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@suo suo commented Aug 19, 2020

Stack from ghstack:

The IR emitter looks for attributes on modules like:

  1. Check the JIT type for the attribute
  2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:

inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)

The IR emitter may check for attributes on inner_module. There is no
originating Python class for inner_module, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:

  1. Check the JIT type for the attribute (not there!)
  2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: D23224337

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

[ghstack-poisoned]
@suo suo requested a review from apaszke as a code owner August 19, 2020 19:44
suo added a commit that referenced this pull request Aug 19, 2020
The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

ghstack-source-id: a27e4a4
Pull Request resolved: #43284
@facebook-github-bot facebook-github-bot added the oncall: jit Add this issue/PR to JIT oncall triage queue label Aug 19, 2020
…ules"

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: [D23224337](https://our.internmc.facebook.com/intern/diff/D23224337)

[ghstack-poisoned]
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dr-ci bot commented Aug 25, 2020

💊 CI failures summary and remediations

As of commit 653f684 (more details on the Dr. CI page):


  • 2/2 failures possibly* introduced in this PR
    • 2/2 non-CircleCI failure(s)

ci.pytorch.org: 2 failed


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This comment has been revised 15 times.

suo added 3 commits August 27, 2020 14:13
…ules"

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: [D23224337](https://our.internmc.facebook.com/intern/diff/D23224337)

[ghstack-poisoned]
…ules"

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: [D23224337](https://our.internmc.facebook.com/intern/diff/D23224337)

[ghstack-poisoned]
…ules"

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: [D23224337](https://our.internmc.facebook.com/intern/diff/D23224337)

[ghstack-poisoned]
@codecov
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codecov bot commented Sep 2, 2020

Codecov Report

Merging #43284 into gh/suo/344/base will increase coverage by 0.00%.
The diff coverage is n/a.

Impacted file tree graph

@@               Coverage Diff                @@
##           gh/suo/344/base   #43284   +/-   ##
================================================
  Coverage            69.27%   69.27%           
================================================
  Files                  381      381           
  Lines                47265    47265           
================================================
+ Hits                 32743    32744    +1     
+ Misses               14522    14521    -1     
Impacted Files Coverage Δ
torch/testing/_internal/expecttest.py 78.57% <0.00%> (+1.02%) ⬆️

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 665feda...653f684. Read the comment docs.

…ules"

The IR emitter looks for attributes on modules like:
1. Check the JIT type for the attribute
2. Check the originating Python class, in order to fulfill requests for, e.g. static methods or ignored methods.

In the case where you do:
```
inner_module = torch.jit.load("inner.pt")
wrapped = Wrapper(inner_module)  # wrap the loaded ScriptModule in an nn.Module
torch.jit.script(wrapped)
```

The IR emitter may check for attributes on `inner_module`. There is no
originating Python class for `inner_module`, since it was directly
compiled from the serialized format.

Due to a bug in the code, we don't guard for this case an a segfault
results if the wrapper asks for an undefined attribute. The lookup in
this case looks like:
1. Check the JIT type for the attribute (not there!)
2. Check the originating Python class (this is a nullptr! segfault!)

This PR guards this case and properly just raises an attribute missing
compiler error instead of segfaulting.

Differential Revision: [D23224337](https://our.internmc.facebook.com/intern/diff/D23224337)

[ghstack-poisoned]
@facebook-github-bot
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@suo merged this pull request in 74f1847.

@facebook-github-bot facebook-github-bot deleted the gh/suo/344/head branch September 7, 2020 14:17
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5 participants