Hello!

I added a judgment about tensorcore 
(“nvcc.have_tensorcore(tvm.gpu(0).compute_version)”) in conv2d schedule, like 
this:

    """schedule optimized for NHWC direct conv2d"""
    pad_data, kernel = s[Conv].op.input_tensors
    s[pad_data].compute_inline()
    test_tensorcore =  nvcc.have_tensorcore(tvm.gpu(0).compute_version)
    if isinstance(kernel.op, tvm.te.ComputeOp) and 'dilate' in kernel.op.tag:
        s[kernel].compute_inline()

But when I used autotvm to tune conv2d, the program reported the following 
error:

DEBUG:autotvm:No: 336   GFLOPS: 0.00/0.00       result: 
MeasureResult(costs=(TVMError('Traceback (most recent call last):\n  [bt] (6) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(TVMFuncCall+0x95) 
[0x7fcef17af612]\n  [bt] (5) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(tvm::runtime::PackedFunc::CallPacked(tvm::runtime::TVMArgs,
 tvm::runtime::TVMRetValue*) const+0x30) [0x7fcef0d2ce6a]\n  [bt] (4) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(std::function<void 
(tvm::runtime::TVMArgs, 
tvm::runtime::TVMRetValue*)>::operator()(tvm::runtime::TVMArgs, 
tvm::runtime::TVMRetValue*) const+0x5a) [0x7fcef0d2d4b6]\n  [bt] (3) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(+0x25e7d70) [0x7fcef17b0d70]\n  
[bt] (2) /home/acc/4test_tvm/test_tvm/build/libtvm.so(+0x25e7531) 
[0x7fcef17b0531]\n  [bt] (1) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(tvm::runtime::CUDADeviceAPI::GetAttr(DLContext,
 tvm::runtime::DeviceAttrKind, tvm::runtime::TVMRetValue*)+0x3b2) 
[0x7fcef1841650]\n  [bt] (0) 
/home/acc/4test_tvm/test_tvm/build/libtvm.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x4a)
 [0x7fcef0bbb4fe]\n  File 
"/home/acc/4test_tvm/test_tvm/src/runtime/cuda/cuda_device_api.cc", line 
68\nCUDA: Check failed: e == cudaSuccess || e == cudaErrorCudartUnloading: 
initialization error',),), error_no=2, all_cost=0.017934799194335938, 
timestamp=1587735735.6513684)   [('tile_n', 4), ('tile_c', 8), ('num_thread_n', 
16), ('num_thread_c', 4), ('vthread_n', 1), ('vthread_c', 1), ('step', 
64)],None,997

If I delete the judgment about tensorcore, the autotvm can run normally.

Does autotvm not support adding judgment about tensorcore in schedule?





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