75afcd766e0e45fdb8bd3007b3114257f11a7ec4,tutorials/auto_scheduler/tune_conv2d_layer_cuda.py,,,#,70

Before Change


// We can kick off the search and let the auto-scheduler do its magic.
// After some measurement trials, it will return the best schedule it found.

sch, args = auto_scheduler.auto_schedule(task, tuning_options=tune_option)

// Kill the process for measurement
del measure_ctx

After Change


print(task.print_best(log_file, print_mode="schedule"))

print("CUDA source code:")
print(task.print_best(log_file, print_mode="cuda"))

////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// A more complicated example is to resume the search.
// In this case, we need to create the search policy and cost model by ourselves
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: apache/incubator-tvm
Commit Name: 75afcd766e0e45fdb8bd3007b3114257f11a7ec4
Time: 2020-12-04
Author: lianminzheng@gmail.com
File Name: tutorials/auto_scheduler/tune_conv2d_layer_cuda.py
Class Name:
Method Name:


Project Name: apache/incubator-tvm
Commit Name: 75afcd766e0e45fdb8bd3007b3114257f11a7ec4
Time: 2020-12-04
Author: lianminzheng@gmail.com
File Name: tests/python/unittest/test_auto_scheduler_search_policy.py
Class Name:
Method Name: search_common


Project Name: apache/incubator-tvm
Commit Name: 75afcd766e0e45fdb8bd3007b3114257f11a7ec4
Time: 2020-12-04
Author: lianminzheng@gmail.com
File Name: tutorials/auto_scheduler/tune_matmul_x86.py
Class Name:
Method Name: