【SCU】【Paddle Tensor 第二期 API 支持 0-size TensorNo.46】paddle.linalg.solve 支持 0-size Tensor #70575
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| if (y_dims.size() == 1) { | ||
| out_dims = | ||
| std::vector<int>(x_dims.Get(), x_dims.Get() + x_dims.size() - 2); | ||
| out_dims.push_back(y_dims[y_dims.size() - 1]); |
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这个分支有测试到吗？
这个好像测不到，python层solve函数有一个检查输入格式的函数了，如果y_dims.size() == 1会raise ValueError，已经添加单测了）
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| int x_dim = (x_it != x_shape.rend()) ? *x_it : 1; | ||
| int y_dim = (y_it != y_shape.rend()) ? *y_it : 1; | ||
| out_dims.push_back(std::max(x_dim, y_dim)); |
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这里有个问题，广播时如果 xdim=1，ydim=0，那么结果的outdim应该是0而不是1
test/legacy_test/test_solve_op.py
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| def test_dygraph(self): | ||
| def run(place, x_shape, y_shape): | ||
| paddle.disable_static(place) |
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改用with xxguard代替disable/enable static
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| if (x.numel() == 0 || y.numel() == 0) { | ||
| auto x_dims = x.dims(); | ||
| auto y_dims = y.dims(); | ||
| std::vector<int> out_dims; | ||
| if (y_dims.size() == 1) { | ||
| out_dims = | ||
| std::vector<int>(x_dims.Get(), x_dims.Get() + x_dims.size() - 2); | ||
| out_dims.push_back(y_dims[y_dims.size() - 1]); | ||
| } else { | ||
| // broadcast | ||
| std::vector<int> x_shape(x_dims.Get(), x_dims.Get() + x_dims.size() - 2); | ||
| std::vector<int> y_shape(y_dims.Get(), y_dims.Get() + y_dims.size() - 2); | ||
| auto x_it = x_shape.rbegin(); | ||
| auto y_it = y_shape.rbegin(); | ||
| while (x_it != x_shape.rend() || y_it != y_shape.rend()) { | ||
| int x_dim = (x_it != x_shape.rend()) ? *x_it : 1; | ||
| int y_dim = (y_it != y_shape.rend()) ? *y_it : 1; | ||
| if (x_dim == 0 || y_dim == 0) { | ||
| out_dims.push_back(0); | ||
| } else { | ||
| out_dims.push_back(std::max(x_dim, y_dim)); | ||
| } | ||
| if (x_it != x_shape.rend()) ++x_it; | ||
| if (y_it != y_shape.rend()) ++y_it; | ||
| } | ||
| std::reverse(out_dims.begin(), out_dims.end()); | ||
| out_dims.insert(out_dims.end(), | ||
| y_dims.Get() + y_dims.size() - 2, | ||
| y_dims.Get() + y_dims.size()); | ||
| } | ||
| out->Resize(phi::make_ddim(out_dims)); |
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这段代码能移动到solve的infermeta里面吗？
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这段代码能移动到solve的infermeta里面吗？
好像不太行诶，移到binary.cc里面输入0-size tensor就报错了
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这段代码能移动到solve的infermeta里面吗？
好像不太行诶，移到binary.cc里面输入0-size tensor就报错了
好的
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Description
单测可以通过0-size的输入，但是
array_api_tests可能存在配置问题（在@pytest.mark.xp_extension('linalg')语句报错），先跑个CI看看。