coffezhou opened a new issue, #17854:
URL: https://github.com/apache/tvm/issues/17854
### Expected behavior
TVM should compile the model correctly with the CUDA backend.
### Actual behavior
When compiling the model with the CUDA backend, TVM crashes as follows:
```c
Traceback (most recent call last):
File "/home/carla/Documents/test/test.py", line 140, in check_correctness
ex = tvm.compile(tvm_model, target="cuda")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/driver/build_module.py", line
104, in compile
return tvm.relax.build(
^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/vm_build.py", line 259,
in build
return _vmlink(
^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/relax/vm_build.py", line 154,
in _vmlink
lib = tvm.tir.build(tir_mod, target=target, pipeline=tir_pipeline)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/tir/build.py", line 186, in
build
return tir_to_runtime(host_mod, device_mod_dict, target_host)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/tir/build.py", line 96, in
tir_to_runtime
device_modules.append(codegen_build(device_mod, target))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/tir/build.py", line 80, in
codegen_build
return bf(mod, target)
^^^^^^^^^^^^^^^
File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in
tvm._ffi._cy3.core.PackedFuncBase.__call__
File "tvm/_ffi/_cython/./packed_func.pxi", line 270, in
tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./packed_func.pxi", line 259, in
tvm._ffi._cy3.core.FuncCall3
File "tvm/_ffi/_cython/./base.pxi", line 185, in
tvm._ffi._cy3.core.CHECK_CALL
File "/home/carla/Documents/tvm/python/tvm/_ffi/base.py", line 468, in
raise_last_ffi_error
raise py_err
File "/home/carla/Documents/tvm/src/target/opt/build_cuda_on.cc", line
161, in tvm::codegen::BuildCUDA(tvm::IRModule, tvm::Target)
ptx = (*f)(code, target).operator std::string();
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in
tvm._ffi._cy3.core.tvm_callback
File "/home/carla/Documents/tvm/python/tvm/contrib/nvcc.py", line 204, in
tvm_callback_cuda_compile
ptx = compile_cuda(code, target_format="fatbin")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/python/tvm/contrib/nvcc.py", line 128, in
compile_cuda
raise RuntimeError(msg)
RuntimeError:
#if (((__CUDACC_VER_MAJOR__ == 11) && (__CUDACC_VER_MINOR__ >= 4)) || \
(__CUDACC_VER_MAJOR__ > 11))
#define TVM_ENABLE_L2_PREFETCH 1
#else
#define TVM_ENABLE_L2_PREFETCH 0
#endif
#ifdef _WIN32
using uint = unsigned int;
using uchar = unsigned char;
using ushort = unsigned short;
using int64_t = long long;
using uint64_t = unsigned long long;
#else
#define uint unsigned int
#define uchar unsigned char
#define ushort unsigned short
#define int64_t long long
#define uint64_t unsigned long long
#endif
extern "C" __global__ void __launch_bounds__(1024) add1_kernel(float*
__restrict__ T_add, float* __restrict__ lv6, float* __restrict__ lv7, int64_t );
extern "C" __global__ void __launch_bounds__(1024) add1_kernel(float*
__restrict__ T_add, float* __restrict__ lv6, float* __restrict__ lv7, int64_t )
{
for (int64_t ax0_ax1_fused_0 = 0; ax0_ax1_fused_0 < ((( * (int64_t)3) +
(int64_t)262143) >> (int64_t)18); ++ax0_ax1_fused_0) {
if ((((ax0_ax1_fused_0 * (int64_t)262144) + (((int64_t)blockIdx.x) *
(int64_t)1024)) + ((int64_t)threadIdx.x)) < ( * (int64_t)3)) {
T_add[(((ax0_ax1_fused_0 * (int64_t)262144) + (((int64_t)blockIdx.x) *
(int64_t)1024)) + ((int64_t)threadIdx.x))] = (lv6[(((ax0_ax1_fused_0 *
(int64_t)262144) + (((int64_t)blockIdx.x) * (int64_t)1024)) +
((int64_t)threadIdx.x))] + lv7[(((ax0_ax1_fused_0 * (int64_t)262144) +
(((int64_t)blockIdx.x) * (int64_t)1024)) + ((int64_t)threadIdx.x))]);
}
}
}
Compilation error:
/tmp/tmpjs6_cjiu/tvm_kernels.cu(24): error: operand of "*" must be a pointer
but has type "long long"
/tmp/tmpjs6_cjiu/tvm_kernels.cu(25): error: operand of "*" must be a pointer
but has type "long long"
2 errors detected in the compilation of "/tmp/tmpjs6_cjiu/tvm_kernels.cu".
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/carla/Documents/test_tvm/test-tvm-llm/test_tvm.py", line 189,
in <module>
main()
File "/home/carla/Documents/test_tvm/test-tvm-llm/test_tvm.py", line 178,
in main
check_correctness(onnx_model)
File "/home/carla/Documents/test_tvm/test-tvm-llm/test_tvm.py", line 136,
in check_correctness
with tvm.target.Target("cuda"):
File "/home/carla/Documents/tvm/python/tvm/target/target.py", line 145, in
__exit__
_ffi_api.TargetExitScope(self)
File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in
tvm._ffi._cy3.core.PackedFuncBase.__call__
File "tvm/_ffi/_cython/./packed_func.pxi", line 270, in
tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./packed_func.pxi", line 259, in
tvm._ffi._cy3.core.FuncCall3
File "tvm/_ffi/_cython/./base.pxi", line 185, in
tvm._ffi._cy3.core.CHECK_CALL
File "/home/carla/Documents/tvm/python/tvm/_ffi/base.py", line 468, in
raise_last_ffi_error
raise py_err
File "/home/carla/Documents/tvm/src/target/target.cc", line 52, in
tvm::TargetInternal::ExitScope(tvm::Target)
static void ExitScope(Target target) { target.ExitWithScope(); }
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/carla/Documents/tvm/src/target/target.cc", line 744, in
tvm::Target::ExitWithScope()
ICHECK(entry->context_stack.top().same_as(*this));
^^^^^^^^^^^^^^^^^^^^^^^^^^^
tvm.error.InternalError: Traceback (most recent call last):
1: tvm::TargetInternal::ExitScope(tvm::Target)
at /home/carla/Documents/tvm/src/target/target.cc:52
0: tvm::Target::ExitWithScope()
at /home/carla/Documents/tvm/src/target/target.cc:744
File "/home/carla/Documents/tvm/src/target/target.cc", line 744
InternalError: Check failed: (entry->context_stack.top().same_as(*this)) is
false:
```
### Environment
OS: Ubuntu 20.04
TVM: 0.21.dev0(c00f52a70)
### Steps to reproduce
This bug can be reproduced by the following code with the model in the
attachment. As shown in the code, the model can be executed by onnxruntime and
also be compiled by tvm with cpu backend. However, tvm failed to compile this
model with CUDA backend.
```python
import sys
import numpy as np
import onnx
import onnxruntime
import tvm
from tvm import relax
from tvm.relax.frontend.onnx import from_onnx
import argparse
import pickle
def main():
onnx_model = onnx.load("a2.onnx")
with open("inputs.pkl", "rb") as fp:
inputs = pickle.load(fp)
try:
ort_session = onnxruntime.InferenceSession(
onnx_model.SerializeToString(),
providers=["CPUExecutionProvider"]
)
ort_output = ort_session.run([], inputs)
except Exception as e:
print(e)
sys.exit(1)
# Convert the onnx model into relax through the onnx importer.
tvm_model = from_onnx(onnx_model, keep_params_in_input=True)
# Convert operators for inference mode.
tvm_model = relax.transform.DecomposeOpsForInference()(tvm_model)
# Legalize any relax ops into tensorir.
tvm_model = relax.transform.LegalizeOps()(tvm_model)
# Separate model from parameters.
tvm_model, params = relax.frontend.detach_params(tvm_model)
# Prepare inputs.
input_list = [
inputs[key.name_hint] for key in tvm_model["main"].params if
key.name_hint in inputs
]
if params:
input_list += params["main"]
# Compile the relax graph into a VM then run.
#----------------------cpu-----------------------
with tvm.transform.PassContext(opt_level=3):
target = tvm.target.Target("llvm", host="llvm")
relax_pipeline = relax.pipeline.get_default_pipeline(target)
ex = relax.build(tvm_model, target="llvm",
relax_pipeline=relax_pipeline)
vm = relax.VirtualMachine(ex, tvm.cpu())
# Run model and check outputs.
vm.set_input("main", *input_list)
vm.invoke_stateful("main")
tvm_cpu_output = vm.get_outputs("main")
#----------------------cpu-----------------------
#----------------------cuda-----------------------
with tvm.target.Target("cuda"):
tvm_model = tvm.tir.transform.DefaultGPUSchedule()(tvm_model)
with tvm.transform.PassContext(opt_level=3):
ex = tvm.compile(tvm_model, target="cuda")
vm1 = relax.VirtualMachine(ex, tvm.cuda())
vm1.set_input("main", *input_list)
vm1.invoke_stateful("main")
tvm_gpu_output = vm1.get_outputs("main")
#----------------------cuda-----------------------
if __name__ == "__main__":
main()
```
[testcase.zip](https://github.com/user-attachments/files/19809073/testcase.zip)
### Triage
* needs-triage
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