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BUG: Fix einsum optimize logic for singleton dimensions #10559

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Merged
merged 4 commits into from
Feb 9, 2018
Merged

BUG: Fix einsum optimize logic for singleton dimensions #10559

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bd505de
FIX: Fix einsum optimize logic for singleton dimensions
larsoner Jan 9, 2018
01e313e
ENH: Add broadcasting test
larsoner Jan 14, 2018
2afc7d5
Patches up broadcasting einsum issues for BLAS cases
dgasmith Jan 17, 2018
ab3e91c
FIX: Deduplicate code
larsoner Jan 18, 2018
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26 changes: 19 additions & 7 deletions numpy/core/einsumfunc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -706,10 +706,13 @@ def einsum_path(*operands, **kwargs):
for cnum, char in enumerate(term):
dim = sh[cnum]
if char in dimension_dict.keys():
if dimension_dict[char] != dim:
raise ValueError("Size of label '%s' for operand %d does "
"not match previous terms."
% (char, tnum))
# For broadcasting cases we always want the largest dim size
if dimension_dict[char] == 1:
dimension_dict[char] = dim
elif dim not in (1, dimension_dict[char]):
raise ValueError("Size of label '%s' for operand %d (%d) "
"does not match previous terms (%d)."
% (char, tnum, dimension_dict[char], dim))
else:
dimension_dict[char] = dim

Expand Down Expand Up @@ -1101,13 +1104,22 @@ def einsum(*operands, **kwargs):
if specified_out and ((num + 1) == len(contraction_list)):
handle_out = True

# Call tensordot
# Handle broadcasting vs BLAS cases
if blas:

# Checks have already been handled
input_str, results_index = einsum_str.split('->')
input_left, input_right = input_str.split(',')

if 1 in tmp_operands[0] or 1 in tmp_operands[1]:
left_dims = {dim: size for dim, size in
zip(input_left, tmp_operands[0].shape)}
right_dims = {dim: size for dim, size in
zip(input_right, tmp_operands[1].shape)}
# If dims do not match we are broadcasting, BLAS off
if any(left_dims[ind] != right_dims[ind] for ind in idx_rm):
blas = False

# Call tensordot if still possible
if blas:
tensor_result = input_left + input_right
for s in idx_rm:
tensor_result = tensor_result.replace(s, "")
Expand Down
19 changes: 19 additions & 0 deletions numpy/core/tests/test_einsum.py
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Expand Up @@ -481,6 +481,25 @@ def check_einsum_sums(self, dtype, do_opt=False):
r = np.arange(4).reshape(2, 2) + 7
assert_equal(np.einsum('z,mz,zm->', p, q, r), 253)

# singleton dimensions broadcast (gh-10343)
p = np.ones((10,2))
q = np.ones((1,2))
assert_array_equal(np.einsum('ij,ij->j', p, q, optimize=True),
np.einsum('ij,ij->j', p, q, optimize=False))
assert_array_equal(np.einsum('ij,ij->j', p, q, optimize=True),
[10.] * 2)

p = np.ones((1, 5))
q = np.ones((5, 5))
for optimize in (True, False):
assert_array_equal(np.einsum("...ij,...jk->...ik", p, p,
optimize=optimize),
np.einsum("...ij,...jk->...ik", p, q,
optimize=optimize))
assert_array_equal(np.einsum("...ij,...jk->...ik", p, q,
optimize=optimize),
np.full((1, 5), 5))

def test_einsum_sums_int8(self):
self.check_einsum_sums('i1')

Expand Down