ptrendx opened a new pull request #16836: Fix InferAttr/InferShapeAttr not calling inference for all nodes in a graph URL: https://github.com/apache/incubator-mxnet/pull/16836 ## Description ## Currently type/shape inference of the operator is only called if the values of input and output attributes are not currently known. This is a bug as it may lead to some operators never seeing the values of those inputs/outputs attributes during InferAttr pass and so never validating them. As an example, this code snippet runs without throwing any exception in current MXNet: ``` v = mx.sym.Variable('V') s = mx.sym.transpose(v) x = mx.sym.Variable('x') s2 = x + v s3 = s + s2 e = s3.simple_bind(ctx=mx.cpu(), x=(2,3), grad_req='null') ``` and it errors out only when calling `e.forward` (in 1.5.1, in 1.6.0 new 2D transpose implementation removed the check for shape inside the forward function of the operator so it does not error out even then). This is because the `transpose` node is early in the topologically sorted graph and ran its shape inference earlier (on unknown input and output shapes) than the `_Plus` operators, which then set all of the shapes by themselves, which prevented `transpose` from running its shape inference again to spot that they are not suitable for this operator. In this PR, I track which operators are actually finished inferring attributes (including validating the attributes they got if all of the inputs/outputs are already known at the point of running their attribute inference). ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [x] Changes are complete (i.e. I finished coding on this PR) - [x] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) ## Comments ## - Currently I check that the operator finished inferring attributes if all input and output attributes are set after the call to operator's InferShape/InferType. This should not be necessary as those functions return the value that should be equivalent. However, since this value was never actually checked, there are a lot of operators that lie and return `true` even if not everything was inferred correctly. This should be tackled in a separate PR.
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