Bidaf model includes CategoryMapper op with rank-4 input, although the input must be a tensor of strings or integers, either [N,C] or [C].

Bug Report

Which model does this pertain to?

Bidaf https://github.com/onnx/models/tree/main/text/machine_comprehension/bidirectional_attention_flow

Describe the bug

The model includes CategoryMapper op with rank-4 input, although the input rank should be one or two.

According to the onnx.ml.CategoryMapper definition at https://github.com/onnx/onnx/blob/main/docs/Operators-ml.md#ai.onnx.ml.CategoryMapper, The input must be a tensor of strings or integers, either [N,C] or [C].

As you know, onnx.CategoryMapper op is a simple string-to-integer (or integer-to-string) mapper, any input shape can be supported naturally, but the operation definition and the bidaf model are not consistent.

I am not sure if the operation definition is too strict or the model is illegal, but I am happy if the official bidaf model will be fixed.

CategoryMapper op definition

ai.onnx.ml.CategoryMapper
Converts strings to integers and vice versa.
...
Inputs
X : T1
    Input data
Outputs
Y : T2
    Output data. If strings are input, the output values are integers, and vice versa.

Type Constraints
T1 : tensor(string), tensor(int64)
    The input must be a tensor of strings or integers, either [N,C] or [C].
T2 : tensor(string), tensor(int64)
    The output is a tensor of strings or integers. Its shape will be the same as the input shape.  

Reproduction instructions

N/A

Notes

N/A

Start with the Bidaf model in the linked model directory, then compare its CategoryMapper input shape with the referenced onnx.ml.CategoryMapper definition. Determine whether the model or the operator definition is inconsistent; done means the official model and the documented permitted input shapes agree.