pytorch/test/cpp
Bert Maher dcfc2050bd VaryingShape<Strides>::isComplete() needs to consider whether each Stride is complete (#58510)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58510

In some case that I don't fully understand we're getting a stride that is:
```
{2:1, 1:1, 0:*}
```
(in this debug output, M:N means stride index M, stride value N).  This shape
should be considered incomplete, since we don't actually know the values of the
stride, but VaryingShape::isComplete considers it complete because it only
checks the presence of elements in the vector, not whether those elements are
themselves complete.
ghstack-source-id: 129279583

Test Plan:
new unit test in test/cpp/jit

To see the failure in the context of a real model:
```
./fblearner/predictor/loadgen/download-requests.sh 272478342_0 10 ~/local/requests/272478342_0.recordio

buck-out/gen/fblearner/predictor/loadgen/replay_model_requests --model_id=272478342_0 --replay_record_source=recordio:/data/users/bertrand/requests/272478342_0.recordio --remote_port=9119 --output_file=/data/users/bertrand/responses/272478342_0_actual.recordio --output_type=recordio

buck-out/gen/fblearner/predictor/loadgen/replay_model_requests --model_id=272478342_0 --replay_record_source=recordio:/data/users/bertrand/requests/272478342_0.recordio --remote_port=9119 --output_file=/data/users/bertrand/responses/272478342_0_actual.recordio --output_type=recordio
```

Reviewed By: Krovatkin

Differential Revision: D28520062

fbshipit-source-id: 3ca900337d86480a40fbd90349a698cbb2fa5f11
2021-05-18 21:45:46 -07:00
..
api Add inference mode python bindings and tests (#58045) 2021-05-13 08:55:35 -07:00
common
dist_autograd Fix distributed autograd gradients synchronization (#57792) 2021-05-09 17:32:59 -07:00
jit VaryingShape<Strides>::isComplete() needs to consider whether each Stride is complete (#58510) 2021-05-18 21:45:46 -07:00
lite_interpreter_runtime Revert D27958477: [PyTorch][Edge] Add v4 and v5 models and remove unused model 2021-04-23 14:42:01 -07:00
rpc Use RPC context streams to cover serde ops (#57926) 2021-05-11 07:07:51 -07:00
tensorexpr [NNC] Do not optimize conditionals when the corresponding loop is not normalized (#57675) 2021-05-18 14:25:53 -07:00
__init__.py