[Static Runtime] Revamp op schema check #57521
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Summary:
When an op is added to static runtime, we manually check the schema (not with the jit schema check, more with IValue.IsTensor()/IsInt() etc) and make sure it's the one we do support. If the schema doesn't match, SR would throw an exception with TORCH_CHECK, which makes the entire graph invalid for SR.
This diff tries to make the op with unsupported schema to use the fallback path and make it go through the dispatcher instead:
```
if (node->kind() != prim::ListConstruct &&
node->kind() != prim::TupleConstruct &&
node->kind() != prim::DictConstruct && node->kind() != prim::ListUnpack) {
const Operator& op = node->getOperator();
TORCH_CHECK(op.hasOperation());
op_ = op.getOperation(node);
VLOG(1) << "Fallback interpreter for node: " << PrintNode(node);
}
```
The 2-arg `torch.norm`, which the SR `torch.norm impl doesn't support (only 3, 4, 5 args are supported), now can run in static runtime with fallback mode.
Reviewed By: ajyu
Differential Revision: D27531447
fbshipit-source-id: 304b9042d3664b0b632d5a2f6a981b6edfabdb65
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This pull request was exported from Phabricator. Differential Revision: D27531447 |
Codecov Report
@@ Coverage Diff @@
## master #57521 +/- ##
==========================================
- Coverage 77.62% 77.62% -0.01%
==========================================
Files 1960 1960
Lines 195759 195757 -2
==========================================
- Hits 151965 151961 -4
- Misses 43794 43796 +2 |
|
This pull request has been merged in 5439977. |
krshrimali
pushed a commit
to krshrimali/pytorch
that referenced
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May 19, 2021
Summary: Pull Request resolved: pytorch#57521 When an op is added to static runtime, we manually check the schema (not with the jit schema check, more with IValue.IsTensor()/IsInt() etc) and make sure it's the one we do support. If the schema doesn't match, SR would throw an exception with TORCH_CHECK, which makes the entire graph invalid for SR. This diff tries to make the op with unsupported schema to use the fallback path and make it go through the dispatcher instead: ``` if (node->kind() != prim::ListConstruct && node->kind() != prim::TupleConstruct && node->kind() != prim::DictConstruct && node->kind() != prim::ListUnpack) { const Operator& op = node->getOperator(); TORCH_CHECK(op.hasOperation()); op_ = op.getOperation(node); VLOG(1) << "Fallback interpreter for node: " << PrintNode(node); } ``` The 2-arg `torch.norm`, which the SR `torch.norm impl doesn't support (only 3, 4, 5 args are supported), now can run in static runtime with fallback mode. (Note: this ignores all push blocking failures!) Reviewed By: ajyu Differential Revision: D27531447 fbshipit-source-id: 0a9c2662ac73ed0393a23cc3a2c7df45fdb00fdd
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Summary:
When an op is added to static runtime, we manually check the schema (not with the jit schema check, more with IValue.IsTensor()/IsInt() etc) and make sure it's the one we do support. If the schema doesn't match, SR would throw an exception with TORCH_CHECK, which makes the entire graph invalid for SR.
This diff tries to make the op with unsupported schema to use the fallback path and make it go through the dispatcher instead:
The 2-arg
torch.norm, which the SR `torch.norm impl doesn't support (only 3, 4, 5 args are supported), now can run in static runtime with fallback mode.Reviewed By: ajyu
Differential Revision: D27531447