Handling the shape for loop condition

[gramalingam]

When mapping python loops to ONNX Loop, we need some strategy for typing (the shape, really) the loop-condition variable.

• One option is that all code uses a scalar (0D tensor) for the loop-condition, and this works fine.

But occasionally we run into situations where a 1D tensor with a single value is used. Currently, ONNX seems to permit this. If we want to allow this in ONNX Script:

• If we type the loop-body-subgraph to expect a 0D value as "condition", the ONNX checker will fail if and when the actual condition is a 1D tensor
• If we leave the loop-body-subgraph condition as a "boolean" without any shape, in some cases at least the ONNX checker fails (complaining about unknown rank).
• If we want to handle both reasonably, we will likely need to integrate shape-inference info into the onnxscript translator so that it can do different things based on the inferred type.
• One simpler short-cut would be for onnxscript to emit a Reshape/Squeeze for the loop-condition to convert it into a 0D tensor. But ideally, we should not emit this when it is unnecessary. Else, we end up with redundant ops (though a downstream optimizer could potentially remove it).