junrushao1994 commented on code in PR #12408: URL: https://github.com/apache/tvm/pull/12408#discussion_r944843560
########## tests/python/unittest/test_meta_schedule_schedule_rule_multi_level_tiling.py: ########## @@ -883,13 +883,13 @@ def test_cuda_tensor_core_matmul_relu_global(): sch.compute_at(block=b70, loop=l46, preserve_unit_loops=True) l71, l72, l73, l74, l75, l76 = sch.get_loops(block=b70) l77 = sch.fuse(l75, l76, preserve_unit_iters=True) -v78 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25]) +v78 = sch.sample_categorical(candidates=[1, 2, 4, 8], probs=[0.25, 0.25, 0.25, 0.25]) sch.annotate(block_or_loop=b70, ann_key="meta_schedule.cooperative_fetch", ann_val=v78) b79 = sch.cache_read(block=b19, read_buffer_index=1, storage_scope="shared") sch.compute_at(block=b79, loop=l46, preserve_unit_loops=True) l80, l81, l82, l83, l84, l85 = sch.get_loops(block=b79) l86 = sch.fuse(l84, l85, preserve_unit_iters=True) -v87 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25]) +v87 = sch.sample_categorical(candidates=[1, 2, 4, 8], probs=[0.25, 0.25, 0.25, 0.25]) Review Comment: BTW, i'm not sure if we should rule out `float3` in CUDA ########## tests/python/unittest/test_meta_schedule_schedule_rule_multi_level_tiling.py: ########## @@ -883,13 +883,13 @@ def test_cuda_tensor_core_matmul_relu_global(): sch.compute_at(block=b70, loop=l46, preserve_unit_loops=True) l71, l72, l73, l74, l75, l76 = sch.get_loops(block=b70) l77 = sch.fuse(l75, l76, preserve_unit_iters=True) -v78 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25]) +v78 = sch.sample_categorical(candidates=[1, 2, 4, 8], probs=[0.25, 0.25, 0.25, 0.25]) sch.annotate(block_or_loop=b70, ann_key="meta_schedule.cooperative_fetch", ann_val=v78) b79 = sch.cache_read(block=b19, read_buffer_index=1, storage_scope="shared") sch.compute_at(block=b79, loop=l46, preserve_unit_loops=True) l80, l81, l82, l83, l84, l85 = sch.get_loops(block=b79) l86 = sch.fuse(l84, l85, preserve_unit_iters=True) -v87 = sch.sample_categorical(candidates=[1, 2, 3, 4], probs=[0.25, 0.25, 0.25, 0.25]) +v87 = sch.sample_categorical(candidates=[1, 2, 4, 8], probs=[0.25, 0.25, 0.25, 0.25]) Review Comment: BTW, i'm not sure if we should rule out `float3` on CUDA -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
