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Fix stack bug for 129inputs #8927

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merged 7 commits into from
Aug 17, 2022
Merged

Fix stack bug for 129inputs #8927

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46eb718
fix(StackOp): fix bug when input number is 128*n+1
wyg1997 Aug 16, 2022
611cb3b
test(Stack): add kMaxInputCount for stack op test
wyg1997 Aug 16, 2022
6a4815c
format code
wyg1997 Aug 16, 2022
39d34c1
add comment
wyg1997 Aug 16, 2022
c476b0b
refine test case
wyg1997 Aug 16, 2022
6724320
fix as static analysis
wyg1997 Aug 16, 2022
b9c4b7a
Merge branch 'master' into fix-stack_bug_for_129inputs
wyg1997 Aug 17, 2022
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10 changes: 7 additions & 3 deletions oneflow/core/functional/impl/array_functor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -596,7 +596,6 @@ class StackFunctor {
int64_t ndims = inputs[0]->ndim();
int64_t stack_dim = dim;
stack_dim = JUST(maybe_wrap_dim(stack_dim, ndims + 1));
if (ninput == 1) { return ExpandDims(inputs[0], dim); }
const std::shared_ptr<const Shape>& first_in_shape = inputs[0]->shape();
for (const auto& input : inputs) {
for (int i = 0; i < ndims; ++i) {
Expand All @@ -615,8 +614,13 @@ class StackFunctor {
size_t size = (i + kMaxInputCount) < ninput ? kMaxInputCount : ninput - i;
TensorTuple partial_inputs(size);
for (int j = 0; j < size; ++j) { partial_inputs[j] = inputs[i + j]; }
outputs.emplace_back(
JUST(OpInterpUtil::Dispatch<Tensor>(*ops_.at(size - 1), partial_inputs, attrs)));
if (partial_inputs.size() == 1) {
// Use ExpandDims functor for only one input
outputs.emplace_back(JUST(functional::ExpandDims(partial_inputs[0], dim)));
} else {
outputs.emplace_back(
JUST(OpInterpUtil::Dispatch<Tensor>(*ops_.at(size - 1), partial_inputs, attrs)));
}
}
if (outputs.size() == 1) { return outputs.at(0); }
return Concat(outputs, stack_dim);
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9 changes: 9 additions & 0 deletions python/oneflow/test/modules/test_stack.py
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Expand Up @@ -44,6 +44,15 @@ def test_stack_bool_with_random_data(test_case):
out = torch.stack((x, y), dim=random(low=1, high=4).to(int))
return out

@autotest(auto_backward=True, check_graph=True)
def test_stack_kMaxInputCount_inputs(test_case):
kMaxInputCount = 128 + 1
stack_list = [
random_tensor(ndim=2, dim0=3, dim1=4) for _ in range(kMaxInputCount)
]
out = torch.stack(stack_list, 0)
return out


if __name__ == "__main__":
unittest.main()