onnxruntime

[js/webgpu] Optimize MatMul with M = 1 (#22577)

### Description
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BUG #22031

In the demucs model, there are lots of MatMul ops with shapes like
below:
`input[0]: [3448,1,512] | float32, input[1]: [512,1536] | float32,
output[0]: [3448,1,1536] | float32`

We can see that for this kind of shape, the batch size is a big value,
but M = 1. Our current algorithm is based on [M, N] to partition tiles,
which is not efficient for such kind of shapes. This PR reshapes the
inputs to improve the matmul performance.
Before:  [3448,1,512] x [512,1536] =  [3448,1,1536]
After: [1, 3448, 512] x [512, 1536] = [1, 3448, 1536] , then the output
can be reshaped to [3448, 1, 1536]

The overall MatMul time in demucs model becomes 1778.45 ms from 4418.17
ms on my iGPUs.

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Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>