def input_tile_data_pad(sch: Schedule):
b115 = sch.get_block(name="input_tile")
(b116,) = sch.get_consumers(block=b115)
_, _, _, l120, _, _, _, _ = sch.get_loops(block=b116)
sch.compute_at(block=b115, loop=l120, preserve_unit_loops=True)
sch.set_scope(block=b115, buffer_index=0, storage_scope="local")
b127 = sch.get_block(name="data_pad")
sch.compute_inline(block=b127)
b3 = sch.get_block(name="data_pack")
l25, l26, l27, l28, _, _, _, _ = sch.get_loops(block=b3)
l33 = sch.fuse(l25, l26, l27, l28)
v34 = sch.sample_categorical(
candidates=[32, 64, 128, 256, 512, 1024],
probs=[
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
],
decision=2,
)
l35, l36 = sch.split(loop=l33, factors=[None, v34])
sch.bind(loop=l35, thread_axis="blockIdx.x")
sch.bind(loop=l36, thread_axis="threadIdx.x")
def input_tile_data_pad(sch: Schedule):
b78 = sch.get_block(name="input_tile")
l80 = sch.sample_compute_location(block=b78, decision=4)
sch.compute_at(block=b78, loop=l80, preserve_unit_loops=True)
b81 = sch.get_block(name="data_pad")
l83 = sch.sample_compute_location(block=b81, decision=-2)
sch.compute_at(block=b81, loop=l83, preserve_unit_loops=True)
def input_tile_data_pad(sch: Schedule):
b115 = sch.get_block(name="input_tile")
(b116, ) = sch.get_consumers(block=b115)
_, _, _, l120, _, _, _, _ = sch.get_loops(block=b116)
sch.compute_at(block=b115, loop=l120, preserve_unit_loops=True)
sch.set_scope(block=b115, buffer_index=0, storage_scope="local")
b127 = sch.get_block(name="data_pad")
sch.compute_inline(block=b127)
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(i, sch.sample_perfect_tile(i, n=4))
j_0, j_1, j_2, j_3 = sch.split(j, sch.sample_perfect_tile(j, n=4))
k_0, k_1 = sch.split(k, sch.sample_perfect_tile(k, n=2))
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 root_anno(sch: Schedule):
b8 = sch.get_block(name="root", func_name="main")
v140 = sch.sample_categorical(
candidates=[0, 16, 64, 512, 1024],
probs=[
0.20000000000000001,
0.20000000000000001,
0.20000000000000001,
0.20000000000000001,
0.20000000000000001,
],
decision=2,
)
sch.annotate(block_or_loop=b8, ann_key="meta_schedule.unroll_explicit", ann_val=v140)
def conv2d(sch: Schedule):
b7 = sch.get_block(name="conv2d_winograd")
l141, l142, l143, l144 = sch.get_loops(block=b7)
l145 = sch.fuse(l141, l142, l143, l144)
v146 = sch.sample_categorical(
candidates=[32, 64, 128, 256, 512, 1024],
probs=[
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
],
decision=2,
)
l147, l148 = sch.split(loop=l145, factors=[None, v146])
sch.bind(loop=l147, thread_axis="blockIdx.x")
sch.bind(loop=l148, thread_axis="threadIdx.x")
def inverse(sch: Schedule):
b3 = sch.get_block(name="inverse")
l4, l5, l6, l7, l8, l9 = sch.get_loops(block=b3)
sch.unroll(loop=l4)
sch.unroll(loop=l5)
v10, v11 = sch.sample_perfect_tile(
n=2,
loop=l6,
max_innermost_factor=64,
decision=[1, 9],
)
l12, l13 = sch.split(loop=l6, factors=[v10, v11])
v14, v15 = sch.sample_perfect_tile(
n=2,
loop=l7,
max_innermost_factor=64,
decision=[2, 64],
)
l16, l17 = sch.split(loop=l7, factors=[v14, v15])
sch.unroll(loop=l8)
sch.unroll(loop=l9)
sch.reorder(l12, l16, l13, l17, l4, l5, l8, l9)
def data_pack(sch: Schedule):
b16 = sch.get_block(name="data_pack")
l17, l18, l19, l20, l21, l22 = sch.get_loops(block=b16)
sch.unroll(loop=l17)
sch.unroll(loop=l18)
v23, v24 = sch.sample_perfect_tile(
n=2,
loop=l19,
max_innermost_factor=64,
decision=[3, 3],
)
l25, l26 = sch.split(loop=l19, factors=[v23, v24])
v27, v28 = sch.sample_perfect_tile(
n=2,
loop=l20,
max_innermost_factor=64,
decision=[64, 2],
)
l29, l30 = sch.split(loop=l20, factors=[v27, v28])
sch.unroll(loop=l21)
sch.unroll(loop=l22)
sch.reorder(l25, l29, l26, l30, l17, l18, l21, l22)
def data_pack(sch: Schedule):
b18 = sch.get_block(name="data_pack")
l19, l20, l21, l22, l23, l24 = sch.get_loops(block=b18)
sch.unroll(loop=l19)
sch.unroll(loop=l20)
v25, v26 = sch.sample_perfect_tile(
n=2,
loop=l21,
max_innermost_factor=64,
decision=[9, 1],
)
l27, l28 = sch.split(loop=l21, factors=[v25, v26])
v29, v30 = sch.sample_perfect_tile(
n=2,
loop=l22,
max_innermost_factor=64,
decision=[32, 4],
)
l31, l32 = sch.split(loop=l22, factors=[v29, v30])
sch.unroll(loop=l23)
sch.unroll(loop=l24)
sch.reorder(l27, l31, l28, l32, l19, l20, l23, l24)
def inverse(sch: Schedule):
b1 = sch.get_block(name="inverse")
l2, l3, l4, l5, l6, l7 = sch.get_loops(block=b1)
sch.unroll(loop=l2)
sch.unroll(loop=l3)
v8, v9 = sch.sample_perfect_tile(
n=2,
loop=l4,
max_innermost_factor=64,
decision=[3, 3],
)
l10, l11 = sch.split(loop=l4, factors=[v8, v9])
v12, v13 = sch.sample_perfect_tile(
n=2,
loop=l5,
max_innermost_factor=64,
decision=[2, 64],
)
l14, l15 = sch.split(loop=l5, factors=[v12, v13])
sch.unroll(loop=l6)
sch.unroll(loop=l7)
sch.reorder(l10, l14, l11, l15, l2, l3, l6, l7)
def inverse(sch: Schedule):
b1 = sch.get_block(name="inverse")
l2, l3, l4, l5, l6, l7 = sch.get_loops(block=b1)
sch.unroll(loop=l2)
sch.unroll(loop=l3)
v8, v9 = sch.sample_perfect_tile(
n=2,
loop=l4,
max_innermost_factor=64,
decision=[3, 3],
)
l10, l11 = sch.split(loop=l4, factors=[v8, v9])
v12, v13 = sch.sample_perfect_tile(
n=2,
loop=l5,
max_innermost_factor=64,
decision=[2, 64],
)
l14, l15 = sch.split(loop=l5, factors=[v12, v13])
sch.unroll(loop=l6)
sch.unroll(loop=l7)
sch.reorder(l10, l14, l11, l15, l2, l3, l6, l7)
l59 = sch.fuse(l10, l14, l11, l15)
v60 = sch.sample_categorical(
candidates=[32, 64, 128, 256, 512, 1024],
probs=[
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
],
decision=2,
)
l61, l62 = sch.split(loop=l59, factors=[None, v60])
sch.bind(loop=l61, thread_axis="blockIdx.x")
sch.bind(loop=l62, thread_axis="threadIdx.x")
def bgemm(sch: Schedule):
b31 = sch.get_block(name="bgemm")
sch.annotate(
block_or_loop=b31,
ann_key="meta_schedule.tiling_structure",
ann_val="SSSRRSRS",
)
b32 = sch.cache_write(block=b31,
write_buffer_index=0,
storage_scope="local")
b31, b32 = b32, b31
l33, l34, l35, l36, l37 = sch.get_loops(block=b32)
v38, v39, v40, v41, v42 = sch.sample_perfect_tile(
n=5,
loop=l33,
max_innermost_factor=64,
decision=[1, 1, 1, 1, 6],
)
l43, l44, l45, l46, l47 = sch.split(loop=l33,
factors=[v38, v39, v40, v41, v42])
v48, v49, v50, v51, v52 = sch.sample_perfect_tile(
n=5,
loop=l34,
max_innermost_factor=64,
decision=[1, 1, 1, 3, 2],
)
l53, l54, l55, l56, l57 = sch.split(loop=l34,
factors=[v48, v49, v50, v51, v52])
v58, v59, v60, v61, v62 = sch.sample_perfect_tile(
n=5,
loop=l35,
max_innermost_factor=64,
decision=[3, 1, 1, 1, 3],
)
l63, l64, l65, l66, l67 = sch.split(loop=l35,
factors=[v58, v59, v60, v61, v62])
v68, v69, v70, v71, v72 = sch.sample_perfect_tile(
n=5,
loop=l36,
max_innermost_factor=64,
decision=[4, 2, 1, 4, 4],
)
l73, l74, l75, l76, l77 = sch.split(loop=l36,
factors=[v68, v69, v70, v71, v72])
v78, v79, v80 = sch.sample_perfect_tile(
n=3,
loop=l37,
max_innermost_factor=64,
decision=[32, 1, 4],
)
l81, l82, l83 = sch.split(loop=l37, factors=[v78, v79, v80])
sch.reorder(
# fmt: off
l43,
l53,
l63,
l73,
l44,
l54,
l64,
l74,
l45,
l55,
l65,
l75,
l81,
l82,
l46,
l56,
l66,
l76,
l83,
l47,
l57,
l67,
l77,
# fmt: on
)
l84 = sch.fuse(l43, l53, l63, l73)
sch.bind(loop=l84, thread_axis="blockIdx.x")
l85 = sch.fuse(l44, l54, l64, l74)
sch.bind(loop=l85, thread_axis="vthread.x")
l86 = sch.fuse(l45, l55, l65, l75)
sch.bind(loop=l86, thread_axis="threadIdx.x")
b87 = sch.cache_read(block=b32,
read_buffer_index=1,
storage_scope="shared")
sch.compute_at(block=b87, loop=l81, preserve_unit_loops=True)
_, _, _, _, l92, l93, l94, l95 = sch.get_loops(block=b87)
sch.fuse(l92, l93, l94, l95)
v97 = sch.sample_categorical(
candidates=[1, 2, 3, 4],
probs=[0.25, 0.25, 0.25, 0.25],
decision=1,
)
sch.annotate(
block_or_loop=b87,
ann_key="meta_schedule.cooperative_fetch",
ann_val=v97,
)
b101 = sch.cache_read(block=b32,
read_buffer_index=2,
storage_scope="shared")
sch.compute_at(block=b101, loop=l81, preserve_unit_loops=True)
_, _, _, _, l106, l107, l108, l109 = sch.get_loops(block=b101)
sch.fuse(l106, l107, l108, l109)
v110 = sch.sample_categorical(
candidates=[1, 2, 3, 4],
probs=[0.25, 0.25, 0.25, 0.25],
decision=1,
)
sch.annotate(
block_or_loop=b101,
ann_key="meta_schedule.cooperative_fetch",
ann_val=v110,
)
sch.reverse_compute_at(block=b31, loop=l86, preserve_unit_loops=True)
def inline(sch: Schedule):
b125 = sch.get_block(name="A")
sch.compute_inline(block=b125)
b126 = sch.get_block(name="B")
sch.compute_inline(block=b126)
def bgemm(sch: Schedule):
bgemm = sch.get_block(name="bgemm")
write_cache = sch.cache_write(
block=bgemm,
write_buffer_index=0,
storage_scope="global",
)
sch.annotate(
block_or_loop=bgemm,
ann_key="meta_schedule.tiling_structure",
ann_val="SSRSRS",
)
# b33, b34 = b34, b33
l35, l36, l37, l38, l39 = sch.get_loops(block=bgemm)
v40, v41, v42, v43 = sch.sample_perfect_tile(
n=4,
loop=l35,
max_innermost_factor=64,
decision=[1, 2, 3, 1],
)
l44, l45, l46, l47 = sch.split(loop=l35, factors=[v40, v41, v42, v43])
v48, v49, v50, v51 = sch.sample_perfect_tile(
n=4,
loop=l36,
max_innermost_factor=64,
decision=[1, 1, 1, 6],
)
l52, l53, l54, l55 = sch.split(loop=l36, factors=[v48, v49, v50, v51])
v56, v57, v58, v59 = sch.sample_perfect_tile(
n=4,
loop=l37,
max_innermost_factor=64,
decision=[1, 1, 1, 9],
)
l60, l61, l62, l63 = sch.split(loop=l37, factors=[v56, v57, v58, v59])
v64, v65, v66, v67 = sch.sample_perfect_tile(
n=4,
loop=l38,
max_innermost_factor=64,
decision=[2, 1, 16, 4],
)
l68, l69, l70, l71 = sch.split(loop=l38, factors=[v64, v65, v66, v67])
v72, v73 = sch.sample_perfect_tile(
n=2,
loop=l39,
max_innermost_factor=64,
decision=[16, 8],
)
l74, l75 = sch.split(loop=l39, factors=[v72, v73])
sch.reorder(
# fmt: off
l44,
l52,
l60,
l68,
l45,
l53,
l61,
l69,
l74,
l46,
l54,
l62,
l70,
l75,
l47,
l55,
l63,
l71,
# fmt: on
)
sch.reverse_compute_at(block=write_cache,
loop=l69,
preserve_unit_loops=True)
def _schedule_matmul_small(sch: Schedule):
block = sch.get_block("matmul")
_, j, k = sch.get_loops(block=block)
_, _ = sch.split(j, sch.sample_perfect_tile(j, n=2))
_, _ = sch.split(k, sch.sample_perfect_tile(k, n=2))
def inline(sch: Schedule):
b1 = sch.get_block(name="A")
b2 = sch.get_block(name="B")
sch.compute_inline(block=b1)
sch.compute_inline(block=b2)