comaniac commented on a change in pull request #8794:
URL: https://github.com/apache/tvm/pull/8794#discussion_r692337709
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File path: tutorials/autotvm/tune_relay_x86.py
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@@ -256,6 +274,29 @@ def tune_and_evaluate(tuning_opt):
# [Task 10/12] Current/Best: 182.33/1734.45 GFLOPS | Progress: (360/360)
| 1755.06 s Done.
# [Task 11/12] Current/Best: 372.18/1745.15 GFLOPS | Progress: (360/360)
| 1684.50 s Done.
# [Task 12/12] Current/Best: 215.34/2271.11 GFLOPS | Progress: (400/400)
| 2128.74 s Done.
+# INFO Start to benchmark layout transformation...
+# INFO Benchmarking layout transformation successful.
+# INFO Start to run dynamic programming algorithm...
+# INFO Start forward pass...
+# INFO Finished forward pass.
+# INFO Start backward pass...
+# INFO Finished backward pass...
+# INFO Finished DPExecutor run.
+# INFO Writing optimal schedules to resnet-18_graph_opt.log successfully.
+#
+# Evaluation of the network compiled in 'default' mode without auto tune:
+# Compile...
+# Evaluate inference time cost...
+# Mean inference time (std dev): 4.5 ms (0.03 ms)
+#
+# Evaluation of the network been tuned on kernel level:
+# Compile...
+# Evaluate inference time cost...
+# Mean inference time (std dev): 3.2 ms (0.03 ms)
+#
+# Evaluation of the network been tuned on graph level:
# Compile...
+# Config for target=llvm -keys=cpu -link-params=0,
workload=('dense_nopack.x86', ('TENSOR', (1, 512), 'float32'), ('TENSOR',
(1000, 512), 'float32'), None, 'float32') is missing in ApplyGraphBest context.
A fallback configuration is used, which may bring great performance regression.
+# Config for target=llvm -keys=cpu -link-params=0,
workload=('dense_pack.x86', ('TENSOR', (1, 512), 'float32'), ('TENSOR', (1000,
512), 'float32'), None, 'float32') is missing in ApplyGraphBest context. A
fallback configuration is used, which may bring great performance regression.
Review comment:
Do we know the root cause of these warnings?
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