tqchen commented on a change in pull request #6728:
URL: https://github.com/apache/incubator-tvm/pull/6728#discussion_r509780707
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File path: tutorials/auto_scheduler/tune_conv2d_layer_cuda.py
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@@ -82,17 +84,19 @@ def conv2d_layer(N, H, W, CO, CI, KH, KW, stride, padding):
# * :code:`num_measure_trials` is the number of measurement trials we can use
during the search.
# We only make 10 trials in this tutorial for a fast demonstration. In
practice, 1000 is a
# good value for the search to converge. You can do more trials according to
your time budget.
-# * In addition, we use :code:`RecordToFile` to dump measurement records into
a file `conv2d.json`.
+# * In addition, we use :code:`RecordToFile` to dump measurement records into
a file.
+# Note that here we use a temporarty file for demonstraction, but in
practice you should use
+# a more maintainable file name such as `conv2d.json`.
# The measurement records can be used to query the history best, resume the
search,
# and do more analyses later.
# * see :any:`auto_scheduler.TuningOptions`,
# :any:`auto_scheduler.LocalRPCMeasureContext` for more parameters.
-
+logfile = tempfile.NamedTemporaryFile(prefix="conv2d", suffix=".json")
Review comment:
can we use tvm.contrib.util.tempdir instead? It will be able to clean up
the content at exit
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