onnxruntime

[NNAPI EP] Add ReduceMean Op support (#16294)

### Description
<!-- Describe your changes. -->

As title.

Special cases for ReduceMean:
[UPDATE] The following cases are supported now by converting to
providing an input with all axes for NNAPI.
Behaviors when axes is not provided or axes provided as an empty vector:
For ReduceMean Opset version 18:
- Support case `axes` is provided as empty with `noop_with_empty_axes`
set to true.
- Support case `axes` is not provided with `noop_with_empty_axes` set to
true.
All treat as identity op.
- Does not support the case when `axes` is not provided/provided as
empty but `noop_with_empty_axes` is set to false.

For ReduceMean OpSet Version 13-:
- Does not support when `axes` attribute is not provided. (as onnx
treats it as default behavior to reduce all dimensions, and the case is
not implemented by NNAPI.)


https://developer.android.com/ndk/reference/group/neural-networks#group___neural_networks_1ggaabbe492c60331b13038e39d4207940e0a047fe95a35b27f45c05432b6ca18eb6c

> 1: A 1-D Tensor of
[ANEURALNETWORKS_TENSOR_INT32](https://developer.android.com/ndk/reference/group/neural-networks#group___neural_networks_1ggaf06d1affd33f3bc698d0c04eceb23298ac34965d8e76ac5acfddf5acd9e40f896).
The dimensions to reduce. Must be in the range [-rank(input_tensor),
rank(input_tensor)).NOTE: When the operation was introduced, the
documentation incorrectly stated that if dimensions were empty, the
operation would reduce across all dimensions. This behavior was never
implemented.

### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

Fixes issue #16194

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Co-authored-by: rachguo <rachguo@rachguos-Mini.attlocal.net>