GPU bug with Unpooling layer and large size inputs

Describe the bug
Large input size SegNet like model with unpooling layer (return_indices= True) fails to run on GPU.

Urgency
Using unpooling layer on GPU with large input size is blocked by this issue.

System information

• OS Platform and Distribution: Linux Ubuntu 16.04
• ONNX Runtime installed from: source
• ONNX Runtime version: 1.1.1 (2cec09a, 2020-01-22)
• Python version: 3.7
• Visual Studio version (if applicable): -
• GCC/Compiler version (if compiling from source): 5.4.0
• CUDA/cuDNN version: 10.1 / 7.6.4
• GPU model and memory: 1080 Ti / 11 Gb

To Reproduce
Link to source and models.
Compile test.cpp with ionnx class interface to onnxruntime and run it with command:
“test model_name.onnx”

Expected behavior
Should successfully run.

Additional context

All tests are carried out with C++ (CPU and GPU) and python interface (CPU). “Upsample” model converted directly from pytorch. “Unpooling” models were created in python manually (example link).

I get “Process finished with exit code 135 (interrupted by signal 7: SIGEMT)” on Ubuntu 16.04 with onnxruntime built from source.

I get “Ort::Exception at memory location 0x000000A007AFBB50” error in release mode and “Exception thrown: read access violation. Y_data was 0x111011101110111” in debug mode for similar models on Windows 10 with onnxruntime prebuild v1.1.