[Fix][Relax][ONNX] Fix Upsample and Resize-10 import

[LiRunGuo]

The ONNX importer's handling of the legacy upsampling ops was broken in ways that affect most real models that use them. Upsample only exists in opsets 7 to 9 and Resize-10 is its direct successor, so these are exactly the ops found in older exported models such as YOLOv3-era detectors.

For Upsample-9, scales became an input, but the converter still read the removed attribute, so every opset 9 model failed with TypeError: object of type 'NoneType' has no len(). For Upsample-7/8 the model imported, but nearest mode was lowered with resize2d's default round rounding. Upsample maps each output index to floor(x_out / scale), so the imported model silently produced wrong values even for plain 2x upsampling (max abs diff around 4.8 against onnxruntime on random input). Every input dimension was also forced through int(), so a dynamic batch or spatial extent failed with int(Var), and non-4-D inputs were rejected by bare asserts.

Resize-10 has the signature (X, scales) and the same semantics as Upsample-9, but because only _impl_v18 existed it was dispatched to the Resize-18 converter, which interpreted scales as roi and failed for every Resize-10 model.

This PR lowers Upsample-7, Upsample-9 and Resize-10 through one helper that follows the legacy semantics as implemented by onnxruntime. Output extents are floor(input * scale), coordinates are asymmetric, and nearest mode rounds the source index down when upsampling and up when downsampling (Resize-10 accepts scales below one). Symbolic extents with integer scales are kept as exact products such as 2 * H, so they still unify with other shapes, for example a skip connection concatenated after the upsample. 3-D and 5-D inputs go through resize1d and resize3d. Scaling the batch or channel dimension, or mixing upsampling and downsampling axes in nearest mode, raises OpAttributeUnImplemented instead of an assertion. Resize-11 through Resize-17 are explicitly mapped to the existing converter so their behaviour does not change.

The new tests compare against onnxruntime for all three op versions across nearest and linear modes, 3-D/4-D/5-D inputs, a non-integer scale, Resize-10 downsampling, and symbolic batch and spatial dimensions. 26 of the 28 fail without this change; the other two guard behaviour that was already correct.

Two related cases are not covered here. Linear mode with a non-integer scale where input * scale is not an integer still differs from onnxruntime, because TOPI derives the coordinate ratio from the output size rather than the given scale; that is the problem addressed for Resize by #19698. Linear mode with a symbolic extent and an integer scale hits a separate crash in the interval-set analysis, fixed in #20414.

[LiRunGuo]

Hi @tlopex, could you help review this when you have time? It fixes the legacy Upsample (opset 7/9) and Resize-10 import paths, which were failing or giving wrong nearest-mode results. Thanks!