comaniac commented on a change in pull request #7063:
URL: https://github.com/apache/tvm/pull/7063#discussion_r539516443
##########
File path: python/tvm/contrib/nvcc.py
##########
@@ -269,15 +270,24 @@ def have_int8(compute_version):
return False
-def have_tensorcore(compute_version):
+def have_tensorcore(compute_version=None):
"""Either TensorCore support is provided in the compute capability or not
Parameters
----------
compute_version : str
compute capability of a GPU (e.g. "7.0")
"""
+ if compute_version is None:
+ if tvm.gpu(0).exist:
+ compute_version = tvm.gpu(0).compute_version
+ else:
+ compute_version = AutotvmGlobalScope.current.cuda_target_arch
Review comment:
Hmm this is a good point. Putting CUDA target arch to target definitely
makes more sense. Then the solution becomes:
```python
target = Target("cuda -arch=sm_80")
...
cuda_target_arch = target.attrs["arch"] if "arch" in target.attrs else
"sm_75"
...
```
I found that CUDA target already has this attribute so the above solution
actually works now.
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