Both `str` and `bytes` are `Sequence` classes. ```python In [1]: from typing import Sequence In [2]: issubclass(bytes, Sequence) Out[2]: True In [3]: issubclass(str, Sequence) Out[3]: True ``` Re-add `bytes` to type guards like: ```python def is_seq(obj): return isinstance(obj, Sequence) and not isinstance(obj, (str, bytes)) ``` Ref: - pytorch#94709 (comment) - pytorch#97737 - pytorch#97789 Pull Request resolved: pytorch#97863 Approved by: https://github.com/Skylion007, https://github.com/albanD
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Torch does not support torch._six anymore, so removed from torch._six import string_classes Replaced string_classes with str. Reference: pytorch/pytorch#94709
NivekT
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Apr 4, 2023
…es (#97737) Slack thread: https://pytorch.slack.com/archives/GEEQ2K4MD/p1679962409906099 I was seeing some massive (~2x) slowdowns on a job after running it on PyTorch 2.0. From some profiling in `py-spy` it looked like the pin_memory thread was doing a lot more work than before. Looking at a trace in `nsys` I saw the thread doing the forward pass having a bunch of `pthread_cond_timedwait` with GIL reacquire calls in it’s call stack, and it seemed like the thread doing the forward pass was getting blocked (waiting for the GIL) by the pin memory thread (which was holding the GIL). After some debugging I found out the issue. If a `bytes` was passed into `pin_memory`, previously in 1.13 (before #94709) it would short-circuit and return here https://github.com/pytorch/pytorch/blob/d922c29a22e4bf0fba49526f7536395eb8cd66f4/torch/utils/data/_utils/pin_memory.py#L54-L55 since `bytes` was in `torch._six.string_classes`: ``` >>> from torch._six import string_classes >>> string_classes (<class 'str'>, <class 'bytes'>) >>> ``` However after #94709, if a `bytes` was passed into `pin_memory` it would fall into here instead https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L68-L73 because the previous check is now doing `isinstance(data, str)` instead of `isinstance(data, (str, bytes))`! https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L56-L57 As a result, `pin_memory` gets called recursively for each element in the `bytes` leading to a ton of wasted recursion. This also explains the slowdown / GIL contention I was seeing. This PR simply changes `isinstance(data, str)` to `isinstance(data, (str, bytes))` to match the behavior before #94709 Pull Request resolved: #97737 Approved by: https://github.com/albanD, https://github.com/NivekT
atalman
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Apr 5, 2023
…97789, #97863) (#98055) * [DataLoader] Short circuit pin_memory recursion when operating on bytes (#97737) Slack thread: https://pytorch.slack.com/archives/GEEQ2K4MD/p1679962409906099 I was seeing some massive (~2x) slowdowns on a job after running it on PyTorch 2.0. From some profiling in `py-spy` it looked like the pin_memory thread was doing a lot more work than before. Looking at a trace in `nsys` I saw the thread doing the forward pass having a bunch of `pthread_cond_timedwait` with GIL reacquire calls in it’s call stack, and it seemed like the thread doing the forward pass was getting blocked (waiting for the GIL) by the pin memory thread (which was holding the GIL). After some debugging I found out the issue. If a `bytes` was passed into `pin_memory`, previously in 1.13 (before #94709) it would short-circuit and return here https://github.com/pytorch/pytorch/blob/d922c29a22e4bf0fba49526f7536395eb8cd66f4/torch/utils/data/_utils/pin_memory.py#L54-L55 since `bytes` was in `torch._six.string_classes`: ``` >>> from torch._six import string_classes >>> string_classes (<class 'str'>, <class 'bytes'>) >>> ``` However after #94709, if a `bytes` was passed into `pin_memory` it would fall into here instead https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L68-L73 because the previous check is now doing `isinstance(data, str)` instead of `isinstance(data, (str, bytes))`! https://github.com/pytorch/pytorch/blob/c263bd43e8e8502d4726643bc6fd046f0130ac0e/torch/utils/data/_utils/pin_memory.py#L56-L57 As a result, `pin_memory` gets called recursively for each element in the `bytes` leading to a ton of wasted recursion. This also explains the slowdown / GIL contention I was seeing. This PR simply changes `isinstance(data, str)` to `isinstance(data, (str, bytes))` to match the behavior before #94709 Pull Request resolved: #97737 Approved by: https://github.com/albanD, https://github.com/NivekT * [DataLoader] Fix collation logic (#97789) Similar to #97737, a previous auto-refactor changed how `bytes` are handled during collation, which can potentially lead to performance regression. This PR undoes that. Pull Request resolved: #97789 Approved by: https://github.com/albanD * Revisit `torch._six.string_classes` removal (#94709) (#97863) Revisit `torch._six.string_classes` (which is `(str, bytes)`) removal: `isinstance(obj, string_classes) -> isinstance(obj, str)`. Both `str` and `bytes` are `Sequence` classes. ```python In [1]: from typing import Sequence In [2]: issubclass(bytes, Sequence) Out[2]: True In [3]: issubclass(str, Sequence) Out[3]: True ``` Re-add `bytes` to type guards like: ```python def is_seq(obj): return isinstance(obj, Sequence) and not isinstance(obj, (str, bytes)) ``` Ref: - #94709 (comment) - #97737 - #97789 Pull Request resolved: #97863 Approved by: https://github.com/Skylion007, https://github.com/albanD --------- Co-authored-by: Eric Zhang <ezhang887@gmail.com> Co-authored-by: Kevin Tse <ktse@fb.com>
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This commit fixes a deprecated import statement in the codebase that uses the string_classes module from PyTorch. The deprecated import statement from torch import string_classes has been replaced with a simpler and more Pythonic alternative string_classes = str. The string_classes module was previously used to define the type of a string, but it has been removed in more recent versions of PyTorch. This commit provides a cleaner and more compatible solution that works with newer versions of PyTorch. See pytorch/pytorch#94709
This was referenced Apr 29, 2023
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# Torch does not support torch._six anymore and it has been removed. # Refer - pytorch/pytorch#94709
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Remove the Python 2 and 3 compatibility library six and future and
torch._six. We only support Python 3.8+ now. It's time to retire them.cc @mlazos @soumith @voznesenskym @yanboliang @penguinwu @anijain2305 @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @desertfire