Shape prop view/reshape/as_strided through prim::ListConstructs #11877
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Previously, aten::view returned a Dynamic type when attr::size is a prim::ListConstruct. See [this for a repro](https://gist.github.com/zou3519/cbd610472ba3369f556fa612a7d93b28). This prevented a pre-multipled lstm input graph from being fusible (aten::view is necessary to do premultiplication). If aten::view is passed an output of a prim::ListConstruct node, then shape prop should be able to figure out its TensorType because we statically know the number of inputs to prim::ListConstruct. This PR implements that.
zou3519
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apaszke,
colesbury,
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gchanan,
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zdevito
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apaszke
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Sep 20, 2018
| auto input_node = node->namedInput(shape_input)->node(); | ||
| if (input_node->kind() == prim::ListConstruct) { | ||
| return tensor_types.at(0)->withDim(input_node->inputs().size()); | ||
| } |
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test/test_jit.py
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| x = torch.randn(3, 1, 5, requires_grad=True) | ||
| graph = torch.jit.script(fn).graph | ||
| torch._C._jit_pass_complete_shape_analysis(graph, (x,), False) | ||
| self.assertExpectedGraph(graph) |
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… test with better test
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test/test_jit.py
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| x = torch.randn(3, 1, 5, requires_grad=True) | ||
| graph = torch.jit.script(fn).graph | ||
| torch._C._jit_pass_complete_shape_analysis(graph, (x,), False) |
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Previously, aten::view returned a Dynamic type when attr::size is a prim::ListConstruct.
See this for a repro.
This prevented a pre-multipled lstm input graph from being fusible (aten::view is necessary
to do premultiplication).
If aten::view is passed an output of a prim::ListConstruct node, then shape prop should
be able to figure out its TensorType because we statically know the number of inputs to
prim::ListConstruct. This PR implements that.