areusch commented on a change in pull request #8113:
URL: https://github.com/apache/tvm/pull/8113#discussion_r638925859
##########
File path: python/tvm/autotvm/measure/measure_methods.py
##########
@@ -575,18 +596,22 @@ def run_through_rpc(
f_preproc=f_prepare,
)
- try:
- random_fill =
remote.get_function("tvm.contrib.random.random_fill")
- except AttributeError:
- raise AttributeError(
- "Please make sure USE_RANDOM is ON in the config.cmake "
"on the remote devices"
- )
- args = [nd.empty(x[0], x[1], dev) for x in build_result.arg_info]
- if "scatter" not in measure_input.task.name:
- # the index tensor of scatter op cannot be randomly initialized
- for arg in args:
- random_fill(arg)
- dev.sync()
+ if ref_input:
+ args = [nd.array(x, device=dev) for x in ref_input]
+ else:
+ try:
+ random_fill =
remote.get_function("tvm.contrib.random.random_fill")
+ except AttributeError:
+ raise AttributeError(
+ "Please make sure USE_RANDOM is ON in the config.cmake
"
+ "on the remote devices"
+ )
+ args = [nd.empty(x[0], x[1], dev) for x in
build_result.arg_info]
+ if "scatter" not in measure_input.task.name:
+ # the index tensor of scatter op cannot be randomly
initialized
+ for arg in args:
+ random_fill(arg)
+ dev.sync()
Review comment:
actually i was referring to the outer `if ref_input:`. but i think i'm
retracting my ask here, because i believe the point of `sync` is to ensure
`random_fill` has been materialized into memory.
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