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[TOPI] Allow batch matmul to be fused into injective ops #4537

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Dec 18, 2019
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[TOPI] Allow batch matmul to be fused into injective ops #4537

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45 changes: 26 additions & 19 deletions topi/python/topi/x86/batch_matmul.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,33 +92,40 @@ def schedule_batch_matmul(cfg, outs):
def _callback(op):
if "batch_matmul" in op.tag:
C = op.output(0)
A, B = s[C].op.input_tensors
A, B = op.input_tensors
_, M, K = get_const_tuple(A.shape)
_, _, N = get_const_tuple(C.shape)

if op not in s.outputs:
s[C].compute_inline()
O = outs[0]
else:
O = C

CC = s.cache_write(C, "global")

# create tuning space
cfg.define_split("tile_y", M, num_outputs=2)
cfg.define_split("tile_x", N, num_outputs=2)
cfg.define_split("tile_k", K, num_outputs=2)

k, = s[C].op.reduce_axis

ko, ki = cfg["tile_k"].apply(s, C, k)
CC = s.rfactor(C, ki)

b, y, x = s[C].op.axis
yo, yi = cfg["tile_y"].apply(s, C, y)
xo, xi = cfg["tile_x"].apply(s, C, x)
s[C].reorder(b, yo, xo, yi, xi)
bxyo = s[C].fuse(b, yo, xo)
s[C].parallel(bxyo)
s[C].fuse(yi, xi)

s[CC].compute_at(s[C], bxyo)
_, _, y, x = s[CC].op.axis
s[CC].fuse(y, x)
s[CC].vectorize(s[CC].op.axis[0])
s[C].pragma(bxyo, 'auto_unroll_max_step', 16)
b, y, x = s[O].op.axis
yo, yi = cfg["tile_y"].apply(s, O, y)
xo, xi = cfg["tile_x"].apply(s, O, x)
s[O].reorder(b, yo, xo, yi, xi)
bxyo = s[O].fuse(b, yo, xo)
s[O].parallel(bxyo)

s[CC].compute_at(s[O], bxyo)
k, = s[CC].op.reduce_axis
ko, ki = cfg["tile_k"].apply(s, CC, k)

Crf = s.rfactor(CC, ki)
s[Crf].compute_at(s[CC], s[CC].op.axis[0])
_, _, y, x = s[Crf].op.axis
s[Crf].fuse(y, x)
s[Crf].vectorize(s[Crf].op.axis[0])
s[O].pragma(bxyo, 'auto_unroll_max_step', 16)

traverse_inline(s, outs[0].op, _callback)
return s
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