[NVFuser] RuntimeError: ref_id_it != replayed_concrete_ids_.vector().end() INTERNAL ASSERT FAILED
Labels: triaged, module: assert failure, module: nvfuser

### 🐛 Describe the bug

```python
# debug_aev_nvfuser_minimal.py

import torch

torch._C._jit_set_nvfuser_single_node_mode(True)
torch._C._debug_set_autodiff_subgraph_inlining(False)
torch.manual_seed(0)


def func(x, y, z):
    return (x + y)**z


func_script = torch.jit.script(func)

x = torch.rand([3, 1, 1, 1, 1], device="cuda").requires_grad_()
y = torch.rand([1, 1, 1, 4], device="cuda")
z = torch.rand([1, 1, 1, 1], device="cuda")

for i in range(10):
    res = func(x, y, z)
    grad = torch.autograd.grad(res, x, torch.ones_like(res))[0]

    res_script = func_script(x, y, z)
    grad_script = torch.autograd.grad(res_script, x, torch.ones_like(res))[0]

    print(f"{i}: max_result_error {(res_script-res).abs().max()}, max_grad_error {(grad_script-grad).abs().max()}")
```

Run with
```
PYTORCH_NVFUSER_DISABLE=fallback PYTORCH_JIT_LOG_LEVEL=">partition:graph_fuser:>>kernel_cache" python debug_aev_nvfuser_minimal.py
```

error message:
```
[DEBUG kernel_cache.cpp:638] GraphCache constructor: 0x7fb774056cc0
[DUMP kernel_cache.cpp:639] GraphCache created for graph
[DUMP kernel_cache.cpp:639] graph(%0 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0),
[DUMP kernel_cache.cpp:639]       %1 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0),
[DUMP kernel_cache.cpp:639]       %2 : Float(1, 1, 1, 1, strides=[1, 1, 1, 1], requires_grad=0, device=cuda:0),
[DUMP kernel_cache.cpp:639]       %3 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0)):
[DUMP kernel_cache.cpp:639]   %4 : int[] = prim::Constant[value=[3, 1, 1, 1, 1]]()
[DUMP kernel_cache.cpp:639]   %5 : int = prim::Constant[value=1]() # <string>:240:94
[DUMP kernel_cache.cpp:639]   %6 : float = prim::Constant[value=0.]() # <string>:240:52
[DUMP kernel_cache.cpp:639]   %7 : Bool(1, 1, 1, 1, strides=[1, 1, 1, 1], requires_grad=0, device=cuda:0) = aten::eq(%2, %6) # <string>:240:40
[DUMP kernel_cache.cpp:639]   %8 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0) = aten::mul(%3, %2) # <string>:240:98
[DUMP kernel_cache.cpp:639]   %9 : Float(1, 1, 1, 1, strides=[1, 1, 1, 1], requires_grad=0, device=cuda:0) = aten::sub(%2, %5, %5) # <string>:240:139
[DUMP kernel_cache.cpp:639]   %10 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0) = aten::pow(%1, %9) # <string>:240:123
[DUMP kernel_cache.cpp:639]   %11 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0) = aten::mul(%8, %10) # <string>:240:98
[DUMP kernel_cache.cpp:639]   %12 : Float(3, 1, 1, 1, 4, strides=[4, 4, 4, 4, 1], requires_grad=0, device=cuda:0) = aten::where(%7, %0, %11) # <string>:240:28
[DUMP kernel_cache.cpp:639]   %grad_self.20 : Float(3, 1, 1, 1, 1, strides=[1, 1, 1, 1, 1], requires_grad=0, device=cuda:0) = aten::_grad_sum_to_size(%12, %4) # <string>:13:29
[DUMP kernel_cache.cpp:639]   return (%grad_self.20)
[DEBUG kernel_cache.cpp:647] running GraphCache: 0x7fb774056cc0
Traceback (most recent call last):
  File "debug_aev_nvfuser_minimal.py", line 23, in <module>
    grad_script = torch.autograd.grad(res_script, x, torch.ones_like(res))[0]
  File "/home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/autograd/__init__.py", line 294, in grad
    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
RuntimeError: The following operation failed in the TorchScript interpreter.
Traceback of TorchScript (most recent call last):
RuntimeError: ref_id_it != replayed_concrete_ids_.vector().end() INTERNAL ASSERT FAILED at "/opt/conda/conda-bld/pytorch_1662103173222/work/torch/csrc/jit/codegen/cuda/lower_index_compute.cpp":724, please report a bug to PyTorch. Could not find required iter domain in reference replay: bblockIdx.y214{( 1 * ( 1 * 1 ) )}
ref_id_it != replayed_concrete_ids_.vector().end() INTERNAL ASSERT FAILED at "/opt/conda/conda-bld/pytorch_1662103173222/work/torch/csrc/jit/codegen/cuda/lower_index_compute.cpp":724, please report a bug to PyTorch. Could not find required iter domain in reference replay: bblockIdx.y214{( 1 * ( 1 * 1 ) )}
Exception raised from constructLoopDomains at /opt/conda/conda-bld/pytorch_1662103173222/work/torch/csrc/jit/codegen/cuda/lower_index_compute.cpp:724 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd528ba9577 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x7fd528b77e2c in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #2: c10::detail::torchInternalAssertFail(char const*, char const*, unsigned int, char const*, std::string const&) + 0x3f (0x7fd528ba749f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #3: <unknown function> + 0x2f5c6aa (0x7fd52bb566aa in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #4: <unknown function> + 0x2f5df57 (0x7fd52bb57f57 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #5: <unknown function> + 0x2f5e263 (0x7fd52bb58263 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #6: <unknown function> + 0x2f48370 (0x7fd52bb42370 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #7: <unknown function> + 0x2f4e569 (0x7fd52bb48569 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #8: <unknown function> + 0x2f4e692 (0x7fd52bb48692 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #9: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::BinaryOp const*) + 0x21 (0x7fd52bbd7301 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #10: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::IfThenElse const*) + 0xc0 (0x7fd52bbd6e90 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #11: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::ForLoop const*) + 0xdf (0x7fd52bbd815f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #12: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::IfThenElse const*) + 0xc0 (0x7fd52bbd6e90 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #13: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::ForLoop const*) + 0xdf (0x7fd52bbd815f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #14: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::ForLoop const*) + 0xdf (0x7fd52bbd815f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #15: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::ForLoop const*) + 0xdf (0x7fd52bbd815f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #16: torch::jit::fuser::cuda::IndexLowering::handle(torch::jit::fuser::cuda::kir::ForLoop const*) + 0xdf (0x7fd52bbd815f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #17: torch::jit::fuser::cuda::IndexLowering::generate(std::vector<torch::jit::fuser::cuda::Expr*, std::allocator<torch::jit::fuser::cuda::Expr*> > const&) + 0x27 (0x7fd52bbd6ca7 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #18: torch::jit::fuser::cuda::GpuLower::lower(torch::jit::fuser::cuda::Fusion*, torch::jit::fuser::cuda::DataType) + 0x13c7 (0x7fd52bc276e7 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #19: torch::jit::fuser::cuda::FusionExecutor::compileFusion(torch::jit::fuser::cuda::Fusion*, c10::ArrayRef<c10::IValue> const&, torch::jit::fuser::cuda::LaunchParams const&, torch::jit::fuser::cuda::CompileOptions) + 0xcc1 (0x7fd52baea111 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #20: torch::jit::fuser::cuda::FusionKernelRuntime::runKernelWithInput(c10::ArrayRef<c10::IValue> const&, unsigned long, torch::jit::fuser::cuda::SegmentedGroup*) + 0x591 (0x7fd52bba7421 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #21: torch::jit::fuser::cuda::FusionKernelRuntime::runWithInput(c10::ArrayRef<c10::IValue> const&, unsigned long) + 0x4ff (0x7fd52bba908f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #22: torch::jit::fuser::cuda::FusionExecutorCache::runFusionWithInputs(c10::ArrayRef<c10::IValue> const&) + 0x375 (0x7fd52bbab915 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #23: <unknown function> + 0x2fb1c8f (0x7fd52bbabc8f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #24: <unknown function> + 0x302ffa8 (0x7fd52bc29fa8 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #25: torch::jit::fuser::cuda::runCudaFusionGroup(torch::jit::Node const*, std::vector<c10::IValue, std::allocator<c10::IValue> >&) + 0x43c (0x7fd52bc2a7fc in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cuda_cu.so)
frame #26: <unknown function> + 0x443fef2 (0x7fd55c8f7ef2 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #27: torch::jit::InterpreterState::run(std::vector<c10::IValue, std::allocator<c10::IValue> >&) + 0x3f (0x7fd55c8e407f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #28: <unknown function> + 0x441c61a (0x7fd55c8d461a in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #29: <unknown function> + 0x441f4f6 (0x7fd55c8d74f6 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #30: <unknown function> + 0x406051b (0x7fd55c51851b in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #31: torch::autograd::Engine::evaluate_function(std::shared_ptr<torch::autograd::GraphTask>&, torch::autograd::Node*, torch::autograd::InputBuffer&, std::shared_ptr<torch::autograd::ReadyQueue> const&) + 0x1638 (0x7fd55c511c28 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #32: torch::autograd::Engine::thread_main(std::shared_ptr<torch::autograd::GraphTask> const&) + 0x698 (0x7fd55c512798 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #33: torch::autograd::Engine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) + 0x8b (0x7fd55c509b3b in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so)
frame #34: torch::autograd::python::PythonEngine::thread_init(int, std::shared_ptr<torch::autograd::ReadyQueue> const&, bool) + 0x4f (0x7fd56ce42d4f in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/libtorch_python.so)
frame #35: <unknown function> + 0xdbbf4 (0x7fd57f9d8bf4 in /home/richard/program/anaconda3/envs/torch_nightly/lib/python3.8/site-packages/torch/lib/../../../../libstdc++.so.6)
frame #36: <unknown function> + 0x8609 (0x7fd5a0383609 in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #37: clone + 0x43 (0x7fd5a02a8133 in /lib/x86_64-linux-gnu/libc.so.6)
```

cc @ngimel @jjsjann123 @zasdfgbnm 

### Versions

the latest pytorch nightly
```
PyTorch version: 1.13.0.dev20220902
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.5 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.8.13 (default, Mar 28 2022, 11:38:47)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.4.0-125-generic-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.3.109
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3080
Nvidia driver version: 510.85.02
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.23.1
[pip3] torch==1.13.0.dev20220902
[pip3] torchani==2.3.dev174+gbe932233.d20220903
[pip3] torchaudio==0.13.0.dev20220902
[pip3] torchvision==0.14.0.dev20220902
[conda] blas                      1.0                         mkl
[conda] cudatoolkit               11.3.1               h2bc3f7f_2
[conda] mkl                       2021.4.0           h06a4308_640
[conda] mkl-service               2.4.0            py38h7f8727e_0
[conda] mkl_fft                   1.3.1            py38hd3c417c_0
[conda] mkl_random                1.2.2            py38h51133e4_0
[conda] numpy                     1.23.1           py38h6c91a56_0
[conda] numpy-base                1.23.1           py38ha15fc14_0
[conda] pytorch                   1.13.0.dev20220902 py3.8_cuda11.3_cudnn8.3.2_0    pytorch-nightly
[conda] pytorch-mutex             1.0                        cuda    pytorch-nightly
[conda] torchani                  2.3.dev174+gbe932233.d20220903          pypi_0    pypi
[conda] torchaudio                0.13.0.dev20220902      py38_cu113    pytorch-nightly
[conda] torchvision               0.14.0.dev20220902      py38_cu113    pytorch-nightly
```