def _sch(decisions: List[List[int]], ann_val: int) -> Schedule:
sch = Schedule(matmul, debug_mask="all")
# pylint: disable=invalid-name
d0, d1, d2 = decisions
b0 = sch.get_block(name="C", func_name="main")
root = sch.get_block(name="root", func_name="main")
sch.get_consumers(block=b0)
b1 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="global")
l2, l3, l4 = sch.get_loops(block=b0)
v5, v6, v7, v8 = sch.sample_perfect_tile(
loop=l2,
n=4,
max_innermost_factor=64,
decision=d0,
)
l9, l10, l11, l12 = sch.split(loop=l2, factors=[v5, v6, v7, v8])
v13, v14, v15, v16 = sch.sample_perfect_tile(
loop=l3,
n=4,
max_innermost_factor=64,
decision=d1,
)
l17, l18, l19, l20 = sch.split(loop=l3, factors=[v13, v14, v15, v16])
v21, v22 = sch.sample_perfect_tile(
loop=l4,
n=2,
max_innermost_factor=64,
decision=d2,
)
l23, l24 = sch.split(loop=l4, factors=[v21, v22])
sch.reorder(l9, l17, l10, l18, l23, l11, l19, l24, l12, l20)
sch.reverse_compute_at(block=b1, loop=l18, preserve_unit_loops=True)
sch.annotate(block_or_loop=root, ann_key="meta_schedule.parallel", ann_val=ann_val)
# pylint: enable=invalid-name
return sch
def _schedule_matmul(sch: Schedule):
block = sch.get_block("matmul")
i, j, k = sch.get_loops(block=block)
i_0, i_1, i_2, i_3 = sch.split(loop=i, factors=[2, 4, 64, 2])
j_0, j_1, j_2, j_3 = sch.split(loop=j, factors=[4, 64, 2, 2])
k_0, k_1 = sch.split(loop=k, factors=[32, 32])
sch.reorder(i_0, j_0, i_1, j_1, k_0, i_2, j_2, k_1, i_3, j_3)
def _schedule_matmul(sch: Schedule):
block = sch.get_block("matmul")
i, j, k = sch.get_loops(block=block)
# TODO(@zxybazh): Change to `sample_perfect_tile` after upstreaming
i_0, i_1, i_2, i_3 = sch.split(loop=i, factors=[2, 4, 64, 2])
j_0, j_1, j_2, j_3 = sch.split(loop=j, factors=[4, 64, 2, 2])
k_0, k_1 = sch.split(loop=k, factors=[32, 32])
sch.reorder(i_0, j_0, i_1, j_1, k_0, i_2, j_2, k_1, i_3, j_3)
def _schedule_matmul(sch: Schedule):
block = sch.get_block("matmul")
i, j, k = sch.get_loops(block=block)
i_tiles = [1, 1, 2, 512]
j_tiles = [1, 512, 1, 2]
k_tiles = [256, 4]
i_0, i_1, i_2, i_3 = sch.split(loop=i, factors=i_tiles)
j_0, j_1, j_2, j_3 = sch.split(loop=j, factors=j_tiles)
k_0, k_1 = sch.split(loop=k, factors=k_tiles)
sch.reorder(i_0, j_0, i_1, j_1, k_0, i_2, j_2, k_1, i_3, j_3)
def _sch(decisions: List[List[int]]) -> Schedule:
sch = Schedule(matmul, debug_mask="all")
# pylint: disable=invalid-name
(d0,) = decisions
b0 = sch.get_block(name="C", func_name="main")
sch.get_consumers(block=b0)
b1 = sch.cache_write(block=b0, write_buffer_index=0, storage_scope="global")
l2, l3, l4 = sch.get_loops(block=b0)
v5, v6, v7, v8 = sch.sample_perfect_tile(
loop=l2,
n=4,
max_innermost_factor=64,
decision=d0,
)
l9, l10, l11, l12 = sch.split(loop=l2, factors=[v5, v6, v7, v8])
l17, l18, l19, l20 = sch.split(loop=l3, factors=[8, 4, 8, 2])
l23, l24 = sch.split(loop=l4, factors=[512, 1])
sch.reorder(l9, l17, l10, l18, l23, l11, l19, l24, l12, l20)
sch.reverse_compute_at(block=b1, loop=l18, preserve_unit_loops=True)
# pylint: enable=invalid-name
return sch
def _sch() -> Schedule:
sch = Schedule(element_wise, debug_mask="all")
# pylint: disable=invalid-name
b0 = sch.get_block(name="C", func_name="main")
l1, l2 = sch.get_loops(block=b0)
l3 = sch.fuse(l1, l2)
v4 = sch.sample_categorical(
candidates=[32, 64, 128, 256, 512, 1024],
probs=[
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
],
decision=3,
)
l5, l6 = sch.split(loop=l3, factors=[None, v4])
sch.bind(loop=l5, thread_axis="blockIdx.x")
sch.bind(loop=l6, thread_axis="threadIdx.x")
# pylint: enable=invalid-name
return sch
