comaniac commented on a change in pull request #7063:
URL: https://github.com/apache/tvm/pull/7063#discussion_r538921161
##########
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:
I was expecting something like:
```python
with tvm.transform.PassContext(opt_level=3,
config={"relay.backend.cuda_target_arch": "sm_75"}):
lib = relay.build(mod, target=target, params=params)
```
And in `ncvv.py`:
```python
cuda_target_arch =
PassContext.current().config.get("relay.backend.cuda_target_arch", "sm_75")
major, minor = cuda_target_arch.split("_")[1]
compute_version = major + "." + minor
```
Does that make sense to you?
If so, you may refer to a recent PR I sent, which adds
"relay.backend.use_auto_scheduler" to PassContext:
https://github.com/apache/tvm/pull/6903
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