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[TOPI][batch_matmul] Allow cblas batch_matmul implicit batch_size broadcast #8250

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Merged
masahi merged 2 commits into from
Jun 12, 2021
Merged

[TOPI][batch_matmul] Allow cblas batch_matmul implicit batch_size broadcast #8250

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d8c48ed
Allow cblas batch_matmul implicit bcast
ymwangg Jun 11, 2021
34c2314
Add cblas batch_matmul bcast when batch_a=1
ymwangg Jun 11, 2021
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2 changes: 1 addition & 1 deletion python/tvm/contrib/cblas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@ def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False, **kwargs
C: Tensor
The result tensor.
"""
b = lhs.shape[0]
b = te.max(lhs.shape[0], rhs.shape[0])
n = lhs.shape[2] if transa else lhs.shape[1]
m = rhs.shape[1] if transb else rhs.shape[2]
return te.extern(
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2 changes: 1 addition & 1 deletion python/tvm/contrib/mkl.py
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Expand Up @@ -105,7 +105,7 @@ def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False, **kwargs
C: Tensor
The result tensor.
"""
b = lhs.shape[0]
b = te.max(lhs.shape[0], rhs.shape[0])
n = lhs.shape[2] if transa else lhs.shape[1]
m = rhs.shape[1] if transb else rhs.shape[2]
return te.extern(
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6 changes: 3 additions & 3 deletions python/tvm/topi/x86/batch_matmul.py
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Expand Up @@ -139,7 +139,7 @@ def _default_batch_matmul_config(cfg, M, N, K):

def batch_matmul_blas_common(cfg, x, y, out_shape, lib):
"""Computes batch matrix multiplication of `x` and `y` when `x` and `y` are
data in batch, using one of BLAS libraries.
data in batch, using one of BLAS libraries. Supports broadcasting in batch dimension.

Parameters
----------
Expand All @@ -162,10 +162,10 @@ def batch_matmul_blas_common(cfg, x, y, out_shape, lib):
assert len(x.shape) == 3 and len(y.shape) == 3, "only support 3-dim batch_matmul"
XB, M, XK = get_const_tuple(x.shape)
YB, N, YK = get_const_tuple(y.shape)
assert XB == YB, "batch dimension doesn't match"
assert (XB == YB) or (YB == 1) or (XB == 1), "batch dimension doesn't match"
assert XK == YK, "shapes of x and y is inconsistent"
if out_shape is not None:
assert out_shape[0] == XB, "got invalid output shape"
assert out_shape[0] in (XB, YB), "got invalid output shape"
assert out_shape[1] == M, "got invalid output shape"
assert out_shape[2] == N, "got invalid output shape"
cfg.add_flop(XB * M * N * XK * 2)
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53 changes: 31 additions & 22 deletions tests/python/contrib/test_cblas.py
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Expand Up @@ -158,13 +158,14 @@ def test_quantized_matmul_add():


def verify_batch_matmul(
batch, m, l, n, lib, transa=False, transb=False, iterative=False, dtype="float32"
batch_a, batch_b, m, l, n, lib, transa=False, transb=False, iterative=False, dtype="float32"
):
ashape = (batch, l, n) if transa else (batch, n, l)
bshape = (batch, m, l) if transb else (batch, l, m)
batch = max(batch_a, batch_b)
ashape = (batch_a, l, n) if transa else (batch_a, n, l)
bshape = (batch_b, m, l) if transb else (batch_b, l, m)
A = te.placeholder(ashape, name="A", dtype=dtype)
B = te.placeholder(bshape, name="B", dtype=dtype)
C = cblas.batch_matmul(A, B, transa, transb)
C = lib.batch_matmul(A, B, transa, transb)
D = te.compute(C.shape, lambda k, i, j: C[k, i, j], name="D")
s = te.create_schedule(D.op)

Expand Down Expand Up @@ -207,24 +208,32 @@ def verify(target="llvm"):


def test_batch_matmul():
verify_batch_matmul(16, 235, 128, 1024, cblas)
verify_batch_matmul(16, 235, 128, 1024, cblas, True, False)
verify_batch_matmul(16, 235, 128, 1024, cblas, False, True)
verify_batch_matmul(16, 235, 128, 1024, cblas, True, True)
verify_batch_matmul(16, 235, 128, 1024, mkl)
verify_batch_matmul(16, 235, 128, 1024, mkl, True, False)
verify_batch_matmul(16, 235, 128, 1024, mkl, False, True)
verify_batch_matmul(16, 235, 128, 1024, mkl, True, True)
verify_batch_matmul(1, 1, 16, 3, cblas)
verify_batch_matmul(1, 1, 16, 3, cblas, True, False)
verify_batch_matmul(1, 1, 16, 3, cblas, False, False)
verify_batch_matmul(1, 1, 16, 3, cblas, True, True)
verify_batch_matmul(1, 1, 16, 3, cblas, iterative=True)
verify_batch_matmul(1, 1, 16, 3, mkl)
verify_batch_matmul(1, 1, 16, 3, mkl, True, False)
verify_batch_matmul(1, 1, 16, 3, mkl, False, False)
verify_batch_matmul(1, 1, 16, 3, mkl, True, True)
verify_batch_matmul(1, 1, 16, 3, mkl, iterative=True)
verify_batch_matmul(16, 16, 235, 128, 1024, cblas)
verify_batch_matmul(16, 16, 235, 128, 1024, cblas, True, False)
verify_batch_matmul(16, 16, 235, 128, 1024, cblas, False, True)
verify_batch_matmul(16, 16, 235, 128, 1024, cblas, True, True)
verify_batch_matmul(16, 16, 235, 128, 1024, mkl)
verify_batch_matmul(16, 16, 235, 128, 1024, mkl, True, False)
verify_batch_matmul(16, 16, 235, 128, 1024, mkl, False, True)
verify_batch_matmul(16, 16, 235, 128, 1024, mkl, True, True)
verify_batch_matmul(16, 1, 235, 128, 1024, cblas)
verify_batch_matmul(1, 16, 235, 128, 1024, cblas)
verify_batch_matmul(16, 1, 235, 128, 1024, cblas, iterative=True)
verify_batch_matmul(1, 16, 235, 128, 1024, cblas, iterative=True)
verify_batch_matmul(16, 1, 235, 128, 1024, mkl)
verify_batch_matmul(1, 16, 235, 128, 1024, mkl)
verify_batch_matmul(16, 1, 235, 128, 1024, mkl, iterative=True)
verify_batch_matmul(1, 16, 235, 128, 1024, mkl, iterative=True)
verify_batch_matmul(1, 1, 1, 16, 3, cblas)
verify_batch_matmul(1, 1, 1, 16, 3, cblas, True, False)
verify_batch_matmul(1, 1, 1, 16, 3, cblas, False, False)
verify_batch_matmul(1, 1, 1, 16, 3, cblas, True, True)
verify_batch_matmul(1, 1, 1, 16, 3, cblas, iterative=True)
verify_batch_matmul(1, 1, 1, 16, 3, mkl)
verify_batch_matmul(1, 1, 1, 16, 3, mkl, True, False)
verify_batch_matmul(1, 1, 1, 16, 3, mkl, False, False)
verify_batch_matmul(1, 1, 1, 16, 3, mkl, True, True)
verify_batch_matmul(1, 1, 1, 16, 3, mkl, iterative=True)


if __name__ == "__main__":
Expand Down